Pierre André
email: pierre.andre@univ-cergy.fr

Sandrine Mesplé-Somps

Sylvie Lambert

Politics and the geographic allocation of public funds in a semi-democracy

Keywords: Public goods, Elections, Politics, Ghana. JEL classication codes: D72, O55, R53

The body of literature on purely democratic countries can sometimes fail to explain the behavior of government in semi-democratic African countries. Empirical and theoretical political economic papers nd that public funds target ruling party supporters and swing districts. Our results, however, suggest that the opposite was true of Ghana. We observe that pro-government districts received less public investment when the NDC was in power.

We posit that this nding is partially driven by the government's will to curry favor with opposition politicians. Indeed, in addition to pursuing its electoral objectives, the government of an emerging democracy may fear political instability and keep the lid on potential unrest by bargaining with opposition leaders. Our analysis also shows that, when controlling for votes and other covariates (including wealth, urbanization and density), public goods allocation is not driven by ethnic group targeting either.

1 Introduction: Political motives and public funds allocation, a short review of the literature A growing number of developing countries have become (fully or partially) democratic since the 1990s. The impact of these political changes on the development process is a major issue in the economic debate. Most of the papers that analyze the links between these political changes and economic performance in developing countries are inspired by models designed for developed countries. This is particularly true of the geographic allocation of public funds [START_REF] Diaz-Cayeros | Electoral risk and redistributive politics in Mexico and the United States[END_REF]Miguel and Zaidi, 2003;Schady, 2000;Moser, 2008;[START_REF] Case | Election goals and income redistribution: Recent evidence from Albania[END_REF][START_REF] Cole | Fixing market failures or xing elections? agricultural credit in India[END_REF].

Usually, a democratic government gunning seeking re-election will have incentives that target two groups of people. 1 The rst kind of targeted transfer is for the incumbent government's core support group, and is sometimes called machine politics: politicians reward their core supporters by means of the preferential allocation of public goods (or private transfers). Theoretically, [START_REF] Dixit | The determinants of success of special interests in redistributive politics[END_REF] predict this will happen mainly if the leading party is more ecient at providing public goods to its core support group than to opposition supporters. Most of the abovementioned papers on developing countries point up this mechanism. 2

The second kind of targeted public transfer is explained by the swing voter model. It comes about mainly if some voters have strong preferences for one of the political parties.

In that case, public goods provision targets the median voters, who are the politically central group and could vote for either party. A number of empirical papers have pointed up such a mechanism (like [START_REF] Dahlberg | On the vote-purchasing behavior of incumbents[END_REF][START_REF] Diaz-Cayeros | Electoral risk and redistributive politics in Mexico and the United States[END_REF][START_REF] Cole | Fixing market failures or xing elections? agricultural credit in India[END_REF][START_REF] Banful | Do formula-based intergovernmental transfer mechanisms eliminate politically motivated targeting? evidence from Ghana[END_REF] respectively in Sweden, USA, India and Ghana). [START_REF] Levitt | The impact of federal spending on House election outcomes[END_REF] mention that MPs may step up their eort to obtain government funds when they are seeking re-election. Therefore, MPs may make more of an eort in politically central districts, so that government spending is higher in these districts.

This would generate a negative correlation between the votes for the incumbent MP at the last election and government spending. This is therefore a version of the swing voter model for election with constituencies (with politically central constituencies instead of 1 Earlier theoretical studies (including [START_REF] Downs | An economic theory of democracy[END_REF][START_REF] Bowen | The interpretation of voting in the allocation of economic resources[END_REF] have been summarized and extended by [START_REF] Dixit | The determinants of success of special interests in redistributive politics[END_REF].

politically central voters).

Although this literature provides relevant insights into political life in established democracies, we believe it may well fail to describe some semi-democracies, and some African countries in particular where the political institutions are much weaker.

This assertion is related to some recent political economic literature. North, Wallis, andWeingast, (2009a, 2009b) assert that social orders are dierent in developing countries and developed countries. They explain that the social order of developing countries is a limited-access order (or natural state). By contrast, an open-access social order has long been in place in most developed countries. In a natural state order, personal relationships among the elite form the basis for political organization and constitute the grounds for individual interaction. A natural state is ruled by a dominant coalition; people outside the coalition have only limited access to organizations, privileges and valuable resources and activities, (North, Wallis, and Weingast, 2009b). In these circumstances, elections typically do not provide an institutional, competitive environment. This prevents political competition from conveying information to politicians and constraining them. Therefore, public goods are provided personally: governments are inclined to use public goods as a means of rewarding members of the elite coalition. This mechanism may make it pointless to target public funds on specic groups of people for electoral purposes.

