Ali Recayi Ogcem

Ruth Tacneng

Amine Tarazi

Trust in banks and borrower discouragement

Keywords: discouraged borrowers, trust in banks, interpersonal trust, credit constraints, financial inclusion JEL Codes : G21, G41, O17, Z1, L26 discouraged borrowers, trust in banks, interpersonal trust, credit constraints, financial inclusion JEL Codes : G21, G41, O17, Z1, L26

This paper contributes to unravel the determinants of borrower discouragement, i.e., the fact that economic agents who need credit feel less inclined to borrow from a bank. Specifically, we use worldwide firm-level data to examine the role played by informal institutions, particularly trust in banks, in potentially reducing borrower discouragement. Lack of trust may explain such discouragement, and hence to enhance funding stability and the use of formal financial instruments, increasing trust could be determinant. Our empirical results show that firms are less likely to get discouraged from borrowing from financial institutions in countries where trust in banks is relatively high. Moreover, we also find a lower prevalence of borrower discouragement in countries where both trust in banks and interpersonal trust are high. These results stress the role played by informal institutions in influencing firms' access to credit via self-rationing. Overall, our results highlight the importance of building confidence and trust in banks to encourage formal credit demand and the use of formal finance, which is crucial for achieving financial inclusion.

Introduction

The literature highlights the need for firms, especially small and medium enterprises (SMEs), to have access to stable funding to take advantage of growth, expansion, and innovation opportunities [START_REF] Beck | Financial and legal constraints to growth: does firm size matter[END_REF][START_REF] Aghion | Credit constraints as a barrier to the entry and postentry growth of firms[END_REF][START_REF] Ayyagari | Firm Innovation in Emerging Markets: The Role of Finance, Governance, and Competition[END_REF][START_REF] Banerjee | Do Firms Want to Borrow More? Testing Credit Constraints Using a Directed Lending Program[END_REF], and hence, attain a dynamic and inclusive economy. Some SMEs, however, are inclined to rely on internal capital, profits, and short-term financing sources [START_REF] Ayyagari | SME finance[END_REF][START_REF] Behr | Credit risk assessment and relationship lending: An empirical analysis of German small and medium-sized enterprises[END_REF], including trade credit and informal ones, to finance their operations. This is because they often lack a reliable financial history to back up their creditworthiness that is often crucial when seeking funding from financial institutions [START_REF] Beck | Financing patterns around the world: Are small firms different[END_REF][START_REF] Scholtens | Analytical Issues in External Financing Alternatives[END_REF], especially younger and smaller businesses. In addition, banks may ration credit due to the asymmetric information between borrowers and lenders [START_REF] Stiglitz | Credit rationing in Markets with Imperfect Information[END_REF]. Moreover, some firms may not rely on formal finance, despite their capital needs, because they are discouraged from applying for loans. While most studies highlight fear of rejection as the reason behind borrower discouragement [START_REF] Cowling | UK credit and discouragement during the GFC[END_REF][START_REF] Kon | A theory of discouraged borrowers[END_REF][START_REF] Jappelli | Who is credit constrained in the US economy[END_REF]; several findings from firm surveys worldwide cite other reasons why firms do not apply for loans, including high cost of credit, unfavorable economic conditions, complex application procedures, debt aversion, among others.

Discerning the reasons behind borrower discouragement is important because it is a selfrationing mechanism that exacerbates firms' credit constraints. Several studies show a higher incidence of discouraged borrowers than rejected borrowers [START_REF] Freel | The latent demand for bank debt: Characterizing discouraged borrowers[END_REF]Wernli and Dietrich, 2022;[START_REF] Ferrando | The real effects of credit constraints: Evidence from discouraged borrowers[END_REF]. Borrower discouragement is also found to be more prevalent in developing countries [START_REF] Chakravarty | The international evidence on discouraged small businesses[END_REF]. Moreover, although some evidence suggests that discouraged borrowers are riskier and are less creditworthy [START_REF] Han | Are good or bad borrowers discouraged from applying for loans? Evidence from US small business credit markets[END_REF] and thus form a rational strategy to avoid pursuing an application with low success probability, more recent papers highlight that at least 40% of discouraged borrowers in the UK, Switzerland, and Belgium would have likely obtained a loan if they had applied for one [START_REF] Cowling | UK credit and discouragement during the GFC[END_REF]Wernli and Dietrich, 2022;[START_REF] Ferrando | The real effects of credit constraints: Evidence from discouraged borrowers[END_REF]. In addition, [START_REF] Ferrando | The real effects of credit constraints: Evidence from discouraged borrowers[END_REF] find strong adverse real effects of discouragement on firm outcomes. More specifically, they find that reducing firms' application costs for bank loans is significant in increasing firm sales by 5 to 10 percentage points, investment rate by about 6 to 10 percentage points, and employment growth by 2 to 4 percentage points. Previous research findings show that entrepreneurial and owner characteristics such as gender, education, firm banking relationship, innovation activity, and age are linked to borrower discouragement [START_REF] Han | Are good or bad borrowers discouraged from applying for loans? Evidence from US small business credit markets[END_REF][START_REF] Cowling | UK credit and discouragement during the GFC[END_REF][START_REF] Freel | The latent demand for bank debt: Characterizing discouraged borrowers[END_REF][START_REF] Cole | Who needs credit and who gets credit? Evidence from the surveys of small business finances[END_REF]Nguyen et al., 2021;[START_REF] Brown | Innovation and borrower discouragement in SMEs[END_REF]. This paper presents novel evidence showing that trust in banks affects borrower discouragement as well.

Trust in financial institutions 1 is vital in the intermediation process. It affects funding sustainability, capital allocation efficiency, and productivity. The collapse of the Silicon Valley Bank (SVB) and difficulties faced by the Crédit Suisse in 2023 have caused immediate panic worldwide, raising fears of another systemic banking crisis. The 2007-2008 Global Financial Crisis (GFC), triggered by financial institutions' excessive risk-taking behavior, impaired confidence in banks [START_REF] Sapienza | A trust crisis[END_REF][START_REF] Iyer | Understanding bank runs: The importance of depositor-bank relationships and networks[END_REF] and has stressed the importance of well-functioning banks for the economy. Trust in banks may be defined as the expectation that banks are dependable and relied on to fulfill their promises [START_REF] Sirdeshmukh | Consumer trust, value, and loyalty in relational exchanges[END_REF]van der Cruijsen et al., 2021a). It is different from interpersonal trust 2 which refers to trust to other people, in general, to whom one has no direct relationship. Increased distrust in 1 Trust in financial institutions and trust in banks are used interchangeably in the text.

2

Other studies refer to interpersonal trust as generalized trust or societal trust. banks may increase borrower discouragement in several ways. First, distrust in banks impairs bank deposits and discourages formal household saving behavior, which adversely affects the supply of loans. This may consequently raise firms' fear of rejection and expectations of higher cost of credit and stringent credit conditions especially smaller businesses, which are more informationally opaque and have less business assets to pledge as collateral. Second, lower trust in banks may discourage firms from using formal credit. Indeed, distrust in banks may inhibit consumers from becoming clients of the bank (van der Cruijsen et al., 2021a). Studies show that trust in financial institutions affect the use of formal financial instruments, such as savings accounts [START_REF] Beckmann | Formal and informal household savings: how does trust in financial institutions influence the choice of savings instruments?[END_REF][START_REF] Ampudia | Trust and the household-bank relationship[END_REF] due to fear of hidden charges and high transaction costs [START_REF] Galiani | Trust and saving in financial institutions by the poor[END_REF][START_REF] Bachas | How Debit Cards Enable the Poor to Save More[END_REF]. As growing savings in banks is often perceived as a first step toward using other formal financial services, such as credit and insurance, distrust in banks may foster borrower discouragement. Third, lower trust in banks may discourage firms from applying for loans because the development of trust in banks may be linked to the familiarity with and knowledge about financial institutions and their services [START_REF] Allen | The foundations of financial inclusion: Understanding ownership and use of formal accounts[END_REF]van der Cruijsen et al., 2021b). Moreover, higher trust in banks, which may be developed through repeated interactions between economic agents and financial institutions, may reduce the incidence of borrower discouragement. This is in line with firm-level studies that find businesses with established banking relationships less likely to be discouraged from applying for loans [START_REF] Freel | The latent demand for bank debt: Characterizing discouraged borrowers[END_REF].

The main objective of this paper is to examine the influence of trust in banks on borrower discouragement. We also analyze the role of interpersonal trust in the trust in banksborrower discouragement link. Interpersonal trust may reinforce the impact of trust in financial institutions in potentially reducing the incidence of borrower discouragement by influencing a firm's expectation of the cost of credit and success of a potential loan application. Several studies stress that interpersonal trust encourages a cooperative attitude and pro-social behavior [START_REF] Fehr | On the Economics and Biology of Trust[END_REF][START_REF] Carlo | Exploring the Relations among Trust Beliefs, Prosocial tendencies, and Friendships[END_REF], and increases contracting efficiency that could complement contract enforcement mechanisms, especially in countries with weak regulation [START_REF] Cline | Trust, regulation, and contracting institutions[END_REF].

Our paper contributes to several strands in the literature. Our study adds to the emerging literature on demand-side credit constraints by investigating the role played by cross-country variations in trust in financial institutions in driving firm-level borrower discouragement. Recent studies find firm size, age, ownership and owner characteristics, risk profiles, innovative activity, financial fragmentation, firm-banking relationship, explain borrower discouragement [START_REF] Levenson | Do firms get the financing they want? Measuring credit rationing experienced by small businesses in the U[END_REF][START_REF] Cavalluzzo | Competition, small business financing, and discrimination: Evidence from a new survey[END_REF][START_REF] Cole | Who needs credit and who gets credit? Evidence from the surveys of small business finances[END_REF][START_REF] Han | Are good or bad borrowers discouraged from applying for loans? Evidence from US small business credit markets[END_REF][START_REF] Chakravarty | A multistage model of loans and the role of relationships[END_REF][START_REF] Brown | Who needs credit and who gets credit in Eastern Europe?[END_REF][START_REF] Freel | The latent demand for bank debt: Characterizing discouraged borrowers[END_REF][START_REF] Cole | Who needs credit and who gets credit? Evidence from the surveys of small business finances[END_REF][START_REF] Cowling | UK credit and discouragement during the GFC[END_REF][START_REF] Popov | Gender bias and credit access[END_REF][START_REF] Rostamkalaei | Borrower discouragement: the role of informal turndowns[END_REF][START_REF] Calabrese | Financial fragmentation and SMEs' access to finance[END_REF]Nguyen et al., 2021;[START_REF] Brown | Innovation and borrower discouragement in SMEs[END_REF]. Moreover, we also contribute to the literature exploring the impact of culture or informal institutions on economic outcomes and firm behavior [START_REF] Guiso | Does Culture Affect Economic Outcomes?[END_REF][START_REF] Hilary | Does religion matter in corporate decision making in America?[END_REF][START_REF] Nguyen | Formal and informal financing decisions of small businesses[END_REF], and the impact of interpersonal trust on firms' access to finance and financing constraints [START_REF] Guiso | Social Capital as Good Culture[END_REF][START_REF] Leblang | The effect of trust on economic performance and financial access[END_REF]. [START_REF] Guiso | Social Capital as Good Culture[END_REF] purport that individual beliefs are initially formed by cultural transmission and are slowly changed from one generation to another. Trust beliefs are therefore transmitted between generations, and may be altered by the experience of temporary shocks.

We address potential endogeneity issues by using the instrumental variable probit model and use robust regression techniques to address potential sample selection issues. We mainly use a country's experience with systemic banking crises and religion as instruments for trust in banks and interpersonal trust, respectively, consistent with studies that find banking crises' experience alters people's trust in financial institutions [START_REF] Fungáčová | Trust in Banks[END_REF][START_REF] Fungáčová | Does Experience of Banking Crises Affect Trust in Banks[END_REF], and evidence linking hierarchical religion, that focuses on a vertical bond vis-à-vis horizontal bond with fellow citizens, to lower interpersonal trust [START_REF] Putnam | Making democracy work: Civic traditions in modern Italy[END_REF][START_REF] Porta | Trust in Large Organizations[END_REF]. Studying a sample of respondent firms to several World Bank Enterprise Surveys conducted from 2015 to 2019, our findings show that firms in high-trust-in-banks countries are less likely to get discouraged from borrowing from financial institutions than their counterparts. Moreover, we also find complementary effects of trust in banks and interpersonal trust in reducing the incidence of borrower discouragement. Further, we also study whether the interaction of both forms of trusttrust in banks and interpersonal trust, influence the proportion of firms' working capital operations financed by banks. Overall, our findings contribute to the understanding of how culture or informal institutions affect firms' credit constraints.

This paper is organized as follows. Section 2 reviews the related literature and discusses our research focus. We present the data and variables used in our empirical analyses in Section 3. Section 4 tackles the empirical methodology, while Section 5 reports the results. We check the robustness of our findings and investigate further issues in Section 6. We conclude in Section 7.

Research Framework and Hypotheses

Trust in Banks and Borrower Discouragement

Several studies show that trust in banks fell sharply in countries hit by the GFC [START_REF] Iyer | Understanding bank runs: The importance of depositor-bank relationships and networks[END_REF][START_REF] Sapienza | A trust crisis[END_REF][START_REF] Knell | Trust in banks: evidence from normal times and from times of crises[END_REF]. The experience of loss in a banking crisis influences personal perceptions and expectations [START_REF] Mudd | The Effect of Loss Experiences in a Banking Crisis on Future Expectations and Behavior[END_REF], affecting decision-making and risk preferences [START_REF] Malmendier | Depression babies: Do macroeconomic experiences affect risk taking?[END_REF]. Consequently, this may lead to the erosion of trust [START_REF] Lewicki | Trust in relationships[END_REF][START_REF] Lewicki | Trust, trust development, and trust repair[END_REF]. In addition, [START_REF] Fungáčová | Does Experience of Banking Crises Affect Trust in Banks[END_REF], investigating how experience with banking crises impacts an individual's trust in banks, find both the experience of a banking crisis and its length negatively related to trust in banks, degrading the trust of especially older people. Distrust in banks negatively affects both the availability and stability of funds via deposits [START_REF] Sapienza | A trust crisis[END_REF][START_REF] Iyer | Understanding bank runs: The importance of depositor-bank relationships and networks[END_REF]. In addition, the erosion of trust impairs the relationship with banks [START_REF] Guiso | The Determinants of Attitudes toward Strategic Default on Mortgages[END_REF], forcing firms to find other alternatives to fund their operations, such as non-financial suppliers or the peer-to-peer lending market, or to forego their investments. Indeed, the emergence of fintech companies has been partly attributed to the GFC [START_REF] Blaseg | Equity crowdfunding: high-quality or lowquality entrepreneurs[END_REF][START_REF] Cortina | The Fintech Revolution: A Threat to Global Banking[END_REF]. The collapse of the Silicon Valley Bank (SVB) in 2023 has caused a bank run not only on SVB but also to other banks such as Signature Bank. In addition, the financial difficulties experienced by globally systemically important banks such as Crédit Suisse, and Deutsche Bank at the same time, increased fears of contagion in the banking sector. Such episodes are expected to increase firms' supply-side and demandside credit constraints, with increased expectations of rejection and tighter credit conditions.

