Irena Grosfeld

Etienne Madinier

Seyhun Orcan Sakalli

Ekaterina Zhuravskaya

Micael Castanheira

Mathias Dewatripont

Seema Jayachandran

Nina Mcmurry

Maria Petrova

Alexandra Scacco

Aleksander Smolar

Benjamin Olken

Independent Media, Propaganda, and Religiosity: Evidence from Poland *

Exploring a drastic change in media landscape in Poland, we show that mainstream media can significantly affect religious participation. After nationalist populist party PiS came to power in 2015, news on state and private independent TV diverged due to propaganda on state TV, resulting in a switch of some of its audience to independent TV. Municipalities with access to independent TV continued to follow a long-term secularization trend, while municipalities with access only to state TV experienced a reversal of this trend. An online experiment sheds light on the mechanisms underlying the effect of exposure to independent news on religiosity.

Introduction

Historically, the Catholic Church advocated control over the press to promote Church values and popularity. In an encyclical Mirari vos, Pope Gregory XVI (1831)(1832)(1833)(1834)(1835)(1836)(1837)(1838)(1839)(1840)(1841)(1842)(1843)(1844)(1845)(1846) claimed that the freedom of the press should be "abhorred and anathematized" and Pope Pius IX (1846-1878) called it "intrinsically evil" (as quoted by Hasler, 1981, p. 43, p. 109). Starting in the 20th century, the official rhetoric of the Church has changed to become more aligned with modern democratic values. Pope Francis (1936-), for instance, embraced media freedom as a fundamental right [START_REF] Pullella | Pope pays tribute to journalists who were killed; says press freedom vital[END_REF]. Concurrent to the change in Church's attitude toward media pluralism, one can observe a general secularization trend in many European Catholic countries. Could the decrease in religiosity be, at least in part, related to how the Church is portrayed in the media?

This paper, to the best of our knowledge, is the first to study how the availability of media that criticizes the Church affects the popularity of the Church. We estimate the effect of a change in media landscape on religious participation using a quasi-natural social experiment in Poland, one of the most religious countries in contemporary Europe. It occurred as a result of the electoral victory of the nationalist conservative populist party Law and Justice, PiS (for Prawo i Sprawiedliwość). Before PiS came to power, all major mainstream news media, both public and private, maintained editorial policies independent from the government and had similar coverage of the government and the Church. After its victory in 2015, PiS took many steps in the direction of subverting democratic institutions. One of the most significant steps was taking control of the editorial policy of public media outlets. As a result, formerly public and now de facto state media, including the largest state TV network Telewizja Polska (TVPolska), launched bold pro-government and pro-Church propaganda.1 This is why, hereafter, we refer to Polish public media as state media.

Only few independent news media outlets remained. Most notably, the two biggest freelyavailable private TV networks, TVN and Polsat, remained formally independent from the government. 2 As we document in the background section, TVN, owned by Warner Bros. Discovery, Inc., an American multinational, has managed to sustain an independent editorial policy, whereas domestically-owned Polsat adopted a (mild) pro-government slant in exchange for political and financial favors from the ruling party, leaving TVN as the only source of freely available truly independent news on TV. When TVPolska started to broadcast pro-government and pro-Church propaganda in 2015, the news on independent TV-primarily TVN-criticized Poland's illiberal turn and exposed the growing financial and political ties between the Church and the ruling party. TVN also exposed numerous scandals about child sexual abuse within the Church, which surfaced after 2018 and were largely ignored by the state TV. We document the differences in the content of TV networks over time and between networks using anecdotal evidence as well as systematic text analyses of their official social-media accounts.

We use the drastic change in the Polish media landscape in 2015 to estimate the effect of access to independent TV on religious participation in an environment dominated by state-led media propaganda. We measure religious participation with the rates of mass attendance and of taking Holy Communion at the municipality level annually between 2009 and 2019. 3 These measures come from parish censuses conducted by the Institute of Statistics of the Catholic Church. We relate them to variation in the availability of state vs. independent TV and the change in TV content, initiated by PiS take-over of state media.

We gauge the availability of each main TV network from predicted signal strength calculated from the official data on the location and power of their TV transmitters. We use the Irregular Terrain Model (ITM) following [START_REF] Olken | Do television and radio destroy social capital? evidence from Indonesian villages[END_REF]; [START_REF] Enikolopov | Media and political persuasion: Evidence from Russia[END_REF]; [START_REF] Adena | Radio and the rise of the nazis in prewar germany[END_REF]; [START_REF] Durante | The political legacy of entertainment TV[END_REF] and relate the predicted signal strength to data on actual TV reception. TVPolska is available in 90% of municipalities, whereas TVN and Polsat, which share the same broadcasting infrastructure and therefore have the same reception, are available in 71% of municipalities. We use a difference-in-differences methodology relying on the crosssectional variation in the availability of different TV networks and on the overtime change in the political bias of TVPolska. We use the TV availability measured at the beginning of 2015, just before the PiS victory, to avoid potential concerns with endogenous changes in location or power of transmitters. To account for potential differential effects of PiS victory depending on local characteristics that could correlate with proximity to broadcasting infrastructure (such as population density or local development), in our baseline specification we follow the literature (e.g., [START_REF] Olken | Do television and radio destroy social capital? evidence from Indonesian villages[END_REF] and control for the free-space signal strength interacted with a dummy for the post-PiS-victory period, thus, relying only on the plausibly idiosyncratic variation in TV availability coming from topographic irregularities.

The results yield that, before PiS came to power, trends in religious participation were parallel in municipalities with and without access to TVN and Polsat: the religious participation was slowly declining everywhere. After PiS consolidated its control of state media, the rates of mass attendance stopped falling and the rates of taking Communion increased in municipalities where independent TV was not available, i.e., where there was no TV news alternative to state propaganda. In contrast, in municipalities where independent free-to-air TV was available, religious participation continued to decline. The viewership data show that, after unleashing state propaganda, TVPolska lost viewership disproportionately compared to the independent news networks. At the same time, it is clear that not all of this loss of viewership by state TV was directed to consuming entertainment instead of news. First, we show that TVN gained in ratings after 2015 relative to the overall trend of a decreasing TV viewership. Second, we find no effect of the entertainment TV on religious participation. Third, the effects of having access to independent news on TV are robust to controlling for the availability of the state and entertainment TV. The sharp divergence, caused by PiS victory, in the content of news programs on TVPolska vs. TVN, the only TV network that managed to remain truly independent, is the most likely reason for this effect. We also examine the heterogeneity of the main effect and show that it is stronger among more religious and rural municipalities.

The results are robust to controlling for a wide range of socio-economic, demographic, and historical characteristics of municipalities. Most notably, in the baseline specification, we control for the cross-sectional measures of access to both mobile and stationary internet interacted with year fixed effects and for time-varying cable TV subscriptions. These are the most important potential confounding factors because the independent news and, more generally, liberallyslanted content continued to be available on the internet and cable even after PiS came to power; and, therefore, independent TV is not the only source of such information. We also control for night-time light density, as a proxy for local economic development, and for the legacy of historical partitions of Poland by three empires interacted with year fixed effects to account for different levels of religiosity in different partitions. A battery of additional checks and falsification exercises confirm the robustness of our results, showing that they are very unlikely to be driven by unobserved confounders. In particular, we conduct the analysis proposed by [START_REF] Oster | Unobservable selection and coefficient stability: Theory and evidence[END_REF] and also replicate the results in a matched sample of municipalities that have different TV reception, but are similar in terms of all other observables. We show that the countervailing effects of the independent TV in light of pro-Church state propaganda on religious participation cannot be simply explained by the effects of the exposure to TVN and Polsat on political views of the electorate. The effect of the availability of TVN and Polsat after PiS came to power on the vote for PiS party in the subsequent elections is small in magnitude and statistically insignificant.

To examine what type of information about the Catholic Church-available only via independent media-affects religiosity, we conduct a large-scale online randomized experiment. We expose randomly-chosen subsets of Polish adult population to two information treatments about: (1) clerical child abuse and the apparent lack of adequate reaction of the Catholic Church to these cases; and (2) close relationship and the exchange of political and financial favors between the ruling party and the Church. In each case, we specify exactly the sources of all pieces of information, which are the independent Polish media, allowing the respondents to verify the web-links to the sources. In two rounds, i.e., right after the treatments and two to four weeks later, we elicit the attitudes of respondents toward the Church and Church-related behavior and compare them to those of the control group, which did not get any information treatment. The results of the experiment confirm that both types of content lead to a decrease in trust in religious institutions and the intention to go to church in the future. The effect of exposing child sexual abuse cases by priests on trust in the Church is larger in magnitude. This treatment also reduces donations to Church-affiliated NGOs. The effects of the treatments are present in the follow-up round and, therefore, cannot be explained by a temporary increase in the salience of these issues caused by the information treatments. One of the reasons for the persistence of the experiment results is that-after being exposed to the information about pedophilia scandals in the Church in the first round-some participants actively searched for the information related to the treatment in the media and on the internet. Consistent with heterogeneities in the observational analysis, the effects of exposure to the stories normally available only on independent media are significantly higher for religious people, residents of small towns or rural areas, and respondents who support PiS or watch state TV, i.e., those who are less likely to consume news from independent media in the first place. In order to validate our experiment, we test for and find no evidence of the Experimenter Demand Effects.

One should exercise caution in generalizing the results of the experiment to the effects of the content of TV news because our experimental design cannot fully replicate the environment of TV news consumption. In particular, the respondents may consider that the objectives of the researchers differ from those of journalists. However, the consistency of the heterogeneity results between the experiment and observational data suggests that one can learn from the experimental results. The combined findings of observational and experimental analyses suggest that the information about Church's cover-up of sexual abuse of children and its ties to PiS was more novel for religious people and rural residents. This implies that these individuals may not seek out such information on the internet or through subscription-based media, and only come across it when it is available on free-to-air independent TV.

Overall, our findings suggest that, when it was possible, some people turned away from propaganda to independent media, which then significantly affected their religious behavior and trust in religious institutions. The persuasion rate of watching independent rather than state TV, based on our estimates coupled with data on viewership, is 11.5% for the decision not to attend mass and 17.0% for the decision not to take Holy Communion. Conversely, the persuasion rate of TVPolska, when independent TV is not available, is considerably smaller: 4.6% for the decision to attend mass and 2.3% for the decision to take Holy Communion. These effects are large in comparison to the overall secularization trends: we find that in places where independent TV was not freely available, pro-Church state propaganda slowed down the decline in the rate of mass attendance by 28% and fully reversed the decline in the rate of taking Communion; the trends continued in places where the independent TV was available.

The experimental results imply that exposure to the information about the lack of response of the Church's leadership to sexual abuse of minors by the clergy leads to a persuasion rate of 7.6% for the decision to choose a non-religious charitable foundation over a religious charitable foundation. In addition, it leads to a three-week-persistent persuasion rates of 7.6% for the intention to stop attending mass every week in the future and of 5.9% for a decreasing trust in religious institutions. In addition, exposure to the information about the exchange of mutual favors between the ruling party and the Church is also associated with a persistent persuasion rate of 7.1% for the decision not to attend mass weekly in the future.

The literature has documented the important effects of media on a wide range of economic, social, and political outcomes (see, for instance, surveys by [START_REF] Dellavigna | Persuasion: Empirical evidence[END_REF][START_REF] Enikolopov | Media capture[END_REF][START_REF] Dellavigna | Economic and social impacts of the media[END_REF]. There is evidence, in particular, that entertainment media can affect cultural traits, such as gender attitudes and behavior (e.g., [START_REF] Jensen | The power of TV: cable television and women's status in India[END_REF][START_REF] Chong | Television and divorce: Evidence from brazilian novelas[END_REF][START_REF] Ferrara | Soap operas and fertility: Evidence from brazil[END_REF][START_REF] Cheung | Edutainment Radio, Women's Status and Primary School Participation: Evidence from Cambodia[END_REF][START_REF] Kearney | Media influences on social outcomes: the impact of MTV's 16 and Pregnant on teen childbearing[END_REF][START_REF] Banerjee | Entertainment, education, and attitudes toward domestic violence[END_REF]). Yet, little evidence currently exists that media can affect religiosity, a particularly deeply-rooted cultural attribute and an important determinant of economic and political development (e.g., [START_REF] Becker | Religion in economic history: a survey[END_REF][START_REF] Bentzen | The power of religion[END_REF]. A notable exception is the recent paper by [START_REF] Mello | Religious media, conversion, and the socioeconomic consequences: The rise of pentecostals in Brazil[END_REF], who demonstrate the effect of exposure to a private Evangelical Pentecostal-Church TV channel in Brazil on the size of the Pentecostal religious movement and on the behavior promoted by the Church and by this channel. Our paper contributes to this literature by showing that nonreligious media can also significantly affect religious behavior. Focusing on Poland, a country where Catholicism represents one of the most fundamental and identity-forming features (PEW Research Center, 2017), allows us to conclude that the presence of mainstream media outlets with content that the Church considers as criticism could reinforce the secularization trend, even in the most religious countries. 4 We also contribute to the literature on mass media propaganda (e.g., [START_REF] Yanagizawa-Drott | Propaganda and conflict: Evidence from the rwandan genocide[END_REF][START_REF] Dellavigna | Cross-border media and nationalism: Evidence from serbian radio in croatia[END_REF][START_REF] Adena | Radio and the rise of the nazis in prewar germany[END_REF][START_REF] Blouin | Erasing ethnicity? propaganda, nation building and identity in rwanda[END_REF]. Our results demonstrate that the effectiveness of widespread propaganda by mainstream government-controlled media varies depending on the existence of alternative sources of news. [START_REF] Knight | Partisan control, media bias, and viewer responses: evidence from berlusconi's italy[END_REF] were the first to document significant changes in viewership composition as a result of a change in partisan slant of a TV channel in the context of Silvio Berlusconi's media. Our findings are related to [START_REF] Knight | Opposition media, state censorship, and political accountability: Evidence from chavez's venezuela[END_REF], who analyze the effect of the introduction of government control over a previously-independent TV channel in Venezuela during Chaves's autocratic rule. They show a decline in viewership of the censored channel and a rise in viewership of another opposition channel, which mitigated the impact of censorship on political opinions. Our results suggest that independent media also can limit the effects of propaganda on religiosity.

The rest of the paper is organized as follows. Section 2 presents background information on religiosity in Poland and on the content of TVPolska and TVN before and after PiS came to power. In Section 3, we present the data, methodology, and the results of the analysis of the observational panel data. Section 4 describes the design and the results of the experiment. In Section 5, we conclude.

Background

In this section, we briefly describe the level of religiosity in Poland as compared to other European countries and provide anecdotal and systematic evidence on the similarity in the content 4 By highlighting the impact of media on religious behavior, we also contribute to the growing literature on the determinants of religiosity (see recent surveys by [START_REF] Iyer | The new economics of religion[END_REF][START_REF] Becker | Religion in economic history: a survey[END_REF]. [START_REF] Bottan | Losing my religion: The effects of religious scandals on religious participation and charitable giving[END_REF] show that sex scandals in the Catholic Church in the US result in substantial decrease in religious participation in the localities where they occur. Our results suggest that the information about sex scandals in the Church can affect a considerably wider audience on the national level if delivered by mainstream media. Information diffusion about the Church sex scandals is not the only mechanism behind our results as the Church sex scandals have become a prominent topic of the independent news in Poland only since 2018, whereas the content of the state and independent media diverged right after PiS came to power, and this is when one starts seeing the effect of media on religious participation. [START_REF] Bassi | Persuasion: A case study of papal influences on fertility-related beliefs and behavior[END_REF] demonstrate the direct effect of Papal speeches during a visit to a largely-Catholic country on fertility-related behavior. In addition, [START_REF] Wang | Media, pulpit, and populist persuasion: Evidence from father coughlin[END_REF] shows that religious media can significantly affect political outcomes if its content is highly politicized.

of news by state and private TV networks before PiS came to power and the divergence that occurred after.

Religion in Poland

Poland is one of the most Catholic countries in Europe and, by a number of measures, the most religious one. According to a report by PEW Research Center (2017), in 2015, 87% of the Polish population self-identified as Catholic. The European Values Study (EVS, 2017) conducted in 2017, reports that 93% of Poles believe in God, compared to 73% average in the other 35 countries surveyed. 5 The European Social Survey conducted in 2018 [START_REF] Ess | European social survey. Data[END_REF] shows that the share of people who claim that they attend religious services at least once a week is the highest in Poland among 29 European countries: the number for Poland is 45% and the average for the rest of the 28 countries surveyed is 12.2%. (The average results of both the EVS and ESS surveys by country are presented in the Online Appendix Figure A1.) PEW Research Center (2017) also shows that among countries in Eastern Europe with Catholic majority, Poland is the leader in terms of the percentage of people who believe that being Catholic is important for their national identity. 64% in Poland think so, whereas the comparable figures are 58% in Croatia, 56% in Lithuania, and 43% in Hungary.

There is a general long-term trend towards secularization in most Catholic countries, particularly in Europe (PEW Research Center, 2017); and Poland is not an exception. Both religious participation and the share of people who say that they believe in God gradually decline. We illustrate this trend in Online Appendix Figure A2

TV in Poland

TV remains a very important source of news for Poles, despite an increasing importance of social media. According to a representative survey of the Polish adult population, in 2020, 65% of respondents watched TV every day. An average Pole watched TV for 4 hours and 35 minutes per day. Among those respondents, who watched TV at least sometimes, the average time spent in front of a TV set was 6 hours and 56 minutes per day. Almost 100% of all dwellings in Poland are equipped with a TV receiver. 6 According to the leading Polish operator of terrestrial TV and radio broadcast infrastructure, Emitel, over one third of all households in Poland use only the terrestrial television, others have some access to cable or internet TV. 7

5 On this question, Poland ranks the 7th out of 35 countries only after Azerbaijan, Georgia, Albania, Romania, Bosnia and Herzegovina, and Montenegro, all of which have non-Catholic majority, making Poland the top among Catholic countries.

6 Source: http://www.archiwum.krrit.gov.pl/Data/Files/_public/Portals/0/kontrola/program/tv/kwartalne/ rynek-telewizyjny-w-iv-kwartale-2020.pdf, accessed May 12, 2021. See also: https://wyborcza.pl/7,75968,21170158,dlaczego-dla-kaczynskiego-tak-wazna-jest-telewizja-bo-3mln.html, accessed May 12, 2021.

7 Source: https://emitel.pl/en/news/telewizja-polska-is-entering-mux-8/, accessed May 12, 2021.

Viewership of the main news programs

There are three main free-to-air TV networks in Poland with large viewership that devote significant part of their broadcast to news: TVPolska, the state-owned network, TVN, a subsidiary of American Warner Bros. Discovery, Inc., and Polsat, a network owned by a Warsaw-based businessman. 8 TVPolska and TVN are the two main sources of TV news in Poland, followed by Polsat. We illustrate the popularity of these channels in Online Appendix Figure A3, which presents trends in the aggregate viewership of the main prime-time news programs of these three networks aired between 7 and 8 pm-TVPolska's Wiadomosci, TVN's Fakty, Polsat's Wydarzenia.

In the beginning of our observation period, in 2009, 84% of all prime-time TV viewers watched one of these three programs. In particular, 31.7% watched TVN, 31.1% watched TVPolska, and 21% -Polsat. These shares continuously declined over time reaching 52% by 2019 for all three programs, with TVN at 21%, TVPolska at 15.7%, and Polsat at 15.5%. An important reason for this overall decline is the expansion of entertainment TV available over the internet and cable as well as the expansion of entertainment free-to-air TV channels. 9 Furthermore, after PiS took control over TVPolska, we observe a relative decline in state TV viewership. Between 2009 and 2015, TVPolska and TVN had exactly the same rankings, with Polsat significantly lagging behind. After 2015, TVPolska lost disproportionate share of viewers compared to both TVN and Polsat, such that by 2018 the ratings of TVPolska fell to the level of Polsat, making TVN's Fakty the most popular news program.

Content of the state TV news and of the independent TV news

In this subsection, we first summarize ample anecdotal evidence about the change in TV content that occurred as a result of PiS victory, present systematic analysis of the content similarity between TV networks and over time, and then describe briefly the TV coverage of the Catholic Church.

Anecdotal evidence. Most of the observers within Poland and outside agree that when PiS won the parliamentary election in 2015, the government policy regarding all democratic checks and balances, including the freedom of the press, drastically changed. The ranking of Poland in the World Press Freedom Index fell from 18 th in 2015 (at the moment when PiS came to power) to 62 nd in 2020. 10 A report by the Carnegie Europe think tank states: " [PiS] transformed public media into a propaganda organ of the ruling party." 11 A linguistic study of news tickers of the main TVPolska's news program Wiadomosci in 2016-2017 conducted by the Council for the Polish Language (2019) concludes that 70% of news tickers, instead of 8 Each of these networks is a collection of several TV channels with a different focus, but a common owner. Channels that belong to the same TV network and provide any political content have a similar political slant and, typically, use the same transmitting infrastructure. However, only one eponymous news channel in each of the two non-state TV networks, TVN and Polsat, actually is available for free through terrestrial television; we focus on these free-to-air TV channels. 9 In our empirical analysis, we control for cable TV subscriptions by region and year and for cross-sectional municipal-level internet availability interacted with year fixed effects. providing objective information, intend to influence viewers through emotional, expressive, and judgmental formulations. Online Appendix Section B.1 provides quotes from historians and essayists Anne [START_REF] Applebaum | A warning from europe: The worst is yet to come[END_REF] and Timothy Garton Ash (2021) who describe in their essays the extreme nature of propaganda on TVPolska, chronicle how PiS's leadership changed the director of TVPolska who, in turn, fired independent journalists, and illustrate how content of TVPolska has diverged from TVN.

While it is a commonplace that both the content and the tone of TVPolska changed drastically with PiS's ascent to power, it is harder to assess whether the slant of TVN changed post-PiS as well. TVN started to criticize the government for both their words and their actions after the government's authoritarian turn, which could have contributed to the increase in political polarization. In the words of Garton Ash (2021), TVN "is not BBC-impartial, but it does serious journalism and gives you the other side of the story."

Some divergence in the news slant of TVPolska and TVN began to emerge already after an unexpected outcome of the May 2015 Presidential election, in which the right-wing pro-PiS and pro-Church candidate, Andrzej Duda, was elected president with 55.3% of the total vote in the second round. During this election, the Church actively participated in the election campaign on Duda's side. Such direct political involvement of the Church was unprecedented [START_REF] Lesniczak | The communicative role of the catholic church in poland in the 2015 presidential election and its perception by the public[END_REF]. TVN was more critical than TVPolska of the political support the Church gave to the newly elected president. However, the difference in news content between TVPolska and TVN substantially widened after PiS's narrow victory in the October 2015 Parliamentary elections, which enabled PiS to interfere directly in public media.

PiS party also put pressure on non-state media, including TVN and Polsat. Garton Ash (2021) writes: PiS "has launched a systematic attack on independent media. The methods are straight out of Viktor Orban's playbook in Hungary. Public sector advertising and subscriptions are withdrawn from independent media. All sorts of regulatory chicanery is used against them." Despite the pressure on private media, TVN managed to stay independent, in part, because of an open support by the U.S. State Department. 12 In contrast, domestically-owned Polsat could not resist the pressure. It remained independent only for about one year. Then, it started broadcasting pro-government news in exchange for political and financial protection from the ruling party (e.g., [START_REF] Dabrowska | Polsat skreca w prawo[END_REF]. To change the editorial policy, Polsat's owners asked journalists to be careful in expressing anti-government and anti-Church opinions, including on social media, and laid off those who did not comply. The observers, however, note that even after the Polsat's turn to the right, its pro-government slant remained substantially milder than the outright pro-PiS and pro-Church propaganda of the state media. 13

12 See, for instance, https://notesfrompoland.com/2020/04/20/american-ambassador-defends-us-ownedstation-attacked-as-fake-news-factory-by-polish-state-tv/, accessed May 5, 2021). PiS has made several (so far unsuccessful) attempts to ban foreign ownership of media which is widely regarded as an attack directly targeting TVN (see, for instance, https://www.nytimes.com/2021/08/11/world/europe/polands-media-lawpasses.html and https://www.nytimes.com/2021/12/27/world/europe/poland-media-law.html, both accessed September 20, 2022). 13 We provide links to ample anecdotal evidence of Polsat's pro-government editorial policy in Online Appendix Section B.3.