In addition, in a semi-democratic country, the dictatorial mechanisms may be relevant for the incumbent government and its opponent(s). Indeed, dictatorship (or rebellion) is a potentially relevant alternative for them. This is particularly true when the democratic political reforms are recent and undertaken by former dictators. The literature on post-conict political economics denes conditions whereby a peace equilibrium occurs [START_REF] Esteban | A theory of agreements in the shadow of conict: the genesis of bargaining power[END_REF][START_REF] Hirshleifer | The paradox of power. The Dark Side of the Force: Economic Foundations of Conict Theory[END_REF][START_REF] Azam | The paradox of power reconsidered: A theory of political regimes in Africa[END_REF]. In particular, [START_REF] Azam | The paradox of power reconsidered: A theory of political regimes in Africa[END_REF] builds a model with reference to African countries that denes conditions for a peaceful equilibrium in a bargaining game between dictators and their opponents. In his model, peace is systematic when the opponent faces high opportunity costs of conict or when the opponent's military technology is too poor. When the incumbent faces high opportunity costs of conict, but the opponent does not, there may be coordination between them to avoid conict. The incumbent may (partly) commit to giving a transfer to the opponent conditional on peace, which works if this promise is credible enough.

A common feature of the framework proposed by North and his co-authors and by the post-conict political models is that personal relationships are central to an understand-ing of the social and economic order in some developing countries (and/or semi-democratic countries). In both cases, the government makes compromises with the opposition elite.

In the former case, this is due to personal relationships between elite members. In the latter, it is due to military threat.

This paper focuses on Ghana to show that political mechanisms in developing countries may very well be counterintuitive. We nd that, while Jerry Rawlings was President (or at least between 1998 and 2000), the accumulation of publicly provided infrastructures was greater in districts voting for the opposition. This was due to politically sensitive districts -districts where national opposition leaders had been general election candidates -and districts in the capital area. We nd this result to be in line with the natural state social order model described by North et al. (2009a) and with the bargaining mechanisms found by [START_REF] Azam | The paradox of power reconsidered: A theory of political regimes in Africa[END_REF] in an emerging democracy.

In the late 1990s, Ghana displayed conditions conducive to such a mechanism. First, Ghana had experienced political instability prior to 1982, so the threat of political instability was credible and bargaining between the President and his opponents was equally credible. Second, the former dictator, Jerry Rawlings, had been President for more than 15 years at that date. This may have made it easier to coordinate to nd a peaceful equilibrium with his opponents and with all the members of the elite. Indeed, the incumbent leader's commitment to give a transfer to the opponent has more credibility if he has already made such a transfer in the past. This also makes it less likely for the opposition to win subsequent elections, as African opposition parties rarely win elections when the former dictator is still in charge. Lastly, regular presidential and general elections have been held peacefully every four years since 1992. Ghana was therefore an emerging democracy between 1998 and 2003.

To our knowledge, one other paper analyzes the political motivations of public fund transfers in the Ghanaian case. [START_REF] Banful | Do formula-based intergovernmental transfer mechanisms eliminate politically motivated targeting? evidence from Ghana[END_REF] studies an intergovernmental transfer: the District Assemblies Common Fund (DACF). The DACF is supposed to be allocated in keeping with a national formula, which is designed to favor needs-based allocation. Banful rst shows that central government allocated fewer funds from the DACF endowment to districts with larger vote margins in the last presidential elections. This corresponds to the swing voter model (actually swing districts): when there is a lot of electoral competition in a district, the provision of public funds is high. Second, her results provide evidence that the DACF has been targeted at districts voting for the opposition party (except in 2003). This result seems counterintuitive and remains unexplained.

We rst show that her latter paradoxical result is not only specic to the District Assemblies Common Fund, but reects the actual national allocation of public goods. With our nationally representative data on public goods allocation, we observe that districts voting for the opposition saw a particularly sharp increase in public goods availability between 1998 and 2000. Most importantly, however, we develop an economic interpretation of this observation based on the need to curry favor with opponents in an emerging democracy, as Ghana was in the late 1990s. Standard theories based on democratic competition actually fail to explain this Ghanaian pattern. Besides, our data do not reveal the swing districts pattern found by [START_REF] Banful | Do formula-based intergovernmental transfer mechanisms eliminate politically motivated targeting? evidence from Ghana[END_REF]: districts with smaller vote margins did not see a particularly large accumulation of public infrastructure in our aggregated data.

This paper is structured as follows. Section 2 presents the Ghanaian political and macroeconomic environment. Sections 3 and 4 describe the data and the empirical strategy. Section 5 presents the results. Section 6 discusses the robustness of our results and Section 7 oers concluding remarks.

2 Ghanaian environment Under both international and domestic pressure, Rawlings' government ushered in democracy with the rst parliamentary and presidential elections in 1992. 4 Rawlings stood for his own succession as candidate for the National Democratic Congress (NDC). ideologically close to the Nkrumah tradition (see [START_REF] Morrison | Political parties in Ghana through four republics, a path to democratic consolidation[END_REF].