Trust in banks may affect borrower discouragement through several channels. First, trust in banks influences depositors, which affects credit supply. Distrust in banks impairs the growth of deposits and hampers the intermediation process, which consequently increases fears of rejection and expectations of more stringent credit conditions, thus discouraging firms from applying for loans. Moreover, firms that have made deposits in banks may decide to secure their bank deposits and forego applying for a loan even if they needed one when faced with increased distrust in banks, hence, decreasing their demand for formal credit.

Second, lower trust in banks may discourage firms from using formal financial services, including bank credit. Several studies find trust in financial institutions positively linked with household saving behavior, use of formal savings instruments, and savings diversity [START_REF] Dupas | Challenges in banking the rural poor: Evidence from Kenya's Western Province[END_REF][START_REF] Beckmann | Formal and informal household savings: how does trust in financial institutions influence the choice of savings instruments?[END_REF][START_REF] Ampudia | Trust and the household-bank relationship[END_REF][START_REF] Garz | Consumer protection for financial inclusion in low-and middle-income countries: Bridging regulator and academic perspectives[END_REF][START_REF] Galiani | Trust and saving in financial institutions by the poor[END_REF][START_REF] Bachas | How Debit Cards Enable the Poor to Save More[END_REF]. Conducting a field experiment in Peru, [START_REF] Galiani | Trust and saving in financial institutions by the poor[END_REF] find building trust in financial institutions essential in increasing the use of formal financial services, suggesting that financial inclusion requires trust. [START_REF] Bachas | How Debit Cards Enable the Poor to Save More[END_REF] point out that poor households receiving cash transfers from the Mexican government through debit cards left small amounts in their accounts due to a lack of trust in banks. This is due to the high transaction costs associated with saving in a bank and the fear of hidden charges. Similar behavior was also found in India [START_REF] Muralidharan | Building state capacity: Evidence from biometric smartcards in India[END_REF]. Moreover, evidence indicating that the use of formal saving tools increases bank deposit funding stability [START_REF] Han | Broader use of saving products among people can make deposit funding of the banking system more resilient[END_REF] suggests that increased distrust in banks may lead to instability in bank deposit funding, and hence, increased uncertainty of a loan application's approval, especially for smaller, younger businesses. [START_REF] Han | Broader use of saving products among people can make deposit funding of the banking system more resilient[END_REF]. Thus, aside from influencing credit supply through increased saving behavior, trust in banks may serve as a gateway for firms to use other financial services, including credit and insurance, that fosters investment and better risk management. Although one could argue that trust is less of a concern for the borrower than for the bank in lending decisions, our view is that trust in banks propels borrowers to take the first step, which is to seek formal credit. [START_REF] Ferrando | The real effects of credit constraints: Evidence from discouraged borrowers[END_REF][START_REF] Ferrando | The real effects of credit constraints: Evidence from discouraged borrowers[END_REF]Wernli andDietrich (2022) estimate that about 40% 3 , and 60%, respectively, of discouraged firms in Belgium and Switzerland would have obtained a bank loan if they sought for it. Third, trust in banks is linked with knowledge about and experience with financial institutions and their services, and hence, a higher trust in banks may imply higher propensity to demand bank credit, and lower borrower discouragement. Several studies show that trust in banks is associated with familiarity about financial institutions and financial literacy [START_REF] Allen | The foundations of financial inclusion: Understanding ownership and use of formal accounts[END_REF]van der Cruijsen et al., 2021b). Furthermore, trust in banks may be further strengthened from repeated interactions with banks or through established banking relationships that reduce borrower discouragement in line with firm-level studies [START_REF] Freel | The latent demand for bank debt: Characterizing discouraged borrowers[END_REF]. Moreover, low trust in banks may be driven by a culture of informality [START_REF] Perry | Informality: Exit and exclusion[END_REF], where informality becomes a social norm, including the use of informal finance. Thus, we purport that higher trust in banks increases a firm's propensity to demand bank credit and, hence, decreases the incidence of borrower discouragement.

Hypothesis 1.

Higher trust in banks decreases the incidence of borrower discouragement.

Trust in Banks and Borrower Discouragement: Does Interpersonal Trust Matter?

Interpersonal trust, an essential mechanism for social capital, plays a significant role in enhancing economic performance [START_REF] Putnam | Making democracy work: Civic traditions in modern Italy[END_REF]Zak and Knack, 2001;[START_REF] Knack | Trust, associational life, and economic performance[END_REF]. It enhances cooperative attitude, pro-social behavior [START_REF] Fehr | On the Economics and Biology of Trust[END_REF][START_REF] Carlo | Exploring the Relations among Trust Beliefs, Prosocial tendencies, and Friendships[END_REF], and reduces 3 This corresponds to the percentage of discouraged borrowers who have a high likelihood of being approved if they applied for a loan. They note, in addition, that 40% of discouraged borrowers have reasonable likelihood of obtaining a bank loan if they applied for one. the uncertainty about economic agents' willingness to reciprocate. Social capital can also improve economic efficiency and encourage reputation-building for honest dealing in transactions through the disciplinary mechanism of reputation loss (Kandori, 1992, McMillan and[START_REF] Mcmillan | Private order under dysfunctional public order[END_REF]. By increasing the costs of expropriation and breach, social capital enhances contract enforcement, especially in weak regulatory environments [START_REF] Knack | Does social capital have an economic pay-off? A cross-country investigation[END_REF][START_REF] Carlin | Public trust, the law, and financial investment[END_REF][START_REF] Cline | Trust, regulation, and contracting institutions[END_REF]. Through this channel, social capital diminishes financial contracting costs and facilitates access to external financing. In addition, social capital may serve as an alternative mechanism to resolve disputes through voluntary cooperation within a social network that diminishes the expected breadth and costs of legal interventions. This makes it easier for firms to obtain external financing. SMEs, in particular, tend to follow the pecking order theory in their financing decisions and therefore have an initial preference for internal sources of finance, followed by debt (López-Gracia and Sogorb-Mira, 2008). However, an increase or expansion in the scope of social ties raises the potential use external financeboth formal, and informal. Indeed, [START_REF] Nguyen | Formal and informal financing decisions of small businesses[END_REF] find habitual entrepreneurs or those with wider networks more likely to use external finance. In formal financial contracts, lenders often require historical financial information from potential borrowers to screen and monitor them. In addition, they also often ask for collateral to ensure their credibility. Trust plays a crucial role in reducing adverse selection and moral hazard problems, especially in the case of smaller banks and those that delegate operational autonomy to local managers [START_REF] Degryse | Relationship lending, Trust, and SME bank financing in the U[END_REF]. Several studies find high levels of interpersonal trust facilitate firms' credit access even if the bank faces an information gap [START_REF] Hernández-Cánovas | Relationship Lending and SME financing in the continental European bank-based system[END_REF][START_REF] Moro | Loan managers' trust and credit access for SMEs[END_REF][START_REF] Palazuelos | Accounting information quality and trust as determinants of credit granting to SMEs: the role of external audit[END_REF][START_REF] Kautonen | Trust-based banking and SMEs' access to credit[END_REF]. This is because interpersonal trust may reduce the uncertainty left when the bank has processed all information to assess the quality of the borrowing firm [START_REF] Moro | Loan managers' trust and credit access for SMEs[END_REF]. Furthermore, trust creates a positive expectation of the firms' behavior, even if it could exploit the bank's vulnerability [START_REF] Mayer | An integrative model of organizational trust[END_REF][START_REF] Rousseau | Not so different after all: A cross-discipline view of trust[END_REF]. At the same time, it allows the bank's lending posture to be more benevolent towards the firm. Moreover, financial transactions are perceived to be less risky, mitigating opportunistic firm behavior, in high trust environments [START_REF] Hasan | Social Capital and Debt Contracting: Evidence from Bank Loans and Public Bonds[END_REF]. In contrast, informal financial transactions neither require financial information nor a reliable debtor guarantee. Informal finance lenders have to use personal relationships to reduce asymmetric information and use information built upon the network to screen the borrowers and price the loans. In this case, trust could facilitate the flow of private information about the credibility of the borrowers [START_REF] Agarwal | Distance and private information in lending[END_REF]. [START_REF] Karlan | Trust and Social Collateral[END_REF] show that network-based trust leads to higher informal borrowing, suggesting that network connections serve as social collateral, which is crucial in obtaining informal finance. Hence, a firm's expectation about the credit conditions and likelihood of the success of its demand for loan from formal or informal lenders could be influenced by its interpersonal trust environment. Thus, we argue that while higher trust in banks encourages firms in need of credit to take the first step in applying for a bank loan, a high interpersonal trust environment could further boost this decision. To the extent that interpersonal trust may reduce loan officers' hesitation4 and encourage a cooperative attitude toward a borrowing firm after evaluating its project and credit needs, trust in banks is primordial for firms to seek credit from banks. Thus, we posit that interpersonal trust and trust in banks are complements in reducing borrower discouragement.

Hypothesis 2. Interpersonal trust complements trust in banks in reducing borrower discouragement

Data, Variables, and Descriptive Statistics

Data and Sample

We obtain cross-section firm-level information on respondent firms from the World Bank Enterprise Surveys (WBES) conducted from 2015 to 2019 in 80 countries. Country-level trust data were gathered from the World Values Survey (WVS) database [START_REF] Inglehart | World Values Survey: Round Six -Country-Pooled Datafile[END_REF][START_REF] Haerpfer | World Values Survey: Round Seven -Country-Pooled Datafile[END_REF]. We note that only 27 countries report latest country-level trust information just before the firm surveys were conducted. We obtain macroeconomic indicators from the World Development Indicators and Global Financial Development Database, and institutional quality data from the Doing Business Database of the World Bank. We identify 15505 respondent firms in 245 countries for which we have complete information on firmspecific, country-based trust, macroeconomic, and institutional quality variables. Out of the 15505 firms6 , we identify 8395 firms that needed external financing in the past 12 months before the survey was conducted, and thus, have either applied for a loan or were discouraged to do so because of unfavorable interest rates, high collateral requirements, fear of rejection, etc.

Trust in Banks and Interpersonal Trust

We measure country-level trust in banks, and interpersonal trust based on individual responses to Waves 6 (2012-2016) and 7 (2017-2020) of the World Values Survey (WVS). The WVS provides a reliable comparison of trust across countries [START_REF] Algan | Trust, growth, and well-being: New evidence and policy implications[END_REF] and has been used in several trust-related studies [START_REF] Horváth | Does Trust promote growth[END_REF][START_REF] Fungáčová | Trust in Banks[END_REF][START_REF] Fungáčová | Does Experience of Banking Crises Affect Trust in Banks[END_REF]. The samples are selected using a combination of probability-proportional-to-size and multistage sampling techniques7 . Thus, we rely on two sets of questions to distinguish between trust in banks, and interpersonal trust.

To measure trust in banks (TrustinBanks), we calculate the proportion of respondents who answered having a 'great deal of confidence' or 'quite a lot of confidence' to the question: "Could you tell me how much confidence you have in banks: Is it a great deal of confidence [START_REF] Hall | Why do some countries produce so much more output per worker than others[END_REF], quite a lot of confidence (2), not very much confidence (3) or none at all (4)?" To quantify interpersonal trust, we rely on respondents' answers to the question: "Generally speaking, would you say that most people can be trusted, or that you can't be too careful in dealing with people?". We calculate the proportion of respondents who answer: "Most people can be trusted" (InterpersonalTrust).

Borrower Discouragement

There is no consensus in the literature about the definition of borrower discouragement. Studies differ in the scope of the underlying causes of borrower discouragement [START_REF] Brown | Innovation and borrower discouragement in SMEs[END_REF]. While most consider fear of rejection as the reason behind firms' self-rationing, some survey studies consider other factors such as collateral requirements and other credit conditions [START_REF] Cowling | UK credit and discouragement during the GFC[END_REF][START_REF] Chakravarty | The international evidence on discouraged small businesses[END_REF]Wernli and Dietrich, 2022), debt aversion (Nguyen et al., 2021), and informal turndowns [START_REF] Rostamkalaei | Borrower discouragement: the role of informal turndowns[END_REF].

We measure borrower discouragement based on firms' responses to the WBES. Consistent with [START_REF] Chakravarty | The international evidence on discouraged small businesses[END_REF] who also use data from the WBES, and Wernli and Dietrich (2022), we define the dummy variable, BorrowerDiscouragement, which is equal to one for discouraged firms or those who did not apply for a loan or line of credit during the previous 12 months for other reasons besides not needing external financing (i.e., complex loan application procedures, unfavorable interest rates, high rejection likelihood…), and zero, for those who applied for a loan or line of credit.

Control Variables

For the control variables, we consider a range of firm-level and country-level factors that may affect a firm's credit access based on previous studies [START_REF] Distinguin | Can Informal Firms Hurt Registered SMEs' Access to Credit?[END_REF][START_REF] Carreira | No deep pockets: Some stylized empirical results on firms' financial constraints[END_REF][START_REF] Beck | Financial and legal constraints to growth: does firm size matter[END_REF].

We consider the firm's size by defining three dummy variables: Small-sized, Mediumsized, and Large-sized. We follow the WBES definition. Small-sized, Medium-sized, and Largesized are dummy variables equal to one if the firm has five to 19, 20 to 99, and at least 100 fulltime employees, respectively, and zero otherwise. In our estimations, we omit Small-sized, the benchmark, to avoid the singular matrix problem. We also account for a firm's age (Age) or the natural logarithm of the firm's age since its establishment. The literature documents a negative relationship between age, and size, on borrower discouragement. We also consider the characteristics of the firm's location and define the variable Population1M, which is equal to one if the locality where the firm operates has a population of over 1 million, and zero if less. More populated areas vis-à-vis less populous ones have different local banking market characteristics. We also control the firm's legal status and define three dummy indicators-SoleProprietorship, Partnership, and Others. The latter serves as the benchmark, and is thus, omitted in our estimations. Moreover, we also control for a firm's productivity (Productivity), defined as the natural logarithm of the value of the firm's sales over the number of permanent employees, scaled three years before the survey was conducted. We expect more productive firms to be less discouraged from borrowing from financial institutions because of their profitability potential. In addition, we control the firm's audit status (Audited). Audited is a dummy variable equal to one if an external auditor checks and verifies the firm's annual financial statement, and zero, otherwise. We also consider the firm's ownership and define two dummy variables -State-owned and Foreign-owned. State-owned and Foreign-owned are dummy variables equal to one if at least 50% of the firm is owned by the government/state and private foreign individuals and firms, respectively, and zero otherwise. We also distinguish firms that are affiliated with larger establishments from those which are not. Thus, we define Multiple, a dummy variable equal to one if the firm is part of a larger establishment and zero otherwise.