Similarly to Orban's policy studied by [START_REF] Szeidl | Media capture through favor exchange[END_REF], PiS secured generous stream of advertising revenues from state-controlled Polish companies to Polsat as a remuneration for its shift to the right and punished TVN for remaining independent by withdrawing state advertising, despite the relative growth in TVN's audience. According to a Supreme Audit Office (2018) report, out of the total advertising expenditure of state-controlled companies on TV, TVPolska received 41.5%, TVN -22.3%, and Polsat -15.8% in 2015 (all other TV channels got 20.4%); by 2017, TVPolska received 59.7%, Polsat -33.9%, whereas TVN -only 1.6% (while remaining channels got less than 5%). Online Appendix Figure A4 visualizes this drastic change by year between 2015 and 2017. It shows that already in 2016, TVN lost while Polsat substantially increased their respective shares of state advertising.

Content similarity. There are no transcripts of Polish TV news that go back in time. To conduct a systematic analysis of news content, we scraped tweets from the official Twitter accounts of each of the three main TV networks and their respective prime-time news programs using Twitter API. As tweets contain headlines with only a short description of the actual news programs, the differences in the content of Twitter accounts does not fully reflect the differences in the content of the actual news. However, if the topics and headlines of TV networks differ, one should expect this to translate into differences in the content of their Twitter accounts. We use the official accounts of the three main TV networks: @tvp_info and @WiadomosciTVP for TVPolska; @tvn24 and @faktytvn for TVN; and @PolsatNews.pl and @WIOwPN for Polsat. We downloaded all 871,475 tweets from these accounts that were published in ten years between 2012 and 2021 and were not deleted by 2022. At least one of the Twitter accounts of TVPolska and of TVN was active between 2012 and 2021; in contrast, Polsat's accounts started to generate content regularly only in 2016. 14 Using the tweets, we build indices of content similarity between each pair of TV networks in each year and also measure how the content of each of the TV networks changed over time. 15 Figure 1 presents the results. Consistent with the anecdotal evidence presented in the previous subsection, Panel A shows that, before PiS came to power, the content of the Twitter account of TVPolska had remained relatively constant over time, and it has changed drastically after PiS came to power. In contrast, TVN's twitter account remained relatively similar to its own content in 2014 both before and after PiS victory in 2015. In Panel B, we present the similarity indices calculated for each year between TVPolska account, on the one hand, and the two main 14 @PolsatNews.pl was registered in 2014, but there were no tweets in 2014 on this account. In 2015, there were only 273 tweets, whereas in 2016-2021, the number of tweets from @PolsatNews.pl each year exceeds 6,000.

15 To calculate content similarity, we first tokenize all tweets using TweetTokenizer from the standard python library nltk. Then, we remove urls, usernames, numeric characters, and non-alphanumeric characters. We also remove stop words in Polish language from https://github.com/bieli/stopwords/blob/master/polish.stopwords.txt (accessed September 15, 2022) and singletons, i.e., words that are present only once in the entire corpus. This yields a vocabulary of 176,165 words. Then, we count the occurrence of each word in twitter accounts of each TV network each year to create a vector, in which each dimension represents a single word and the length represents the number of occurrences of this word. Then, we compute the similarity index between any two of these vectors using the standard cosine measure, i.e., the scalar product of these vectors divided by the product of their norm. This measure is commonly used to compute the similarity between two corpora and varies from 0 to 1.

private TV channels, on the other hand. 16We illustrate the differences in the content of TVN and TVPolska by calculating the relative frequency of mentions of topics sensitive for the Polish government by the Twitter accounts of these TV networks. For example, during the pandemic, COVID-19 was mentioned, on average, 19.4% more often by TVN than by TVPolska. During the peak of the migrant crisis on the Poland-Belarus border, TVN mentioned this topic 31.2% more than TVPolska, as TVN described the work of NGOs trying to help migrants and the brutality of the Polish guard who pushed migrants back. But when this topic was mentioned by both TV networks, TVN was 38% less likely than TVPolska to call the attempted border crossings "illegal," which was the official government position.

Overall, the evidence presented in this section illustrates that (i) before PiS came to power, the news coverage was similar in different networks; (ii) after PiS's victory, the content of TVPolska's news drastically changed. It diverged from both pre-PiS TVPolska and from the most popular independent TV network TVN. Anecdotal evidence suggests that Polsat, even though formally independent from the government, chose to avoid talking about issues unfavorable for the government in exchange for regulatory protection and state advertising.

TV coverage of the Catholic Church. Since PiS came to power, TVPolska has covered the Catholic Church very favorably. Later on, there was even an official agreement signed between TVPolska and the Episcopate. In this agreement, TVPolska has committed to cover rites and other events organized by the Church, and to take the position of the Catholic Church in its programs about moral, social, professional, and cultural issues. TVPolska broadcasts a live morning mass every day at 7 a.m. from Jasna Gora Monastery, which is one of the most important pilgrimage sites in Poland. Additionally, on Sundays, there is a religious program on TVPolska at 11 a.m., which is followed by a live broadcast of a prayer from Piazza San Pietro in the Vatican. 17 In contrast to TVPolska, TVN does not provide a platform for the Church. Instead, it has been critical of the Church's close ties with the ruling party and has exposed scandals within the Church. For example, their main evening news program Fakty reported on the extensive state financing of the Church media and business projects. They also showed a reportage on how the prime minister as well as government members and PiS parliamentarians publicly thanked the Church for political favors and rewarded this support with generous state financing of the Catholic Radio Maryja. 18 TVN also exposed pedophilia scandals in the Church when they became prominent starting in 2018. For example, TVN was the only TV channel that showed the two documentaries "Tell no one" (2019) and "Hide and seek" (2020) that reveal the crimes of sexual abuse of children confirmed by victims and confessed by perpetrators. Despite a considerable public attention to the first film "Tell no one"-it got 11 million views on YouTube within 3 days of its release and 20 million within 10 days-TVPolska did not mention it at all for over one year, until July 2020 when the film was mentioned in a discussion that was spun to focus on the Church's help to the victims of the crimes. 19 TVN also reported on how the Church leadership covers up cases of sexual abuse by Catholic priests; whereas TVPolska, in contrast, has argued that exposing pedophilia cases in the Catholic Church is equivalent to attacking the ruling party PiS; and the leadership of TVPolska has stated openly that TVPolska news program is used as a weapon of a counterattack. Polsat's coverage of the Church has been less critical than that of TVN, but also more balanced than TVPolska's propaganda.

TV and Religious Participation, Observational Data

In this section, we focus on the evidence from the observational data about the impact of media on religious participation. First, we describe the datasets, and then present the empirical methodology and results.

Data

Table A1 in the Online Appendix summarizes all variables used in the analysis of the observational data. Below, we describe their sources and provide details on variable construction.

Religious participation. We use data on the rates of mass attendance (Dominicantes) and taking Holy Communion (Communicantes) among Catholic population at municipality-year level as measures of religious participation. These data are collected by the Institute of Statistics of the Catholic Church (ISKK, 2020). The dataset covers 2,478 municipalities (Gminy) between 2009 and 2019. ISKK representatives count everyone who attends the Sunday mass and who takes Communion in each parish throughout Poland on the third Sunday of October each year. ISKK also collects information from each parish on the total number of baptized people, used as a proxy for the number of Catholics. Then, ISKK calculates the rates of mass attendance and taking Communion in each municipality by dividing the corresponding numbers of mass attendees and Communion takers by the number of baptized and then aggregates these parishlevel rates to the municipality level. 20 Online Appendix Figure A6 visualizes the distribution of these religiosity measures across space in 2009 and 2019. The maps confirm the findings of [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF] that differences in religiosity levels across Poland are highly persistent and can be traced back to the partitions of Poland at the end of the 18th century, as the partition borders are visible on the maps. The rates of mass attendance and taking Communion are the best available measures of religious participation in Poland. They reflect both the trends and the spatial variation in religiosity. Online Appendix Figure A7 illustrates the strong positive correlation between the rate of mass attendance from our data and the three self-reported measures of religiosity from the main biennial nationally representative Polish social survey, Social Diagnosis (Diagnoza, 2015). Online Appendix Figure A2 shows that the rate of mass attendance exhibits a downward trend consistent with data from ESS, while rate of taking Communion is more stable suggesting that fervent practicing Catholics are much less affected by this general secularization trend.

TV signal. Each terrestrial TV uses a network of transmitters, called MUX. TVN and Polsat share the same broadcasting infrastructure. A different network of transmitters is used by TVPolska. There is also a separate network of transmitters dedicated to entertainment multiplex, which we refer to as entertainment TV. 21 To proxy for the local exposure to these TV networks, we compute the signal strength and a dummy for having a good signal for each network of terrestrial transmitters at the level of municipality. For the two main transmitter networks that broadcast news, i.e., the one that broadcasts TVN and Polsat and the other that broadcasts TVPolska, we measure signal strength at the beginning of 2015, i.e., right before PiS's victory. The entertainment TV multiplex started to be fully operational only in 2016. We measure its signal in 2019 due to data limitations.

To build these measures, we, first, collected information on the location, height, power, and frequency of each transmitter in 2015 and 2019 for TVN and TVPolska and in 2019 for the entertainment TV. The source of these data is the telecommunication infrastructure company [START_REF] Emitel | Interactive map of transmitting infrastructure for the main polish multiplexes. We web-scraped these data from[END_REF]. Following, e.g., [START_REF] Olken | Do television and radio destroy social capital? evidence from Indonesian villages[END_REF][START_REF] Dellavigna | Cross-border media and nationalism: Evidence from serbian radio in croatia[END_REF]; [START_REF] Adena | Radio and the rise of the nazis in prewar germany[END_REF]; [START_REF] Bursztyn | A tear in the iron curtain: the impact of western television on consumption behavior[END_REF]; [START_REF] Durante | The political legacy of entertainment TV[END_REF]; [START_REF] Wang | Media, pulpit, and populist persuasion: Evidence from father coughlin[END_REF], we use the Irregular Terrain Model (ITM) to compute the signal loss both taking into account the information about topography and ignoring it (in free space) for every transmitter in each grid cell with 2.5-by-2.5 km resolution. Then, we calculate the signal strength of each transmitter by subtracting from its power the signal loss computed with the ITM (with and without topography) at the receiving grid cell. As the next step, we calculate the signal strength of each transmitter network (MUX) in each grid cell (again, both taking terrain into account and in free space) by taking the maximum signal strength among all transmitters that belong to the same network. We aggregate these measures of signal strength for each MUX to municipality level by taking the average across grid cells within each municipality. For the sake of brevity and because TVN of their respective distributions because there are occasional outliers with mass participation in excess of the number of registered Catholics due to pilgrimage. 21 The network of transmitters used by TVN and Polsat is called MUX-2. The one used by TVPolska is called MUX-3. Entertainment TV uses MUX-8.

is the only truly independent network, as discussed in the previous section, hereafter, we refer to the signal of the network of transmitters shared by TVN and Polsat simply as TVN signal. Online Appendix visualizes the locations of transmitters and their respective signal strengths for each of the three networks of transmitters taking into account topography in Figure A8 and the residuals of signal strength after regressing it on the signal in free space in Figure A9. TVPolska's signal coverage is much larger as it has many more transmitters than TVN.

Online Appendix Figure A10 shows that between 2015 and 2019 there were very few changes in the transmitter infrastructure of TVN and TVPolska. We use the signal strength as of 2015 rather than time-varying measures in order to avoid the potential endogeneity of infrastructure upgrades by TV networks after PiS came to power (even though the time variation is minimal). The data before 2015 are unavailable. 22 Dummies for good TV reception. Based on the signal strength measures, we generate dummies for having a good TV reception for each of the three transmitter networks. The relationship between the signal strength and the possibility to watch TV broadcast without an amplifier depends on many factors, such as atmospheric conditions. The engineering guidelines prescribe signals in the range between -45 to -30 dB for having a good reception and in the range of -55 to -45 dB for a normal-quality reception. 23 In order to find a reasonable cut-off for the case of Poland, we use the information from the Polish broadcasting regulator, the National Broadcasting Council, Krajowa Rada Radiofonii i Telewizji (KRRiT, 2021), which provides maps of areas with TV reception good enough to watch TV with a regular home antenna for each transmitter network. We regress the dummy for having a good reception from KRRiT on the signal strength from ITM across grid cells using a local polynomial regression, which-consistent with the literature [START_REF] Olken | Do television and radio destroy social capital? evidence from Indonesian villages[END_REF]-yields a monotonic S-shape relationship presented in Panel A of Online Appendix Figure A11 for TVN network of transmitters. The reason for dichotomizing signal strength is illustrated by this relationship: the variation in the signal strength translates into differences in reception quality only when the signal strength is in the middle range and not when it is already high or low. We find that for every value of the ITM signal strength above -40 dB, the majority of grid cells with this value of signal strength have good reception according to the regulator KRRiT and for every value of the signal strength below -40 dB the majority of grid cells with that signal strength have bad reception. Thus, we deem a municipality to have a good TV reception for each TV network if its signal strength is above -40 dB. Panel B of Online Appendix Figure A11 presents the density distributions of the signal strengths of TVN and TVPolska across municipalities relative to the threshold for having a good signal. 22 The main physical infrastructure for each of the transmitter networks was built before the beginning of our observation period. However, there was one important change, that took place between 2012 and 2013: transmitters were upgraded from analogue to digital. We have collected data on the exact timing of the analog switch-off in each locality and we verify below that our results are robust to using only the data after the digital transition and to controlling for the timing of the analog switch-off. These data come from Telewizja-cyfrowa.com (2021).

23 See, for instance, https://otadtv.com/reception/minimum_signal/index.html, accessed September 21, 2022.

Viewership. Panel data on viewership of the main prime-time news programs by TVN and TVPolska (Fakty and Wiadomosci, respectively) at the level of 16 regions (Voivodships) between 2009 and 2019 come from [START_REF] Nielsen | Viewership of tvn's Fakty and telewizja polska's Wiadomosci[END_REF].

Other variables. We also use a number of socio-economic and historical covariates, see Online Appendix Section C for the details about these data. We construct measures of fixed and mobile internet availability in 2019 at the municipality level. Following [START_REF] Henderson | A Bright Idea for Measuring Economic Growth[END_REF][START_REF] Henderson | Measuring Economic Growth from Outer Space[END_REF], we proxy time-varying levels of economic development of municipalities with data on the nighttime light density per capita from [START_REF] Bluhm | Top lights: Bright cities and their contribution to economic development[END_REF] and Earth Observation Group Data (2020). We control for the occurrence of natural disasters within the last 3 years at the municipality level from EM-DAT (2020). The following covariates come from Central Statistical Office of Poland (2020), they are available as cross-sections: total population, age distribution of the population, revenue per capita, EU subsidies per capita, education distribution of the population are at the municipality level; share of population who speaks only Polish, wages as percent of country average; share of agriculture among employed; industrial production per capita are at the county (powiaty) level. The same source also provides panel data on the number of cable TV subscriptions at the region level in 2009-2019. The map of the historical partitions and the data on access to railway network are from [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF].

Determinants of TV signal and the location of antennas

In Section D of the Online Appendix, we explore the correlates of the cross sectional variation in the signal strength of different TV networks in order to understand what are the potential confounding variables. There are two main take-aways from this analysis. First, as one should expect, transmitters are placed in locations that allow reaching larger numbers of people and more developed areas. Controlling for free-space signal strength, which measures the proximity to transmitting infrastructure, accounts for much of this variation. Second, the historical partitions of Poland, which are an important determinant of the spatial variation in religiosity [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF], also are correlated with the topographical features that affect how far TV signals can travel. Thus, it is important to account for this variation as well. Our baseline specification, presented below, controls for partitions-by-year fixed effect and free-space signal strength interacted with post-PiS dummy. In the robustness section, we also show that our results are robust to controlling for the initial levels of religious participation and initial political preferences interacted with year fixed effects as well as a large set of other potential confounders.

Viewership of TVN and TVPolska post-PiS

In Table 1, we test whether the viewership of TVN and TVPolska was affected by the change in TVPolska content, depending on TVN's availability. 24 The first four columns consider the share of TVN viewers among all prime-time viewers of TVN and TVPolska as dependent variable; in Columns 5 and 6, the dependent variable is the log number of TVN viewers, and in Columns 7 and 8 -the log number of viewers of TVPolska. In Columns 2 to 8, we control for the overall trends in prime-time TV viewership. Columns 1, 2, 5, and 7 show that the populationweighted share of municipalities with good TVN signal in a region is associated with a higher share of TVN viewers among viewers of the two channels, a higher TVN audience, and a lower TVPolska's audience. This is a cross-region correlation, as we do not control for region fixed effects in these regressions. This association, however, is not driven by the correlates of the proximity to transmitters because it is robust to controlling for the free-space signal strength (as shown in Columns 2, 5, and 7). Furthermore, the coefficient on the interaction term between TVN's availability and post-PiS dummy, also included in these columns, shows that, after TVPolska changed its content to propaganda, TVN gained and TVPolska lost viewership disproportionately in those regions, where TVN was available. We confirm this finding in a difference-in-differences setting in Columns 3, 4, 6, and 8, which control for region fixed effects.

Column 4 also shows that the results are robust to controlling for cable TV subscriptions and internet availability. Based on the point estimate in Column 4, we conclude that, out of all prime-time viewers of both channels, 14.5% switched from TVPolska to TVN after PiS came to power. Online Appendix Figure A13 illustrates these results with corresponding event-study graphs.

Empirical methodology: the effect on religious participation

Our aim is to estimate the effect of TV news on religious participation. In particular, we explore the divergence in the content between TVN and TVPolska that took place after PiS came to power and started actively interfering in the TVPolska's editorial policy. We utilize the overtime change in the content and the cross-municipality variation in the TV availability which comes from plausibly idiosyncratic variation in terrain in a difference-in-differences setting. The baseline specification uses each of the two measures of religious participation (Religiosity)-the rates of mass attendance and taking Communion-as the dependent variable and the interaction between a measure of the availability of the private independent news TV network TVN (T V signal) and a dummy indicating the onset of the PiS control of the government (P ostP iS) as the main explanatory variable:

Religiosity mt = α 1 T V signal m × P ostP iS t + β 1 F reeSpaceSignal m × P ostP iS t + α 2 T V signal m × 2015 t + β 2 F reeSpaceSignal m × 2015 t + X mt δ + µ m + τ t + mt ,
where subscripts m and t index municipalities (gminas) and years. The set of controls includes municipality and year fixed effects (µ m , τ t ), the interactions of the free-space signal strength of TVN (F reeSpaceSignal) with P ostP iS dummy, the interactions between the TVN availability and TVN signal in free space and a dummy for 2015, the year when the two elections that brought PiS to power took place, which we deem a transition year, and a wide set of other controls (X mt ), described below. The baseline measure of TVN availability is a dummy for good reception of TVN in the municipality. We show that the results are robust to using the continuous TVN signal strength. First, for simplicity, we consider TVPolska to have good reception everywhere. As in reality TVPolska is available in 90% of municipalities, we show that the results are robust to flexible controls for its availability. The results are also unaffected by controlling for the entertainment TV. We adjust standard errors to account for spatial and overtime correlation in the data. As a baseline, we allow the error terms mt to be autocorrelated within each municipality and between different municipalities within 100 kilometers of each other. 25 We also report robustness to alternative assumptions about the variance-covariance matrix.

We show that our results are robust to having no covariates in addition to municipality and year fixed effects and to including an extensive set of controls. The main two potential confounding factors are the level of development and the availability of other sources of information independent from the government. To account for the level of economic development, we include the nighttime light density per capita to the list of baseline controls and the interaction between the free-space signal with post-PiS dummy. To account for potential effects of the presence of alternative sources of information and for the rise of social media during the decade that we study, we control for the interactions of the cross-sectional measures of fixed and mobile internet infrastructure with year fixed effects and for log cable TV subscriptions. In addition, we control for the presence of a natural disaster in the municipality within the last 3 years, which is an important predictor of religious participation, as people may turn to religion in the face of disasters (e.g., [START_REF] Belloc | Earthquakes, religion, and transition to selfgovernment in italian cities[END_REF][START_REF] Bentzen | Acts of god? religiosity and natural disasters across subnational world districts[END_REF]. To account for a potential differential effect of historical legacies on contemporary outcomes [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF][START_REF] Ochsner | Mobilizing history[END_REF], in the baseline specification, we control for the partitions of Poland among the three Empires interacted with year fixed effects. We also establish robustness to controlling for the interactions of year fixed effects with: dummies for each population-size decile, altitude, the pre-2009 political support for the PiS party, and the 2009 religious participation.

There are two main identification assumptions behind our identification strategy. First, the trends in religious participation should be parallel in municipalities with and without good TVN signal before PiS took control of TVPolska once we account for proximity to transmitting infrastructure by controlling for free-space signal strength (signal strength in free space is inversely proportional to the square of the distance from the transmitter). This assumption is testable. Below, together with the main estimates, we report the results of the event-study specification, which shows the absence of pretrends. We also perform the tests developed by [START_REF] Roth | Pretest with caution: Event-study estimates after testing for parallel trends[END_REF] to calculate the magnitude of the pretrends that we can statistically reject. The second assumption is that, conditional on covariates, there is no omitted variable that correlates with the TVN's availability and could differentially affect religious participation after PiS came to power. This assumption is untestable, but below, we present the results of the tests in the spirit of [START_REF] Altonji | Selection on observed and unobserved variables: Assessing the effectiveness of catholic schools[END_REF] and [START_REF] Oster | Unobservable selection and coefficient stability: Theory and evidence[END_REF] to show that our results are highly unlikely to be driven by such omitted-variable bias. Furthermore, we show that our results are robust to using a sub-sample of municipalities matched on the basis of observable characteristics.

The main persuasion result: the effect on religious participation

Baseline, the effect of TVN. Table 2 presents the baseline estimation results. Panel A focuses on the rate of mass attendance and Panel B -on the rate of taking Holy Communion, as dependent variable. The first five columns use a dummy for good TVN reception as the measure of TVN availability. In Column 1, there are no additional covariates apart from municipality and year fixed effects. In Column 2, we control separately for fixed and for mobile internet access, available only as cross section, interacted with year fixed effects, nighttime light density, and four dummies for the occurrence of disasters in the current year and the previous 3 years. In Column 3, we add the interactions of free-space TVN signal strength with post-PiS and 2015 dummies. In Columns 4 and 5, we show that the results are robust to controlling for partitionspecific trends and partition-by-year fixed effects. In Columns 6 and 7, we re-estimate the same specifications as in Columns 4 and 5, but with a continuous TVN signal strength measure, as the main explanatory variable. Irrespective of the specification, we find a negative and significant coefficient on the interaction between the TVN availability and a post-PiS dummy for both outcomes measuring religious participation.