Today, the NDC is considered to be the left-wing party in Ghana, and is a member of Socialist International, whereas the Nkrumahists are now minor parties. The NPP is deemed the right-wing party. However, the political parties are also dierentiated on an ethnic basis. The NPP is largely supported by the Ashanti and has its geographic strongholds in the Ashanti region. Conversely, the Volta region is inhabited by Ewe, Rawlings' ethnic group, and votes for the NDC. The poorest Northern regions also tend to vote for the NDC (see [START_REF] Bossuroy | Voting in an african democracy: does only ethnicity rule? an empirical assessment on contemporary Ghana[END_REF]. These geographic patterns have been constant

since 1992 (see Figure 1).

Since this time, presidential and parliamentary elections have been held every four years. In 1996, with Ghana's political system leaning towards a two-party system, the two main parties secured most of the votes, and the NDC won both the presidential (Jerry Rawlings) and parliamentary elections.

The 2000 elections were very dierent from the previous ones. First, Jerry Rawlings was constitutionally prevented from running for a third presidential term. He is one of the rare African presidents to have fullled this obligation. So the NDC candidate was John Atta Mills, who was seen as less charismatic and was less well-known at the time. In addition, the NDC's campaign was perceived by some as arrogant and the economic situation had taken a downturn (Boafo-Arthur, 2008). The elections were won by John Kufuor for the NPP, which also won the parliamentary elections. However, voting patterns revealed a geographically heterogeneous shift. In 1996, broadly 80% of 4 However, the rst parliamentary elections were not representative since they were boycotted by the opposition.

5 Joseph B. Danquah led the rst Ghanaian political party in the days before independence, the United Gold Coast Convention (UGCC). Ko Busia was one of the founders of the National Liberation Movement (NLM) party, a conservative party supported by the Ashanti region and the educated elite. in the Brong-Ahafo, where the shift was impressive [START_REF] Asante | Ethnic structure, inequality and governance of the public sector in Ghana[END_REF].

Overall, the NPP essentially won the support of Accra and the Akan regions (Ashanti, Eastern, Brong-Ahafo and, to a lesser extent, Central regions). 6

In 2004, the NPP (led by Kufuor) won the presidential and parliamentary elections, but this dominance remained fragile and the party had lost part of its inuence in Accra. The second democratic shift in Ghanaian history took place in 2008. John Atta Mills (NDC)

won the presidential elections with 50.23% in the second round, and the NDC took 114 of the 228 seats (107 for the NPP). Nana Akufo-Addo was the NPP's presidential candidate.

Public service policies in Ghana

A centralized system behind decentralization reforms Decentralization reforms have been implemented in Ghana since the 80's. However, the central government remains the main political decision-maker.

6 [START_REF] Asante | Ethnic structure, inequality and governance of the public sector in Ghana[END_REF] talk of anti-Ashanti sentiments in some regions (Ashanti is the largest ethnic group among the Akan and is associated with the NPP). This could explain why softening the NPP's ethnic identity could be protable for this party in non-Ashanti Akan regions.

The major decentralization program was launched in 1988. It was designed mainly to devolve some political and central government power 7 to the district assemblies. However, most observers of the decentralization process believe that many factors impeded local government capacities, autonomy and performance [START_REF] Asante | Economic Analysis of Decentralisation in Rural Ghana[END_REF][START_REF] Asante | The Economy of Ghana, Analytical Perspectives on Stability, Growth & Poverty, chap. Decentralization & Poverty Reduction[END_REF][START_REF] Akramov | Decentralization and local public services in Ghana: Do geography and ethnic diversity matter?[END_REF]. Lack of funds is one of the reasons for their weak decisionmaking power: transfers from central government account for over 80% of local revenues and around 2.5% of central government public expenditure. 8 The will to maintain as strong a central government as possible has actually driven policy and reforms in Ghana since independence. For instance, a federalist system has always been rejected, and it is well known that one of the aims of the decentralization reforms -rst implemented by

Rawlings -was to curb the chieftaincies' power [START_REF] Jacquemot | Cheeries et décentralisation au Ghana[END_REF].

Investments in local infrastructures

Ghana's growth performances over the past two decades have been positive and stable with real GDP per capita growth rates standing at around 2% per year. As shown by Figure 2, per capita public expenditure rose steadily during this period of stability and growth, even though public capital expenditure growth was erratic. Note that most of public capital expenditure is nanced by Ocial Development Assistance (ODA), which funds the majority of the reforms and investment in the social sectors. Figure 3 presents the national mean levels for the public facilities analyzed in this paper. The indicators on primary and secondary school and healthcare facilities are presented for the rural areas only, since our data do not provide statistics on school and health centre facilities in towns (see the Data section below and Appendix A for more detailed information on the data).