We also include manager-specific factors, such as the firm's top manager's sex (FemaleManager) and experience in the sector (ManagerExperience). Firms with more experienced managers are expected to be less discouraged from applying for formal credit. ManagerExperience is a dummy variable equal to 1 if the top manager has at least ten years of experience working in the sector and zero if less. FemaleManager is a dummy variable equal to one if the firm's top manager is female and zero otherwise. We also capture industry-specific differences by including industry dummies in our estimations. We note that 64.57% of the firms in the sample belong to the manufacturing sector, while 31.37%, and 4.06%, respectively, are from the construction, and other sectors (i.e. transport, renting and business activities) 8 . We also include year-specific differences concerning the period when the survey in a country was conducted by introducing survey year dummies.

We also consider macroeconomic variables such as inflation rate (Inflation) and the natural logarithm of the real GDP per capita, orthogonalized with the trust measures (LnGDP). Moreover, we also include a country's strength of legal rights as an indicator of firm credit access. It measures the degree to which collateral and bankruptcy laws protect the rights of borrowers and lenders, thus facilitating lending. The index (GettingCredit) ranges from zero (weak) to 12 (strong), with higher scores indicating that collateral and bankruptcy laws are better designed to expand access to credit. To assess the level of particularized trust, we also include trust in family as a control variable. We calculate the proportion of respondents in the WVS who trust or somewhat trust their family members (TrustinFamily). We note that because TrustinFamily is highly correlated with InterpersonalTrust and TrustinBanks, at 0.5205 and 0.3243, respectively, we consider its orthogonalized values with interpersonal trust and trust in banks. In addition, we also consider bank net interest margin9 aggregated at the country level, NetIntMargin, defined as the accounting value of a bank's net interest revenue as a percentage of its average interest-bearing asset. This measure captures cross-country variations in banks' ability to generate net interest income, market power, interest rate risk, and credit risk [START_REF] Angbazo | Commercial bank net interest margins, default risk, interest-rate risk, and off-balance sheet banking[END_REF][START_REF] Hawtrey | Bank interest margins in OECD Countries[END_REF].

Table A3 in the Appendix contains all the definitions and sources for the variables used in the study.

Descriptive statistics

Table 1 reports the summary statistics of the variables used in our estimations for the sample of 8395 borrower firms10 . Statistics show that 54.70% of firms needing credit are discouraged from applying for a loan or a line of credit. The majority of firms that need access to formal finance are dissuaded from applying for loans from financial institutions for various reasons. They include complex loan application procedures (17.94%), unfavorable interest rates (41.49%), high collateral requirements (12.96%), expectations about the loan not being approved (7.38%), and insufficient loan size and maturity (5.29%), and others (14.94%). Several studies show that in the case of developed countries, such as Switzerland (Wernli and Dietrich, 2022) and Belgium [START_REF] Ferrando | The real effects of credit constraints: Evidence from discouraged borrowers[END_REF], around 60% and 40% of discouraged firms, respectively, would have been granted a loan if they applied for one. Lack of loan application when a firm needs credit is, thus, a reason why firms rely less on formal financing. On average, only 17.88% of the working capital needs of firms in our sample are financed by banks.

[Insert Table 1] Regarding trust in banks, around half (52.85%) portray a great deal or quite a lot of confidence in banks, with significant cross-country variations (a minimum of 21.74% and a maximum of 91.74%). The level of interpersonal trust, however, is relatively low. Indeed, a large proportion of WVS respondents from the countries included in our study indicates that one needs to be very careful in dealing with people (around 85%, on average). In terms of firmlevel characteristics, most top managers are male (78.55%), and experienced (83.23%). Moreover, around 40% of the firms in our sample have their financial statements checked and verified by an external auditor. Most of the firms are small and medium-sized (76%). We also note that the countries included in our study display high particularized trust, with 95.34%, on average, of the WVS respondents indicating that they completely or somewhat trust their family. We also observe significant variations in country-level net interest margins, with a minimum of 1.46% and a maximum of 8.46%, and in the getting credit index, which ranges from zero to 11.

We also present the descriptive statistics of our main trust indicators of interest -trust in banks, and interpersonal trust, by country in Table 2. The statistics show that Greece has the lowest trust in banks, with only 21.74% of the WVS respondents showing a great deal or quite a lot of confidence in banks. Other countries with relatively low trust in banks include Eastern European countries such as Romania, Cyprus, and Serbia. Southeast Asian countries, on the other hand, display relatively higher trust in banks, with Vietnam reporting that almost 92% of the WVS respondents show a great deal or quite a lot of confidence in their financial institutions. In terms of interpersonal trust, Zimbabwe (2.14%), Nicaragua (4.25%), and Colombia (4.54%) have low interpersonal trust levels, while Thailand (31.36%) and Ukraine (30.65%) display relatively high interpersonal trust.

[Insert Table 2]

Table 3 reports the average values of firms' reliance on banks to finance their working capital needs. Peru topped the list regarding the demand for and reliance on formal credit. Indeed, at least 35%, on average, of Peruvian firms in the sample finance their working capital through banks, while only 15% are considered discouraged borrowers. On the other hand, Egypt, Zimbabwe, and Ukraine rely the least on banks to finance their working capital requirements. Thailand and Indonesia document the highest proportion of discouraged borrower firms.

[Insert Table 3]

Empirical Methodology

Trust in banks and Borrower Discouragement

To examine the impact of trust in banks on borrower discouragement and test Hypothesis 1, we estimate Equation 1(Eq. 1) using probit and IV probit regressions. Pr( 1)

j j t t k t k TrustinBanks InterpersonalTrust Z BorrowerDiscouragement SurveyYear Sector     = = + + +      = =    + +       (Eq. 1)
We calculate the marginal probability effects of TrustinBanks on borrower discouragement as follows (Eq. (1')):

Eq. ( 1

') ( ) 2 ' X   
Where BorrowerDiscouragement is a dummy variable equal to one for discouraged borrowers, and zero, otherwise. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the survey was conducted. InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS trust question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?" Z is a vector of firm-specific and country-specific control variables that consider the firm's level of productivity, age, size, firm's locality, legal status, ownership, manager-specific characteristics, audit status, the country's strength of legal rights, net interest margin, trust in family, economic development, and inflation. Moreover, we also control for industry-specific differences by including industry dummies based on the firm's International Standard Industry Classification (ISIC), and year-specific effects by including survey year dummies.

Using the instrumental variables regression, we deal with plausible endogeneity issues that could arise from reverse causality. Although TrustinBanks is country-specific, discouraged borrowers are more likely to distrust banks because they are less likely to have established lending relationships with financial institutions. Moreover, measurement error could arise due to misinterpretation of the survey question or omitted variables that could be correlated to the trust in banks WVS question. Indeed, [START_REF] Fungáčová | Trust in Banks[END_REF] indicate that respondents tend to think about the banks' role in the economy, financial institutions' stability, confidence in bank supervisory authorities, and confidence in bankers when asked about their level of trust or confidence in banks. Moreover, interpersonal trust (InterpersonalTrust) might also be correlated to the error term because of measurement error or disparity in interpreting the WVS question across countries. Thus, we use the IV-probit regression.

As in Wernli and Dietrich (2022), we also deal with a plausible sample selection problem because we can only observe BorrowerDiscouragement for firms that expressed a need for financing, by using the maximum-likelihood probit model with sample selection. Further discussion and results using this method are reported in the Robustness Checks section.

Instruments

We use several instruments for trust in banks (TrustinBanks) and interpersonal trust (InterpersonalTrust). For trust in banks, we use as instrument a country's experience with a banking crisis -NumSysBankCrisis. NumSysBankCrisis is the number of systemic banking crises experienced by country j since 1970. We rely on the systemic banking crises database of [START_REF] Laeven | Systemic Banking Crises Revisited[END_REF] to calculate our measures. Several studies, such as [START_REF] Fungáčová | Does Experience of Banking Crises Affect Trust in Banks[END_REF], find that the experience of a banking crisis diminishes a person's trust in banks, which may be explained by the adverse effects of negative experiences on trust, consistent with findings in the behavioral science literature [START_REF] Glanville | How Do We Learn to Trust? A Confirmatory Tetrad Analysis of the Sources of Generalized Trust[END_REF]. Indeed, the experience of a banking crisis may alter a person's expectations and confidence in financial institutions, which is in line with studies that show higher future inflation expectations of individuals who have lived during high inflation periods [START_REF] Malmendier | Learning from Inflation Experiences[END_REF]. Moreover, increasing distrust in banks after the Global Financial Crisis in 2007/2008 has been one of the pinpointed causes of the emergence of fintech. Indeed, banking crises enable individuals, households, and firms not only to tap other financial service providers but could also shrink bank deposits, especially in countries without explicit deposit insurance schemes. We also use as an instrument for confidence in banks the number of sovereign debt crises experienced by a country (NumSovereignCrisis) since 1970. Indeed, some sovereign debt crises in recent years either coincided with or followed banking crises. Moreover, the two sectors are closely interconnected, with transmission channels in both directions. Sovereign shocks can influence the banking system, and fragility in the banking system affects the sovereign [START_REF] Correa | Sovereign debt crises[END_REF].

In addition, we also include religious values as an instrument for both interpersonal trust and trust in banks. [START_REF] Putnam | Making democracy work: Civic traditions in modern Italy[END_REF] purports that hierarchical religion that includes Catholicism, Islam, and Orthodox Christianity discourages trust formation. Moreover, La [START_REF] Porta | Trust in Large Organizations[END_REF] find a negative link between the dominance of a strong hierarchical religion in a country, especially Catholicism, and trust. Meanwhile, [START_REF] Fungáčová | Trust in Banks[END_REF] show a negative association between trust in banks and hierarchical religions (relative to Protestantism), particularly Catholicism and Orthodox Christianity, which could be explained by hierarchical religions' negative views on usury or charging of interest rates. Thus, we define HierarchicalReligion, which is equal to the percentage of the population whose religions are either Catholicism, Islam, or Orthodox Christianity. We obtain country-level data on religious affiliations from the World Values Survey [START_REF] Inglehart | World Values Survey: Round Six -Country-Pooled Datafile[END_REF][START_REF] Haerpfer | World Values Survey: Round Seven -Country-Pooled Datafile[END_REF].

We note that using these instruments is expected to eliminate the direct correlation between trust in banks and interpersonal trust and firm-specific unobserved characteristics. Moreover, we reduce further endogeneity bias due to omitted variables by controlling for other firm-specific, country-specific, and year-fixed effects. We test the validity and relevance of our instruments, ensuring the satisfaction of the exclusion restriction and, hence, the IV estimator's consistency. Thus, we perform the weak identification test using the Sanderson-Windmeijer (SW) first-stage F test of excluded instruments, the underidentification test using the Kleibergen-Paap rk LM test, and verify the exclusion restriction using the Hansen-J test or test of overidentifying restrictions. Furthermore, we carry out an exogeneity test by calculating the C-statistic to verify that trust in banks, and interpersonal trust are indeed endogenous. We alternatively use other sets of instruments, relying on previous studies that find variations in geographic and biogeographical (initial) conditions as drivers of differences in cultural preferences [START_REF] Olsson | Biography and long-run economic development[END_REF]Galor and Özak, 2016a;[START_REF] Falk | Global Evidence on Economic Preferences[END_REF] in the Robustness Checks Section.

Trust in Banks and Interpersonal Trust: Complements or Substitutes?

We also test Hypothesis 2 and examine whether there are complementary effects of trust in banks and interpersonal trust on borrower discouragement. Thus, we estimate Equation 2(Eq. 2):

( )

1 2 3 4 2019 34 2016 2
Pr( 1)

j j j t t k t k TrustinBanks InterpersonalTrust BorrowerDiscouragement TrustinBanks InterpersonalTrust Z SurveyYear Sector      = =     + + +     = =   +  +     +         (Eq. 2)
Where TrustinBanks x InterpersonalTrust is the interaction term between trust in banks and interpersonal trust.

Moreover, to obtain the marginal probability effects of TrustinBanks on borrower discouragement at different percentile levels of InterpersonalTrust, we calculate Eq. (2') as follows:

Eq. (2')

( )( ) 2 4 ' i X InterpersonalTrust     +
Higher positive marginal probability effects of trust in banks on borrower discouragement at higher percentile levels of interpersonal trust imply complementary effects of trust in banks and interpersonal trust.

Empirical Results

Results: Baseline Specification -Does trust in banks matter in reducing borrower discouragement?

We present the probit and instrument variable (IV)-probit estimation results of our baseline specification in Table 4a, where trust in banks, and interpersonal trust are considered endogenous. The Wald test of exogeneity confirms the correlation between these explanatory variables and the error term or the unobserved characteristics influencing borrower discouragement. Moreover, performing the Kleibergen Paap rk LM test and the Sanderson-Windmeijer (SW) first stage F-test of excluded instruments, we reject the null hypothesis of under identification and weak identification, thus, underlining the relevance of our instruments. To confirm the validity of our instruments and hence, the satisfaction of the exclusion restriction condition, we execute the test of overidentifying restrictions using the Hansen J test. The results suggest the absence of a correlation between the excluded instruments and the error term. Meanwhile, the weak-instrument robust inference test (Anderson-Rubin Wald test) indicates the significance of TrustinBanks and InterpersonalTrust in the structural equation. We present in Table 4b the first-stage regression results of the IV probit estimation. As expected, we find a negative relationship between our three excluded instruments: NumSysBankCrisis, NumSovereignCrisis, and HierarchicalReligion, and trust in banks. In terms of economic significance, we find hierarchical religion (expressed in percentage) to have the strongest influence on trust in banks, followed by the number of systemic banking crises experienced by a country. Indeed, a one-standard-deviation increase in HierarchicalReligion (NumSysBankCrisis) leads to a 0.8102 (0.1640) standard deviation decrease in TrustinBanks. This indirectly confirms the finding of [START_REF] Guiso | Social Capital as Good Culture[END_REF], who suggest that individual values and beliefs are initially formed through cultural transmission and slowly change with the experience of temporary shocks. With regard to interpersonal trust, we find a negative impact of hierarchical religion and the number of sovereign crises experienced by a country on interpersonal trust, while we find a positive impact of the number of systemic banking crises a country experienced on interpersonal trust11 . In terms of economic significance, we find hierarchical religion to have the strongest influence on interpersonal trust. A one-standarddeviation increase in HierarchicalReligion results in a 1.0447 standard deviation decrease in interpersonal trust.