Panel A of Figure 2 presents the results of the event-study specification on the full sample, in which we interact the dummy for good TVN signal strength with the full set of year fixed effects, keeping 2014-the pre-election year-as the comparison group.26 (In all other respects, the specification is equivalent to Column 4 of Table 2.) The left graph considers the rate of mass attendance as the dependent variable and the right graph -the rate of taking Communion. In both cases, we find no differential trends in religious participation between municipalities with a good and bad TVN signal before PiS came to power; trends diverge after PiS came to power. The event-study results also show that the effect is increasing over time. Because the absence of the pretrends is crucial for the validity of our identification assumptions, we use the methodology developed by [START_REF] Roth | Pretest with caution: Event-study estimates after testing for parallel trends[END_REF] to assess the power of the test for pretrends. We find that we can reject any pretrend that is larger than 31.4% of the estimated treatment effect for the rate of mass attendance and 29.3% for the rate of taking Communion (see Online Appendix Section E for the details of this calculation). Online Appendix Figure A14 presents the event-study graphs for the continuous measure of signal strength. They are similar to the ones based on dichotomized measure of TVN availability, and actually are more precise. Overall, we conclude that pretrends do not constitute a threat to our identification strategy. 27The effects of TVPolska and entertainment TV. In Table 3, we consider other TV channels. As above, Panel A focuses on the rate of mass attendance and Panel B -on the rate of taking Communion. First, we show that the effect of TVN does not depend on whether we account for the availability of TVPolska and of entertainment TV interacted with post-PiS period. Column 1 adds to the list of covariates (from Column 5 of Table 2) the interactions of the post-PiS dummy with dummies for good signal of TVPolska and good signal of entertainment TV and with the free-space signal strength of these networks. We also include controls for 2015 dummy interacted with the TVPolska availability and free-space signal strength. Interactions of 2015 with the entertainment multiplex are omitted because it started broadcasting only in 2016. The coefficient on a dummy for good TVN signal remains negative and statistically significant and its magnitude, if anything, is larger than without controlling for the signal of the other two networks. In Columns 2 and 3, we show that the effect of TVN is also robust to using subsamples of municipalities with good TVPolska reception and good entertainment TV reception. 28 As the next step, we consider the effects of other TV networks. Column 1 shows that neither TVPolska nor entertainment TV has a significant effect. In Column 4, we verify that it is also the case in the subsample of municipalities with bad TVN signal. The fact that TVPolska does not have an effect may seem surprising given that it was TVPolska and not TVN that changed its content. To understand it further, we study whether and how the two TV networks with news interact. In Column 5, we consider a specification with the full set of interactions between availability of TVN and TVPolska, controlling for availability of entertainment TV. We estimate the effects of having good reception of both networks, good TVN and bad TVPolska, and good TVPolska and bad TVN signals relative to having bad reception of both networks. Online Appendix Figure A15 presents the corresponding event-study graphs. Out of 2,478 municipalities, 1,746 have good reception of both networks, 237 have no reception of either network, 478 have bad TVN and good TVPolska signals, and only 17 have good TVN and bad TVPolska signals. We find that the effect of TVN is driven by the fall in religious participation post-PiS in municipalities with access to both TVN and TVPolska relative to those without access to the two networks. This effect is explained by the switch from TVPolska to TVN post-PiS, which we document in Table 1. There are too few municipalities with good TVN and bad TVPolska signals to estimate the effect of TVN without TVPolska, resulting in noisy estimates with very large standard errors.

The last row in each panel indicates that having access to TVPolska when TVN's reception is poor does not affect religious participation post-PiS. This null effect is estimated PiS party, age structure of the population, and availability of fixed and mobile internet. We find that the effects are larger in magnitude in places with higher initial religious participation (significant for both outcome variables) and in rural areas (significant only for the rate of taking Communion). There are no other detectable heterogeneities.

28 As all TV networks aim at reaching the more densely populated areas, their signals were positively correlated while their content diverged after 2015. The pairwise correlation coefficient between dummies indicating a good reception for TVN and TVPolska is 0.44; and for TVN and the entertainment TV, it is 0.48. Online Appendix Figure A12 presents the scatter plots of signal strength measures for different TV networks against each other and reports the number of municipalities with good and bad reception of each TV network.

with relatively high precision. No effect of TVPolska, however, does not imply that the state pro-Church propaganda has no impact. This is because TVPolska is not the only medium of propaganda. As shown in detail in Online Appendix Section B.4, since PiS came to power, state propaganda has become omnipresent, reaching the Polish population through various channels in addition to state TV. Notably, the state radio network Polskie Radio, consisting of multiple stations, and Church-owned Radio Maryja, subsidized by PiS, have widespread coverage throughout Poland. Most importantly, they cover all municipalities not reached by TVPolska, which constitute 10% of the sample. In these places, the population also has access to daily local and national newspapers, as well as weekly magazines, each of which receives generous state funding via direct subsidies and advertisement by state-controlled companies in exchange for disseminating pro-PiS and pro-Church content. Overall, our empirical exercise estimates the effect of independent TV in the presence of propaganda that employs different means and has universal coverage.29

Interpretation and magnitudes

The first differences. This difference-in-differences estimation identifies the relative differences between religious participation in places with and without access to TVN post-PiS. Yet, to understand the mechanism, it is useful to know whether TVN speeded up the decline in religiosity relative to the pre-existing trend in places where it was available or whether TVPolska slowed down or even reversed the decline in religious participation in areas where TVN was not available. In Panel A of Figure 3, we illustrate the raw (unconditional) trends in the two measures of religious participation by showing the aggregate dynamics of the rates of mass attendance and of taking Communion separately in municipalities with good and bad TVN reception. The graphs do show that the trends in religious participation diverged after PiS came to power. In particular, the figure shows that the trends in the rates of attending mass and taking Communion did not change in places with good TVN signal, whereas they shifted to a different trajectory with higher rates of religious participation in places with bad TVN signal. However, as these graphs are unconditional, it could be the case that some of the dynamics in the outcome variables is due to the effect of control variables. In Panel B, we present the residuals of religious participation measures, after regressing them on all controls, except for municipality fixed effects. These series are presented separately by good and bad TVN reception. The figure shows that, after PiS came to power, both the exposure to the unchecked state propaganda in areas without access to TVN led to an increase in religious participation and the exposure to TVN led to a decline in religious participation. The effect of post-PiS TVN reception is smaller in magnitude than the effect of not having access to TVN post-PiS, especially for the rates of taking Communion, but both effects are statistically significant. This suggests that the independent media plays an important role in neutralizing the state propaganda.

Magnitudes. According to the event-study estimates, after 5 years of exposure to state propaganda, i.e., in 2019, the average difference between municipalities with and without access to independent TV-caused by the difference in media environment-was 0.69 percentage points in the rate of mass attendance, equivalent to 2% of its overall mean, and 0.54 percentage points in the rate of taking Holy Communion, i.e., 3.7% of its mean. Considering the persistent religious participation in Poland, these magnitudes are substantial. According to the long-term secularization trends (presented in Panel C of Online Appendix Figure A2), every 5 years before 2015, the rate of mass attendance decreased on average by 2.46 percentage points and the rate of taking Communion by 0.29 percentage points. Thus, the pro-Church state propaganda slowed down the decline in the rate of mass attendance by 28% and fully reversed the decline in the rate of taking Communion, so that it grew by 0.25 percentage points instead of falling, in places where this propaganda was unchecked by the presence of independent TV. This is in contrast to places, where independent TV was available, in which the secularization trends were not affected (as illustrated in Panel A of Figure 3).

To calculate the persuasion rates implied by our analysis, we use the information on how TV availability translates into viewership. Online Appendix Section F explains the calculation. 30The persuasion rate of TVN is 11.5% for the decision not to attend the mass and 17.0% for the decision not to take the Holy Communion. It is important to note that the independent TV does not want to persuade viewers to stop going to the Church, but the facts about the Church that it reports do have such an effect. The persuasion rate of state propaganda, when independent TV is not available, is considerably smaller. State media convinces 4.6% of its viewers who did not attend mass before to start doing it and 2.3% of its viewers to start taking Holy Communion. One of the reasons why state-media propaganda is less persuasive than independent media is that it has been losing credibility due to a very aggressive nature of its propaganda.31

Robustness, identification checks, and matching estimation

Additional covariates and clusters. In Online Appendix Table A3, we establish robustness of our results to adding a large number of potential confounders in addition to baseline covariates, including all the cross-sectional determinants of TVN availability chosen by LASSO (see Online Appendix Section D), which we interact with year fixed effects. As above, the two panels focus on the two main measures of religious participation. In Column 1, we replicate the results of Column 5 of Table 2 on the sample of municipalities where all additional covariates are non-missing (to use the same sample in the entire table). In Columns 2 to 5, we include controls for population deciles, log altitude, pre-2009 PiS political support, and the initial level of religious participation one by one interacted with year fixed effects. Column 6 includes all of these additional covariates at the same time. The results are robust. Overall, our estimates are very stable across different specifications.

At the bottom of each Panel for the most elaborate specification (Column 6 of Table A3), we calculate Oster's δ, making an assumption that, net of municipality and year fixed effects, the R 2 max -the R 2 from a hypothetical regression of the outcome on the treatment and all covariates, including the unobserved ones-equals to 1.3R 2 , where R 2 is from the actual estimation [START_REF] Altonji | Selection on observed and unobserved variables: Assessing the effectiveness of catholic schools[END_REF][START_REF] Oster | Unobservable selection and coefficient stability: Theory and evidence[END_REF]. 32 The Oster's δ statistics indicate how important the selection on unobservables needs to be, compared to the selection on observables, to fully explain our results with omitted variable bias. Their magnitude-5.78 for the rate of attending mass and 3.11 for the rate of taking Communion-suggests that it is highly unlikely that our results are spuriously driven by unobserved variation, given how much we already control for. Online Appendix Figure A16 presents the residual scatter plots for the baseline estimations presented in Columns 5 and 7 of Table 2. It is evident from the figures that the results are not driven by outliers. 33 Finally, in Online Appendix Figure A17, we also present the robustness of the baseline estimates to changing the assumptions about spatial correlation in the data. In particular, we show that the results are robust to allowing for spatial correlation in a radius of any size from zero to at least up to 250 kilometers in addition to the autocorrelation for the full length of the observation period [START_REF] Conley | GMM estimation with cross sectional dependence[END_REF][START_REF] Bester | Inference with dependent data using cluster covariance estimators[END_REF][START_REF] Collela | Inference with arbitrary clustering[END_REF].

Matching. As an alternative identification strategy, we repeat the difference-in-differences analysis in the sample of matched municipalities that do not differ in terms of observable characteristics other than their treatment status, which is the good TVN reception. Panel A of Online Appendix Figure A18 presents the spatial distribution of the dummy for good TVN reception. To build the matched sample, we start with the full sample of all municipalities and compute the propensity score of being treated, i.e., having good TVN reception dummy equal to one, from a probit regression with this dummy as outcome variable and the following covariates: fixed and mobile internet availability in 2009, nighttime light density per capita, average pretreatment level of religiosity (2009)(2010)(2011)(2012)(2013)(2014), pre-2009 level of support for PiS, dummy variables for Austro-Hungarian and Prussian partitions, log total population, and the share of workingage population. We use the propensity score to match treated and untreated municipalities among municipalities without a TVN transmitter. We construct a sample of municipality pairs that are within 50-kilometer distance of each other, such that each treated municipality (with good TVN signal) is matched to the untreated municipality (with the dummy for good TVN signal equal to zero) with the closest propensity score to the treated municipality, subject to the following restriction. For each pair, we impose a minimum distance of one standard deviation in the continuous measure of the TVN signal strength between the treated and untreated mu-32 Formally, let R 2 f e denote the R 2 from a regression with only year and municipality fixed effects (from Column 1 of Table 2) and R 2 obs denote the R 2 from a regression with all observables included (from Column 6 of Table A3). Then, we define A4 replicates the main results restricting the subsample to 2013-2019, i.e., after all transmitters switched from analogue to digital TV signal (see footnote 22 for details). The results are practically unchanged, as one should expect given the absence of pretrends (illustrated in Figure 2). nicipality. Panel B of the Online Appendix Figure A18 maps the municipalities in the resulting matched sample with their treatment status. In the Online Appendix Table A5, we verify that the matched sample is balanced between treated and untreated municipalities for all covariates used in the propensity score calculation, for log cable TV subscriptions in 2009, and for all covariates that were selected by LASSO as determinants of the good TVN or TVPolska signal or their transmitter locations (presented in Online Appendix Table D1).

R 2 max = 1.3(R 2 obs -R 2 f e ) + R 2 f e . 33 Online Appendix Table
As the next step, we use the matched sample to estimate the average treatment effect with difference-in-differences regressions. As some untreated municipalities serve as control for several treated municipalities, we account for this using the appropriate weights in the calculation of the treatment effect. 34 Table 4 presents the average treatment effect in the matched sample and Panel B of Figure 2 presents the corresponding results of the event-study specification. The estimated effects are statistically significant; and the point estimates are remarkably similar in magnitude to the baseline. Furthermore, in the matched sample, we also find that the trends in religious participation between treated and untreated municipalities started to diverge only after PiS came to power.

The number of Catholics. The main outcomes of interest are the ratios of the numbers of mass attendees and Communion takers to the total number of Catholics. Online Appendix Table A6 shows that the results are not driven by the effect of the media environment on the denominator. It considers the log numbers of Catholics, mass participants, and Communion takers as dependent variables and shows that TVN availability did not affect the number of Catholics, but significantly decreased religious participation.

The effect on voting outcomes. State media's propaganda after PiS ascend to power was both pro-Church and pro-PiS. Could the effects of the exposure to TVN on religious participation be a mere consequence of the shift of voter political support for PiS as a result of the change in media environment, which in turn, had an effect on attitudes toward the church? We cannot rule this out completely. However, it is unlikely. In the Online Appendix we present the results using voting for PiS and turnout as outcome variables using the baseline specification. Table A7 shows the average treatment effects and Figure A19 -the event study specification. We find small and insignificant effect of TVN post-PiS on voting for PiS and a strong positive effect of TVN Post-PiS on turnout in the parliamentary elections. The effect on turnout is consistent with the mobilization of both supporters and opponents of PiS. If political preferences were a proximate cause of the effects on religious participation, we would have expected to observe larger effects on the PiS vote share.

Overall, the results are robust and are very unlikely to be driven by omitted unobserved confounders. The analysis of the observational data yields a strong and robust causal countervail- 34 In particular, the matching estimator of the average treatment effect is calculated using the formula:

β m = 1 K T =1 Ti=1 R i -1 K T =1 Tj =0
Ti=1 ω(i, j) R j , where i indexes the treated observations and j indexes the control observations in the matched sample, R stands for a measure of religious participation, T is the treatment status, and K T =1 is the number of treated observations. The regression weight of each control observation j is given by Ti=1 ω(i, j), where ω(i, j) = 1 if the municipalities i and j are matched as treatment and control, and zero, otherwise.

ing effect of the independent TV in an environment where state TV is engaged in propaganda, such that in places where independent TV is available religious participation is smaller than in places where it is not available.

Experimental Evidence

To supplement the results from the observational analysis, we conducted a large online surveyexperiment. 35 We exposed random subsets of Polish voters to information available only on independent media after PiS came to power and then measured their attitudes toward the Church and Church-related behavior, such as trust in religious institutions and donations to Catholic vs. non-Catholic NGOs. The aim of the experiment is twofold: (1) to analyze how different types of information about the Catholic Church that is only available in Poland through independent media affects religious behavior and attitudes; (2) to assess the individual-level heterogeneity in these effects.

The survey-experiment was conducted online in Poland by a consortium of two professional survey companies: CBOS and Opinie.pl. 9,416 voting-age Poles were randomly drawn from a pool of over 100,000 subscribers to the Opinie.pl online platform, i.e., individuals who participate in online surveys for pay. After giving an informed consent, participants were allocated to three roughly-equal-size groups: a control and two treatment groups. Randomization was stratified by 24 strata at the intersection of 4 age groups, 2 gender groups, and 3 education-level groups.

In the analysis, we control for strata fixed effects. The resulting sample has good representation with respect to rural vs. urban status, locality sizes, and regional coverage.

The survey-experiment was conducted in two rounds. The first round took place between April 29 and May 11, 2020. It consisted of a 45-minute survey with an information treatment in the middle that took additional 15 minutes. This survey had three parts: questions about pre-treatment characteristics, randomization into two information treatments and a control group, and questions on post-treatment short-term outcomes. The follow-up round took place two to four weeks later, when all participants answered a 20-minute survey about long-term post-treatment outcomes.36

Experimental Treatments

In this section, we briefly describe the content of the two information treatments, on two topics not available from state media, but covered by independent media, and most notably, TVN: Church's cover-up of child sexual abuse cases by clergy and the political and financial favor exchange between the ruling party PiS and the Church.

Pedophilia Cover-up Treatment: One of the three randomly-assigned groups of participants received information about the cases of sexual abuse of children within the Church and the lack of reaction of Church representatives to these cases. The treatment contained the following elements: (1) a map of Poland with the localization of the pedophilia crimes involving priests-perpetrators, which was prepared by a Polish NGO and submitted in a report to Pope Francis; (2) a video interview with a co-creator of this map, in which she talks about cover-ups by the Catholic bishops of these crimes; (3) two stories about child-abuser priests who, instead of being prosecuted, were moved between parishes despite the fact that their superiors were aware of their crimes; and (4) a video of an attempted interview by an independent journalist with a bishop asking about whereabouts of one of these two priest-abusers, in which the bishop ignores the journalist and does not answer any questions.

Balance

Online Appendix Table A10 reports the results of an omnibus test of randomization quality. We regress the treatment status on all pre-treatment characteristics, separately in the two subsamples: one, including the participants of the Control group and the Pedophilia Cover-up Treatment group, and the other, including the Control and the Church's Ties to PiS Treatment groups. We test for joint significance of pre-treatment characteristics in explaining the treatment status and find that randomization worked well, even though there are few small imbalances across treatment groups. The prediction of treatment status in the first subsample yields the p-value of the test of joint significance of all covariates of 0.99; in the second subsample, the corresponding p-value is 0.46. The fact that pre-treatment characteristics do not predict the treatment status is reflected in the extremely low R 2 in these regressions: 0.006 and 0.010. In the Online Appendix Table A11, we also present a series of conventional balance tests, in which we regress each pre-treatment characteristic on dummies for each treatment and strata fixed effects. These tests confirm the relatively good balance across treatments, despite few significant differences. In the analysis of the treatment effects, we control for the variables that show any 37 To keep the participants engaged and to make the treatments and the experimenter's own attitudes towards the topic inconspicuous, we asked the participants few questions between different pieces of information within each treatment about their attitude towards the facts described in the treatment. With these questions included, the treatment part was not so different from the rest of the questionnaire. In addition, the formulation of these questions provided the participants with a framework to think that one could have different attitudes towards the topic of the treatment. We do not use the answers to these questions in the analysis, as they are treatmentspecific. The experimenter's demands were-to a certain extent-concealed by these questions. We discuss the role of Experimenter Demand Effects in Section 4.6 below.

misbalance when considered individually, as suggested by Gerber and Green (2012, p. 109). These variables are the household size, consumption of social media, turnout in the European 2019 elections, exposure two Polish films, critical of the Church, a fictional film "Clergy" (2018) that depicts corruption within the Church and a documentary "Tell no one" (2019) that exposes priests-pedophiles. Below we find the most robust and sizable effects of exposure to Pedophilia Cover-up Treatment, whereas all of the misbalances, but one, are between the Control and Church's Ties to PiS Treatment. The only exception is a slight misbalance in the household size between the Control and Pedophilia Cover-up Treatment; however, the household size is uncorrelated with the outcomes of interest.

Experiment's Average Treatment Effects

As the randomization was stratified, to get correct inference, one needs to control for strata fixed effects [START_REF] Bruhn | In pursuit of balance: randomization in practice in development field experiments[END_REF]. Furthermore, the most important determinant of the outcomes of interest is the respondent's self-reported pre-treatment religiosity. Even though it is perfectly balanced across treatments (see Online Appendix Table A11), controlling for religiosity substantially increases the precision of the estimated treatment effects. Thus, our baseline estimation of the average treatment effects comes from OLS regressions, in which we regress outcome variables on the treatment status dummies, controlling for strata fixed effects, dummies for each of the five possible answers to the pre-treatment question "Independently of participating in religious practices, do you consider yourself as a religious person?" and, as mentioned above, for few variables that are not balanced across treatments when considered individually.

First round's outcomes. Panel A of Figure 4 and the first two columns of Table 5 present the results for the two main outcomes of the first round: trust in religious institutions and the donations to Catholic foundations, measured right after the treatments. Trust in religious institutions is the first principal component of the questions that measure trust in different religious leaders or institutions; it aggregates trust in the Church, trust in parish priests, in the Episcopate, and in the Pope. The donations to the Catholic foundations is the only outcome of the experiment that reflects an actual choice, rather than a self-reported attitude. We pledged to the participants to donate on their behalf 2500 Polish Złoty-equivalent to $625 in May 2020 or about one half of per-capita monthly nominal GDP-to four Polish charitable foundations that give education scholarships to children and young people. Two of these foundations were affiliated with the Church, the other two were secular. The share of money that each foundation got is proportional to the number of participants who chose that particular foundation. We find that trust in religious institutions is significantly lower in both treatment groups compared to the control group. However, the effect of Pedophilia Cover-up Treatment is substantially and significantly stronger. The donations to the Catholic foundations are also lower in both treatment groups compared to the control group, but the difference is statistically significant only for Pedophilia Cover-up Treatment, despite the fact that we cannot reject the equality of the two treatment effects.

The table reports a number of key statistics on the validity of the estimation with regard to distributional assumptions, multiple hypotheses testing, and attrition. Column 1 of Table 5 focuses on the trust in religious institutions as outcome variable. It shows that even with the corrections for the multiple hypotheses testing, attrition, and randomization inference, Pedophilia Cover-up Treatment significantly reduced trust in religious institutions in the first round. As far as the effect of Church's Ties to PiS Treatment is concerned, the significance of its effect survives corrections for randomization inference, attrition, and one out of three corrections for the multiple hypotheses testing, sharpened-q-value, which is reasonable, but less conservative than other methods; it is our preferred correction method. In Column 2, we present the specification tests for the donations to religious vs. nonreligious foundations as outcome variable. The significance of the ATE of Pedophilia Cover-up Treatment for this outcome survives correcting for attrition, using randomization-t p-value, and using our preferred method of correcting for the multiple hypotheses testing. The effect of Church's Ties to PiS Treatment on this outcome is less precisely estimated: the baseline specification is just below conventional level of significance; and the effect is marginally significant with sharpened-q-value correction. Results for additional first-round outcomes are presented in Online Appendix Section G.1.

Follow-up round's outcomes. The effect of the treatments in the first round could be explained by a temporary increase in the salience of the issues they describe. To test for a longerterm effect, we conducted the follow-up round. The median number of days between the two rounds is 23 days, the minimum is 14 days, and the maximum is 29 days (see Online Appendix Figure A20 for the distribution of the number of days between the rounds). 7,369 respondents participated in the follow-up round. Because the experiment was conducted online, attrition was inevitable. As presented in the Online Appendix Figure A21, the participation rate in the follow-up round was 77.4% in Control group; 79.8% in Pedophilia Cover-up Treatment group, and 77.6% in Church's Ties to PiS Treatment group. The rate of attrition in Pedophilia Coverup Treatment group was slightly but significantly smaller than in the other treatment or control groups. Online Appendix Table A12 formally tests whether this attrition was selective. We follow [START_REF] Ghanem | Testing Attrition Bias in Field Experiments[END_REF] and regress the outcomes of the first round on whether the respondents participated in the second round separately for each treatment and find no significant differences. This suggests that the attrition rates were not driven by the effect of the treatments on the respondents' attitudes. In Online Appendix Table A13, we repeat this analysis substituting the first round outcomes by the pretreatment characteristics. Again, we find no difference between those who attrited between the two rounds and those who did not. These analyses strongly suggest that one could be reasonably sure that the treatment effects in the follow-up round are not a result of a selection bias from attrition.

Panel B of Figure 4 summarizes the results for the main outcomes in the follow-up round. First, it shows that the effect of Pedophilia Cover-up Treatment on trust in religious institutions persisted until the second round. Second, we see a significant negative effect of both treatments on the intention to attend the mass in the future. Thus, we conclude that the results of the experiment are not solely driven by the temporary rise in the salience of the treatments' topics. In Panel C of Figure 4, we consider outcomes that help explain why the effects are persistent. The participants of Pedophilia Cover-up Treatment were significantly more likely to search for the information about pedophilia cases among priests in the media and on the internet between the two rounds. This is presumably because they wanted to verify the information that was provided to them in the treatment. In addition, among the respondents who did not watch the film "Tell no one" before the first round, the participants of both treatment groups were more likely to watch it between the two rounds than the participants of the control group.

Columns 3 to 6 of Table 5 present the formal analysis for the main follow-up-round outcomes. All results significant in the baseline survive all specification tests, with the exception of the two most conservative corrections for multiple hypotheses testing. 38 The fact that we find consistent results in the two rounds suggests there is a real long-term effect of treatments, and in particular of Pedophilia Cover-up Treatment, on the attitude toward the Church.