[Insert Tables 4a and4b] We report the calculated marginal effects of TrustinBanks and InterpersonalTrust on the probability that a firm gets discouraged from borrowing from financial institutions (BorrowerDiscouragement) in Table 4c.

[Insert Table 4c]

Our findings show that firms in countries with higher trust in banks are less likely to get discouraged from borrowing from financial institutions, using both probit and IV-probit regression techniques. In terms of economic significance, our IV-probit results indicate that a one-standard-deviation increase in trust in banks lowers the probability of a firm getting discouraged from borrowing from financial institutions by 14.64 percentage points, which is about 10 percentage points larger in absolute value than the prediction of the probit estimation (4.86 p.p.). The larger marginal probability effect of trust in banks in reducing borrower discouragement using the IV-probit vis-à-vis the probit estimation technique may be explained by the use of the predicted value of trust in banks determined by the instruments in the first stage regression, rather than the observed value of trust in banks. The use of alternative instruments in the Robustness Checks section indicate consistent results; a one-standarddeviation increase in trust in banks diminishes the probability that a firm which needs credit gets discouraged from applying for a loan by 9.58 to 21.92 percentage points.

The results regarding the impact of interpersonal trust on borrower discouragement are, however, less robust. We only find a significant link between interpersonal trust and borrower discouragement using IV-probit regression but not with probit estimation. The IV-probit results suggest that firms in countries with higher interpersonal trust are more likely to be discouraged from applying for loans from financial institutions. This may be explained by the impact of social capital, such as network-based trust, in facilitating access to informal borrowing [START_REF] Karlan | Trust and Social Collateral[END_REF]. Wu et al. (2016) suggest that differences in the financing contract provisions between formal and informal credit may affect firms' decision to use informal vis-à-vis formal finance. Informal finance may be more attractive to firms because of its speed (Wu et al., 2016;[START_REF] Hu | Promoting the participation of microfinance in entrepreneurial ventures' technological innovation[END_REF] and negotiation flexibility [START_REF] Buckley | Microfinance in Africa: is it either the problem or the solution?[END_REF].

Regarding our control variables, we find NetIntMargin positively linked with borrower discouragement. This suggests that firms in countries with higher net interest margins, and thus, are exposed to relatively higher interest rate and credit risks, are more likely to be discouraged from applying for loans from financial institutions than their counterparts. Moreover, we find GettingCredit significant in reducing the likelihood of borrower discouragement in the IV-probit estimation. This is not surprising since better collateral and bankruptcy laws that safeguard the rights of both borrowers and lenders facilitate the borrowing and lending process and decision-making. Moreover, consistent with our expectations, larger firms are less likely to be discouraged from applying for loans than smaller firms. Meanwhile, we find audited firms less likely to be discouraged from applying for loans than their counterparts. Audited firms are more informationally transparent and are more likely to have already established a lending relationship with formal financial institutions. In contrast, unaudited firms do not have reliable financial information demonstrating their operations' viability and sustainability, which could dissuade them from seeking formal credit. We also find firms with experienced top managers (at least ten years of experience) less likely to be discouraged from borrowing from financial institutions. Furthermore, we find firms whose legal status are sole proprietorship and partnerships more likely to be discouraged borrowers than other firms (i.e., limited liability companies). We do not, however, find the gender of the top manager a significant determinant of borrower discouragement.

Transmission channel

We further investigate how trust in banks affects borrower discouragement by excluding firms that do not rely on banks to finance their working capital needs. This allows us to examine whether the impact of trust in banks on borrower discouragement holds even for firms that have an existing lending relationship with banks. We report the calculated marginal probability effects of trust in banks on borrower discouragement from estimating the baseline equation (Eq. 1) in Table 5. The results indicate that even when excluding businesses that may not have a lending relationship with banks, we find firms in countries with relatively higher trust in banks less likely to be discouraged from applying for loans from financial institutions. Indeed, a onestandard-deviation increase in trust in banks reduces the likelihood of credit self-rationing by 28.29 percentage points using the IV-probit regression and 8.26 percentage points using the probit estimation technique. Moreover, we also find that when using the probit regression, a one-standard-deviation increase in interpersonal trust reduces the probability of a firm getting discouraged from applying for loans by 5 percentage points.

[Insert Table 5]

Results: Effect of the interaction between TrustinBanks and InterpersonalTrust on firms' formal credit reliance

We present the regression results of the impact of the interaction between trust in banks and interpersonal trust on borrower discouragement in Table 6a. Moreover, we show the calculated marginal effects of higher trust in banks on the firm's likelihood of being a discouraged borrower in Table 6b. The findings generally indicate complementary effects of trust in banks and interpersonal trust in reducing borrower discouragement.

[Insert Tables 6a and6b] Indeed, trust in banks significantly lowers a firm's likelihood of becoming a discouraged borrower, but only in countries with relatively higher interpersonal trust levels. Using the IVprobit estimation technique, we find that for firms located in countries where at least 20% of the population indicates that most people can be trusted (evaluated at the 75 th percentile), a one-standard-deviation increase in trust in banks lowers a firm's probability of being a discouraged borrower by 19.57 percentage points (p.p.). Firms in countries where interpersonal trust level is very high (evaluated at the 90 th percentile), the likelihood of being a discouraged borrower decreases by 26.91 p.p. with a one-standard-deviation increase in trust in banks. We find consistent results using the probit regression for firms in countries with high interpersonal trust levels. Indeed, a one-standard-deviation increase in trust in banks reduces the probability that a firm gets discouraged from borrowing from financial institutions by 15.69 and 22.27 percentage points, respectively, in countries with relatively higher interpersonal trust levels (evaluated at the 75 th and 90 th percentiles, respectively).

Robustness Checks and Further Issues

We perform several robustness checks by 1) estimating our model using alternative instruments; 2) considering subsamples of audited vs. unaudited firms and firms of different sizes; 3) addressing multicollinearity concerns across our trust measures; 4) excluding countries where Islamic banking is important; and 5) examining the impact of the interaction between trust in banks and interpersonal trust on bank financing of firms' working capital needs.

Using alternative instruments

We also use alternative instruments for trust in banks and interpersonal trust that have been used in the literature [START_REF] Horváth | Does Trust promote growth[END_REF][START_REF] Ahlerup | Social capital vs. institutions in the growth process[END_REF][START_REF] Olsson | Biography and long-run economic development[END_REF]; Galor and Özak, 2016a)absolute latitude, initial biogeographic endowments, and genetic distance. Moreover, we consider the duration of colonization in a country as an alternative instrument for trust.

The variable AbsLatitude is the natural logarithm of the absolute value of the latitude of a country's approximate geodesic centroid, reported by the CIA World Factbook (Galor and Özak, 2016a). It is expected to be negatively linked to trust because of the prevalence of infectious diseases in countries nearer the equator [START_REF] Hall | Why do some countries produce so much more output per worker than others[END_REF], and more ethnic and linguistic heterogeneity that adversely affects the viability of mutually reinforcing societal characteristics [START_REF] Le | Societal Trust and Geography[END_REF]. [START_REF] Ahlerup | Social capital vs. institutions in the growth process[END_REF] and Horváth (2013) also use absolute latitude as instrument for trust. We gather information about a country's geographical latitude, either of the capital city or most populated city, from [START_REF] Galor | Replication data for : The Agricultural Origins of Time Preference[END_REF].

A recent study by [START_REF] Falk | Global Evidence on Economic Preferences[END_REF] shows positive correlations between biogeographic conditions (or the presence of large domesticable animals) and absolute latitude with trust preferences. Thus, we also use initial biogeographic endowments, particularly large domesticable animal presence, as an alternative instrument for trust. We collect data on the initial biogeographic endowments from [START_REF] Olsson | Biography and long-run economic development[END_REF]. We define the variable Animals as the number of domesticable mammals that weigh more than 45 kg known to exist in prehistory. The prevalence of such domesticable mammals sped up the hunter-gatherer to sedentary agriculture transition, that created new demands on social organization, which led to emerging cities, states, institutions, among others. [START_REF] Diamond | Guns, Germs and Steel: The Fates of Human Societies[END_REF] presents varied distribution in terms of the species suitable for domestication, across continents. He finds that only 14 out of 148 species weighing more than 45kg have been domesticated. In Sub-Saharan Africa, for example, although they find 51 of the heaviest mammals, no one passed the grounds they set for domestication.

ColonialDuration refers to the duration of colonization in a country or the time spent under colonial rule, expressed in hundreds of years. Countries with higher values of ColonialDuration indicate higher degree of destruction of indigenous social and economic structures, and thus, have a younger current social, political and economic structure compared to other countries, which is crucial to the formation of trust not only between each other but also to its institutions.

We also consider a country's genetic distance to the U.S. as an alternative instrument. The use of the U.S. as a benchmark is consistent with [START_REF] Horváth | Does Trust promote growth[END_REF] and [START_REF] Gorodnichenko | Culture, Institutions and the Wealth of Nations[END_REF] because of the country's high degree of individualism. Several studies such as [START_REF] Desmet | The stability and breakup of nations: a quantitative analysis[END_REF] find correlation between genetic distance and cultural heterogeneity. We use the new FST genetic or ancestral distance data constructed by [START_REF] Spolaore | Ancestry and Development: New Evidence[END_REF], and based on the work of [START_REF] Pemberton | Population Structure in a Comprehensive Genomic Data Set on Human Microsatellite Variation[END_REF]. Unlike the classic genetic markers such as immunoglobulins, they are based on microsatellite variation that covers 267 populations and 645 microsatellite loci. By studying microsatellite variation, geneticists can infer relatedness between human populations. We use the weighted FST genetic distance (GeneticDistance) between each country j and the U.S. This measure indicates the expected genetic distance between a randomly selected individual in country j and another randomly selected individual in the U.S.

We present the calculated marginal probability effects of trust in banks and interpersonal trust on borrower discouragement in (iv) NumSysBankCrisis, NumSovereignCrisis, AbsLatitude, HierarchicalReligion; and (v) NumSysBankCrisis, HierarchicalReligion, GeneticDistance. Overall, we find consistent results regarding the impact of trust in banks on borrower discouragement when using alternative instruments. We find firms in countries with higher trust in banks less likely to be discouraged from borrowing from financial institutions than firms in countries with lower trust in banks. Indeed, a one-standard-deviation increase in trust in banks decreases the probability that a firm becomes discouraged from applying for loans from financial institutions by 21.92 percentage points (p.p.), 17.46 p.p., 14.30 p.p., 14.81 p.p., and 9.58 p.p., respectively using instruments (i), (ii), (iii), (iv), and (v). Moreover, the statistics confirm the relevance and validity of our instruments and, thus, verify the exclusion restriction. Concerning the impact of interpersonal trust on borrower discouragement, we only find significant results when using the presence of large domesticable mammals (ii), and colonialization duration (iii) as alternative instruments for hierarchical religion, but not when using absolute latitude (i), and genetic distance (v).

[Insert Tables 7a and7b]

Subsamples: Audited vs. Unaudited Firms

We also investigate the subsample of audited and unaudited firms in exploring the impact of trust in banks on borrower discouragement. We report the estimation results and calculated marginal probability effects of TrustinBanks on borrower discouragement in Tables 8a and8b, respectively. Our findings show that the positive impact of trust in banks in reducing the likelihood that a firm becomes a discouraged borrower holds only for unaudited firms. Indeed, a one-standard-deviation increase in trust in banks decreases the probability that an unaudited firm gets discouraged from applying for a loan from a financial institution by 7.30 to 13.09 percentage points. These findings confirm the crucial role played by informal institutions, particularly by trust in banks, in increasing reliance on formal credit.

[Insert Tables 8a and8b]

Subsamples according to firm size

We also examine the impact of trust in banks on borrower discouragement for a subsample of firms according to size (SMEs and non-small enterprises). We rely on the WBES definition to distinguish firms according to size. We note that we initially examined subsamples of small-sized, medium-sized, and large-sized firms. This disaggregation, however, results in violations in the full rank condition of the estimated covariance matrix in the IV-probit regression, which could be due to decreased variations in some firm-specific control variables. We estimate our baseline specification (Eq.1), report the results, and calculated marginal probability effects of trust in banks on borrower discouragement in Tables 9a and9b, respectively.

[Insert Tables 9a and9b] Our findings show that subsamples of SMEs, and non-small firms, encompassing medium-sized and large-sized enterprises, benefit from the positive impact of increased trust in banks in reducing the likelihood of borrower discouragement. We note, however, that the coefficient estimates are larger for non-small firms than SMEs. Indeed, our results indicate that a one-standard-deviation increase in trust in banks leads to a decrease in the likelihood of an SME getting discouraged from applying for credit from financial institutions by 3.58 to 13.04 percentage points. Moreover, for medium-sized and large-sized firms (non-small firms), a onestandard-deviation increase in trust in banks leads to a decreased incidence of borrower discouragement by 6.38 to 17.76 percentage points.

Multicollinearity issues between TrustinBanks and InterpersonalTrust

We consider potential multicollinearity concerns between our trust variables that may cause interpretation problems concerning our main variable of interest, TrustinBanks. Table 10a shows the correlation matrix between TrustinBanks and InterpersonalTrust. Although the correlation coefficient is relatively low (0.1772), to mitigate the impact of multicollinearity on the efficiency of our IV estimator, we calculate the orthogonalized value of trust in banks, TrustinBanks-oth, retaining only the component that is not explained by interpersonal trust. We report the results using the orthogonalized value of trust in banks in Tables 10b. Moreover, we present the calculated marginal probability effects of trust in banks on borrower discouragement in Table 10c and at varying percentile values of InterpersonalTrust in Table 10d. Overall, our findings regarding the impact of our main variable of interest, TrustinBanks-orth, on borrower discouragement hold even after considering multicollinearity issues.

[Insert Tables 10a, 10b, 10c, and 10d] 6.5. Firms' bank credit reliance: does trust matter?

We also examine the impact of the interaction between trust in banks and interpersonal trust on firms' bank credit reliance to finance their working capital needs12 . Tapping banks to finance firms' working capital requirements is an important first step especially for smaller firms toward using more complex formal financial services and long-term bank credit. Moreover, focusing on working capital (WC) financing is important because of its implications for firms' investment decisions [START_REF] Nicolas | Short-term financial constraints and SMEs' investment decision: evidence from the working channel[END_REF].

We conjecture that trust in banks may also lead to higher bank credit reliance but only in high interpersonal trust environments. Indeed, the degree of bank credit reliance is also determined by supply-side factors beyond firms' expectations of loan officers' decisions. A strong borrower-lender trust provides extra insurance for lenders that may bridge potential opportunistic behaviors' in lending transactions [START_REF] Anderson | Financing and corporate growth under repeated moral hazard[END_REF][START_REF] Hasan | Social Capital and Debt Contracting: Evidence from Bank Loans and Public Bonds[END_REF]. High interpersonal trust facilitates access to external financing by enhancing pro-social behavior and cooperative attitude, reputation-building and honest dealing with transactions [START_REF] Kandori | Social Norms and Community Enforcement[END_REF][START_REF] Mcmillan | Private order under dysfunctional public order[END_REF]. Moreover, some studies show that societal trust promotes financial reporting transparency and suggest that increased trust improves information production and enhances information sharing mechanisms [START_REF] Garrett | Trust and Financial Reporting Quality[END_REF][START_REF] Nanda | Trust, External Capital, and Financial Transparency[END_REF]. Trust is also found to reduce monitoring costs [START_REF] Lewicki | Trust and distrust: new relationships and realities[END_REF]. Thus, to the extent that social capital or trust enhances the use of external financingformal or informal, as found by recent studies [START_REF] Nguyen | Formal and informal financing decisions of small businesses[END_REF], higher trust in banks could drive firms to rely more on banks to finance their working capital needs. Thus, to test whether interpersonal trust complements trust in banks in enhancing the use of bank financing to fund working capital needs, we examine a sample of firms that exclude discouraged borrowers. This allows us to have a more homogenous sample of firms that expressed a need for a bank loan, or those that do not need credit but have obtained one in previous years. We present the descriptive statistics of this sample of firms in the Appendix (Table A4).

We mainly base our bank credit reliance measure on the firms' responses to the WBES question: "Over the fiscal year, please estimate the proportion of this establishment's working capital, that is, the funds available for day-to-day operations, that was financed from each of the following sources?". The sources of financing listed were (a) internal funds or retained earnings, (b) borrowed from banks, (c) borrowed from non-bank financial institutions [microfinance institutions, credit cooperatives, credit unions, or finance companies], (d) purchases on credit from suppliers, and advances from customers, and (e) others that include moneylenders, friends, relatives, etc. We define the variable, BankFinance, as the ratio of a firm's working capital financed by banks to its total working capital 13 . We use the OLS, IV, and Heckman selection estimation techniques to test whether there is a significant interaction effect between trust in banks and interpersonal trust on firms' bank credit reliance. To ensure that the Heckman selection model is well-identified, the selection equation (NeedExternalFinancing or the need for external financing) should contain at least one variable that is not in the outcome equation (BankFinance). The variable NeedExternalFinancing is a dummy variable equal to one if the firm has applied for a loan in the past 12 months or has an existing line of credit, and zero, if the firm did not apply for a loan. We note that BankFinance can only be observed if NeedExternalFinancing is equal to one. As in [START_REF] Leon | Does bank competition alleviate credit constraints in developing countries[END_REF], we consider the share of sales (goods and services) paid after delivery (PercSalesAfterDelivery), which is a measure of the funds needed by a firm to finance its working capital as an instrument or excluded variable that is present in the selection equation but not in the outcome equation. Moreover, we have also performed robustness checks by using other excluded selection variables that indicate a firm's growth potential: the presence of an ISO certification (ISOCertification), and a license to import (ImportLicense). We test the relevance of the Heckman selection model using the Wald test of independent equations. Moreover, we also calculate the athrho, which is a non-linear transformation of ρ or the correlation between the error terms of the outcome and selection equations, to evaluate the presence of a sample selection bias. The negative inverse mills ratio implies that firms with lower BankFinance are more likely to be observed. The results indicate a sample selection problem. We present the OLS, Heckman, and IV estimation results in Table 11a, and the calculated marginal effect of trust in banks at varying interpersonal trust levels in Table 11b.

[Insert Tables 11a and11b] The regression results show a positive interaction effect of trust in banks and interpersonal trust on the proportion of working capital needs financed by banks. These findings are robust to various specifications: OLS, Heckman, and IV regression. The calculated marginal effects in Table 11b indicate a positive, increasing impact of trust in banks on bank credit reliance but only at high interpersonal trust levels. A one-standard-deviation increase in trust in banks raises the proportion of a firm's working capital needs financed by banks by 0.0908 to 0.1090 (0.1240 to 0.1364) using the Heckman selection estimation, and IV regression techniques, respectively, at the 75 th (90 th ) percentile value of interpersonal trust. Moreover, we note that in countries with very low interpersonal trust levels, we find a negative relationship between trust in banks and firms' reliance on bank credit. Furthermore, the findings in Table 12a suggest that increasing interpersonal trust level would not be enough to raise firms' bank credit reliance in low trust-in-banks environments. Overall, these findings indicate that trust in banks and interpersonal trust go hand-in-hand in increasing reliance and access to bank credit.

Using Alternative Estimation Technique: Heckman Probit

13 We only retain firms for which at least 90% of their working capital funding sources is reported (banks, internal funds or retained earnings, non-bank financial institutions, other sources).

We also examine the impact of trust in banks, and the interaction effect of trust in banks and interpersonal trust using the Heckman probit regression. As discouraged borrowers are only observed when firms are credit-constrained, we address potential sample selection bias by using a probit model with sample selection (Van de Ven and Van Praag, 1981). Thus, we assume that there exists an underlying relationship:

* 1 i i BorrowerDiscouragement X   = +
such that we only observe the binary outcome (BorrowerDiscouragement):

( )

Pr * 0 obit i i BorrowerDiscouragement BorrowerDiscouragement =  . The dependent variable, however, is only observed if ( ) 2 0 Select i i BorrowerDiscouragement Z  = +
 or when the firm is creditconstrained (selection equation), where 𝜀 1 ∼ 𝑁(0,1); 𝜀 2 ∼ 𝑁(0,1); 𝑐𝑜𝑟𝑟(𝜀 1 , 𝜀 2 ) = 𝜌. When 0   , standard probit techniques yield biased results. For identification purposes, the selection equation should contain at least one variable that is excluded from the outcome equation (BorrowerDiscouragement). CreditConstrained is a dummy variable equal to one if the firm applied for a loan in the past 12 months and has no existing line of credit, and if the firm needs credit but has not applied for a loan, and zero if the firm has a current line of credit or has not applied for a loan because it does not need external financing. We use three instruments or excluded variables affecting a firm's credit constraint (CreditConstrained) but not directly impacting its discouragement from applying for loans. As in [START_REF] Leon | Does bank competition alleviate credit constraints in developing countries[END_REF], we use the percentage of sales paid by customers after the delivery of goods and services (PercSalesAfterDelivery), which measures the firm's working capital needs. We also use two other excluded variables that indicate a firm's growth potential: the presence of an ISO certification (ISOCertification), and a license to import (ImportLicense).

We present the probit with sample selection estimation results examining the impact of trust in banks, and the interaction between trust in banks and interpersonal trust, on borrower discouragement in Table 12a. Meanwhile, we show the conditional marginal probability effects of TrustinBanks on borrower discouragement in Table 12b, and at varying levels of InterpersonalTrust in Table 12c. Our findings suggest the presence of selection bias, as indicated by the significance of the athrho, which is a non-linear transformation of 𝜌. We note that even after tackling the presence of selection bias, our results regarding the impact of trust in banks on borrower discouragement remain unchanged. Indeed, firms in countries with higher trust in banks are less likely to be discouraged borrowers. Indeed, a one-standard-deviation increase in trust in banks lowers the likelihood of a firm getting discouraged from borrowing from financial institutions by around 2.67 percentage points. In countries with relatively higher interpersonal trust levels, at the 75 th and 90 th percentile levels of InterpersonalTrust, respectively, a one-standard-deviation increase in trust in banks reduces the probability that a firm becomes discouraged from applying for loans from financial institutions, when it needs one, by 5 to 7.68 percentage points.

[Insert Tables 12a,12b, 12c]

Excluding countries where Islamic banking is important

We also check the robustness of our results by investigating the subsample of firms in countries where Islamic banking is not prevalent. Islamic banking and finance, or Shariacompliant finance, whose main principles include the prohibition of paying or charging interest rates, has expanded in recent decades. We, thus, look into the impact of trust in banks without considering the ambiguity that respondents may face-whether the bank in question refers to conventional or Islamic banks.

We report the marginal probability effects of trust in banks on borrower discouragement in Table 13. We find the same results even after excluding countries where Islamic financial institutions have proliferated in recent years. Firms in countries with higher trust in banks are less likely to be discouraged from seeking loans from financial institutions than in countries with relatively lower trust in banks.

[Insert Table 13]

Discussion and Concluding Remarks

The main objective of this paper is to examine how informal institutions, specifically trust in banks, affect a firm's likelihood of being a discouraged borrower. Our findings using empirical estimation techniques that address endogeneity and sample selection issues indicate a positive impact of increased trust in banks in reducing the likelihood of credit self-rationing in firms. Trust in banks is vital for deposit stability, which is crucial in the intermediation process. Loss of trust in banks may impair the allocation of funds to productive use and increase expectations of stricter lending standards and tighter credit conditions. Moreover, in low-trustin-bank environments, firms are less likely to use formal financial services because of the fear of hidden charges and high transaction costs. We also investigate whether interpersonal trust alters the mechanism through which trust in banks reduce the likelihood of borrower discouragement. We hypothesize that a firm's interpersonal trust environment may affect loan approval and cost of credit expectations. Our results show that interpersonal trust and trust in banks go hand-in-hand in fostering the decision of a firm that needs credit to seek loan from a financial institution. We find a stronger influence of trust in banks in reducing the incidence of borrower discouragement in countries with relatively higher interpersonal trust levels, where financial transactions are perceived as less risky and cooperative attitudes and pro-social behavior are more pronounced. We also examine a further issue by studying whether a firm's trust environment affects the proportion of its working capital needs financed by banks. Our findings suggest complementary effects of trust in banks and interpersonal trust on bank credit reliance to finance firms' working capital requirements. Indeed, in high interpersonal trust environments, trust in banks has a stronger impact on firm's reliance on banks to fund their working capital needs. Our results are robust to various alternative econometric specifications in which other instruments are used for trust, potential sample selection issues are considered, and in which specific subsamples of firms are assessed.

Overall, this study provides additional insights for policymakers in understanding the mechanisms through which they could reduce firms' self-rationing credit constraints and improve firms' use of and access to formal finance. Our findings highlight the importance of trust in banks not only for capital allocation efficiency but also for achieving financial inclusion. The results of our study also stress the importance of strengthening the resilience of the banking industry to diminish the adverse effects of bank failures on the confidence in the banking system. van der Cruijsen, C., de Haan, J., Roerink, R. (2021a) BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those that need credit but did not apply for a loan or line of credit because of complex application procedures, unfavorable interest rates, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted, InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?" TrustinBanks x InterpersonalTrust is the interaction term between TrustinBanks and InterpersonalTrust. Firm-specific and country-specific control variables include the firm's level of productivity (Productivity), age (Age), size (Medium-sized, Largesized), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-owned, Foreignowned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), audit status (Audited), the country's getting credit indicator (GettingCredit), net interest margin (NetIntMargin), particularized trust (TrustinFamily, orthogonalized), economic development (LnGDP, orthogonalized) and inflation (Inflation). For full definition of the variables, please refer to Appendix Table A3. We also include survey-year and industry dummies based on the firm's ISIC. Excluded instruments (IV-probit): NumSysBankCrisis, NumSovereignCrisis, HierarchicalReligion, NumSysBankCrisis*AbsLatitude, NumSovereignCrisis*AbsLatitude, HierarchicalReligion*AbsLatitude dummy indicator equal to one for discouraged firms or those who did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". Control variables include TrustinFamily (orthogonalized), the firm's level of productivity (Productivity), age (Age), size (Medium-sized, Large-sized), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-owned, Foreign-owned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), audit status (Audited), a country's getting credit indicator (GettingCredit), a country's average net interest margin (NetIntMargin), economic development (LnGDP, orthogonalized) and inflation (Inflation). For full definition of the variables, please refer to Appendix (Table A3). We also include survey-year and industry dummies based on the firm's ISIC. BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those that need financing but did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks-orth is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted, orthogonalized with InterpersonalTrust; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". Control variables include trust in family (TrustinFamily, orthogonalized), the firm's level of productivity (Productivity), age (Age), size (Medium-sized, Large-sized), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-owned, Foreign-owned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), audit status (Audited), the country's getting credit indicator (GettingCredit), a country's average net interest margin (NetIntMargin), economic development (LnGDP, orthogonalized) and inflation (Inflation). For full definition of the variables, please refer to Appendix (Table A3). We also include survey-year and industry dummies based on the firm's ISIC. indicator equal to one for discouraged firms or those that need financing but did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". TrustinBanks*InterpersonalTrust is the interaction term between TrustinBanks and InterpersonalTrust. CreditConstrained is a dummy variable equal to one if the firm applied for a loan in the past 12 months and has no existing line of credit, and if the firm needs credit but has not applied for a loan, and zero if the firm has an existing line of credit or has not applied for a loan because it does not need external financing. PercSalesAfterDelivery is the percentage of sales paid by customers after the delivery of goods and services (PercSalesAfterDelivery); ISOCertification is a dummy variable equal to one if a firm has an ISO certification, and zero, otherwise; ImportLicense is a dummy variable equal to one if a firm has an import license, and zero, otherwise. 2013)). This is also consistent to the definition used by Wernli and Dietrich ( 2022)).

WBES 2015-2019

TrustinBanks This captures the level of trust in banks, calculated based on responses to the question: "Could you tell me how much confidence you have in banks: Is it a great deal of confidence, quite a lot, not very much or none at all. This variable corresponds to the proportion of respondents who responded having a great deal or quite a lot of confidence in banks.

World Values Survey (WVS)

InterpersonalTrust

This captures the level of interpersonal trust, calculated based on responses to the question: ''Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?" This variable corresponds to the proportion of the respondents in a given country who responded that most people can be trusted.

WVS

Small-sized

It is equal to 1 if the firm is small (5-19 full-time employees), and zero, otherwise, following the definition used in the WBES. In our estimations, it is the reference firm size.

WBES

Industry Dummies

Dummies indicating the firm's industry according to the ISIC classification. More information on the firms' ISIC in Table A2.

WBES 2015-2019

NumSysBankCrisis

The number of systemic banking crises experienced by country j since 1970.

Laeven and Valencia (2018) NumSovereignCrisis

The number of sovereign debt crises experienced by country j since 1970.

Laeven and Valencia (2018) HierarchicalReligion

The percentage of the population in a country whose religions are either Catholicism, Islam, or Orthodox Christianity

WVS

AbsLatitude

The natural logarithm of the absolute value of the latitude of a country's approximate geodesic centroid.

Galor and Özak (2016b), CIA World Factbook

Animals

The number of domesticable mammals that weigh more than 45 kg known to exist in prehistory in country j.

Olsson and Hibbs (2005)

ColonialDuration

The duration of colonization in a country (expressed in hundreds of years).