Magnitudes and the persuasion rates of the experiment

The point estimates of the coefficients on the dummies for each treatment have a straightforward interpretation: the ATEs in percentage points. Exposure to Pedophilia Cover-up Treatment, on average, leads to a 4.6 percentage-point decline in trust in religious institutions in the first round and a 2.2 percentage-point decline in trust in religious institutions in the follow-up round, both relative to trust in religious institutions in the control group. It also leads to a 1.7 percentagepoint decline in the probability to chose a religious foundation over a non-religious foundation for a charitable donation (in the first round) and to a 2.4 percentage-point decline in the intention to attend mass weekly in the future (in the follow-up round). Church's Ties to PiS Treatment, on average, caused a 1.9 percentage-point decline in trust in religious institutions (in the first round) and a 2.2 percentage-point decline in the intent to attend mass weekly (in the follow-up round).

The persuasion rate of exposure to the information about Church's reaction to child sexual abuse by clergy is 12.1% for the decision not to trust religious institutions in the first round and 5.9% in the follow-up round. This treatment also results in the persuasion rates of 7.6% both for choosing to donate to a non-religious rather than a religious foundation and for the intention not to attend mass weekly in the future. Information about mutual favors between the PiS party and the Church results in persuasion rates of 5.2% for the decision not to trust religious institutions (in the first round) and of 7.1% for the decision not to attend the mass in the future regularly (in the follow-up round). Details of these calculations are presented in Section F.2 of the Online Appendix.

Individual-level heterogeneity

Figure 5 shows that, in the first round, exposure to the information about Church's cover-ups of pedophilia scandals among clergy leads to a significantly larger declines in trust in religious institutions among religious people compared to non-religious people, among residents of small towns or rural areas compared to residents of large cities, and among those who are more likely to be exposed to propaganda, i.e., voted for PiS in the past or watch news on TVPolska, compared to those who did not vote for PiS and does not watch TVPolska. Online Appendix Section G.2 presents details of this heterogeneity analysis.

A plausible explanation for this individual-level heterogeneity is that more religious people, those from rural areas or smaller towns, and those who consume propaganda, are simply less aware of the content available only on independent media. This is consistent with the fact that Pedophilia Cover-up Treatment induced some participants to search for information about this problem and to watch the documentary "Tell no-one" after the first round (as shown in Section 4.3). As these individual-level heterogeneities are congruous with those found in the observational data-the effect of TVN is stronger in more religious and rural areas-they help shed light on the mechanism behind observational results. It appears that, when state media is engaged in pro-Church propaganda, the messages of the independent media may not reach an important part of the population in places where independent free-to-air TV is unavailable. This is because people whose prior beliefs are more in line with state propaganda do not search for alternative information if it is not readily available on TV. Religious people and rural residents continue using free-to-air state TV as their primary source of information despite the fact that this TV is dominated by state propaganda and there are possibilities to switch to consuming news on other media, such as, for instance, internet media. For example, all experiment participants by design had access to the internet; yet, it is evident that some of them were unaware of the child abuse within the Church.

Addressing the Experimenter Demand Effects

A potentially valid concern is whether the results of our experiment are driven by Experimenter Demand Effects (EDEs), such as, for instance, the Hawthorne effect [START_REF] Zizzo | Experimenter demand effects in economic experiments[END_REF]. It is impossible to rule EDEs out completely, as the main ATEs go in the direction of the treatments. Yet, in this subsection, we present evidence suggesting that EDEs are not likely to drive our results.

We test for the importance of EDEs in our experiment using the methodology suggested by [START_REF] Dhar | Reshaping adolescents' gender attitudes: Evidence from a school-based experiment in india[END_REF] (see also [START_REF] Henry | Checking and sharing alt-facts[END_REF]. There is one question among those asked before the treatments that can be considered as a measure of "social desirability": "Did you devote last year your time, services, money, cloth or books for charity?" The answers to this question are likely to correlate with the strength of the intrinsic desire of respondents to look good in the eyes of other people, including the experimenters. The share of respondents who positively answered this question is 67%. To test for the EDEs, we examine the heterogeneity of the treatment effects with respect to the answers to this question. If EDEs drove our results, one should expect larger average treatment effects for the respondents who answered this question affirmatively. This is not what we find for any of our four main outcomes. The results are reported in Online Appendix Figure A22 and Table A14; they are inconsistent with EDEs if self-reported donations are a good measure of social desirability (see Online Appendix Section G.3 for details.) This is in line with [START_REF] Mummolo | Demand effects in survey experiments: An empirical assessment[END_REF], who show that EDEs are not common in experiments similar to ours. This is also consistent with the findings of de [START_REF] De Quidt | Measuring and bounding experimenter demand[END_REF], who examine the magnitude of the EDEs and show that they typically are economically small and statistically insignificant even when experimenters explicitly express their demands in the experiment.

Overall, the results of the experiment confirm that both types of information provided by our treatments, which people typically receive through independent media, reduce trust in religious institutions. The effect of providing information about the sexual abuse of children within the Church is persistent, which at least in part is explained by the fact that after being exposed to such information people verify it by reading more about this issue. The results of the experiment corroborate the results on the effect of media on religious participation.

Conclusion

The main lesson from our analysis is that nonreligious media can significantly affect trust in religious institutions and religious participation, suggesting that it also can have an effect on religiosity, a deeply-rooted cultural trait. State-led propaganda, when unchecked, may result in a boost in religiosity among subgroups of the population. Access to independent media, in contrast, can contribute to a secularization trend by playing a significant countervailing role to state propaganda.

We show that the rates of church attendance and taking Holy Communion diverged in Poland between municipalities with and without access to independent TV, after the radicalright populist party PiS came to power in 2015 and transformed state media into an instrument serving government and Church interests. In places with no reception of independent TV, the secularization trend that preceded PiS victory was halted and even partially reversed as the rate of mass participation stabilized while the rate of taking Communion grew after 2015. In contrast, in places where independent TV was available, the fall in the rates of religious participation intensified and viewership of the independent TV increased. The impact of the TV environment is stronger in more religious and rural municipalities. A large-scale online experiment helps to understand how different individuals react to critical information about the Catholic Church that is available in Poland only through independent media. Exposing experiment's participants to information about the exchange of mutual favors between the ruling party PiS and the Church as well as the cover-ups by the Church of cases of child sexual abuse by priests lead to a persistent decrease in trust in religious institutions and a change in religious behavior. Consistent with observational data, the effects of the experimental information treatments are larger among more religious people and those from rural areas and small towns. They are also larger among participants who were less likely to be exposed to independent news media.

The experiment results suggest the mechanism behind the aggregate effects of media environment that we find in the observational data. In those places where independent media are not readily available, some people simply do not have access to information that repudiates state propaganda, including critical information about the Church. More religious people and people in rural areas do not use alternative sources of information such as the internet and social media and instead rely on state television, despite its propagandistic nature. Thus, the availability of independent free-to-air TV channels still remains important in the age of social media and the internet and even for such deeply-rooted traits as religious participation.

Taking Communion

Notes. The figure presents trends in religious participation by TVN's availability. Graphs in Panel A presents the smoothed MA(1) time series of the rates of attending mass and taking Communion separately for municipalities with good and bad TVN signal. Solid lines in each plot represent best linear fit for years before 2015. Graphs in Panel B represents the residual variation in the measures of religious participation over time; obtained from regressing them on year fixed effects, interactions of fixed and mobile internet with municipality dummies, year dummies, time-varying nighttime light density per capita, and dummy variables for a natural disaster in the last three years, along with the interactions of the dummies for Polish partitions with year trends and the interactions of the free-space TVN signal strength with Post-PiS dummy and with 2015 year dummy. We present this figure aggregating by two-year periods to smooth the overtime shocks. .

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. Notes. The table presents the difference-in-differences estimation of the effect of TVN on religious participation after PiS came to power. OLS estimates. The unit of analysis is municipality × year. The dependent variables are the shares of Catholics attending mass and taking Communion in Panels A and B, respectively. The main explanatory variable is the interaction between a measure of TVN reception and post-PiS dummy. In Columns 1 to 5, we measure TVN reception as the dichotomized signal strength, i.e., a dummy for "Good TVN signal strength" that takes the value of 1 in 71% of municipalities. Columns 6 and 7 consider the continuous TVN signal strength at municipality level. Column 1 controls only for year and municipality fixed effects. Column 2, in addition, controls for the interactions of fixed and mobile internet with year dummies, time-varying nighttime light density per capita, dummy variables for a natural disaster in the last three years, and log cable TV subscriptions. Columns 3 to 7 add controls for the free-space TVN signal strength at municipality level interacted with Post-PiS dummy and with 2015 year dummy. Columns 4 and 6 include the interactions of the dummies for historical partitions of Poland with year trends in addition to controls used in Column 3. Columns 5 and 7 include the interactions of the partitions of Poland with year dummies in addition to controls used in Column 3. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the difference-in-differences estimation of the effect of TVN controlling for the signal strength of TVPolska and of the entertainment TV. It also examines the effects of TVPolska and the entertainment TV. OLS estimates.

The unit of analysis is municipality × year. The dependent variables are the shares of Catholics attending mass and taking Communion in Panels A and B, respectively. The dummies for "Good TVN signal strength", "Good TVPolska signal strength", and "Good entertainment TV signal strength" are calculated using the same continuous signal strength threshold, -40 dB.

All regressions control for year and municipality fixed effects and the interactions of fixed and mobile internet with year dummies, time-varying nighttime light density per capita, dummy variables for a natural disaster in the last three years, and cable TV subscriptions. Columns 1, 2, 3 and 5, in addition, controls for free-space TVN signal strength interacted with post-PiS dummy and with 2015 dummy, whereas Columns 1, 4 and 5, control for free-space TVPolska signal strength and free-space entertainment TV signal strength also interacted with the same time periods. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the difference-in-differences estimation in the matched sample of municipalities. OLS estimates. The unit of analysis is municipality × year. The dependent variables are the share of Catholics attending mass in Columns 1 and 2 and taking Communion in Columns 3 and 4. We match each treated municipality (with "Good TVN signal") to a untreated municipality (without "Good TVN signal") within 50 km distance, based on a propensity score imposing a minimum distance of one standard deviation in TVN signal strength between pairs. We exclude from the sample all municipalities with a TVN transmitter antenna. Untreated municipalities are weighted using the weights representing the number of treated municipalities for which they serve as counterfactual. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the estimated ATE of the experimental treatments on religious outcomes in both rounds of the survey-experiment. OLS estimates. The unit of analysis is individuals. In Columns 3 to 6, the sample is restricted to individuals who participated in the follow-up round of the survey-experiment; in Column 6, the sample is further restricted to individuals who did not watch the documentary "Tell no one" before the surveyexperiment. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pre-treatment characteristics reported in Online Appendix Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] are reported in curly brackets. P-values corrected for multiple hypothesis testing using the methods developed by [START_REF] Anderson | Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects[END_REF] (sharpened q-value), [START_REF] List | Multiple hypothesis testing in experimental economics[END_REF] and Steinmayr (2020) (FWER p-value), [START_REF] Holm | A simple sequentially rejective multiple test procedure[END_REF] (Holm-Bonferroni p-value) are reported in square brackets. Lee bounds for the treatment effects [START_REF] Lee | Training, wages, and sample selection: Estimating sharp bounds on treatment effects[END_REF]) are reported at the bottom of the table along with p-values from the test of equality of treatment effects of the two treatments. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes: The figures present binned scatter plots of the relationship between the rate of mass attendance from the Church Census (on the vertical axes) and the average by year and municipality self-reported religiosity measures from the Diagnoza survey in 2009, 2011[START_REF] Belloni | Inference on Treatment Effects after Selection among High-Dimensional Controls †[END_REF], and 2015(Diagnoza, 2015)). The three measures are the shares of respondents who: (1) claim that they attend mass every weak, (2) say that they pray in times of crisis, and (3) chose "God" in the list of several possible alternative answers to the question: "What is the condition of a successful life."

Online Appendix

A Additional Results

A7

Figure A8: Transmitter location and signal strength of the multiplexes used by TVN, TVPolska, and entertainment TV channels Notes. The maps visualize the residual signal strength of different TV networks at the municipality level after controlling for their signal in free space. Authors' own calculation. 2. The horizontal blue lines represent the point estimates; the shaded areas represent the confidence intervals at 90% for different spatial Conley correction thresholds (indicated on the x-axis). Each threshold in each panel represents the confidence interval obtained from a different regression where standard errors are corrected for spatial autocorrelation within that distance threshold and temporal autocorrelation for the whole time period. The results presented for distance threshold "0" are equivalent to the standard errors clustered at the municipality level. The horizontal red lines represent the null effect.

(a) TVN Signal Strength G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F
G F Antennas (b) TVPolska Signal Strength G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F
G F Antennas (c) Entertainment TV Signal Strength G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F

A9

A17

Figure A18: Municipalities with good and bad TVN reception and the matched sample Notes. The maps visualize the "Good TVN signal strength" at the municipality level and the matched sample. We match each treated municipality (with "Good TVN signal") to an untreated municipality (without "Good TVN signal") within 50 km distance, based on a propensity score imposing a minimum distance of one standard deviation in TVN signal strength between municipalities in each pair. We exclude from the sample all municipalities with a TVN transmitter. Propensity score is calculated by regressing a dummy variable, indicating whether a municipality is treated, on the following covariates: fixed and mobile internet availability, nighttime light density per capita in 2009, average pretreatment level of religiosity (2009)(2010)(2011)(2012)(2013)(2014), pre-2009 level of support for PiS, dummy variables for Austro-Hungarian and Prussian partitions, log total population, and share of working-age population. Notes. The figure presents the event-study estimates of the exposure to good TVN signal strength on political outcomes. The unit of analysis is municipality × year. Point estimates and 90% confidence intervals are from OLS regressions of the respective outcome variables on year and municipality fixed effects, conditional on covariates listed in Columns 1 and 3 of Table A7. Years 2011 and 2014 are the excluded time periods for parliamentary and European parliament elections, respectively. Standard errors are corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period. .

(a) Good TVN Signal G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F G F

A19

798

.775 .775 Intends to participate in the mass at least once a week in the future, Follow-up round

⎫ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎬ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎭ ⎫ ⎪ ⎪ ⎬ ⎪ ⎪ ⎭ ⎫ ⎪ ⎪ ⎬ ⎪ ⎪
Notes. The figure presents the heterogeneous effects of the experimental treatments on the main religiosity outcomes with respect to having donated time or money to a charity in the last year, in each round of the survey-experiment. OLS estimates. Each graph on the figure presents results from a different regression. The unit of analysis is individual. All regressions control for randomization strata fixed effects, unbalanced controls reported in Online Appendix Table A11, and initial level of religiosity self-reported in pretreatment survey. P-values from heteroskedasticity-robust standard errors are reported. Notes. The table presents the robustness of the difference-in-differences estimation to controlling for various potential confounding factors. OLS estimates. The unit of analysis is municipality × year. The dependent variables are the shares of Catholics attending mass and taking Communion in Panels A and B, respectively. Column 1 controls for year and municipality fixed effects and the interactions of fixed and mobile internet with year dummies, time-varying nighttime light density per capita, and dummy variables for a natural disaster in the last three years, free-space TVN signal strength interacted with post-PiS and 2015 dummies, and the interactions of the dummies for Polish partitions with year dummies. In addition, Column 2 includes the interactions of dummies for population deciles with year dummies; Column 3 controls for the inte interactions of log altitude of municipalities with year dummies; Column 4 -for the interactions of the pre-2009 level of support for PiS with year dummies; Column 5 -for the interactions of the 2009 level of religiosity with year dummies. Column 6 controls for all additional covariates included in Columns 2 to 5 together. At the bottom of each panel, we report Oster's δ, which is calculated under the assumption that, net of municipality and year fixed effects, the R 2 max is equal to 1.3R 2 from Column 6. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents robustness of the difference-in-differences estimation to restricting the sample to the period after the switch from analogue to digital transmission, 2013-2019. OLS estimates. The unit of analysis is municipality × year. The dependent variables are the share of Catholics attending mass in Columns 1 and 2 and taking Communion in Columns 3 and 4. All specifications control for year and municipality fixed effects, the interactions of fixed and mobile internet with year dummies, time-varying nighttime light density per capita, dummy variables for a natural disaster in the last three years, log cable TV subscribers, the freespace TVN signal strength at municipality level interacted with post-PiS and 2015 dummies, and the interactions of the dummies for Polish partitions with year dummies. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the balance test between treated and untreated municipalities in terms of socio-economic characteristics in the matched sample. The unit of analysis is municipality. The value displayed for t-tests are the differences in the means across the treated and untreated groups. Untreated municipalities are weighted using the weights representing the number of treated municipalities for which they serve as counterfactual. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the difference-in-differences estimation of the effect of TVN on political outcomes after PiS came to power. OLS estimates. The unit of analysis is municipality × year. Panel A considers the national parliamentary elections, while Panel B considers European Parliament elections. The dependent variables are the vote share for PiS in Columns 1 and 2 and turnout rate in Columns 3 and 4. All columns control for year and municipality fixed effects, interactions of fixed and mobile internet with year dummies, time-varying nighttime light density per capita, and dummy variables for a natural disaster in the last three years, and the free-space TVN signal strength at municipality level interacted with post-PiS and 2015 dummies. In addition, Columns 1 and 3 include the interactions of the dummies for Polish partitions with year trends, while Columns 2 and 4 include the interactions of the dummies for Polish partitions with year dummies. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents a test for selective attrition by treatment status between the first round and the follow-up round of the survey-experiment using the religiosity outcomes from the first round. OLS estimates without an intercept.

A25

A26

A29

The unit of analysis is individual. Each coefficient represents the average of the outcome reported in each column title by treatment status × an indicator variable for whether the respondent participated in the follow-up round of the survey. The regressions are conditional on strata fixed effects, unbalanced controls reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses.

The p-values for the test of the equality of means between those who participated and those who did not for each treatment are reported at the bottom of the table. Notes. The table presents a test for selective attrition by treatment status between first round and follow-up round of the surveyexperiment using the pre-treatment characteristics. OLS estimates without an intercept. The unit of analysis is individual. Each coefficient represents the average of the outcome reported in each column title by treatment status × an indicator variable for whether the respondent participated in the follow-up round of the survey. The regressions are conditional on strata fixed effects, unbalanced controls reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. The p-values for the test of the equality of means between those who participated and those who did not for each treatment are reported at the bottom of the table.

A34

B Anecdotal evidence about media environment A British historian and essayist Timothy Garton Ash described the difference between TVPolska and TVN's news coverage of the COVID19 pandemic, by writing: "If you watched only Polish state television news over the last fortnight, you would have no idea that Poland is currently among the countries doing the worst during the pandemic. According to Bloomberg's Covid resilience ranking, Poland has fallen to 50th place among the world's 53 largest economies, with only Brazil, the Czech Republic and Mexico performing worse. 40 But switch on the official news and [...] there are long items about how the government is speeding up the vaccination campaign [...] and how terrible the opposition's record was on public health when it was in power. In other "news," you learn [...] how Christians are being persecuted all over the world and how a grave was recently uncovered showing more victims of wartime German occupation. The propaganda is more extreme but also more skillful than during the last decade of communist rule. Only when you turn to the independent TVN24 news [i.e., a 24-hour version of TVN news] do you see footage of long queues of ambulances waiting outside hospitals, because there are no more intensive care beds, and hear doctors explaining how terrible the public health situation really is.

B.3 Additional sources describing Polsat's pro-government editorial policy

• https://www.newsweek.pl/polska/jak-polsat-pokochal-pis/vckxvg6, accessed September 21, 2022.

• https://www.press.pl/tresc/58523,polsat-news_-obiektywnie-w-prawo, accessed September 21, 2022.

• https://www.wirtualnemedia.pl/artykul/spot-pis-platne-ogloszenie-spoleczne-partii-politycznejprogram-po-polsat-tvp, accessed September 21, 2022.

• https://innpoland.pl/143433,solorz-wpadl-we-wlasne-sidla-chcial-byc-obok-teraz-musi-chwalicrzad, accessed September 21, 2022.

B.4 Pro-PiS and pro-Church propaganda outside TVPolska

PiS's efforts to influence Polish population are not limited to propaganda on TV. PiS has also transformed radio and print media environment in Poland by means of heavily subsidizing pro-PiS and pro-Church content and exercising political pressure on those media that do not comply.

Radio:

The state radio company Polskie Radio owns four stations: Jedynka (PR1), Dwojka (PR2), Trojka (PR3), and Czwórka (PR4). They have seen a similar content transformation to the one at TVPolska after PiS came to power. For example, according to the data provided by the Polskie Radio to the Polish broadcasting regulator (KRRiT), in the first three quarters of 2022, Polskie Radio devoted 294 hours to PiS and 40 hours to the main opposition party, Civic Platform (https://www.rp.pl/polityka/art37483261-pluralizm-w-polskimradiu-294-godziny-dla-pis-40-godzin-dla-platformy, accessed May 5, 2023).

The two state radio stations with regular news programs, Jedynka (PR1) and Trojka (PR3) have nearly universal coverage. The maps of areas with reception of these radio stations without an amplifier are available here: PR1 -https://www2.polskieradio.pl/czestotliwosci/jedynka.aspx (accessed May 5, 2023) and PR3 -https://www2.polskieradio.pl/czestotliwosci/trojka.aspx (accessed May 5, 2023).

Another important medium of pro-PiS and pro-Church propaganda is a private Catholic radio, Radio Maryja, which is part of a media network created by Father Tadeusz Rydzyk that gets generous funding from state budget since 2015. Data on transmitters and signal coverage of Radio Maryja's are available here: https://fmscan.org/net.php?r=f&m=m&itu=POL&pxf=Radio+Maryja (accessed May 5, 2023).

We have verified that at least one of these three radio stations (PR1, PR3, or Radio Maryja) is available in every municipality where TVPolska has poor reception.

Press: Since 2015, PiS also controls the content of a large number of print media by providing them with state funds in exchange for support and for dissemination pro-PiS propaganda. There are many articles describing this phenomenon in the few independent media outlets that remain, see, for instance: elderly population (aged 65 or more) by dividing the number of population in each category by the total population in 2007. In our regression analyses, we set the share of young population as the omitted category.

Education structure of population. The data on education of municipal population come from the Census of 2002, which is provided by the Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We compute the share of population with higher education, the share of population with secondary education, and the share of population with less than secondary education by dividing the number of population in each category by the total population in 2002. In our regression analyses, we set the share of population with less than secondary education as the omitted category.

Access to railways. The data on railway network come from [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF]. We generate a dummy variable indicating whether a municipality is within 10-km distance from the railway network in 2006.

Wages. The data on the average wage level at the municipality level in 2007 come from the Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We compute the relative wages of each municipality with respect to the country average, by dividing the average wages in the municipality by the average wage in Poland in 2007.

Municipality revenue. The data on municipality revenue in 2007 come from the Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We compute the municipal revenue per capita by dividing the total municipality revenue by population in 2007, then taking its natural log.

European Union subsidies. The data on European Union (EU) subsidies in 2007 comes from the Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We compute the EU subsidies per capita by dividing the total amount of EU subsidy each municipality received by population in 2007, then taking its natural log.

Industrial production. The data on industrial production levels in 2007 are available at the county level and come from Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We divide the value of industrial production by the total population in 2007 and take its natural log.

Employment in agriculture. The data on employment in agriculture in 2005 are available at the county level and come from Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We compute the share of population employed in agriculture by dividing the number of people working in agriculture by the total employment level in 2005.

Language proficiency. The data on language proficiency are available at the county level and come from the 2002 Census, which is provided by the Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022). We compute the share of population that speaks only Polish by dividing the their number by the total population in 2002.

Support for PiS. The data on the support for PiS in the period before 2009 come from the Official Electoral Commission of Poland (Panstwowa Komisja Wyborcza, http://pkw.gov.pl/, accessed October 20, 2022). We compute the share of votes for PiS by dividing the number of valid votes for PiS by the total number of valid votes for the presidential election in 2005, the parliamentary election in 2007, and for the European Parliament election in 2009. Then, we compute the first principal component of these three variables to generate our pre-2009 support for PiS.

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Religious participation. The data on religious participation, i.e., mass attendance (Dominicantes) and taking Holy Communion (Communicantes), in 2009 at the municipality level comes from the Institute of Statistics of the Catholic Church [START_REF] Iskk | Dataset on religious participation in Poland at municipality level. The same data at diocese level are freely available from the same source[END_REF]. We compute the first principal component of these two religious participation measures to generate our religious participation variable in 2009.