  Table 7a, and the first-stage regression results and instrument validity tests in Table 7b, using the alternative sets of instruments: (i)

	NumSysBankCrisis,	NumSovereignCrisis,	AbsLatitude;	(ii)	NumSysBankCrisis,
	NumSovereignCrisis,	Animals;	(iii)	NumSysBankCrisis,	NumSovereignCrisis,
	ColonialDuration;

Table 1 .

 1 . Trust in financial institutions: A survey. Journal of Economic Surveys, 2021. van der Cruijsen, C., de Haan, J., Roerink, R. (2021b). Financial knowledge and trust in financial institutions. Journal of Consumer Affairs, 55(2): 680-714. Summary statistics of the variables used in the study

	Van de Ven, W.P., Van Praag, B.M. (1981). The demand for deductibles in private health
	insurance: A probit model with sample selection. Journal of Econometrics, 17(2): 229-252.
	Wernli, R., Dietrich, A. (2022). Only the brave: improving self-rationing efficiency among
	discouraged Swiss SMEs. Small Business Economics, 59, 977-1003.
	Wu, J., Si, S., Wu, X. (2016). Entrepreneurial finance and innovation: informal debt as an
	empirical case. Strategic Entrepreneurship Journal, 10(3): 257-273.
	Zak, P.J., Knack, S. (2001). Trust and Growth. The Economic Journal, 111(470): 295-321.

Table 2 .

 2 Average values of various trust measures(TrustinBanks, and InterpersonalTrust), by country

		TrustinBanks	InterpersonalTrust	Obs
	Bolivia	0.4796	0.0860	160
	Colombia	0.2829	0.0454	674
	Cyprus	0.2532	0.0802	76
	Ecuador	0.5461	0.0586	235
	Egypt	0.6515	0.0735	221
	Greece	0.2174	0.0842	243
	Guatemala	0.3209	0.1796	52
	Indonesia	0.8363	0.0519	811
	Kazakhstan	0.5689	0.2389	466
	Kyrgyz Republic	0.7847	0.1185	119
	Lebanon	0.2873	0.0992	224
	Malaysia	0.7550	0.1957	406
	Myanmar	0.8342	0.1508	248
	Nicaragua	0.3400	0.0425	55
	Peru	0.3289	0.0530	609
	Philippines	0.8057	0.0535	243
	Romania	0.2468	0.1187	402
	Russia	0.4474	0.2391	557
	Serbia	0.2951	0.1662	137
	Thailand	0.8011	0.3137	344
	Turkey	0.4246	0.1426	615
	Ukraine	0.3387	0.3065	614
	Vietnam	0.9174	0.2767	481
	Zimbabwe	0.5075	0.0214	403
	Whole Sample	0.5436	0.1453	8395

Table 3 .

 3 Average values of discouraged borrowers (BorrowerDiscouragement), and the proportion of working capital financed by banks (BankFinance), by country

		Full sample	Firms that need credit sample
		BankFinance	BankFinance	BorrowerDiscouragement
	Bolivia	0.1627	0.2007	0.3438
	Colombia	0.2232	0.2601	0.2493
	Cyprus	0.2416	0.3579	0.5132
	Ecuador	0.1704	0.2342	0.2936
	Egypt	0.0285	0.0480	0.7421
	Greece	0.0930	0.1542	0.5267
	Guatemala	0.1144	0.1885	0.2885
	Indonesia	0.1030	0.1241	0.8002
	Kazakhstan	0.0716	0.1149	0.6288
	Kyrgyz Republic	0.0928	0.1734	0.5042
	Lebanon	0.2044	0.2481	0.5714
	Malaysia	0.2128	0.2204	0.5197
	Myanmar	0.0724	0.1203	0.7016
	Nicaragua	0.0915	0.1565	0.4909
	Peru	0.3150	0.3715	0.1511
	Philippines	0.0777	0.1638	0.3663
	Romania	0.1364	0.1656	0.7239
	Russia	0.0671	0.1012	0.7558
	Serbia	0.1656	0.2457	0.1679
	Thailand	0.0960	0.1206	0.8837
	Turkey	0.1107	0.1754	0.5236
	Ukraine	0.0606	0.0770	0.7345
	Vietnam	0.1884	0.3052	0.2079
	Zimbabwe	0.0692	0.0729	0.7916
	Total	0.1266	0.1788	0.5470

Table 4a .

 4a The impact of trust in banks on borrower discouragement, 2015-2019 t statistics in parentheses. Robust standard errors are used. * p < 0.1, ** p < 0.05, *** p < 0.01. Description of variables: BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those that need financing but did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is LnGDP, orthogonalized) and inflation (Inflation). For a full definition of the variables, please refer to Appendix TableA3. We also include survey-year and industry dummies based on the firm's ISIC. List of instruments (IV-probit): NumSysBankCrisis, NumSovereignCrisis, and HierarchicalReligion.

	orthogonalized), economic development (
		Probit Regression	IV probit
		Pr (BorrowerDiscouragement=1)
	TrustinBanks	-0.651 ***	-1.974 ***
		(-3.24)	(-5.39)
	InterpersonalTrust	-0.451	1.823 ***
		(-1.48)	(3.02)
	TrustinFamily	-6.763 ***	-3.984 **
		(-5.20)	(-2.57)
	Productivity	-0.00800 **	0.000691
		(-2.15)	(0.16)
	NetIntMargin	0.123 ***	0.166 ***
		(9.09)	(9.64)
	GettingCredit	0.00243	-0.0432 ***
		(0.27)	(-3.21)
	Medium-sized	-0.274 ***	-0.273 ***
		(-7.61)	(-7.61)
	Large-sized	-0.495 ***	-0.490 ***
		(-11.40)	(-11.31)
	Population1M	-0.00521	0.0468
		(-0.14)	(1.21)
	Age	-0.00234	-0.0319
		(-0.08)	(-1.08)
	SoleProprietorship	0.0522	0.0937 *
		(1.10)	(1.91)
	Partnership	0.0995 **	0.120 ***
		(2.35)	(2.77)
	State-owned	-0.372	-0.375
		(-1.02)	(-1.02)
	Foreign-owned	0.180 **	0.203 ***
		(2.56)	(2.86)
	Multiple	-0.0824 *	-0.0582
		(-1.80)	(-1.27)
	ManagerExperience	-0.0795 *	-0.0995 **
		(-1.85)	(-2.30)
	FemaleManager	0.0454	0.0108
		(1.18)	(0.27)
	Audited	-0.287 ***	-0.284 ***
		(-8.56)	(-8.42)
	LnGDP	0.302 ***	0.441 ***
		(8.82)	(9.37)
	Inflation	0.00148	0.000134
		(0.33)	(0.03)
	Industry dummies	Yes	Yes
	Survey year dummies	Yes	Yes
	Constant	0.525 **	1.236 ***
		(2.34)	(4.14)
	Obs	8395	8395
	Chi-squared test	1500.2 ***	1539.8 ***
	Wald test of exogeneity		19.12 ***

the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?"; Firm-specific and country-specific control variables include the firm's level of productivity (Productivity), age (Age), size (Medium-sized, Largesized), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-owned, Foreignowned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), audit status (Audited), the country's getting credit indicator (GettingCredit), net interest margin (NetIntMargin), particularized trust

(TrustinFamily,

Table 4b .

 4b First stage regression results -IV probit regressions and test of the validity of instruments

		TrustinBanks	InterpersonalTrust
	Excluded Instruments
	NumSysBankCrisis	-0.0529 ***	0.0185 ***
		(-30.85)	(18.12)
	NumSovereignCrisis	-0.0228 ***	-0.00621 ***
		(-11.74)	(-6.69)
	HierarchicalReligion	-0.00645 ***	-0.00352 ***
		(-57.15)	(-63.18)
	Control variables	Yes	Yes
	Constant	Yes	Yes
	Test of validity & relevance of instruments
	F-test of excluded instruments (1 st -stage)	1171.41 ***	2129.79 ***
	Sanderson-Windmeijer F-test of excluded	459.72 ***	939.74 ***
	instruments (Weak identification)
	Kleibergen Paap rk LM test	896.12 ***
	Anderson-Rubin Wald test (Weak-instrument-	8.93 ***
	robust inference)
	Hansen-J test	0.121
	p-value	0.7283
	Wald test of exogeneity	15.336 ***

t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Definition of variables: TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?" Instruments' definitions: NumSysBankCrisis is the number of systemic banking crises experienced by country j since 1970; NumSovereignCrisis is the number of sovereign debt crises experienced by country j since 1970; HierarchicalReligion is equal to the percentage of the population whose religions are either Catholicism, Islam, or Orthodox Christianity.

Table 4c .

 4c Marginal Effects of TrustinBanks and InterpersonalTrust on the probability that a

	firm becomes discouraged from borrowing from financial institutions (Pr
	(BorrowerDiscouragement=1)
		Probit	IV-Probit
	TrustinBanks	-0.2136 ***	-0.6440 ***
		(0.0656)	(0.1174)
	InterpersonalTrust	-0.1481	0.5949 ***
		(0.1000)	(0.1962)
	Delta standard errors in parentheses.

Table 5 .

 5 Marginal effects of TrustinBanks and InterpersonalTrust on the probability of borrower discouragement, excluding firms that do not rely on banks to finance their working capital operations.

		Probit	IV-Probit
	TrustinBanks	-0.3546 ***	-1.2130 ***
		(0.0873)	(0.1684)
	InterpersonalTrust	-0.7468 ***	0.4973
		(0.1516)	(0.3544)
	Delta standard errors in parentheses.

Table 6a .

 6a The impact of the interaction between trust in banks (TrustinBanks) and interpersonal trust (InterpersonalTrust) on borrower discouragement.

		(i)	(ii)
		Probit	IV-Probit
		Pr (BorrowerDiscouragement=1)
	TrustinBanks	1.636 ***	0.870
		(5.72)	(1.17)
	InterpersonalTrust	8.416 ***	9.554 ***
		(10.09)	(5.80)
	TrustinBanks*InterpersonalTrust	-15.52 ***	-14.88 ***
		(-11.62)	(-4.67)
	Control Variables	Yes	Yes
	Industry Dummies	Yes	Yes
	Survey Year Dummies	Yes	Yes
	Constant	-0.564 **	-0.240
		(-2.34)	(-0.53)
	Obs	8395	8395
	Wald test of exogeneity		19.85***
	Chi-squared test	1784.3***	1692.3***

t and z statistics in parentheses. Robust standard errors are used. * p < 0.1, ** p < 0.05, *** p < 0.01. Description of variables:

Table 6b .

 6b Marginal probability effects of TrustinBanks on borrower discouragement (Pr(BorrowerDiscouragement=1)) at different percentile levels of InterpersonalTrust p < 0.1, ** p < 0.05, *** p < 0.01. Description of variables: BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those who need financing but did not apply for a loan or line of credit because of complex loan application procedures, unfavorable interest rates, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES survey was conducted, InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?"

	Percentile Levels	(i)	(ii)
		Probit	IV-Probit
	P10	0.2911 ***	0.0623
		(3.94)	(0.10)
	P25	0.2564 ***	0.0261
		(3.51)	(0.02)
	P50	-0.0691	-0.2875 ***
		(-1.06)	(-2.71)
	P75	-0.6903 ***	-0.8611 ***
		(-10.14)	(-9.78)
	P90	-0.9799 ***	-1.1838 ***
		(-14.03)	(-9.50)
	z-statistics in parentheses.

*

Table 7a .

 7a Marginal Effects of TrustinBanks and InterpersonalTrust on the probability that a firm becomes a discouraged borrower (BorrowerDiscouragement) using alternative instruments -IV-probit

		(i)	(ii)	(iii)	(iv)	(v)
	TrustinBanks	-0.9644 ***	-0.7680 ***	-0.6291 ***	-0.6514 ***	-0.4213 ***
		(0.1905)	(0.1744)	(0.1166)	(0.1186)	(0.1102)
	InterpersonalTrust	0.1905	0.4539 ***	0.6104 **	0.5685	0.1746
		(0.2702)	(0.1612)	(0.2410)	(0.1970)	(0.1820)

Excluded Instruments: (i) NumSysBankCrisis, NumSovereignCrisis, AbsLatitude; (ii) NumSysBankCrisis, NumSovereignCrisis, Animals; (iii) NumSysBankCrisis, NumSovereignCrisis, ColonialDuration; (iv) NumSysBankCrisis, NumSovereignCrisis, AbsLatitude, HierarchicalReligion; (v) NumSysBankCrisis, GeneticDistance, HierarchicalReligion Delta standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Variable definitions: BorrowerDiscouragement is a

Table 7b .

 7b First-Stage Regressions using Alternative Instruments Endogenous variables: TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". Instruments' definitions: NumSysBankCrisis is the number of systemic banking crises experienced by country j since 1970; NumSovereignCrisis is the number of sovereign debt crises experienced by country j since 1970; HierarchicalReligion is equal to the percentage of the population whose religions are either Catholicism, Islam, or Orthodox Christianity. AbsLatitude is the natural logarithm of the absolute value of the latitude of a country's approximate geodesic centroid. Animals is the number of domesticable mammals that weigh more than 45 kg known to exist in prehistory. ColonialDuration refers to the duration of colonization in a country, in hundreds of years.