Other geographical characteristics. The data on elevation come from the MODIS Land Digital Elevation Model provided by the NASA, with a 15 arc seconds resolution (https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MODDEMHKM, accessed October 20, 2022). We compute the average altitude of each municipality and take its natural logs. We use the definition provided by the Central Statistical Office of Poland (https://stat.gov.pl/, accessed October 20, 2022) to classify municipalities as rural areas and cities.

Table C1: Aggregation level and time availability of control variables

Covariate Aggregation

D Determinants of TV signal and the location of antennas

In this section, we explore the correlates of the cross sectional variation in the signal strength of different TV networks. Table D1 presents the results of cross-municipality OLS regressions. As dependent variable, Columns 1 to 4 use dummies for having a good signal strength in the municipality for the two main transmitting networks that we study: one used by TVN and Polsat and the other used by TVPolska. To illustrate the residual variation in TV availability that is the basis of our identification strategy, we account for the proximity to transmitters by controlling for the free-space signal strength. Columns 5 to 8 illustrate the correlates of transmitter locations; they use the dummies for the presence of a transmitting antenna in the vicinity of 10 kilometers for TVN and TVPolska as dependent variables. We regress these variables on a long list of socio-economic, geographical, and historical municipal characteristics.

Because the list of potential correlates of the signal strength is long and many of them are strongly correlated, we also use the robust LASSO method [START_REF] Belloni | Inference on Treatment Effects after Selection among High-Dimensional Controls †[END_REF] to select the most relevant correlates of the TVN's and TVPolska's availability. 42 The full list of considered covariates is as follows: dummy for the top population decile, dummies for historical partitions of Poland, log altitude, share of population employed in agriculture, speed of 3G mobile internet, shares of population with different education levels, log night-time lights per capita, share of working age population, log distance to optic-fiber internet nodes, railways within 10 km, log municipality revenue per capita, log EU subsidies to municipality per capita, wages relative to country average, log industrial production per capita, rural dummy, share of elderly population, share of population that speaks only Polish, log number of cable TV subscriptions, religious participation in 2009, and pre-2009 support for PiS. (Online Appendix Section C provides definitions of each of these variables.) Odd columns present the "kitchen-sink" regressions with all covariates included; even columns show the results of regressions with covariates selected by LASSO. Online Appendix Table D2 presents a similar analysis of the correlates of the availability of the entertainment TV. One should expect transmitters to be placed in locations that allow reaching larger numbers of people and more developed areas. This is exactly what we find. Column 1 shows that a good reception of TVN network (available in 71% of municipalities) is significantly more likely in municipalities that are in the top population decile, have higher nighttime light density, are closer to optic-fiber nodes, and have lower share of agricultural employment. Column 2 shows that the only robust significant drivers of variation in TVN availability, once we control for free-space signal strength, are the dummy for the top population decile and the dummy for the historical Austro-Hungarian partition of Poland. The historical partitions matter for TV availability due to local topography, which affects how far the TV waves can travel. There is a higher number of TVN transmitters in mountainous areas in the south-East of Poland that coincide with the Austro-Hungarian partition (see Columns 5 and 6); but the reception in these areas is weaker (Columns 1 and 2). Similarly, if anything, there is a lower reception, but more transmitters in municipalities with higher average altitude. Columns 3 and 4 show that there is significantly smaller likelihood of a good TVPolska reception in agricultural areas. It is also the case for the entertainment TV reception (see Online Appendix Table D2).

The fact that many potential covariates of the good TV reception are not picked up by LASSO highlights the overwhelming importance of controlling for free-space signal strength, which accounts for all characteristics that correlate with proximity to transmitting infrastructure, and for partition dummies, which account for topographical differences that happen to correlate with levels of religiosity [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF]. In particular, the reli-gious participation in 2009-the initial level of our main dependent variables-is not chosen by LASSO as an important correlate of the good TV signal strength for both any of the TV channels. Yet, as we show in Table D3, mass attendance in 2009 is negatively and significantly correlated with the dummy for good TVN signal strength and the rate of taking Communion in 2009 is negatively correlated with good TVPolska signal strength when no additional covariates are included. The table also shows that this correlation disappears once we condition on the historical partitions of Poland, to account for a much higher level of religious participation in the former Austro-Hungarian partition [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF], and on the free-space signal strength, to account for other correlates of the proximity to transmitters [START_REF] Olken | Do television and radio destroy social capital? evidence from Indonesian villages[END_REF]. Our baseline specification, presented below, controls for partitions-by-year fixed effect and free-space signal strength interacted with post-PiS dummy. In the robustness section, we also show that our results are robust to controlling for the population-decile dummies, log altitude of municipalities, initial political preferences, and initial levels of religious participation and interacted with year fixed effects.

A47

E The Calculation of the Slope of the Pretrend That We Can Reject

Assume that there is a linear pretrend with slope ζ and that the time-varying coefficients on TV signal are jointly normally distributed. The mean of these coefficients is (Sζ,4ζ,3ζ,2ζ ,ζ), where S is the average difference in the number of years between the period t -1 and each of the period before t -5. (Taking into account the fact that S ≤ 5 and that the pretrend is more easily rejected for larger S, for simplicity, we set S = 5.) For a given ζ, we take the variance-covariance matrix from the estimation of the 5 pre-event coefficients in the event study and perform 100,000 random draws from the corresponding multivariate normal distribution. We calculate the percentage of draws with at least one of the pretrend coefficients significant at 10% significance level. Then, we find those ζ for which in 90% of draws at least one of the pretrend coefficients is significant. It is equal to -0.18 for the rate of mass attendance and -0.104 for the rate of taking Communion. Finally, we compare these numbers to the absolute values of the corresponding treatment effects from Column 5 of Table 2, -0.574 and -0.355.

F The Calculation of Persuasion Rates

In this section, we present the exact calculations of persuasion rates. Subsection F.1 focuses on the results using observational data, whereas Subsection F.2 focuses on the results of the experiment.

F.1 Persuasion rates implied by the analysis of the observational data

To compare the magnitude of these effects to those from other persuasive communications studied in the literature, we calculate the persuasion rates relying on the formula developed by DellaVigna and Kaplan (2007):

f = 100 × y T -y C e T -e C × 1 1 -y 0 , (F.1)
where f stands for the persuasion rate, y is the behavior of interest, e is exposure, subscripts T and C stand for treatment and control groups, respectively. y 0 is the share of subjects who would adopt the behavior of interest in a hypothetical case of no message. For an infinitesimally small change in exposure to the message de, the formula becomes [START_REF] Enikolopov | Media and political persuasion: Evidence from Russia[END_REF]:

f = 100 × 1 1 -y 0 (t dy de + y dt de ). (F.2)
Persuasion rate of TVN to abstain from religious participation. First, we calculate the persuasion rate of TVN, such that y refers not going to the mass and not taking Communion.

In order to apply this formula to the estimates of the effect of local TV signal on local religious participation, several assumptions are needed. First, one needs to define exposure, i.e., explain how the change in local TVN signal (denoted by s) affects viewers' exposure (e) to the messages critical of the Polish Catholic Church. With this additional notation, Equation (F.2) becomes:

f = 100 × 1 1 -y 0 × dy ds × 1 de/ds . (F.3)
To find de ds , we first measure the share of people watching TVN among those who watch either TVN or TVPolska main prime-time news programs. In Table 1, we show that TVN A48 signal strength is significantly associated with a higher share of people watching TVN's news. To proxy for de ds , we multiply the coefficient on "Weighted mean 1{Good TVN signal strength}" from Column 2 of Table 1, which we denote as dV ds , by the share of households in Poland having access to TV, i.e., 98%.43 V here stands for "viewership."

To measure dy ds , we consider the coefficients on "1{Good TVN signal strength} × Post" and "1{Good TVN signal strength} × 2015" obtained from Column 5 of Table 2, divided by 100. As they are expressed relative to the number of Catholics, we multiply them by the share of Catholics in Poland. We assume that the share of Catholics is unaffected by TV coverage and retain that 87% of Poles are Catholics (see the background section for the source). y 0 is the share of Poles that would not go to the mass or not take Holy Communion if there were no TVN. To estimate their values, we use the regressions of Column 5 of Table 2 and predict the share of Catholics attending the mass or taking Communion at the municipality level, if no place had access to TVN. We then consider the population weighted value at the national level to compute the share of Catholics not going to the mass or taking Communion. The respective estimates are 67.2% and 86.2%, which we multiply by the share of Catholics. Finally we add the 13% of non-Catholics who never go to the mass or take Communion to obtain our estimate of y 0 .

Thus, the persuasion rates can be written as:

f = 100 × 1 1 -0.13 -0.87 × ỹ0 0.87 100 × dỹ ds 1 0.98 × dV ds , (F.4)
where ỹ0 is the share of Catholics attending the mass or taking Communion.

This implies the following numbers for the persuasion rates:

• For the outcome of not attending the mass: Persuasion rate of state propaganda. We can also calculate the persuasiveness of state propaganda, i.e., compute the persuasion rate of not having access to TVN on attending mass and on taking Communion. In this case, we adjust the formula as follows: To estimate the share of Catholics not going to the mass (1 -ỹ0 ), we use the same regressions of Column 5 of Table 2 but now predict the share of Catholics attending the mass or taking Communion at the municipality level, in a hypothetical scenario in which TVN is available in all municipalities, and thus, state propaganda is counter-balanced. Again, we then consider the population weighted value at the national level.

f = 100 × 1 1-0.
f = 100 × 1 1 -0.
This implies the following numbers for the persuasion rates:

G Additional Experiment Results

G.1 Additional first-round outcomes

Table G1 presents the results for each of the components of the trust in religious institutions separately. It shows that Pedophilia Cover-up Treatment affected all components, whereas Favor Exchange Treatment affected only trust in the Episcopate, which is not surprising because Episcopate is featured in this treatment. Table G2 focuses on how the respondents assess the importance of pedophilia problem in the Church. We asked whether the respondents agree that:

(1) "the reaction of the Church to these cases is insufficient," (2) "the problem of pedophilia in the Church is exaggerated," and (3) "the news about pedophilia in the Church is a deliberate attack aimed at reducing the authority of the Church." Pedophilia Cover-up Treatment makes respondents more aware of and concerned about this problem. There is also some, albeit less robust, effect of Favor Exchange Treatment on these outcomes. Table G3 focuses on the attitude of respondents to religious education and whether it should be conducted at school or on the parish premises. Pedophilia Cover-up Treatment raises the share of respondents who think that religious education should be done at school because of a better control of what priests do with the children. Tables G4 andG5 show that Favor Exchange Treatment has a significant negative effect on support for PiS, whereas trust in political institutions generally is not affected by either treatment. These results on the political outcomes are in line with the hypotheses outlined in the pre-analysis plan. We consider them auxiliary, as we focus on religiosity outcomes in this paper.

G.2 Heterogeneity of results in the experiment

We examine heterogeneity of the experiment's results along the following three dimensions, measured before treatments: (1) whether the respondent considers oneself a religious person (26% of respondents are not religious); (2) whether the respondent lives in rural areas or small towns vs. in large cities (44.8% of respondents live in large cities, i.e., with population greater than 50,000), and (3) whether the respondent is, a priori, more or less likely to be exposed to independent media. For the third dimension of heterogeneity, we combine two pre-treatment characteristics: whether respondent voted for PiS in the past and whether respondent watches TVPolska. 44 We deem those who never voted for PiS and those who do not watch news on TVPolska more likely to have been exposed to independent media prior to our experiment than the rest of the sample (those people constitute 59% of respondents). In all three dimensions of heterogeneity, we find statistically significant differences in the size of the effect of Pedophilia Cover-up Treatment on trust in religious institutions in the first round. Exposure to the information about Church's cover-ups of pedophilia scandals among clergy leads to a significantly larger declines in trust in religious institutions among religious people compared to non-religious people, among residents of small towns or rural areas compared to residents of large cities, and among those who voted for PiS in the past or watch news on TVPolska compared to those who did not vote for PiS and does not watch news on TVPolska. Tables G6 to G8 report the results. The heterogeneities for trust in religious institutions in the follow-up round tend to go in the same direction, but they are less pronounced. Only one result is significant: the decline in trust in religious institutions as a result of exposure to Pedophilia Cover-up Treatment is significantly higher for residents of rural areas and small cities as compared to residents of large cities. The only significant heterogeneity of the effect of Favor A51 Exchange Treatment is with respect to religiosity level: religious people were significantly more affected by the information provided in this treatment as well. Figure G1 visualizes heterogeneity results for the outcomes of the follow-up round. Most of them are not statistically significant, but they do go in the same direction as for first-round trust in religious institutions. The heterogeneity is significant only with respect to the type of resident's locality for the follow-upround outcome of the intent to attend mass weekly in the future.

G.3 Details of the test for EDE

As reported in Table A14, for the trust in religious institutions both in the first and the follow-up rounds, as well as for the choice between religious and non-religious charitable foundations, we find insignificantly smaller treatment effects among participants who positively answered the question about whether they donated time or money to charity in the last year. For the intention to attend mass weekly in the future, the treatment effects are the same irrespective of the answer to the question on self-reported donations. In Figure G2, we report heterogeneity of results when we further split the sample of respondents who donated to charity last year into those who donated to a religious charity (19%) and to a non-religious charity (81%). As those who donated to a religious charity are predominantly religious, we find a result that is consistent with other results on heterogeneity with respect to religiosity: the treatment effects are the strongest among those who donated to religious charity. Yet, as they are a small minority, the treatment effects for the group that combines those who donated to a religious charity and to a non-religious charity are smaller than for those who did not donate to charity.

H Description of the Survey-Experiment

Sections H.1 and H.2 of this section of the Online Appendix present the transcripts of both treatments. Sections H.3 and H.4 present the full transcripts of the questionnaires, including the introduction and the full set of questions with possible answers in each of the two waves of the survey-experiment.

H.1 Pedophilia Cover-up Treatment

Screen 1: Agata Diduszko-Zyglewska, a journalist, together with a member of the Polish parliament, Joanna Sheuring-Wielgus, have created a data base of the cases of pedophilia crimes committed by priests of the Catholic Church in Poland. This information was the basis of the report that they submitted to the Pope on the 20th of February 2019.

This report contained the following map. Please, look at it carefully: Screen 2: And now please watch a short extract of an interview with Agata Diduszko-Zyglewska (one of the co-authors of the map) who explains the problem of pedophilia in the Catholic Church. (Video can be accessed with the following link: https://vimeo.com/393419992 using the password "treatment1".)

G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G GG G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G
Transcript of the video:

A63 "Hierarchs of the Catholic Church think that priests can abuse children. In case of other pedophiles -because cases of pedophilia occur not only in the Church, they also occur within families -pedophiles who are not ecclesiastic go to prison and nobody has any doubt that this is the only way of reparation for victims. Priests pedophiles go to another parish: that is why we talk about it separately. Common pedophiles usually hurt one or a couple of children. A priest pedophile can operate for decades: he is protected by bishops, and by the institution of the Church. That is why he can hurt a dozen or even several dozens of children."

Screen 3: Do you want to see the video once again?

• Yes

• No

Screen 4: Do you agree with the arguments of Agata Diduszko-Zyglewska?

• Yes, I completely agree

• I partly agree and partly disagree

• No, I completely disagree

• Difficult to say

Screen 5: Media have reported on many of the cases described on the map created by Agata Diduszko-Zyglewska and Joanna Sheuring-Wielgus.

Here is one of such cases. On February 19, 2020 a criminal state trial opened in Nowy Targ against Priest Marian W. from Tarnow diocese, who is accused of having sexually abused 11 boys, 7 of which were under the age of 15, between 2003 and 2012. Already in 2013, the priest was condemned for sexual abuse of children in the canonical trial within the Church: he could not work with children any longer and was supposed to get a treatment. However, the Church did not inform the state prosecutor about this case.

It was only in May 2018 when a new accusation of priest Marian W. arrived to the Tarnow Curie, that the Curie informed the prosecutor. A new law adopted in 2017 was then already applicable: it made mandatory to report to the state prosecutor about known cases of pedophilia.

According to the prosecutor's act, priest Marian W. was abusing kids at presbyteries and on vacations for which he was taking kids. In 2018, one of his victims committed suicide.

Since 1978 when priest Marian W. started to serve, he was vicar and rector in several parishes and worked with children. The church moved him from parish to parish within Tarnow diocese. This is a map showing places where Priest Marian W. worked during 2003-2012: Screen 6: How do you evaluate the behavior of Tarnow Curie? Do you think . . .

• Tarnow Curie was right -although it did not report about the abuse to the state prosecutor, but according to the law applicable then did not have to do it

• Tarnow Curie was wrong -whatever the law applicable then it should have reported to the state prosecutor

H.2 Church's Ties to PiS Treatment

Screen 1: Please read carefully a short text documenting the relationship between the political party Law and Justice (PiS) and the Church. As you probably remember, parliamentary elections took place in autumn 2019. PiS won the majority enabling him to form a government.

Screen 2: In the program PiS in the chapter "Values and principles" we can read: "... The Catholic Church is a depositary and spokesman for the moral teaching commonly known in Poland. In a wide social sense, it does not have any competitor and that is why it is fully justified to say that only nihilism can be opposed to moral teaching of the Catholic Church..."

During an election rally in Lublin on September 6, 2019, Jaroslaw Kaczynski said: "This nihilism we reject because nihilism . . . destroys everything." Screen 4: Here is an example of how some priests and bishops express support for PiS during Sunday homilies. Bishop Senior of Czestochowa, Antoni Dlugosz, said in his homily in January 2018: "We are grateful for the wonderful two years of government, the best years for Poland. Our hope is back." Some priests also appeal for voting for PiS candidates and help organizing rallies for them: A PiS candidates for the position of the president of Siedlce in local elections in 2018, Karol Tchórzewski, organized an electoral meeting in the Chapel of Blessed Virgin in the Saint Stanislas Church A parish priest in Wierzbna announced the collection of signatures supporting the candidacy of the president Andrzej Duda for the upcoming presidential election.

Screen 5: The PiS party supports Catholic media financially and expresses gratitude for their support.

According to OKO.press, since the beginning of PiS government, the total amount of public subsidies allocated to different projects of father Rydzyk amount to over 214 million zlotys (214.158.441 zl).

Please watch a short video from the celebration of the 28th anniversary of the of Radio Maryja on December 8, 2019, two months after the last parliamentary elections, in which the Minister of Defense, Mariusz Blaszczak, reads a letter from Jaroslaw Kaczynski thanking father Rydzyk. (Video can be accessed with the following link: https://vimeo.com/409040943 using the password "treatment3".) Transcript of the video: A67 "Taking this opportunity I would like to thank for your support of Law and Justice party, support of the camp of the United Right, expressed in the parliamentary elections. Thanks to your votes we have absolute majority in Sejm and we can continue our Polish politics of independence. There is another electoral battle awaiting us in spring, which we have to approach extremely mobilized, because a lot of things will depend upon its results." Screen 6: Do you want to see the video once again?

• Yes

• No

  using survey data from nine waves of ESS in 2002-2017 and three waves of EVS in 1999-2017, as well as with measures of actual religious participation collected by the Polish Institute of Statistics of the Catholic Church (ISKK, 2020) in 2009-2019. We benchmark the survey data for Poland with data on other predominantly Catholic European countries.

  Church's Ties to PiS Treatment: The second group of participants received the following information about the relationship between the political party PiS and the Church: (1) quotes from the PiS party manifesto, which assigns the Catholic Church a role of moral authority in Poland; (2) examples of how Catholic priests express their support for PiS during Sunday homilies, appeal for voting for PiS candidates, and help organizing rallies for PiS on Church's premises; (3) evidence of a financial support of Catholic media by the PiS government; (4) a video of a PiS leader expressing gratitude for Church's support during elections.37

Figure 1 :

 1 Figure 1: The similarity of tweets from official Twitter accounts of the main TV networks (a) Content similarity of TVPolska and TVN accounts with their own content in 2014

Figure 2 :

 2 Figure 2: Event-study specification: religious participation, full sample and matched sample

Figure 3 :

 3 Figure 3: Trends in religious participation by good and bad TVN signal strength

Figure 4 :

 4 Figure 4: Experimental ATE on the key experiment's outcomes (a) First-round outcomes

Figure 5 :

 5 Figure 5: Heterogenous experimental effects on trust in religious institutions in the first round

Figure A1 :A1Figure A2 :A2Figure A3 :A3Figure A4 :A4Figure A5 :A5Figure A6 :A6Figure A7 :

 A1A2A3A4A5A6A7 Figure A1: Self-reported religiosity in Poland compared to other European countries (a) Weekly mass attendance, 2018

A8Figure A9 :

 A9 Figure A9: Quartiles of signal strength of the multiplexes used by TVN, TVPolska, and entertainment TV after controlling for their signal strength in free space (a) TVN signal strength net of free-space signal Ü

Figure A10 :Figure A11 :A11Figure A12 :A13Figure A14 :A14Figure A15 :A15Figure A16 :A16Figure A17 :

 A10A11A12A14A15A16A17 Figure A10: Correlation between signal strength in 2015 and 2019 (a) TVN

Figure

  Figure A19: Event-study specification, political outcomes (a) Dependent Variable: Support for PiS in parliamentary elections

Figure A20 :A20Figure A21 :

 A20A21 Figure A20: Distribution of difference in days between two rounds

  " 41 B.2 Additional example of TVN's coverage of Church sex scandals In November 2020, TVN showed a reportage entitled "Don Stanislao. The second face of cardinal Dziwisz" containing evidence that cardinal Stanislaw Dziwisz, Archbishop of Krakow and the personal secretary to the Pope John Paul II, took part in covering up cases of sexual abuse by Catholic priests both in Poland and in other countries (see https://www.polishnews.co.uk/reportage-don-stanislao-the-other-face-of-cardinal-dziwiszpolitical-comments/ (accessed May 21, 2021).

  r i s o n e r s / c a s e s e n d e d wi t h a v e r d i c t ! ( Ca s e s r e p o r t e d i n t h e me d i a G Re p o r t s o f v i c t i mi z e d p e r s o

•

  Difficult to say A64 Screen 7: Below there is another case from the pedophilia map. OKO.press, an online media, described in 2018 the case. A priest, Ks. Wincenty Pawlowicz, from Lowicka diocese, suspected of sexually abusing children was moved from one parish to another between 1992 and 2002. In 2003, he was condemned for 3 years of prison. When he got out of prison in 2006, he still worked with children in a parish near Odessa in Ukraine. When he returned to Poland in 2017 he led an advent retreat with children in the Kashubia region. Journalists tried to ask the whereabout of priest Pawlowicz, but the Curie did not reply. Screen 8: Please watch a short video of a reportage of OKO.press, in which a journalist asks the bishop Dziuba of Lowicz diocese about the place of living of priest Pawlowicz. (Video can be accessed with the following link: https://vimeo.

Screen 3 :

 3 Do you think that the theses included in the program of PiS and the statement by Jaroslaw Kaczynski conform or not to the spirit of the Polish Constitution, which affirms the impartiality of the state as far as religious questions are concerned?

Table A11

 A11

, and initial level of religiosity self-reported in pre-treatment survey. P-values from heteroskedasticity-robust standard errors are reported.

Table 1 :

 1 TVN and TVPolska prime-time viewership and TVN's signal availability The table presents the effect of TVN good reception on the share of viewers of the TVN's main prime-time news among the viewers of both TVN's and TVPolska's prime-time news programs in Columns 1 to 4 and on the log prime-time viewers of TVN and TVPolska in Columns 5 to 8. OLS estimates. The unit of analysis is region × year. The measure of the presence of the TVN signal is the region's population-weighted average of the dummies for good TVN signal across region's municipalities. Column 1 controls only for year fixed effects. Columns 2, 5, and 7, in addition, control for the measure of TVN's signal in free space and the log number of all viewers of TVN and TVPolska at prime time. Columns 3, 6 and 8 also includes region fixed effects to the list of covariates. Column 4 also adds controls for log number of subscribers to cable TV and internet availability interacted with year fixed effects. Standard errors corrected for clusters at the regional level are reported in parentheses. Given the limited number of clusters (16), following[START_REF] Cameron | Bootstrap-Based Improvements for Inference with Clustered Errors[END_REF], we report wild-cluster bootstrap-t p-values for null hypothesis at the bottom of the table. We use Stata command boottest provided by[START_REF] Roodman | Fast and wild: Bootstrap inference in stata using boottest[END_REF] to bootstrap-cluster at the region level with 1,000 replications. * p < 0.10, ** p < 0.05, *** p < 0.01.