		(i)	(ii)	(iii)	(iv)	(v)
	Endogenous: TrustinBanks
	NumSysBankCrisis	-0.0268 ***	-0.0363 ***	-0.0196 ***	-0.0507 ***	-0.0785 ***
		(-13.20)	(-16.33)	(-10.24)	(-27.65)	(-31.37)
	NumSovereignCrisis	-0.0142 ***	-0.0300 ***	-0.0442 ***	-0.0230 ***
		(-5.39)	(-9.69)	(-17.99)	(-11.68)
	AbsLatitude	0.0422 ***			0.0174 ***
		(16.61)			(8.46)
	Animals		0.0213 ***
			(14.07)
	ColonialDuration			-0.0832 ***
				(-39.51)
	HierarchicalReligion				-0.0063 ***	-0.0068 ***
					(-53.22)	(-55.16)
	GeneticDistance					-5.253 ***
						(-13.48)
	F-test of excluded instruments (1 st	305.51 ***	104.24 ***	605.48 ***	1204.81 ***	1054.65 ***
	stage)
	Sanderson-Windmeijer F-test of	309.84 ***	242.62 ***	868.50 ***	398.21 ***	566.15 ***
	excluded instruments (Weak
	Identification)
	Endogenous: InterpersonalTrust
	NumSysBankCrisis	0.0329 ***	0.0230 ***	0.0347 ***	0.0199 ***	0.0124 ***
		(22.95)	(20.71)	(26.26)	(19.25)	(11.22)
	NumSovereignCrisis	-0.0016	-0.0248 ***	-0.0127 ***	-0.0064 ***
		(-1.33)	(-20.31)	(-10.52)	(-7.29)
	AbsLatitude	0.0251 ***			0.0113 ***
		(18.27)			(10.18)
	Animals		0.0302 ***
			(50.69)
	ColonialDuration			-0.0315 ***
				(-27.86)
	HierarchicalReligion				-0.0034 ***	-0.0037 ***
					(-62.89)	(-60.77)
	GeneticDistance					-3.188 ***
						(-20.05)
	F-test of excluded instruments (1 st	295.67 ***	868.15 ***	422.05 ***	1575.99 ***	2449.29 ***
	stage)
	Sanderson-Windmeijer F-test of	358.57 ***	1446.33 ***	534.88 ***	639.80 ***	1466.75 ***
	excluded instruments (Weak
	Identification)
	Obs	8395	8395	8395	8395	8260
	Kleibergen-Paap rk LM test	602.7 ***	292.8 ***	713.3 ***	1028.5 ***	1009.745 ***
	Hansen J-test	0.725	0.262	0.173	4.593	0.351
	Hansen J-test (p-value)	0.395	0.609	0.678	0.101	0.5534
	Anderson-Rubin Wald test (Weak-	8.218 ***	5.295 ***	9.623 ***	8.196 ***	6.34 ***
	instrument robust inference)
	Wald test of exogeneity	22.25 ***	20.08 ***	22.86 ***	18.66 ***	2.82
	t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Excluded Instruments: (i) NumSysBankCrisis, NumSovereignCrisis,
	AbsLatitude; (ii) NumSysBankCrisis, NumSovereignCrisis, Animals; (iii) NumSysBankCrisis, NumSovereignCrisis,
	ColonialDuration; (iv) NumSysBankCrisis, NumSovereignCrisis, AbsLatitude, HierarchicalReligion; (v) NumSysBankCrisis,
	GeneticDistance, HierarchicalReligion.

Table 8a .

 8a The impact of trust in banks on borrower discouragement, audited vs. unaudited firms p < 0.1, ** p < 0.05, *** p < 0.01. Note that InterpersonalTrust is also considered endogenous. For the sake of brevity, we only present the results on our main variable of interest: TrustinBanks. Description of variables: BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those who need financing but did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". orthogonalized) and inflation (Inflation). For full definition of the variables, please refer to Appendix (TableA3). We also include survey-year and industry dummies based on the firm's ISIC. Instruments' definitions: NumSysBankCrisis is the number of systemic banking crises experienced by country j since 1970; NumSovereignCrisis is the number of sovereign debt crises experienced by country j since 1970; HierarchicalReligion is equal to the percentage of the population whose religions are either: Catholicism, Islam, and Orthodox Christianity.

		Probit	IV-Probit	Probit	IV-Probit
		Audited		Unaudited
		Pr(BorrowerDiscouragement = 1)
	TrustinBanks	-0.101	-0.932	-1.020 ***	-1.833 ***
		(-0.34)	(-1.01)	(-3.56)	(-4.66)
	Control variables	Yes	Yes	Yes	Yes
	Industry dummies	Yes	Yes	Yes	Yes
	Survey year dummies	Yes	Yes	Yes	Yes
	Constant	-0.122	0.734	0.749 **	0.969 **
		(-0.38)	(1.32)	(2.26)	(2.57)
	TrustinBanks (First stage) -excluded instruments
	NumSysBankCrisis		-0.0438 ***		-0.0623 ***
			(-18.31)		(-21.20)
	NumSovereignCrisis		-0.0138 ***		-0.0405 ***
			(-5.58)		(-12.15)
	HierarchicalReligion		-0.00598 ***	-0.00720 ***
			(-37.27)		(-45.64)
	F-test of excluded		599.58 ***		704.36 ***
	instruments (1 st stage)
	Sanderson-Windmeijer F-		76.51 ***		289.53 ***
	test of excluded
	instruments
	N	3456	3456	4917	4917
	Wald test of exogeneity		14.81 ***		27.82 ***
	Chi-squared test	571.8 ***	570.1 ***	774.6 ***	817.1 ***
	Kleibergen-Paap rk LM		136.5 ***		694.2 ***
	test
	Hansen J-test		0.152		1.407
	Hansen J-test (p-value)		0.697		0.236
	Anderson-Rubin Wald test		3.360 **		6.953 ***
	(Weak identification)
	t statistics in parentheses. Robust standard errors are used. Control variables include TrustinFamily (orthogonalized), the firm's level of productivity (Productivity), age (Age), size
	(Medium-sized, Large-sized), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-
	owned, Foreign-owned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), a country's
	getting credit indicator (GettingCredit), a country's average net interest margin (NetIntMargin), economic development
	(LnGDP,

*

Table 8b .

 8b Marginal effects of TrustinBanks on borrower discouragement (Pr (BorrowerDiscouragement=1), for audited vs. unaudited firms p < 0.1, ** p < 0.05, *** p < 0.01. Definitions of variables: TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted. BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those who need financing did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit.

		Probit	IV probit	Probit	IV-Probit
		Audited		Unaudited
	TrustinBanks	-0.0340	-0.3129	-0.3210 ***	-0.5761 ***
		(0.1013)	(0.3107)	(0.0890)	(0.1215)
	Delta standard error in parentheses.

*

Table 9a .

 9a The impact of trust in banks on borrower firm discouragement, according to firm size: non-small firms, and non-large firms (SMEs) t statistics in parentheses. Robust standard errors are used. * p < 0.1, ** p < 0.05, *** p < 0.01. Note that InterpersonalTrust is also considered endogenous. For the sake of brevity, we only present the results on our main variable of interest: TrustinBanks. Description of variables: BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those who need financing but did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". Inflation). For full definition of the variables, please refer to Appendix (TableA3). We also include survey-year and industry dummies based on the firm's ISIC. Instruments' definitions: NumSysBankCrisis is the number of systemic banking crises experienced by country j since 1970; NumSovereignCrisis is the number of sovereign debt crises experienced by country j since 1970; HierarchicalReligion is equal to the percentage of the population whose religions are either Catholicism, Islam, or Orthodox Christianity.

	Control variables include TrustinFamily (orthogonalized), the firm's level of productivity (Productivity), age (Age), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-owned, Foreign-owned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), audit status (Audited), a country's getting credit indicator (GettingCredit), a country's average net interest margin (NetIntMargin), economic development (LnGDP, Non-small SMEs SMEs Probit IV Probit Probit IV Probit Pr (BorrowerDiscouragement = 1) TrustinBanks -0.864 *** -2.429 *** -0.471 ** -1.720 *** (-3.23) (-4.60) (-2.17) (-4.58) Control variables Yes Yes Yes Yes Industry dummies Yes Yes Yes Yes Survey year dummies Yes Yes Yes Yes Constant 0.311 1.086 ** 0.411 * 1.087 *** (1.01) (2.55) (1.66) (3.42) TrustinBanks (1 st stage) NumSysBankCrisis -0.0490 *** -0.0593 *** (-22.60) (-28.07) NumSovereignCrisis -0.0238 *** -0.0233 *** (-8.73) (-10.44) HierarchicalReligion -0.00616 *** -0.00685 *** (-43.02) (-50.67) F-test of excluded instruments (1 st stage) 652.80 *** 887.64 *** Sanderson-Windmeijer F-test of excluded instruments 241.52 *** 375.64 *** Obs 4931 4931 6377 6377 Wald test of exogeneity 13.50 *** 16.19 *** Chi-squared test 920.1 *** 970.0 *** 947.8*** 977.6 *** Kleibergen-Paap rk LM test 480.5 *** 713.4 *** Hansen J-test 1.000 2.508 Hansen J-test (p-value) 0.317 0.113 test (Weak identification) orthogonalized) and inflation (Non-small Anderson-Rubin Wald 6.610 *** 7.399 ***

Table 9b .

 9b Marginal effects of TrustinBanks on borrower discouragement (BorrowerDiscouragement), according to firm size (Non-small: Large and Medium-sized firms; Non-large (SMEs): Small and Medium-sized firms) p < 0.1, ** p < 0.05, *** p < 0.01. Definitions of variables: TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted. BorrowerDiscouragement is a dummy indicator equal to one for discouraged firms or those who need financing but did not apply for a loan or line of credit because of complex loan application procedures, among others, and zero, for those who applied for a loan or line of credit.

		Probit	IV probit	Probit	IV-Probit
		Non-small	Non-large firms (SMEs)
	TrustinBanks	-0.2807 ***	-0.7813 ***	-0.1577 ***	-0.5738 ***
		(0.0863)	(0.1653)	(0.0727)	(0.1237)
	Delta standard error in parentheses.

*

Table 10a .

 10a Correlation matrix between our trust variables. TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?".

		TrustinBanks	InterpersonalTrust
	TrustinBanks	1.0000
	InterpersonalTrust	0.1772	1.0000
	Description of variables:

Table 10b .

 10b The impact of trust in banks on borrower discouragement, using orthogonalized value of TrustinBanks and z statistics in parentheses. Robust standard errors are used. * p < 0.1, ** p < 0.05, *** p < 0.01. Description of variables:

	instruments
	Obs	8395	8395
	Wald test of exogeneity		19.02 ***
	Chi-squared test	1500.2 ***	1539.8 ***
	Kleibergen-Paap rk LM test		896 ***
	Hansen J-test		0.113
	Hansen J-test (p-value)		0.737
	Anderson-Rubin Wald test (Weak-instrument		8.919 ***
	robust inference)
		(i)	(ii)
		Probit	IV Probit
	TrustinBanks-orth	-0.651 ***	-1.974 ***
		(-3.24)	(-5.39)
	InterpersonalTrust	-0.724 **	0.995 *
		(-2.38)	(1.91)
	Control variables	Yes	Yes
	Industry dummies	Yes	Yes
	Survey year dummies	Yes	Yes
	Constant	0.220	0.310 *
		(1.35)	(1.70)
	First stage (excluded instruments): InterpersonalTrust
	NumSysBankCrisis		0.0185 ***
			(18.12)
	NumSovereignCrisis		-0.00621 ***
			(-6.69)
	HierarchicalReligion		-0.00352 ***
			(-63.18)
	F-test of excluded instruments (1 st stage)		2129.75 ***
	Sanderson-Windmeijer F-test of excluded		1233.16 ***
	instruments
	First stage (excluded instruments): TrustinBanks
	NumSysBankCrisis		-0.0607 ***
			(-31.39)
	NumSovereignCrisis		-0.0202 ***
			(-10.27)
	HierarchicalReligion		-0.00498 ***
			(-43.14)
	F-test of excluded instruments (1 st stage)		665.21 ***
	Sanderson-Windmeijer F-test of excluded		459.72 ***

t

Table 10c .

 10c Marginal effects of TrustinBanks on the probability of borrower discouragement, using the orthogonalized values of TrustinBanks (to InterpersonalTrust): TrustinBanks-orth

		Probit	IV probit
	TrustinBanks-orth	-0.2136 ***	-0.6440 ***
		(0.0656)	(0.1174)
	InterpersonalTrust	-0.2377 **	0.3248 *
		(0.0994)	(0.1694)

Table 10d .

 10d Marginal effects of TrustinBanks-orth (orthogonalized value of trust in banks) on borrower discouragement (Pr(BorrowerDiscouragement)=1) according to different percentile levels of InterpersonalTrust

	Percentile Levels	(i)	(ii)
		Probit	IV-Probit a
	P10	0.3650 ***	0.1639
		(0.0745)	(0.75)
	P25	0.3287 ***	0.1251
		(0.0738)	(0.59)
	P50	-0.0167	-0.2103 ***
		(0.0656)	(-1.43)
	P75	-0.6791 ***	-0.8238 ***
		(0.0660)	(-9.51)
	P90	-0.9809 ***	-1.1689 ***
		(0.0682)	(-9.42)

Table 11a .

 11a The impact of the interaction between TrustinBanks and InterpersonalTrust on the proportion of working capital operations financed by banks t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Definition of variables: BankFinance is the proportion of the firm's working capital needs that is financed by banks: TrustinBanks is the proportion of individuals in country j who have a great deal or quite a lot of confidence in banks in the most recent World Values Survey (WVS) before the WBES was conducted; InterpersonalTrust is the proportion of individuals in country j who indicate, "Most people can be trusted" to the WVS question: "Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?". TrustinBanks*InterpersonalTrust is the interaction term between TrustinBanks

		OLS	Heckman	Heckman-two	Heckman (ii)	IV
			(i)	step		Regression
				BankFinance
	TrustinBanks	-0.434 ***	-0.508 ***	-0.501 ***	-0.511 ***	-0.275 ***
		(-12.60)	(-5.83)	(-6.14)	(-6.15)	(-3.48)
	InterpersonalTrust	-1.160 ***	-1.511 ***	-1.483 ***	-1.549 ***	-2.275 ***
		(-11.50)	(-6.35)	(-6.02)	(-6.15)	(-6.08)
	TrustinBanks*InterpersonalTrust	2.193 ***	3.758 ***	3.725 ***	3.787 ***	3.108 ***
		(13.12)	(9.92)	(9.69)	(9.67)	(5.65)
	Control Variables	Yes	Yes	Yes	Yes	Yes
	Industry Dummies	Yes	Yes	Yes	Yes	Yes
	Survey Year Dummies	Yes	Yes	Yes	Yes	Yes
	Constant	0.306 ***	0.301 ***	0.332 ***	0.300 ***	0.223 ***
		(9.87)	(3.52)	(4.06)	(3.77)	(4.10)
	Selection Equation: NeedExternalFinancing
	Medium-sized		0.217 ***	0.219 ***	0.228 ***
			(6.82)	(6.84)	(6.81)
	Large-sized		0.290 ***	0.290 ***	0.320 ***
			(8.17)	(8.16)	(7.88)
	Age		0.0457 **	0.0461 **	0.000940
			(2.11)	(2.10)	(0.04)
	PercSalesAfterDelivery		0.00838 ***	0.00832 ***	0.00840 ***
			(22.50)	(22.08)	(20.95)
	ImportLicense				0.258 ***
					(6.05)
	ISOCertification				0.0294
					(0.82)
	Foreign-owned				-0.366 ***
					(-6.23)
	Multiple				0.0689 *
					(1.79)
	ManagerExperience				0.141 ***
					(3.56)
	Industry dummies				Yes
	Constant		-0.975 ***	-0.973 ***	-0.930 ***
			(-15.02)	(-14.86)	(-11.72)
	Inverse Mills Ratio (lambda)			-0.103 ***
				(-4.18)
	atrho		-0.267 ***		-0.278 ***
			(-5.22)		(-4.32)
	Obs	10911	9270	9270	8989	10911
	F-statistics	22.32 ***				20.29 ***
	Kleibergen-Paap rk LM test					809.2 ***
	Hansen J statistic					2.985
	Hansen J (p-value)					0.0841
	Test of exogeneity					106.2 ***
	Anderson-Rubin Wald test					11.60 ***
	Wald test of independent equations		27.23 ***		14.92 ***
	rho		-0.261	-0.382	-0.271
	and InterpersonalTrust. Firm-specific and country-specific control variables include the firm's level of productivity (Productivity), age (Age),
	size (Medium-sized, Large-sized), firm's locality (Population1M), legal status (SoleProprietorship, Partnership), ownership (State-owned,
	Foreign-owned, Multiple), manager-specific characteristics (ManagerExperience, FemaleManager), audit status (Audited), the country's
	getting credit indicator (GettingCredit), net interest margin (NetIntMargin), particularized trust (TrustinFamily, orthogonalized), economic
	development (LnGDP, orthogonalized) and inflation (Inflation). For full definition of the variables, please refer to Appendix (Table A3).