	Dependent variable:

Notes:

Table 2 :

 2 Religious participation and TVN

	(1)	(2)	(3)	(4)	(5)	(6)	(7)

Table 3 :

 3 Religious participation and other TVs

	Sample:	All	Good	Good	Bad TVN	All
		municip. TVPolska Entert. TV reception municip.
		(1)	(2)	(3)	(4)	(5)

Table 4 :

 4 Religious participation and TVN: Results in the matched sample

	Share of Catholic population
	attending mass taking Communion
	(1)	(2)	(3)	(4)

Table 5 :

 5 Experimental ATE: Religiosity outcomes, Both rounds

	First-round outcomes		Follow-up round outcomes
				Attend	Searched	Watched
	Trust in	Donated	Trust in	mass	stories	the movie
	religious	to religious	religious	weekly	about	Tell no one
	institutions foundations institutions	in future	peadophilia since treatment
	(1)	(2)	(3)	(4)	(5)	(6)

up (T1) Church's Ties to PiS (T2)

  ⎭ Test for Experimenter Demand Effects

			Trust in religious institutions (PCA),		Trust in religious institutions (PCA),
			First round				Follow-up round
		Participated in the follow up Pedophilia Cover-up (T1)	Pedophilia Cover-up (T1)
	.835	Donated to charity				Donated to charity
		Did not donate to charity				Did not donate to charity
	.81
		Church's Ties to PiS (T2)				Church's Ties to PiS (T2)
		Donated to charity				Donated to charity
	.785	Did not donate to charity				Did not donate to charity
		-.1	-.05	0	.05	-.1	-.05	0	.05
	.76	Chose a religious foundation to donate, First round
	.735 Pedophilia Cover-up (T1) Donated to charity Did not donate to charity Donated to charity Did not donate to charity Pedophilia Cover--.1	Control -.05	0	Church's Ties to PiS (T2) .05 Donated to charity Did not donate to charity Donated to charity Did not donate to charity Pedophilia Cover-

Notes. The figure presents the ATE of the experimental treatments on the participation status in the follow-up round of the survey-experiment. OLS estimates. The figure presents results from a single regression. The unit of analysis is individual. The regression controls for randomization strata fixed effects, unbalanced controls reported in Table

A11

, and initial level of religiosity self-reported in pre-treatment survey. P-values from heteroskedasticity-robust standard errors are reported.

A21

Figure

A22:

up (T1) Church's Ties to PiS (T2)

	-.1	-.05	0	.05

Table A1 :

 A1 Descriptive statistics: Observational study Mean Median SD Min Max Obs.

	Panel A: Religious participation
	Share of Catholic population attending mass	35.1	32.9	12.3	4	231 26,629
	Share of Catholic population taking Communion	14.7	13.7	5.7	0	147 26,629
	Share of Catholic pop. attending mass [winsorized top 1%]	35.0	32.9	11.8	4	71 26,629
	Share of Catholic pop. taking Communion [winsorized top 1%] 14.6	13.7	5.3	0	35 26,629
	Panel B: TV antennas and signal strength
	TVN antenna within 10 kms in 2015	0.052	0	0.222	0	1	2,478
	TVPolska antenna within 10 kms in 2015	0.177	0	0.382	0	1	2,478
	Entertainment TV antenna within 10 kms in 2019	0.071	0	0.256	0	1	2,478
	Good TVN signal in 2015	0.711	1	0.453	0	1	2,478
	Good TVPolska signal in 2015	0.897	1	0.303	0	1	2,478
	Good entertainment TV signal in 2019	0.724	1	0.447	0	1	2,478
	Panel C: Fixed and Mobile Internet, Night-time lights per capita, Disasters
	Log distance to optic-fiber internet nodes (km)	1.016	1	0.507	0	3	2,478
	Speed of 3G mobile internet	38.494	38.5	9.825	9	74	2,478
	Night-time lights per capita until 2011	0.212	0	0.631	0	10 27,258
	Night-time lights per capita after 2011	0.048	0	0.100	0	6	27,258
	Occurence of natural disaster	0.160	0	0.366	0	1	27,478
	Panel D: Cross-sectional covariates
	Austro-Hungarian partition	0.144	0	0.351	0	1	2,478
	Prussian partition	0.410	0	0.492	0	1	2,478
	Russian partition	0.447	0	0.497	0	1	2,478
	Population (1000s)	15.3	7.4	50.7	1	1707 2,473
	Share of working age population	67.0	67.5	3.0	48	78	2,473
	Share of elderly population	15.8	15.4	3.3	7	42	2,473
	Share of population with higher education	6.1	5.1	2.8	2	31	2,473
	Share of population with secondary education	17.8	17.0	3.9	7	30	2,473
	Share of population employed in agriculture	37.5	34.9	20.0	0	80	2,474
	Share of population that speaks only Polish	97.4	98.8	4.9	61	100 2,474
	Log industrial production per capita	6.4	6.6	1.7	0	11	2,474
	Log municipality revenue per capita	7.7	7.7	0.2	7	10	2,452
	Log EU subsidies to municipality per capita	2.2	1.9	2.2	0	8	2,395
	Wages relative to country average	81.4	79.3	10.4	62	184 2,382
	Rural areas	0.642	1	0.479	0	1	2,478
	Railways within 10 km	0.942	1	0.233	0	1	2,474
	Altitude (m)	185.9	154.8 132.0 -3 1219 2,474
	Pre-2009 support for PiS (PCA)	0	-0.1	1.6	-4	5	2,472
	PiS vote share in 2009 EU elections	29.5	26.9	12.7	2	81	2,475
	PiS vote share in 2007 parliamentary elections	35.6	34.2	12.6	1	79	2,474
	PiS vote share in 2005 presidential elections	63.7	64.3	15.9	17	97	2,475
	Panel E: Political outcomes
	Vote share of PiS in parliamentary elections	41.3	39.8	15.2	1	89	9,922
	Turnout in parliamentary elections	47.6	46.9	9.0	23	100 9,922
	Vote share of PiS in European Parliament elections	43.0	41.3	17.5	2	89	7,457
	Turnout in European Parliament elections	26.3	22.0	11.8	7	100 7,457

Notes:

The table presents the summary statistics for the outcome, main treatment variables, and control variables used in the observational study. A23

Table A2 :

 A2 Difference-in-differences: Heterogeneous effects of TVN on religious participation

		(1)	(2)	(3)	(4)	(5)	(6)
	Panel A:	Share of Catholic population attending mass
	1{Good TVN signal} × 1{Post PiS}	-0.791***-0.559** -0.529* -0.944***-0.554** -0.702*
		(0.227) (0.264) (0.289) (0.328) (0.217)	(0.367)
	1{Good TVN signal} × 1{2015}	-0.401** -0.286 -0.401** -0.402** -0.389** -0.400**
		(0.194) (0.177) (0.193) (0.196) (0.196)	(0.195)
	× 1{Religious participation in 2009 > Median}		-0.701*
			(0.410)
	× 1{Rural}			-0.375
				(0.368)
	× 1{Pre-2009 support for PiS > Median}				0.610
					(0.396)
	× Share of 15-29 year olds					0.159
						(0.105)
	× Share of 65+ year olds					0.097
						(0.082)
	× 1{Stationary internet > Median}						-0.136
							(0.365)
	× 1{Mobile internet > Median}						-0.040
							(0.388)
	R-squared	0.850	0.854	0.850	0.851	0.851	0.850
	Panel B:	Share of Catholic population taking Communion
	1{Good TVN signal} × 1{Post PiS}	-0.557***-0.331** -0.244 -0.507***-0.396*** -0.542**
		(0.124) (0.163) (0.175) (0.190) (0.124)	(0.215)
	1{Good TVN signal} × 1{2015}	-0.273** -0.237* -0.273** -0.273** -0.267* -0.273**
		(0.138) (0.141) (0.138) (0.138) (0.139)	(0.139)
	× 1{Religious participation in 2009 > Median}		-0.487**
			(0.245)
	× 1{Rural}			-0.467**
				(0.229)
	× 1{Pre-2009 support for PiS > Median}				0.119
					(0.234)
	× Share of 15-29 year olds					0.031
						(0.064)
	× Share of 65+ year olds					0.009
						(0.043)
	× 1{Stationary internet > Median}						-0.037
							(0.210)
	× 1{Mobile internet > Median}						0.018
							(0.227)
	R-squared	0.745	0.748	0.745	0.746	0.746	0.745
	Year and Municipality FEs
	Observations	26,617 26,240 26,617 26,617 26,578	26,617
	SD of the TVN signal measure	0.45	0.45	0.45	0.45	0.45	0.45

Notes. The table presents heterogeneity of the difference-in-difference estimates of the effect of TVN on religious participation after PiS came to power with respect to municipality characteristics. OLS estimates. The unit of analysis is municipality × year. The dependent variables are the shares of Catholics attending mass and taking Communion in Panels A and B, respectively. All specifications control for year and municipality fixed effects. Standard errors corrected for spatial autocorrelation within 100 km and temporal autocorrelation for the whole time period are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

Table A3 :

 A3 Robustness of the difference-in-differences estimates to additional controls

		(1)	(2)	(3)	(4)	(5)	(6)
	Panel A: Dependent Variable:	Share of Catholic pop. attending mass
	1{Good TVN signal} × 1{Post PiS}	-0.568** -0.548** -0.613** -0.551** -0.694***-0.633***
		(0.243) (0.243) (0.246) (0.242) (0.241) (0.239)
	1{Good TVN signal} × 1{2015}	-0.262 -0.286 -0.272 -0.263 -0.347 -0.356
		(0.205) (0.211) (0.209) (0.204) (0.212) (0.218)
	R-squared	0.8549 0.8553 0.8550 0.8550 0.8605 0.8605
	Mean of dependent variable	35.03	35.03	35.03	35.03	35.03	35.03
	Osters delta						5.78
	Panel B: Dependent Variable:	Share of Catholic pop. taking Communion
	1{Good TVN signal} × 1{Post PiS}	-0.347** -0.337** -0.353** -0.327** -0.390***-0.348**
		(0.137) (0.138) (0.137) (0.137) (0.140) (0.141)
	1{Good TVN signal} × 1{2015}	-0.200 -0.209 -0.189 -0.190 -0.235 -0.215
		(0.148) (0.156) (0.142) (0.152) (0.156) (0.161)
	R-squared	0.7508 0.7513 0.7508 0.7509 0.7573 0.7573
	Mean of dependent variable	14.62	14.62	14.62	14.62	14.62	14.62
	Osters delta						3.11
	Year and Municipality FEs
	Fixed/Mobile Internet × Year FEs; Night lights; Disasters
	Free-space TVN signal strength × Post PiS and in 2015
	Log cable TV subscribers
	Partitions of Poland × Year FE
	Population deciles × Year FEs
	Log altitude × Year FEs
	Pre-2009 PiS support × Year FEs
	Religious participation, 2009 × Year FEs
	Observations	26,179 26,179 26,179 26,179 26,179 26,179
	SD of variable of interest	0.45	0.45	0.45	0.45	0.45	0.45

Table A4 :

 A4 Difference-in-differences robustness: 2013-2019 sample restriction, after the switch to digital transmission

		Share of Catholic population
		attending mass taking Communion
		(1)	(2)	(3)	(4)
	1{Good TVN signal} × 1{Post PiS}	-0.548**		-0.344**
		(0.262)		(0.153)
	1{Good TVN signal} × 1{2015}	-0.322		-0.221
		(0.271)		(0.146)
	TVN signal strength × 1{Post PiS}		-0.032**		-0.030***
			(0.016)		(0.009)
	TVN signal strength × 1{2015}		-0.011		-0.023**
			(0.014)		(0.011)
	Free-space TVN signal strength × 1{Post PiS} 0.014	0.038	0.002	0.031*
		(0.025) (0.033) (0.013)	(0.018)
	Free-space TVN signal strength × 1{2015}	0.019	0.021	0.004	0.029
		(0.026) (0.034) (0.014)	(0.021)
	Year and Municipality FEs
	Fixed and Mobile Internet × Year FE
	Night-time light density per capita
	Disaster dummy
	Partitions of Poland × Year FEs
	Log cable TV subscribers
	Observations	16,978 16,978 16,978	16,978
	R-squared	0.882	0.882	0.800	0.801
	Mean of dependent variable	34.35	34.35	14.66	14.66
	SD of the TVN signal measure	0.45	10.12	0.45	10.12

Table A5 :

 A5 Matching: Balance test of treatment status with respect to covariates in the matched sample

			(1)		(2)		(1)-(2)
			Control		Treated	Pairwise t-test
	Variable	N Mean/(SE)	N	Mean/(SE)	N	P-value
	Log night-time lights per capita, 2009	451	-1.984	1,495	-1.890	1,946 0.112
			(0.056)		(0.018)
	Log distance to optic-fiber internet nodes (km) 451	0.967	1,495	0.991	1,946 0.513
			(0.034)		(0.013)
	Speed of 3G mobile internet	451	38.327	1,495	38.492	1,946 0.790
			(0.568)		(0.248)
	Religious participation (PCA), 2009-2014	451	-0.098	1,495	-0.083	1,946 0.867
			(0.081)		(0.034)
	Pre-2009 support for PiS (PCA)	451	-0.059	1,495	-0.092	1,946 0.740
			(0.092)		(0.039)
	Austro-Hungarian partition	451	0.120	1,495	0.128	1,946 0.654
			(0.017)		(0.009)
	Prussian partition	451	0.419	1,495	0.445	1,946 0.482
			(0.035)		(0.013)
	Log population	451	9.079	1,495	9.131	1,946 0.418
			(0.060)		(0.022)
	Share of working age population	451	67.363	1,495	67.401	1,946 0.832
			(0.170)		(0.068)
	Log cable TV subscribers, 2009	451	12.599	1,495	12.584	1,946 0.733
			(0.041)		(0.016)
	Log altitude	451	5.032	1,495	4.950	1,946 0.120
			(0.048)		(0.021)
	Share of population employed in agriculture	451	36.861	1,495	35.231	1,946 0.226
			(1.244)		(0.513)
	Share of population with secondary education 451	17.679	1,495	18.046	1,946 0.242
			(0.296)		(0.103)
	Share of population with higher education	451	6.205	1,495	6.231	1,946 0.905
			(0.207)		(0.075)

Table A6 :

 A6 Using the numbers of Catholics, mass participants, and Communion takers as dependent variable The table shows that our main results are not driven by the effect of media environment on the denominator used in calculating the rates of mass attendance and taking Communion, namely, on the number of registered Catholics.

			Log number of
			Mass	Communion
		Catholics participants	takers
		(1)	(2)	(3)
	1{Good TVN signal} × 1{Post PiS}	-0.006	-0.018**	-0.017*
		(0.012)	(0.007)	(0.009)
	1{Good TVN signal} × 1{2015}	-0.015	-0.013*	-0.015*
		(0.016)	(0.008)	(0.009)
	Log number of Catholics		0.874***	0.887***
			(0.013)	(0.015)
	R-squared	0.932	0.980	0.964
	Mean of dependent variable	8.82	7.71	6.83
	Year and Municipality FEs
	Fixed and Mobile Internet × Year FEs
	Nighttime light density per capita
	Disaster dummy
	Log cable TV subscribers
	Partitions of Poland × Year FEs
	Free-space TVN signal strength
	Observations	26,617	26,617	26,608
	SD of the TVN signal measure	0.45	0.45	0.45
	Notes.

* p < 0.10, ** p < 0.05, *** p < 0.01.

A28

Table A7 :

 A7 Difference-in-differences: Political outcomes and TVN

		PiS vote share	Turnout
		(1)	(2)	(3)	(4)
	Panel A: Parliamentary Elections, 2007, 2011, 2015, and 2019
	1{Good TVN signal} × 1{Post PiS}	0.055	0.062	0.801*** 0.660***
		(0.549) (0.541) (0.242) (0.234)
	1{Good TVN signal} × 1{2015}	0.465	0.369	-0.096	0.318*
		(0.303) (0.260) (0.213) (0.186)
	Free-space TVN signal strength × 1{Post PiS} -0.182***-0.172***-0.021 -0.025
		(0.049) (0.051) (0.028) (0.025)
	Free-space TVN signal strength × 1{2015}	-0.072** -0.067** 0.001	-0.031**
		(0.035) (0.031) (0.022) (0.015)
	Observations	9,900	9,900	9,900	9,900
	R-squared	0.936	0.937	0.954	0.956
	Mean of dependent variable	41.29	41.29	47.56	47.56
	SD of the TVN signal measure	0.45	0.45	0.45	0.45
	Panel B: European Parliament Elections, 2009, 2014, and 2019
	1{Good TVN signal} × 1{Post PiS}	-0.005 -0.027	0.084	0.022
		(0.575) (0.568) (0.230) (0.229)
	Free-space TVN signal strength × 1{Post PiS} -0.247***-0.223*** 0.021	0.030
		(0.049) (0.050) (0.022) (0.023)
	Observations	7,428	7,428	7,428	7,428
	R-squared	0.907	0.908	0.968	0.968
	Mean of dependent variable	43.04	43.04	26.17	26.17
	SD of the TVN signal measure	0.45	0.45	0.45	0.45
	Year and Municipality FEs
	Fixed and Mobile Internet × Year FE
	Night-time light density per capita
	Disaster dummy
	Empire × Year trend
	Empire × Year FE

Table A8 :

 A8 Experiment's descriptive statistics: Pre-treatment characteristics Mean Median SD Min Max Obs. The table presents the summary statistics for the pre-treatment socio-economic characteristics of the participants in the survey-experiment.

	Lives in a rural area	0.309	0	0.462	0	1	9,416
	Lives in a city (< 200,000 inhabitants)	0.460	0	0.498	0	1	9,416
	Lives in a big city (> 200,000 inhabitants)	0.230	0	0.421	0	1	9,416
	Marital status: single	0.194	0	0.396	0	1	9,416
	Marital status: married	0.481	0	0.500	0	1	9,416
	Marital status: informal partnership	0.245	0	0.430	0	1	9,416
	Employed	0.662	1	0.473	0	1	9,416
	Unemployed	0.067	0	0.251	0	1	9,416
	Student	0.119	0	0.324	0	1	9,416
	Household size	3.372	3	1.407	1	7	9,416
	Household income	8.473	8	2.732	1	14 8,290
	Has internet access at home	0.864	1	0.343	0	1	9,361
	Internet services used: Facebook, twitter	0.860	1	0.347	0	1	9,416
	Internet services used: pro-PiS portals	0.089	0	0.284	0	1	9,416
	Internet services used: anti-PiS portals	0.255	0	0.436	0	1	9,416
	Time spent watching TV	3.699	4	1.518	1	6	9,416
	Main TV source of information: TVPolska	0.192	0	0.394	0	1	9,416
	Main TV source of information: TVN	0.488	0	0.500	0	1	9,416
	Main other sources of information: internet media	0.546	1	0.498	0	1	9,416
	Main other sources of information: social media	0.441	0	0.497	0	1	9,416
	Main other sources of information: periodicals	0.112	0	0.315	0	1	9,416
	Denomination: Catholic	0.838	1	0.368	0	1	9,161
	Denomination: not religious	0.121	0	0.326	0	1	9,161
	Attends mass weekly	0.340	0	0.474	0	1	7,963
	Takes Communion weekly	0.139	0	0.346	0	1	7,649
	Considers self a religious person	0.762	1	0.426	0	1	9,090
	Donated time or resources to a religious charity	0.130	0	0.337	0	1	9,290
	Voted in the parliamentary elections in 2019	0.719	1	0.449	0	1	9,322
	Voted for PiS in the parliamentary elections in 2019 0.334	0	0.472	0	1	5,886
	Voted in the EU elections in 2019	0.629	1	0.483	0	1	9,301
	Voted for PiS in the EU elections in 2019	0.320	0	0.466	0	1	5,116
	Watched the movie 'Clergy'	0.568	1	0.495	0	1	9,364
	Watched the movie 'Tell no one'	0.598	1	0.490	0	1	9,308
	Notes:

Table A9 :

 A9 Experiment's descriptive statistics: Outcome variables Mean Median SD Min Max Obs. The table presents the summary statistics for the outcome variables in the survey-experiment. Panel A presents the outcomes in the first round of the survey-experiment, separately for primary outcomes that are related to religiosity and secondary outcomes that are related to political preferences. Panel B presents the outcomes in the follow-up round of the survey-experiment.

	Panel A: First-round outcomes
	Primary outcomes:
	Chose a religious foundation to donate	0.220	0	0.414	0	1	9,416
	Trust in religious institutions (PCA)	0.370	0.179 0.340	0	1	9,066
	Trust in the Church	0.340	0	0.474	0	1	9,263
	Trust in parish priests	0.384	0	0.486	0	1	9,257
	Trust in the Episcopate	0.184	0	0.387	0	1	9,216
	Trust in the Pope	0.699	1	0.459	0	1	9,270
	Opinion: The Church's reaction to the pedophilia is insufficient	0.774	1	0.418	0	1	9,264
	Disagree: The problem of pedophilia in Church is exaggerated	0.755	1	0.430	0	1	9,279
	Disagree: The attack on the Church is underway to reduce its authority	0.566	1	0.496	0	1	9,221
	Opinion: Lessons of religion should take place at school	0.430	0	0.495	0	1	9,331
	Opinion: At school because the children are safer	0.500	1	0.500	0	1	3,948
	Opinion: At parish because school should be separated from the Church	0.530	1	0.499	0	1	4,406
	Approve: Prist salaries for teaching at school from the state budget	0.324	0	0.468	0	1	9,339
	Opinion: The mutual support of PiS and the Catholic Church is inadmissible	0.691	1	0.462	0	1	9,416
	Secondary outcomes:
	Intention to vote for Duda if there were no pandemic	0.260	0	0.439	0	1	7,105
	Intention to vote for Duda if vote by correspondence	0.495	0	0.500	0	1	2,742
	Trust in political institutions (PCA)	0.191	0	0.324	0	1	9,154
	Trust in the president	0.286	0	0.452	0	1	9,265
	Trust in the Senate	0.279	0	0.449	0	1	9,238
	Trust in the Sejm (parliament)	0.149	0	0.357	0	1	9,257
	Trust in the government	0.185	0	0.388	0	1	9,277
	Has positive feelings for PiS	0.249	0	0.432	0	1	9,155
	Panel B: Follow-up-round outcomes
	Trust in religious institutions (PCA)	0.368	0.183 0.343	0	1	7,194
	Intends to participate in the mass at least once a week in the future	0.309	0	0.462	0	1	7,277
	Actively searched info on pedophilia in the Church in the media or on the intern 0.254	0	0.435	0	1	7,157
	Pedophiles within the Catholic Church are treated differently	0.806	1	0.396	0	1	7,270
	Watched 'Tell no one' since the first round	0.222	0	0.416	0	1	2,832
	Notes:

Table A12 :

 A12 Experiment. Testing Selective Attrition between the First Round and the Follow-up by Treatment Status, using the outcomes from the First Round

				Disagree with
		Trust in	Donated	Problem of
		religious	to religious	pedophilia
		institutions foundations exaggerated
		(1)	(2)	(3)
	Pedophilia Cover-up Treatment (T1) × Participated in follow up	-0.001	0.079	0.932
		(0.026)	(0.036)	(0.036)
	Pedophilia Cover-up Treatment (T1) × Not participated in follow up	-0.015	0.060	0.942
		(0.028)	(0.039)	(0.039)
	Church's Ties to PiS Treatment (T2) × Participated in follow up	0.022	0.079	0.872
		(0.026)	(0.036)	(0.037)
	Church's Ties to PiS Treatment (T2) × Not participated in follow up	0.030	0.067	0.879
		(0.028)	(0.038)	(0.039)
	Control × Participated in follow up	0.046	0.096	0.855
		(0.026)	(0.036)	(0.036)
	Control × Not participated in follow up	0.028	0.081	0.859
		(0.027)	(0.038)	(0.039)
	Observations	9,066	9,416	9,279
	R-squared	0.633	0.280	0.780
	Mean of dependent variable	0.370	0.220	0.755
	p-value for joint equality of coefficients	0.380	0.495	0.921
	between participated and not participated
	within each treatment group separately
	p-value for equality of coefficients, T1	0.306	0.276	0.558
	p-value for equality of coefficients, T2	0.577	0.468	0.720
	p-value for equality of coefficients, Control	0.190	0.390	0.858

Table A13 :

 A13 Experiment. Testing Selective Attrition between the First Round and the Follow-up by Treatment Status, using the pre-treatment characteristics

					Considers
			Attends	Takes	self a
		Denomination:	mass	Communion religious
		Catholic	weekly	weekly	person
		(1)	(2)	(3)	(4)
	Pedophilia Cover-up Treatment (T1) × Participated in follow up	0.566	0.233	0.157	0.552
		(0.040)	(0.050)	(0.043)	(0.041)
	Pedophilia Cover-up Treatment (T1) × Not participated in follow up	0.575	0.237	0.179	0.575
		(0.042)	(0.052)	(0.044)	(0.043)
	Church's Ties to PiS Treatment (T2) × Participated in follow up	0.571	0.228	0.155	0.581
		(0.041)	(0.050)	(0.043)	(0.041)
	Church's Ties to PiS Treatment (T2) × Not participated in follow up	0.564	0.224	0.153	0.579
		(0.042)	(0.051)	(0.044)	(0.043)
	Control × Participated in follow up	0.562	0.252	0.163	0.554
		(0.041)	(0.050)	(0.043)	(0.041)
	Control × Not participated in follow up	0.568	0.217	0.156	0.580
		(0.042)	(0.052)	(0.044)	(0.043)
	Observations	9,161	7,963	7,649	9,090
	R-squared	0.844	0.370	0.158	0.773
	Mean of dependent variable	0.838	0.340	0.139	0.762
	p-value for joint equality of coefficients	0.890	0.468	0.635	0.337
	between participated and not participated
	within each treatment group separately
	p-value for equality of coefficients, T1	0.571	0.862	0.218	0.226
	p-value for equality of coefficients, T2	0.686	0.839	0.945	0.949
	p-value for equality of coefficients, Control	0.704	0.116	0.676	0.160

  B.1 Divergence in the content of TVPolska and TVN after 2015An American journalist and historian, Anne Applebaum, describes the transformation of TVPolska in an long article in The Atlantic as follows: [PiS] "took over the state public broadcaster, Telewizja Polska; fired popular presenters; and began running unabashed propaganda, sprinkled with easily disprovable lies, at taxpayers' expense. [...] Under Law and Justice [i.e., PiS party], state television doesn't just produce regime propaganda; it celebrates the fact that it is doing so. It doesn't just twist and contort information; it glories in deceit." 39 In the same article, she describes how TVPolska was transformed by PiS: "...In 2015, Kaczyński [the leader of PiS] plucked Jacek [Kurski] out of the relative obscurity of fringe politics and made him the director of state television. Since his arrival at Telewizja Polska, [...] Kurski has changed the station beyond recognition, firing the best-known journalists and radically reorienting its politics. Although the station is funded by taxpayers, the news broadcasts no longer make any pretense of objectivity or neutrality. In April of this year, for example, the station made an advertisement for itself. It showed a clip from a press conference; the leader of the opposition party, Grzegorz Schetyna, is asked what his party achieved during its eight years in government, from 2007 to 2015. Schetyna pauses and frowns; the video slows down and then ends. It's as if he had nothing to say. In reality, Schetyna spoke for several minutes and listed a number of achievements, from the mass construction of roads to rural investments to advances in foreign policy. But this manipulated clip was deemed such a success that for several days, it remained pinned to the top of Telewizja Polska's Twitter feed" (source footnote 39).