Selection Equation: NeedExternalFinancing is equal to one if the firm has applied for a loan in the past 12 months or if the firm has an existing line of credit, and zero, if the firm did not apply for a loan. PercSalesAfterDelivery is the percentage of sales paid by customers after the delivery of goods and services; ISOCertification is a dummy variable equal to one if a firm has an ISO certification, and zero, otherwise; ImportLicense is a dummy variable equal to one if a firm has an import license, and zero, otherwise. Excluded instruments for the IV regression: NumSysBankCrisis, HierarchicalReligion, HierarchicalReligion*NumSysBankCrisis, HierarchicalReligion*FiscalCostCrisis

Table 11b .

 11b Marginal effects of TrustinBanks on bank credit reliance to finance working capital needs (BankFinance), according to different percentile levels of InterpersonalTrust Delta standard error in parentheses. The marginal effect of TrustinBanks on BankFinance, conditional on NeedforExternalFinancing being observed, is reported for the Heckman selection estimation method.

	Percentile Levels		BankFinance
		OLS	Heckman (i)	Heckman (ii)	IV Regression
	P10	-0.3206 ***	-0.3377 ***	-0.3390 ***	-0.1137 **
		(0.0283)	(0.0752)	(0.0709)	(0.0564)
	P25	-0.3171 ***	-0.3072 ***	-0.3083 ***	-0.1088 *
		(0.0282)	(0.0733)	(0.0690)	(0.0558)
	P50	-0.1740 ***	0.0276	0.0291	0.0941 **
		(0.0230)	(0.0590)	(0.0560)	(0.0409)
	P75	0.0896 ***	0.3895 ***	0.3939 ***	0.4676 ***
		(0.0258)	(0.0633)	(0.0642)	(0.0759)
	P90	0.1724 ***	0.5316 ***	0.5370 ***	0.5850 ***
		(0.0296)	(0.0703)	(0.0727)	(0.0941)

Table 12a .

 12a The impact of trust in banks on borrower discouragement, using Heckman Probit estimation p < 0.1, ** p < 0.05, *** p < 0.01. Definition of variables: BorrowerDiscouragement is a dummy

			Heckman Probit
			Pr(BorrowerDiscouragement=1)
		(i)	(ii)	(iii)	(iv)
	TrustinBanks	-0.488 **	-0.480 **	0.656	0.663
		(-2.01)	(-1.99)	(1.55)	(1.56)
	InterpersonalTrust	-0.388	-0.436	3.369 ***	3.317 **
		(-0.77)	(-0.86)	(2.63)	(2.57)
	TrustinBanks*InterpersonalTrust			-6.401 ***	-6.390 ***
				(-3.09)	(-3.06)
	Control Variables	-4.660 **	-4.758 **	-4.188 *	-4.281 **
	Industry Dummies	(-2.08)	(-2.12)	(-1.94)	(-1.97)
	Survey Year Dummies	0.00612	0.00568	0.00655	0.00609
	Constant	1.508 ***	1.479 ***	0.825 **	0.794 **
		(4.58)	(4.50)	(2.18)	(2.09)
	Selection Equation:
	CreditConstrained
	Medium-sized	-0.0873 ***	-0.0975 ***	-0.0881 ***	-0.0981 ***
		(-2.90)	(-3.19)	(-2.93)	(-3.22)
	Large-sized	-0.229 ***	-0.235 ***	-0.231 ***	-0.236 ***
		(-6.27)	(-6.19)	(-6.33)	(-6.24)
	Age	-0.00825	-0.0199	-0.00876	-0.0203
		(-0.40)	(-0.89)	(-0.43)	(-0.91)
	ImportLicense	-0.282 ***	-0.289 ***	-0.283 ***	-0.290 ***
		(-6.33)	(-6.35)	(-6.35)	(-6.36)
	ISOCertification	-0.0823 ***	-0.0580 *	-0.0792 **	-0.0549 *
		(-2.59)	(-1.78)	(-2.50)	(-1.68)
	PercSalesAfterDelivery	-0.00270 ***	-0.00306 ***	-0.00266 ***	-0.00303 ***
		(-7.41)	(-8.18)	(-7.32)	(-8.08)
	Foreign-owned		-0.213 ***		-0.213 ***
			(-3.53)		(-3.54)
	Multiple		-0.0526		-0.0526
			(-1.32)		(-1.32)
	ManagerExperience		-0.0509		-0.0508
			(-1.43)		(-1.42)
	Industry dummies	No	Yes	No	Yes
	Constant	-0.126 **	-0.0448	-0.125 **	-0.0452
		(-2.12)	(-0.64)	(-2.12)	(-0.65)
	Obs	10098	10098	10098	10098
	Chi-squared test	14768.3 ***	22437.0 ***	12823.7 ***	20280.5 ***
	Wald test of independent equations	38.05 ***	35.52 ***	33.00 ***	31.01 ***
	atrho	-1.181 ***	-1.179 ***	-1.231 ***	-1.212 ***
	rho	-0.828	-0.827	-0.843	-0.837

t statistics in parentheses. *

Table 12b .

 12b Conditional marginal effects of TrustinBanks and InterpersonalTrust on the probability of borrower discouragement, excluding firms that do not rely on banks to finance their working capital operations.

	Heckman Probit (i)	Heckman Probit (ii)
	TrustinBanks	-0.1212 **	-0.1194 **
		(0.0605)	(0.0601)
	InterpersonalTrust	-0.0964	-0.1085
		(0.1260)	(0.1270)
	Delta standard error in parentheses.

Table 12c .

 12c Conditional marginal probability effects of TrustinBanks on borrower discouragement (Pr(BorrowerDiscouragement=1)) at different percentile levels of InterpersonalTrust

	Percentile Levels	(iii)	(iv)
	P10	0.0806	0.0819
		(0.0851)	(0.0850)
	P25	0.0781	0.0794
		(0.0845)	(0.0844)
	P50	-0.0645	-0.0624
		(0.0605)	(0.0602)
	P75	-0.2258 ***	-0.2240 ***
		(0.0728)	(0.0725)
	P90	-0.3449 ***	-0.3437 ***
		(0.1043)	(-0.1039)

Delta standard error in parentheses.

Table 13 .

 13 Marginal effects of trust in banks (TrustinBanks) on the probability that a firm gets discouraged from borrowing from financial institutions (BorrowerDiscouragement), using a subsample of firms in countries with relatively lower Islamic banking presence Delta standard error in parentheses. List of excluded instruments in the IV-probit regression: NumSysBankCrisis, AbsLatitude, Animals. List of variables in the selection equation: Small-sized, Age, PercSalesAfterDelivery, ISOCertification, ImportLicense, Industry dummies).

		IV probit	Heckman Probit
	TrustinBanks	-6.508***	-0.4266*
		(0.1992)	(0.2569)

Table A3 .

 A3 Description of variables Variables Description Source BorrowerDiscouragement It indicates whether the firm is a discouraged borrower. It is equal to 1 for firms that need credit but did not apply for loans or line of credit because of complex loan application procedures, unfavorable interest rates, unattainable collateral requirements, insufficient loan size and maturity, expectation that loan would not be approved, among others. It is equal to 0 for firms who applied for a loan or a line of credit. Firms who did not apply for a loan because they have sufficient capital were excluded because they are not considered non-borrowers (following Chakravarty & Xiang (

  AgeIt is the natural logarithm of the firm's age WBES 2015-2019 Multiple It is a dummy variable equal to one if the firm is part of a larger establishment and zero, otherwise. SoleProprietorship It is a firm's legal status indicator. It is equal to 1 if the firm is a sole proprietorship and zero, otherwise WBES 2015-2019 Partnership It is equal to 1 if the firm's legal status is a partnership (limited or not) and zero, otherwise. WBES 2015-2019 ManagerExperience It measures the top manager's working experience in the sector. It is a dummy variable equal to 1 if the top manager has at least 10 years of experience working in the sector and zero, if less WBES 2015-2019 FemaleManager It is equal to one of the firm's top manager is female and zero, otherwise. Population1M It measures the population of the city where the firm is located. It is equal to 1 if the locality has a population of over 1 million, and zero, if less. TrustinFamily This captures the level of family trust, calculated based on responses to the question: «Could you tell me whether you trust your family completely, somewhat, not very much or not at all?" This variable corresponds to the proportion of respondents in a given country who responded: completely or somewhat. The variable is orthogonalized to TrustinBanks and InterpersonalTrust.

						WBES 2015-2019
						WBES 2015-2019
						WVS
	LnGDP	It is the natural logarithm of the real GDP per	World
		capita (constant 2010 USD), orthogonalized with	Development
		the	trust	measures:	InterpersonalTrust,	Indicators
		TrustinFamily and TrustinBanks
	Inflation	It is the inflation rate of the country where the firm	World
		is located.			Development
						Indicators
	GettingCredit	It is an index variable which measures the degree	Doing Business,
		to which collateral and bankruptcy laws protect	World Bank
		the rights of borrowers and lenders and thus
		facilitate lending. The index ranges from 0 to 12
	NetIntMargin	It is the accounting value of a bank's net interest	Global Financial
		revenue as a percentage of its average interest-	2015-2019 Development
		bearing asset.			Database (GFDD)
	BankFinance	The proportion of a firm's working capital	WBES 2015-2019
		financed by banks.
	Medium-sized Survey Year dummies	It is equal to 1 if the firm is medium-sized (20-99 Dummies indicating the year when the survey was	WBES 2015-2019 WBES 2015-2019
		full-time employees), and zero, otherwise. conducted (SurveyYear2015, SurveyYear2016,
	Large-sized	It is equal to 1 if the firm is large (at least 100 full-SurveyYear2017, SurveyYear2018,	WBES 2015-2019
		time employees). SurveyYear2019).
						WBES 2015-2019
	State-owned	It is a dummy variable equal to 1 if at least 50% of	WBES 2015-2019
		the firm is owned by the government/state, and
		zero, otherwise.
	Foreign-owned	It is a dummy variable equal to 1 if at least 50% of	WBES 2015-2019
		the firm is owned by private foreign individuals
		and firms, and zero, otherwise.
	Audited	It is equal to 1 if an external auditor checks and	WBES 2015-2019
		verifies the firm's annual financial statement, and
		zero, otherwise.
	Productivity	It is the natural logarithm of the value of firm sales	WBES 2015-2019
		over the number of permanent employees, scaled
		three years before the survey was conducted

  ISOCertification a dummy variable equal to one if a firm has an ISO certification, and zero, otherwise WBES 2015-2019 ImportLicense a dummy variable equal to one if a firm has an import license, and zero, otherwise WBES 2015-2019 CreditConstrained It is a dummy variable equal to one if the firm applied for a loan in the past 12 months and has no existing line of credit, and if the firm needs credit but has not applied for a loan, and zero if the firm has an existing line of credit or has not applied for a loan because it does not need external financing.NeedExternalFinancingIt is equal to one if the firm has applied for a loan in the past 12 months or if the firm has an existing line of credit, and zero, if the firm did not apply for a loan.

			WBES	2015-
			2019;	Authors'
			calculations
			WBES	2015-
			2019;	Authors'
			calculations
	FiscalCostCrisis	It refers to the outlays directly related to the	Laeven	and
		restructuring of the financial sector (as a % of the	Valencia (2018)
		GDP)
			Galor and Özak
			(2016b)
	PercSalesAfterDelivery	the percentage of sales paid by customers after the	WBES 2015-2019
		delivery of goods and services

This is in line with the definition of trust put forth by[START_REF] Guiso | Social Capital as Good Culture[END_REF] as the "subjective probability that individuals attribute to the possibility of being cheated." Thus, we expect loan officers in high interpersonal trust economies to attribute a relatively lower likelihood of being cheated.

The countries included in the study are Bolivia, Colombia, Cyprus, Ecuador, Egypt, Greece, Guatemala, Indonesia, Kazakhstan, Kyrgyz Republic, Lebanon, Malaysia, Myanmar, Nicaragua, Peru, Philippines, Romania, Russia, Serbia, Thailand, Turkey, Ukraine, Vietnam, and Zimbabwe.

Summary statistics of the 15 505 firms are reported in the Appendix (TableA1).

The WVS Association allows the use of a multi-stage territorial stratified sampling selection in determining a national representative sample.

We present more detailed information about the firms' industries and sectors in Appendix (TableA2).

We also consider a country's average bank lending rate instead of the net interest margin. However, only 18 out of the 24 countries included in the study report this information in the International Financial Statistics. We note that even after controlling the bank lending rate for a subsample of 18 countries, we obtain the same results with our main variable of interest.

We also report in the Appendix the summary statistics of the 15505 firms (TableA1) and a sub-sample of firms excluding discouraged borrowers (TableA4).

A positive link between the number of systemic banking crises experienced and interpersonal trust could be explained by a positive association between economic threat and pro-social tendencies, and the establishment of social support networks[START_REF] Alonso-Ferres | Connecting perceived economic threat and prosocial tendencies: The explanatory role of empathic concern[END_REF]. Moreover,[START_REF] Hörisch | Social capital and the impact of the recent economic crisis: Comparing the effects of economic and fiscal policy developments[END_REF] find state action during a crisis could even lead to social capital development, which is in line with studies that find government performance influences social capital[START_REF] Rothstein | Political institutions and generalized trust[END_REF].

We also consider the proportion of purchased fixed assets financed by banks. However, only 38.52% in the sample which excludes discouraged borrowers (4203 out of 10911) provide information about the financing of their fixed assets. In addition, the sample distribution according to firm size is different when considering the purchase of fixed assets vis-à-vis working capital financing. Only about 29% of the firms with information on fixed asset funding is small, compared to 40% when looking into working capital financing. Furthermore, as investment in fixed assets requires long-term financing, which is limited, especially in less developed economies[START_REF] Hu | Long-term finance provision: National development banks vs commercial banks[END_REF], and which are mainly provided by banks (Martinez-Peria and Schmukler, 2017), we expect supply-side factors to weigh more than demand-side decisions.

Appendix.

Table A1