Table D2 :

 D2 Determinants of Entertainment TV reception and antenna locations

							Entertainment TV
						Good
						signal strength	Antenna present
		Covariates:				All	LASSO	All	LASSO
						(1)	(2)	(3)	(4)
		Free-space entertainment TV signal strength in 2019 0.045*** 0.045***
						(0.004) (0.004)
		Top population decile				0.046	0.034* 0.006	0.040
						(0.031) (0.019) (0.031) (0.026)
		Austro-Hungarian partition				-0.016	-0.085* 0.084*** 0.056***
						(0.052) (0.051) (0.022) (0.019)
		Prussian partition				0.048	0.016	0.023*
						(0.060) (0.032) (0.012)
		Log altitude				-0.020		0.024*** 0.015***
						(0.013)	(0.008) (0.006)
		Share of population employed in agriculture	-0.001** -0.002***-0.000
						(0.001) (0.001) (0.000)
		Speed of 3G mobile internet				-0.003**	0.001	0.002***
	Speed of 3G mobile internet		-0.004***		-0.002** (0.001)	0.000 (0.001) (0.001) 0.001 0.006*** 0.006***
		(0.001) Share of population with higher education		(0.001) -0.004		(0.001) (0.001) (0.002) (0.002) 0.008**
	Share of population with higher education		-0.007		0.002 (0.006)	0.009* (0.004)	0.017*** 0.012***
		(0.007) Share of population with secondary education	(0.005) 0.000		(0.005) 0.001	(0.006) (0.004)
	Share of population with secondary education		0.002		-0.009* (0.003)	0.002 (0.002) 0.005*** 0.001
		Pre-2009 support for PiS (PCA)	(0.004)		(0.005) 0.016		(0.002) (0.002) (0.005) 0.006
	Pre-2009 support for PiS (PCA)		-0.013	-0.017	0.012 (0.017)	0.004 (0.006)	-0.001
		(0.013) (0.013) (0.009) Log night-time lights per capita, 2009 0.048*** 0.043*** 0.017 (0.005)	(0.011)
	Log night-time lights per capita, 2009		0.045**		0.043 (0.016) (0.012) (0.013) 0.016**	-0.002
	(0.018) 0.024 (0.015) -0.240*** Log municipality revenue per capita Share of working age population Share of working age population Log municipality revenue per capita (0.048) Share of elderly population 0.005 Share of elderly population (0.011)		(0.026) 0.021** 0.019* (0.008) (0.011) -0.085*** -0.120*** (0.030) (0.045) 0.007 0.010 (0.007) (0.008)	(0.007) -0.003 -0.001 (0.003) (0.006) 0.033 0.039 (0.035) (0.032) -0.001 -0.000 (0.002) (0.004)	(0.022) -0.007 (0.015) 0.190*** (0.072) 0.001 (0.012)
	Log industrial production per capita Log industrial production per capita -0.010 (0.008)		0.004 0.007 (0.004) (0.006)	-0.003 -0.006 (0.003) (0.004)	-0.002 (0.005)
	Rural areas	Rural areas	0.025 (0.029)		-0.040 0.009 (0.050) (0.024)	-0.004 -0.003 (0.016) (0.013)	0.040** (0.020)
	Log EU subsidies to municipality per capita Log EU subsidies to municipality per capita 0.003 (0.005)	-0.002 0.004 (0.003) (0.003)	-0.005** -0.006*** (0.002) (0.002)	-0.007 (0.005)
	Wages relative to country average Wages relative to country average	0.000		0.001 0.002		0.000 -0.000	-0.002**
			(0.001)		(0.001) (0.002)	(0.000) (0.000)	(0.001)
	Log distance to optic-fiber internet nodes (km) -0.024** Log distance to optic-fiber internet nodes (km)	0.003 -0.019		-0.009 -0.022**	-0.020
			(0.010)		(0.003) (0.019)	(0.009) (0.010)	(0.022)
	Railways within 10 km Railways within 10 km		0.009		-0.037 -0.036		-0.018 0.000	-0.016
			(0.030)		(0.029) (0.031)	(0.026) (0.028)	(0.029)
	Share of population that speaks only Polish Share of population that speaks only Polish 0.001 (0.004)	-0.004*** (0.001) -0.005* (0.003)	-0.000 (0.000) -0.001*** (0.000)	-0.001 (0.002)
	Religious participation (PCA), 2009 Religious participation (PCA), 2009 0.003 (0.009)		-0.006* (0.004) -0.009 (0.006)	-0.001 (0.004) -0.010*** (0.003)	-0.016*** (0.005)
	Log cable TV subscribers, 2009 Log cable TV subscribers, 2009	0.030 (0.031)		0.024*** (0.002) 0.031* (0.017)	0.014 (0.011) 0.021** (0.009)	0.050* (0.026)
	Observations R-squared Mean of dependent variable Observations R-squared Mean of dependent variable		2,478 0.306 0.71	2,478 0.275 0.71	2,478 0.195 2,478 0.90 0.297 0.72	2,478 0.163 2,478 0.90 0.278 0.72	2,478 0.044 2,478 2,478 0.028 2,478 2,478 0.181 0.05 0.05 0.18 0.063 0.028 0.07 0.07	2,478 0.151 0.18

Notes. The table presents the correlates of the good signal strength quality of TVN and TVPolska and of the location of transmitters used by them. OLS estimates. Columns 1, 2, 5, and 6 report the estimates for TVN, Columns 3, 4, 7, and 8 for TVPolska. Transmitter presence is a dummy variable that takes the value of 1 if there is a TV transmitter for the network within 10 km distance to municipality centroid, and 0 otherwise, multiplied by 100. Free-space signal strength (in Db) computed with ITM model is included in the set of regressors in Columns 1 to 4. Columns 1, 3, 5, 7 control for all listed covariates. Columns 2, 4, 6, 8 control for the top population decile and the covariates selected by robust LASSO method

[START_REF] Belloni | Inference on Treatment Effects after Selection among High-Dimensional Controls †[END_REF]

. Standard errors corrected for spatial autocorrelation within 100 km are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

A45

Notes. The table presents the correlates of the good signal strength quality of the Entertainment TV and the location of its transmitters. OLS estimates. The unit of analysis is municipality. Transmitter presence is a dummy variable that takes the value of 1 if there is a TV transmission antenna for the network within 10 km distance of municipality centroid, and 0 otherwise, multiplied by 100. Free-space signal strength (in Db) is computed with ITM model. Columns 1 and 3 control for all the listed covariates. Columns 2 and 4 control for the top population decile and the covariates selected by robust LASSO method

[START_REF] Belloni | Inference on Treatment Effects after Selection among High-Dimensional Controls †[END_REF]

. Standard errors corrected for spatial autocorrelation within 100 km are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

Table D3 :

 D3 Correlation between initial religiosity and good TV signal strength for TVN and TVPolska The table presents the correlation between the initial levels of religious participation and the reception of TVN and TVPolska. OLS estimates. The unit of analysis is municipality. Panel A considers the TVN reception as the variable of interest; while Panel B considers the TVPolska reception. Columns 1 and 3 present unconditional correlations between the share of Catholics attending mass in 2009 and taking Communion in 2009 and the dummies for good signal strength. Columns 2 and 4 present the same correlations controlling for the Polish partitions and free-space signal strength of the TV channel of interest. Standard errors corrected for spatial autocorrelation within 100 km are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

		Mass attendance in 2009 Taking Communion in 2009
		(1)	(2)	(3)	(4)
	Panel A:	Good TVN signal strength and religiosity
	1{Good TVN signal}	-3.461**	-1.355	-0.839	-0.426
		(1.526)	(0.920)	(0.563)	(0.346)
	Free-space TVN signal strength		-0.090		-0.047
			(0.075)		(0.037)
	Prussian partition		0.672		0.388
			(2.536)		(1.295)
	Austro-Hungarian partition		17.543***		2.549**
			(2.021)		(1.291)
	Observations	2,418	2,418	2,418	2,418
	R-squared	0.017	0.263	0.005	0.028
	Panel B:	Good TVPolska signal strength and religiosity
	1{Good TVPolska signal}	-1.396	-0.796	-0.917*	-0.679
		(1.538)	(1.275)	(0.552)	(0.528)
	Free-space TVPolska signal strength		-0.157*		-0.052
			(0.095)		(0.036)
	Prussian partition		0.647		0.385
			(2.555)		(1.319)
	Austro-Hungarian partition		18.399***		2.772**
			(2.287)		(1.264)
	Observations	2,418	2,418	2,418	2,418
	R-squared	0.001	0.265	0.003	0.029

Notes:

  com/393420864 using the password "treat-ment2".) Transcript of the video:Reporter -"Good morning, your excellency. One question only." Bishop -"Yes, what is it, director?" Reporter -"I am not director. Your excellency, I wanted to ask about priest Pawlowicz, the priest pedophile." Bishop -"I have nothing to say." Reporter -"How come? Yet, your excellency is the bishop of Lowicz diocese." Bishop -"I have nothing to say, thank you." Reporter -"Your excellency, should not you give information about what is happening with priest Pawlowicz? We asked several times. There is no answer. This is very serious. It is about the safety of children." Bishop -"..." (silence) A65 Reporter -"I address myself to the most sensitive sphere of your excellency. It is about protecting children from pedophiles. Why your excellency remain silent?" Bishop -"..." (silence) Reporter -Shouldn't bishops care about the safety of the youngest in their dioceses. Bishop -"..." (silence) Reporter -"We do not know what is happening with the priest. He still leads retreats; he still has contact with altar boys. We are trying to find out. Did your excellency report it to Vatican?" Bishop -"..." (silence) Reporter -"What does your silence means in such situation?" Screen 9: Do you want to see the video once again? How do you evaluate the behavior of the bishop of Lowicz diocese?

	• Yes
	• No
	Screen 10: • Definitely positively
	• Rather positively
	• Rather negatively
	• Definitely negatively
	• Difficult to say

The official acronym of Telewizja Polska is TVP, throughout the paper we refer to it as TVPolska in order to make it distinctly different from the acronym of the independent TV channel TVN.

All three main TV networks, namely, TVPolska, TVN, and Polsat, devote a significant part of broadcasts to news and documentaries. TVPolska and TVN produce the two most popular prime-time TV news programs in Poland that had similar ratings before PiS got control over TVPolska; Polsat's news were less popular.

Holy Communion is a sacred Christian ritual that commemorates the sacrifice of Jesus Christ. Confession and priestly forgiveness are often necessary prerequisites for participation.

The content of Polsat Twitter was also rather different from TVPolska, despite the consensus among observers that Polsat has pro-government news. Online Appendix FigureA5presents the similarity of Polsat to TVN and to itself in 2016. It shows that accounts of Polsat and TVN were much closer to each other than those

See, for instance, https://www.lemonde.fr/international/article/2019/05/14/la-pologne-secouee-parun-documentaire-accablant-sur-la-pedophilie-dans-l-eglise_5461938_3210.html (accessed May 15

, 2021) and https://poznan.wyborcza.pl/poznan/7,36001,26088572,zgorszenie-szukanie-hakow-znany-ksiadz-atakujeredakcje-katolicka.html (accessed May 5, 2021). See also Online Appendix B.2 for another example.20 In the original data, these ratios are also divided by 0.82 and presented as the rates among expected mass attendees because ISKK expects only people between 7 and 75 years old to attend the mass, who by assumption constitute 82% of population, on average. We readjust the Church-attendance and taking-Communion rates to be expressed as a share of all Catholics, i.e., all baptized. Note that IKKS does not collect information about the number of people who live in the area covered by each parish and administrative borders of municipalities do not correspond to borders of parishes. We winsorize these religious participation measures at the top 1%

The data on viewership are at the region × year level. There are only 16 regions (Województwa). Thus, at the bottom of the table, for the coefficients in interest, we report the wild-cluster bootstrap-t p-values, robust to using few clusters[START_REF] Cameron | Bootstrap-Based Improvements for Inference with Clustered Errors[END_REF]. The availability of TVPolska varies too little at the regional level to have any bite in predicting variation in viewership. We do not have panel data on Polsat's viewership.

We follow[START_REF] Collela | Inference with arbitrary clustering[END_REF] and pick the threshold for the radius of spatial correlation that yields the most conservative standard errors.

As our treatment is not staggered, a threat of negative weights in the presence of heterogenous treatments does not apply to our set up (e.g., see[START_REF] Borusyak | Revisiting event study designs, with an application to the estimation of the marginal propensity to consume[END_REF][START_REF] Goodman-Bacon | Differences-in-differences with variation in treatment timing[END_REF][START_REF] Sun | Estimating dynamic treatment effects in event studies with heterogeneous treatment effects[END_REF][START_REF] De Chaisemartin | Two-way fixed effects estimators with heterogeneous treatment effects[END_REF].

Online Appendix TableA2tests for the heterogeneity of these effects with respect to religious participation at the beginning of the period in 2009, rural vs. urban status of municipality, pre-2009 political support for

As described above, TVN uses the same broadcasting infrastructure as the other major private TV channel, Polsat. We cannot empirically disentangle the effects of TVN and Polsat. As Polsat receives state advertising and observers point to its pro-government slant, it is reasonable to believe that the effects that we estimate come from exposure to TVN rather than to Polsat.

We combine the estimates reported in Column 2 of Table 1 and in Column 5 of Table 2.

According to a major polling firm, CBOS, news on TVPolska network were considered as trustworthy by 89% of Poles in 2012, 68% in 2017, 62% in 2019, and only 51% in 2021 (see https://wiadomosci.onet.pl/kraj/badaniecbos-runela-wiarygodnosc-tvp-w-oczach-widzow-wystarczy-spojrzec-na-te-liczby/jtv9z12, accessed September 20, 2022).

We obtained the IRB approval at the Paris School of Economics (PSE 2020-007) and pre-registered the experiment at the AEA RCT Registry (AEARCTR-0005767).

Online Appendix Section H presents the full transcript of the treatments (in Sections H.1 and H.2) and the questionnaires used in both rounds of the survey-experiment (in Sections H.3 and H.4). TableA8summarizes all pre-treatment characteristics and Table A9 -all the outcome variables.

In addition, in the second round, respondents were also asked to describe their faith and how many times they went to mass in the last two weeks. We find no significant effects of the treatments on these outcomes.

Source: https://www.theatlantic.com/magazine/archive/2018/10/poland-polarization/568324/, accessed May 5, 2021.

These figures correspond to the Bloomberg's Covid resilience ranking as of April 25, 2021. See: https://web.archive.org/web/20210425035008/https://www.bloomberg.com/graphics/covid-resilienceranking/, accessed June 21, 2021.

41 https://www.theguardian.com/commentisfree/2021/apr/08/covid-poland-democracy-media-europecoronavirus-tax, accessed May 5, 2021.

We implement robust LASSO method in Stata using the package lassopack provided by[START_REF] Ahrens | lassopack: Model selection and prediction with regularized regression in stata[END_REF].

See https://web.archive.org/web/20101121000845/http://data.worldbank.org/indicator/IT.TVS.HOUS.ZS, accessed, June 3 2021.

If we do not combine voting for PiS and TVPolska news consumption and, instead, treat them separately, the results for each of these two potential dimensions of heterogeneity go in the same direction, but are not statistically significant.

We also are grateful to Ilona Kawalec from CBOS and Mateusz Dus from opinie.pl and IQS for outstanding collaboration. Ekaterina Zhuravskaya thanks the European Research Council (ERC) for funding from the European Union's Horizon 2020 Research and Innovation program (grant agreement 646662). The survey-experiment obtained the approval of the internal Institutional Review Board of the Paris School of Economics; the approval number is IRB PSE 2020-007. It was preregistered at the AEA RCT Registry; registry number AEARCTR-0005767.

† Paris School of Economics. s College London.

Availability

Austro-Hungarian partition

Municipality Cross-section, historical Prussian partition Municipality Cross-section, historical

Screen 11: Sources for Pedophilia Cover-up Treatment:

The source of the map on reported cases of pedophilia: http://mapakoscielnejpedofilii.pl/ The report submitted to the Pope can be found here: https://web.archive.org/web/20190222151941/http://nielekajciesie.org.pl/wp-content/uploads/ 2019/02/ReportPOLISH.pdf The full original interview with Mrs. Diduszko-Zyglewska can be accessed with the following link: https://www.newsweek.pl/polska/spoleczenstwo/diduszko-zyglewska-w-newsweek-opinie-pedofilianiszczy-swiat-dziecka/kylylvd Media reports on the case of Priest Marian W.: https://tvn24.pl/krakow/nowy-targ-ruszyl-proces-ksiedza-mariana-w-oskarzonego-o-pedofilie-4169893 https://krakow.onet.pl/pedofilia-w-kosciele-diecezja-tarnowska-czy-ks-marian-w-molestowal/bxs6yww OKO.press reports on Priest Wincenty Pawlowicz: https://oko.press/kosciol-dal-ksiedzupedofilowi-parafie-pod-odessa-i-ministrantow-w-polsce-prowadzirekolekcje/ https://oko.press/bp-dziuba-milczy-w-sprawie-ksiedza-pedofila-nie-mam-nic-do-powiedzenia-zobaczfilm/ Screen 7: Sources for Church's Ties to PiS Treatment: PiS program is here: http://pis.org.pl/materialy-do-pobrania Report about electoral meeting in Lublin september 6, 2019: https://www.rp.pl/Wybory-parlamentarne-2019/190919919-Michal-Szuldrzynski-PiS-robi-z-Kosciolapolitycznego-zakladnika.html Media about picnic in Pułtusk: https://wiadomosci.gazeta.pl/wiadomosci/7,114884,24751324,jaroslaw-kaczynski-w-pultusku-ktopodnosi-reke-na-kosciol.html https://www.pch24.pl/kaczynski-kto-podnosi-reke-na-kosciol-ten-podnosi-reke-na-polske,67956,i.html Information about the bishop from Częstochowa: https://niezalezna.pl/212910-w-wyborczej-sie-zagotuje-biskup-na-jasnej-gorze-zgromil-totalna-opozycjei-pochwalil-pis Media about electoral meeting in Siedlce: https://liberte.pl/wybory-2018-ksieza-pomagaja-w-agitacji-na-rzecz-pis-u/ https://www.facebook.com/DzienDobrySiedlce/posts/468327530321162 Media on collecting signatures supporting Andrzej Duda: https://rzeszow.onet.pl/proboszcz-informuje-o-zbiorce-podpisow-poparcia-dla-andrzeja-dudy/99b3zwq https://ekai.pl/kosciol-popiera-pis-polacy-odpowiedzieli/ oko.press on subsidies for father Rydzyk: https://oko.press/214-238-441-zl-na-dziela-o-rydzyka/

Lives in a city (< 200,000 inhabitants) 0.015 (0.015) 0.004 (0.015) Main TV source of information: TVPolska 0.007 (0.020) 0.007 (0.020) Lives in a big city (> 200,000 inhabitants) 0.005 (0.019) -0.015 (0.019) Main TV source of information: TVN -0.011 (0.016) 0.000 (0.015) Marital status: single -0.006 (0.029) 0.029 (0.029) Main other sources of information: internet media -0.002 (0.014) -0.016 (0.014) Marital status: married -0.029 (0.025) 0.026 (0.026) Main other sources of information: social media 0.005 (0.015) 0.029** (0.015) Marital status: informal partnership -0.013 (0.027) 0.016 (0.028) Main other sources of information: periodicals 0.000 (0.022) -0.008 (0.022) Employed -0.004 (0.016) -0.014 (0.016) Denomination: Catholic -0.003 (0.033) -0.016 (0.033) Unemployed -0.016 (0.027) -0.017 (0.027) Denomination: not religious -0.028 (0.039) -0.025 (0.039) Student -0.003 (0.028) 0.000 (0.027) Attends mass weekly -0.010 (0.018) -0.025 (0.018) Household size 0.013** (0.005) -0.007 (0.005) Takes Communion weekly 0.009 (0.024) -0.005 (0.024) Household income 0.000 (0.003) 0.003 (0.003) Considers self a religious person -0.007 (0.019) 0.043** (0.019) Has internet access at home 0.008 (0.019) -0.007 (0.019) Donated time or resources to a religious charity -0.002 (0.021) -0.018 (0.021) Internet services used: Facebook, twitter -0.004 (0.019) 0.014 (0.020) Voted in the parliamentary elections in 2019 -0.018 (0.025) -0.010 (0.025) Internet services used: pro-PiS portals 0.002 (0.024) 0.020 (0.024) Voted for PiS in the parliamentary elections in 2019 -0.020 (0.029) -0.013 (0.029) Internet services used: anti-PiS portals -0.002 (0.016) -0.005 (0.016) Voted in the EU elections in 2019 0.025 (0.024) 0.039 (0.024) Time spent watching TV 0.000 (0.005) -0.003 (0.005) Voted for PiS in the EU elections in 2019 0.000 (0.031) -0.011 (0.032) Watched the movie 'Tell no one' -0.001 (0.015) 0.016 (0.015) Watched the movie 'Clergy' 0.014 (0.014) 0.019 (0.014) Observations 6,293 6,299 R-squared 0.006 0.010 p-value for joint significance 0.998 0.460

Notes: The table presents the omnibus test of randomization quality for the experiment. It reports the estimates obtained from regressing the treatment status on the full list of pre-treatment covariates. OLS estimates. The unit of analysis is individual. In the first estimation, an indicator variable for being assigned to "Pedophilia Cover-up Treatment" is regressed on the covariates in a sample of respondents assigned to "Pedophilia Cover-up Treatment" and "Control" groups. In the second estimation, an indicator variable for being assigned to "Church's Ties to PiS Treatment" is regressed on the covariates in a sample of respondents assigned to "Church's Ties to PiS Treatment" and "Control" groups. In both regressions, we control for randomization-strata fixed effects. Heteroskedasticity-robust standard errors are in parenthesis. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the estimated heterogeneous effects of the experimental treatments with respect to having donated time or money to a charity in the last year on the main religiosity outcomes in both rounds of the survey-experiment. OLS estimates. The unit of analysis is individual. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pre-treatment characteristics reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] are reported in curly brackets. P-values corrected for multiple hypothesis testing using the methods developed by [START_REF] Anderson | Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects[END_REF] (sharpened q-value), [START_REF] List | Multiple hypothesis testing in experimental economics[END_REF] and Steinmayr (2020) (FWER p-value), [START_REF] Holm | A simple sequentially rejective multiple test procedure[END_REF] (Holm-Bonferroni p-value) are reported in square brackets. Lee bounds for the treatment effects [START_REF] Lee | Training, wages, and sample selection: Estimating sharp bounds on treatment effects[END_REF] are reported at the bottom of the table along with p-values from the test of equality of treatment effects of the two treatments. * p < 0.10, ** p < 0.05, *** p < 0.01.

C Data Appendix

In this section, we describe the variables used as controls in the observational part of our study. We define each variable and provide information on the aggregation level, time coverage, and sources. Online Appendix Table C1 (below in this section) summarizes the aggregation level, at which these variables are measured, and the years for which they are available.

Historical Partitions of Poland. The data on historical partitions of Poland come from [START_REF] Grosfeld | Cultural vs. economic legacies of empires: Evidence from the partition of Poland[END_REF]. We generate three dummy variables indicating whether a municipality was part of the Russian Empire partition, the Austro-Hungarian Empire partition, or the Prussian Partition. In our regression analyses, we set the Russian Empire partition as the omitted category as it was the largest of the three partitions in terms of the surface area.

Stationary and mobile internet availability. The data on the mobile and fix internet availability come from State Office for Electronic Communication (2019), available here: https://www.uke.gov.pl/en/ (accessed October 20, 2022). The dataset provides information on the location of optic-fiber internet nodes for stationary internet, and for mobile internet, it contains antenna locations, along with their directions and data transmission speed (in mb/s). This information is available only for 2019. We compute log of the average distance of each municipality to the optic-fiber internet nodes as our measure of stationary internet availability.

The motivation for this is that distance to nodes reduces data transmission speed because of signal attenuation through copper cables. We use the average speed of mobile internet as a proxy for its availability. More precisely, we proxy the speed at which a user can browse on her mobile device by the average data transmission speed of the antennas surrounding her. For each municipality we compute the average speed of all antennas covering this municipality, each antenna being weighted by the share of the municipality actually covered by it.

Night-time lights. Natural disasters. The data on natural disasters come from the international disasters database (EM-DAT, 2020), https://public.emdat.be/ (accessed October 20, 2022). We generate four dummy variables indicating whether a natural disaster occurred in each municipality in the calendar year, the year before, two years before, and three years before.

Cable TV subscriptions.

F.2 Persuasion rates implied by the results of the experiment

To calculate the persuasion rates implied by the experiment's results, one can apply the formula for the discrete case (Equation F.1), which is reduced to:

We use the coefficients on dummy variables indicating treatment status from Table 5 to compute y T -y C . As the treatment is randomly assigned, y 0 = y C .

Persuasion rate of Pedophilia Cover-up Treatment. The persuasion rates of Pedophilia Cover-up Treatment implied by our experiment are:

• For the first-round outcomes:

-Do not trust religious institutions, 1 st round: f = --0.046 1-0.619 = 12.1% -Donate to a non-religious foundation, 1 st round: f = --0.017 1-0.777 = 7.6% • For the follow-up-round outcomes:

-Do not trust religious institutions, 2 nd round: f = --0.022 1-0.625 = 5.9% -Do not intend to attend mass weekly in the future, 2 nd round: f = --0.024 1-0.686 = 7.6%

Persuasion rate of Church's Ties to PiS Treatment. The persuasion rates of Church's Ties to PiS Treatment implied by our experiment are:

• For the first-round outcome:

-Do not trust religious institutions, 1 st round: f = --0.019 1-0.632 = 5.2% • For the follow-up-round outcome:

-Do not intend to attend mass weekly in the future, 2 nd round: f = --0.022 1-0.689 = 7.1% For the following two outcomes, the effects of Church's Ties to PiS Treatment are insignificant. For comparison, we also calculate the persuasion rates based on these imprecisely estimated effects:

• For the following first-round outcome:

-Do not trust religious institutions (2 nd round): f = --0.011 1-0.633 = 3.0% (insignificant) • For the following follow-up-round outcome:

-Donate to a non-religious foundation (1 st round): f = --0.016 1-0.776 = 7.1% (insignificant) Notes. The table presents the estimated ATE of the experimental treatments on trust in religious institutions in the first round of the survey-experiment. OLS estimates. The unit of analysis is individual. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pre-treatment characteristics reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticityrobust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] are reported in curly brackets. P-values corrected for multiple hypothesis testing using the methods developed by [START_REF] Anderson | Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects[END_REF] (sharpened q-value), [START_REF] List | Multiple hypothesis testing in experimental economics[END_REF] and Steinmayr (2020) (FWER p-value), [START_REF] Holm | A simple sequentially rejective multiple test procedure[END_REF] (Holm-Bonferroni p-value) are reported in square brackets. Lee bounds for the treatment effects [START_REF] Lee | Training, wages, and sample selection: Estimating sharp bounds on treatment effects[END_REF]) are reported at the bottom of the table along with p-values from the test of equality of treatment effects of the two treatments. * p < 0.10, ** p < 0.05, *** p < 0.01. Notes. The table presents the estimated ATE of the experimental treatments on the assessment of the Church's reaction to pedophilia cases in the first round of the survey-experiment. OLS estimates. The unit of analysis is individual. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pretreatment characteristics reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] are reported in curly brackets. P-values corrected for multiple hypothesis testing using the methods developed by [START_REF] Anderson | Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects[END_REF] (sharpened qvalue), [START_REF] List | Multiple hypothesis testing in experimental economics[END_REF] and Steinmayr (2020) (FWER p-value), [START_REF] Holm | A simple sequentially rejective multiple test procedure[END_REF] (Holm-Bonferroni p-value) are reported in square brackets. Lee bounds for the treatment effects [START_REF] Lee | Training, wages, and sample selection: Estimating sharp bounds on treatment effects[END_REF]) are reported at the bottom of the table along with p-values from the test of equality of treatment effects of the two treatments. * p < 0.10, ** p < 0.05, *** p < 0.01.

A54

Table G3 The unit of analysis is individual. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pre-treatment characteristics reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] are reported in curly brackets. P-values corrected for multiple hypothesis testing using the methods developed by [START_REF] Anderson | Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects[END_REF] (sharpened q-value), [START_REF] List | Multiple hypothesis testing in experimental economics[END_REF] Notes. The table presents the estimated heterogeneous effects of the experimental treatments with respect to the locality type of the residence on the main religiosity outcomes, measured in both rounds of the survey-experiment. OLS estimates. The unit of analysis is individual. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pre-treatment characteristics reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] Notes. The table presents the estimated heterogeneous effects of the experimental treatments with respect to support for the PiS party and to TVPolska viewership on the main religiosity outcomes, measured in both rounds of the survey-experiment. OLS estimates. The unit of analysis is individual. All regressions control for strata fixed effects. All regressions also include controls for unbalanced pre-treatment characteristics reported in Table A11, namely, household size, dummies for using social media as a main source of information, for having voted in the EU elections in 2019, and for having watched the movies "Clergy" and "Tell no one," separately. All regressions also control for the level of religiosity self-reported in pre-treatment survey. P-values obtained from heteroskedasticity-robust standard errors are in parentheses. Randomization-t p-values for sharp null hypothesis obtained with 10,000 repetitions using [START_REF] Young | Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results[END_REF] are reported in curly brackets. P-values corrected for multiple hypothesis testing using the methods developed by [START_REF] Anderson | Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects[END_REF] All regressions control for randomization strata fixed effects, unbalanced controls reported in Table A11, and initial level of religiosity self-reported in pre-treatment survey. P-values from heteroskedasticity-robust standard errors are reported.

H.3 Questionnaire, First Round

Screen 1: We invite you to participate in a survey conducted by Opinie.pl of IQS together with CBOS. Our customer is an academic institution so the study has a scientific character. Nevertheless it is not difficult and the first trials show it is interesting for a lot of people.

The survey concerns different issues, among others the question of sexual abuse of children by priests of the Catholic Church and the role of the Catholic Church in Poland. In the survey we will present some information, and then we will ask you what you think about it. All information A68 comes from publicly available (published) sources; we will always indicate what they are. You will always be able to skip any material.

We assure you that your answers will be kept secret. They will only be used in an aggregate form in anonymous statistical summaries. Nobody will ever know what were your answers to the questions. We count very much on your participation in our survey and on your response to all our questions. However, if you find some of the questions too difficult or too sensitive, you will be able to choose the option "refuse to answer." You will also be able to skip any of the presented materials.

Given what is said above, do you agree to participate in our survey?

• I agree

Screen 2: The study will consist of two stages. In the first stage, you will be asked to answer a set of questions. In the second stage, after 3-4 weeks, we will get back to you and ask to answer a very short survey. We would like all respondents participating in the first stage of the study, to also take part in the second stage. The quality (reliability) of our study will depend on this participation.

Our customer decided to support some charity foundations and allocate 2500 PLN to them. The amount transferred to each of the foundations will depend on the share of people who will choose each of the foundation in our survey. If you also participate in the second stage of our project, you will get the information about the results of the vote and the certificate of the actual bank transfer to the foundations. You will also be remunerated for the participation in the study.

Questionnaire

The following questions (until INT, inclusive) are asked at the time when the respondents subscribe to the online polling platform, i.e., before the survey takes place.

Please indicate the size of the locality where you live:

• Rural

• City less than 20,000

• City 20,000-49,000

• City 50,000-99,000

• City 100,000-199,000

• City 200,000-500,000

• City more than 500,000 • Facebook

• Gazeta (Gazeta.pl)

• Interia (Interia.pl)

The following questions are asked at the time of the survey. Questions NQ07 -Q17 are asked pre-treatment, i.e., before the information treatments take place.

NQ07.

Please indicate the locality/gmina where you were born. In which locality were you born? To which gmina belongs this locality?

Q01. How would you describe your interest in politics?

• Very big

• Refuse to answer A75 Q02. Do you think that most people can be trusted or that one should never be too careful in dealing with people?

• One can trust most of people • One is never too careful • Difficult to say

• Refuse to answer Q03. On the scale from 1 (left) to 7 (right), how would you describe your political opinions?

Q04. Did you vote in the parliamentary election to Sejm and Senat on October 13, 2019?

• Yes

• No

• Refuse to answer Q05. (If Yes to Q04) For the candidate of which party did you vote in the elections to Sejm in 2019?

• Polskie Stronnictwo Ludowe -Koalicja Polska (Polskie Stronnictwo Ludowe , Kukiz'15, UED)

• Prawo i Sprawiedliwość (with Solidarna Polska and Porozumienie)

• Lewica (Nowa Lewica (previously SLD), Wiosna, Lewica Razem)

• Konfederacja Wolność i Niepodległość (KORWiN, Ruch Narodowy, Braun)

• Koalicja Obywatelska (Platforma Obywatelska, Nowoczesna, Inicjatywa Polska, Zieloni)

• Other party or electoral committee

• Refuse to answer Q06. Did you vote in the elections to the European Parliament on May 26, 2019?

• Yes

• No

• Refuse to answer Q07. (If Yes to Q06) For the candidate of which party did you vote in the elections to the European Parliament on May 26, 2019?

• Kukiz'15

• Prawo i Sprawiedliwosc

• Wiosna Roberta Biedronia

• Konfederacja Korwin Braun Liroy narodowcy

• Koalicja Europejska (PO PSL .N SLD Zieloni)

• Lewica razem

• Other committee

• Refuse to answer A76 NQ05. What is your confession (to which Church or religious community do you belong)?

• Roman Catholic Church

• Other (please, specify: NQ0509TXT)

• I do not belong to any religious community

• Refuse to answer Q08. Do you participate in religious practices, such as masses, other religious ceremonies, and if so, how often?

• Yes, several times per week

• Yes, once a week

• Yes, on average once or twice per month

• Yes, several times a year

• I do not participate at all

• Refuse to answer NQ02. How often do you take communion?

• Several times per week

• Once a week

• On average once or twice per month

• Several times a year

• Never

• Difficult to say

• Refuse to answer Q09. Independently of participating in religious practices, do you consider yourself as a person:

• Profoundly religious

• Religious

• Rather not religious

• Completely non-religious

• Refuse to answer A77 NQ09A. Did you receive the sacrament of confirmation?

• Yes

• No

• Refuse to answer Q10. Did you devote last year your time, services, money, cloth or books for charity?

• Yes

• No

• Do not remember

• Refuse to answer

NQ03

. If your answer to the previous question is positive, was the charity related to the Catholic Church?

• Yes

• No

• Do not remember

• Refuse to answer NQ09. Did you participate during the last year in non-religious events or activities organized by the Catholic Church (such as for instance collecting money for the needy, helping elderly or unemployed, going for vacation, getting psychological help, participate in cultural or sport events, getting language, professional or computer training)?

• Yes

• No

• Refuse to answer Q11. Which of the following TV channels, and which programs are for you the main source of everyday information about the events in Poland and abroad? You can choose no more than two answers. As the first one please indicate the main source of information: • Radio Maryja

• Polskie radio (Jedynka, Dwojka, Trojka)

• RFM, Radio Zet

• TOK FM

• Newspapers, weeklies

• Other

• None of those

• Refuse to answer Q13. Do you have access to stationary Internet at home?

• Yes

• No

• Refuse to answer

NQ08.

To what extent do you agree with the statement that a woman -if she decides soshould have the right to abortion during the first weeks of pregnancy?

• Definitely agree

• Rather agree

• Rather disagree

• Definitely disagree

• Difficult to say

• Refuse to answer Q14. Did you see the film "Clergy" ("Kler") by Wojciech Smarzowski?

• Yes

• No

• Refuse to answer Q15. In 2019, Tomasz and Marek Sekielski made a documentary "Tell No One" ("Tylko nie mów nikomu") about child sexual abuse in the Catholic Church in Poland. The film could be seen on YouTube online platform. It was also broadcasted on TVN last year.

Did you see this film?

• Yes

• No

• Refuse to answer A79 Q16. If yes, where did you see it?

• On Internet, YouTube

• On TVN

• Somewhere else

• Refuse to answer Q17. Do you think the spread of coronavirus is

• The result of the working of nature

• The result of deliberate action of a group of people

• Difficult to say

• Refuse to answer

RANDOMIZATION INTO:

(1) CONTROL GROUP (2) TREATMENT "Pedophilia Cover-up"

(3) TREATMENT "Church's Ties to PiS" TAKES PLACE AT THIS MOMENT OF THE SURVEY.

The following questions are asked post-treatment.

Q18. Do you know, when was the law requiring anybody to report about the known cases of sexual abuse of children to the state prosecutor adopted? Q19A. If the presidential elections were to take place on May 10, 2020, as initially planned before the pandemia of COVID-19, and if there were no epidemiological danger, would you participate in the elections?

• Yes

• Non

• I haven't decided yet

• Refuse to answer Q19. (If Yes to Q19A) For whom would you vote in such situation in the upcoming presidential elections?

• Odmawiam odpowiedzi Q19B. Given the present situation related to threat of coronavirus, do you intend to take part in voting by correspondence if such vote had to take place in May 2020?

• Yes

• No

• I haven't decided yet

• Refuse to answer Q19C. (If yes to Q19B) For whom would you vote in such situation if the presidential elections were to take place by correspondence?

• Odmawiam odpowiedzi A81 Q20. Do you agree with the following statements:

• "The problem of pedophilia in Church is exaggerated." (Q20_01)

• "The attack on the Church is underway which is used to reduce its authority and introduce moral changes." (Q20_02)

• "The Catholic Church is crucial for morality of the Polish society." (Q20_03)

• I completely agree • I rather agree • I rather disagree • I completely disagree • Difficult to say

• Refuse to answer NQ12. There is a lot of discussions in Poland about the place of religion in the public life.

Please answer if you are offended or not offended by the following situations:

• Blessings by priests of places and public buildings (NQ12_01)

• The Church giving opinion on laws voted by the Parliament (NQ12_02)

• Priests express their political opinions before elections during the mass (NQ12_03)

• I am definitely offended • I am rather offended • I am rather not offended • I am definitely not offended • Difficult to say

• Refuse to answer Q21A. Do you think that the lessons of religion should take place at school or at parish premises?

• At school

• At parish premises

• Difficult to say

• Refuse to answer Q21B. (If replied "at school" to Q21A) Why do you think the lessons of religion should take place at school?

• Because it is more convenient

• Because at school the children are safer -it is easier to control the behavior of priests and teachers

• Other reason: A82 Q21C. (If replied "at parish premises" to Q21A) Why do you think that the lessons of religion should take place at parish premises?

• Because school should be separated from the Church

• Because the church is a natural place for religious experience

• Other reason Q22. Do you think that the salaries of priests teaching religion at school should be paid from the state budget?

• Yes

• No

• Difficult to say

• Refuse to answer Q23. Should the budget money be spent on financing Church-run media, like Radio Maryja or TV Trwam?

• Yes

• No

• Difficult to say

• Refuse to answer Q24. Do you think that the reaction of the Polish Catholic Church to the information of sexual abuse of minors by the clergy is sufficient?

• Sufficient

• Insufficient

• Difficult to say

• Refuse to answer Q26. Do you trust ... ? (The order in which respondents were asked about each institution was randomized.)

• Parliament (Q26_01)

• Senat (Q26_02)

• President (Q26_03)

• Catholic Church (Q26_04)

• Government (Q26_05)

• Courts (Q26_06)

• Priest in your parish (Q26_07)

• Your neighbors (Q26_08)

• Police (Q26_09)

• Episcopate (Q26_10) A83

• The Pope (Q26_11)

• Definitely yes

• Difficult to say

• Refuse to answer Q27. We would like to support on your behalf charity foundations offering scholarships to children and young people. We will allocate 2500 PLN among the following foundations. The amount of money each of the foundations receives will depend on the shares of respondents choosing this foundation. So please indicate to which of the following foundations you would like us to transfer money. When the study is over, you will get the information about the results of this vote and the certificates of the actual transfers to the foundations. Please, put the cross next to one of the four foundations, which you would like us to support on your behalf. (The order in which each respondent saw the foundations was randomized.) study. Now we are coming back to you asking you to answer more questions. Some of the questions will be similar to those we asked in the first part: this is because we would like to know if your opinion has changed. This survey is much shorter than the previous one. We would like everybody who answered our questions in the first stage do it this time as well. The reliability of our study will depend on your participation. We remind you that our contractor decided to support some charity NGOs in your name, allocating 2500 PLN among them. The amount transferred to each of four organizations depended on the number of people who have chosen each NGO. According to this promise, the money was already transferred. At the end of the survey you will find the information about the actual amount transferred to each organization and the proofs of bank transfers.

Screen 2: We inform you that there are questions in the survey which concern sensitive issues such as political preferences or religion. We assure you that all your answers will be kept secret. Information such as names or addresses will not be kept and any identification of a person participating in the study will not be possible. All information will only be used in an aggregate form in anonymous statistical summaries. Nobody will ever know what were your answers to the questions.

P01. If the presidential elections were to take place next Sunday, would you participate in the elections?

• Yes

• No

• I haven't decided yet

• Refuse to answer A85 P01A. (If Yes to P01) For whom would you vote in such situation if the presidential elections were to take place next Sunday?

• Andrzej Duda

• Rafał Trzaskowski

• Szymon Hołownia

• Władysław Kosiniak-Kamysz

• Robert Biedroń

• Krzysztof Bosak

• Inny kandydat

• I haven't decided yet

• Refuse to answer PA. Do you consider the question of pedophilia in the Catholic Church as socially important?

• This is a definitely important question

• This is rather an important question

• This is rather an unimportant question

• This is definitely an unimportant question P02. Did you see the second part of Sekielskis' film "Hide and seek" ("Zabawa w chowanego")?

• Yes

• No

• Refuse to answer P02A1. (If Yes to P02) Where did you see Sekielskis' film "Hide and seek"?:

• In internet, YouTube

• On TVN

• Elsewhere (specify where ...)

• Refuse to answer P02A. Since you participated in the first part of our survey have you seen the first part of Sekielskis' film "Tell no one"?

• Yes

• No

• Refuse to answer P03. According to you, who should be blamed for the pedophilia in the Catholic Church?

• Individual priests

• Not only individual priests but also the entire Church as an institution

• Do not know/difficult to say

• Refuse to answer A86 NQ13. Do you trust ... ? (The order in which respondents were asked about each institution was randomized.)

• Parliament (NQ13_01)

• Senat (NQ13_02)

• President (NQ13_03)

• Catholic Church (NQ13_04)

• Government (NQ13_05)

• Courts (NQ13_06)

• Priest in your parish (NQ13_07)

• Your neighbors (NQ13_08)

• Police (NQ13_09)

• Episcopate (NQ13_10)

• The Pope (NQ13_11) • Refuse to answer NQ17. How would you describe your faith?

• I am a believer and I follow Church's recommendations

• I am a believer in my own way and I do not always follow Church's recommendations

• I am not a believer

• Difficult to say

• Refuse to answer NQ15. How many times did you participate in the mass during the last two weeks? Please, take into account all masses, including those in the church and those in which you participated through TV, radio and the internet.

• Several times per week, altogether more than 4 times

• Once a week, 4 times

• Less than once a week, once or twice

• I did not participate

• Refuse to answer NQ16. In the future, do you think you will go to church?

• Several times a week

• Once or twice a month

• Several times a year, or less • I will not participate

• Difficult to say P4. Did you hear recently about cases of sexual abuse of children by priests of the Catholic Church in your close environment: locality, gmina, parish, neighboring parishes, or diocese?

• Yes

• No

• Do not remember

• Refuse to answer A88 P5. During the last two weeks, were you interested in this issue of the abuse of children by priests to the point that you actively search information on this topic in the media or in the internet?

• Yes

• No

• Refuse to answer NQ18. Do you agree with the statement "pedophiles within the Catholic Church are treated differently than pedophiles outside the Church"?

• I definitely agree

• I rather agree

• I rather disagree

• I definitely disagree

• Difficult to say

• Refuse to answer P6. Consider an adult who was a victim of sexual abuse a long time ago when she/he was a child by a priest of the Catholic Church. Do you think he/she should speak out and testify or, on the contrary, there is no point in speaking out because the abuse happened a long time ago?

• The victim should speak out

• There is no point in speaking out

• Difficult to say

• Refuse to answer

Last Screen: In the first part of our study we asked you to choose a foundation that we can support on behalf of participants of this study. Overall, 12,49% of respondents chose Katolicka Wspólnota Chleb Życia, 61,87% chose Fundacja Fabryki Marzeń, 16,13% chose Edukacyjna Fundacja im. prof. Romana Czerneckiego, and 9,51% chose Fundacja Dzieło Nowego Tysiąclecia. Below we present the payslips confirming that we have transferred the money to the foundations.

Thank you for your participation!