Mean access to primary and secondary schools, even in rural areas, appears to be quite high. Around 90% of rural inhabitants live in areas with at least one primary school. 66% of primary schools were built when Kwame Nkrumah was president (1957)(1958)(1959)(1960)(1961)(1962)(1963)(1964)(1965)(1966)) [START_REF] Akyeampong | Access to basic education in Ghana: The evidence and the issues, country Analytic Report[END_REF]. The main progress since the mid-1980s appears to be in electricity and water supply. The number of people connected to the electricity grid doubled while access to piped water was multiplied by 7 Including decentralized administration, development planning and implementation.

8 These funds (District Assembly Common Funds, DACF) are allocated among the districts based on a formula approved by the National Parliament every year. [START_REF] Akramov | Decentralization and local public services in Ghana: Do geography and ethnic diversity matter?[END_REF] and [START_REF] Banful | Do formula-based intergovernmental transfer mechanisms eliminate politically motivated targeting? evidence from Ghana[END_REF] report that this formula takes in various social and economic factors such as Need, Responsiveness, Service Pressure, and Equality. 2.5. Employment in the public sector fell from 2000 onwards. 9

Regional disparities in public goods in Ghana

These national infrastructure levels conceal large regional disparities (Figure 4). The most obvious regional inequality is between the North and South of the country. This is quite closely correlated with poverty (Figure 5). Yet, over and above the country's

North-South divide, there are disparities between districts. The disparities in the North are especially salient between rural and urban areas. In the South, some districts of the Brong Ahafo, Western and even Ashanti regions are less endowed with public goods than the average of Upper West, Upper East and Northern regions (Figure 4).

Data

This paper draws on election data and national household data. The election results

for the 1996, 2000 and 2004 presidential elections are aggregated at district level. 10

The information on public goods and covariates is drawn from a number of national 12 (all surveys), the share of civil servants (all except the DHS surveys), and the share of the rural population with access to primary schools, secondary schools and community clinics 13 (all surveys except the DHS). All this information is aggregated at district level to generate district access rates for each facility. Appendix A presents the denition of each variable in detail and the sample size for the surveys used.

9 Yet these comparisons using dierent surveys are not necessarily entirely reliable, as they depend on the comparability of the surveys in question.

10 The parliamentary and presidential elections are held at the same time in Ghana. Since both re- sults are highly correlated, we focus on the presidential election outcomes in this paper. Parliamentary constituencies are nested in the 2000 districts.

11 Section 2 draws on the GLSS1 and DHS 93 surveys for its national statistics for 1988 and 1993.

12 Inside or outside the household dwelling.

13 Note, however, that this information is based on the availability of the public good in the community in the GLSS and the facility survey, while it is based on travelling time between the household and the facility in the CWIQ survey. The same national household datasets include socioeconomic information such as education, the quality of the household's dwelling (all except the DHS surveys), and ethnic and religious structure. All this information is aggregated at district level.

Finally, we have two variables to single out districts with inuent members of the elite. We have drawn a list of Ghanaian former ministers at the end of the 1990s and the beginning of the 2000s. and six of these were regional capitals. We also single out the districts where the 1996 parliamentary election candidate was a minister before 2000, under NDC rule. Of the 39 Rawlings' ministers, 18 were NDC candidates and 17 were elected. Only ve of the corresponding 17 districts were urban and two of these regional capitals (Accra and New Juaben).

As the information in this paper is aggregated at the district level, it is worth noting we focus on the Ghanaian districts as of 2000, and there were 110 districts in 2000.

4 Estimation strategy

Baseline model

This paper seeks to identify the link between political mechanisms and public goods allocation in Ghana. As pointed out in the introduction, a number of theoretical models can nd a link between districts' electoral results and this allocation. Firstly, the party machine model predicts that the districts voting for the incumbent will receive more public goods. Secondly, the swing voter model predicts that the politically centre districts will be favored. Lastly, the post-conict literature and the limited-access order model of North et al. (2009b) posit that the government may very well curry favor with its opponents and may therefore invest in their districts.

To assess the relative relevance of these models in the Ghanaian case, we estimate equation (1) over two periods: 1998 -2000 (period 1) and 2000 -2003 (period 2).

14 This list is from Wikipedia and may not be complete.

G g,d,t,s = ρG g,d,t-1,s + αδ(t)dif f d,t-1 + γdif f 2 d,t-1 + X d,t-1 β + g,d,t,s + µ s (G g,d,t ) (1)
G g,d,t,s is the availability of public good g in district d at the end of the period, as found by survey s. G g,d,t-1,s is the availability of public good g in district d at the beginning of the period, as found by survey s. In keeping with the survey dates, for period 1, t is 2000 and t -1 is 1998; for period 2, t is 2003 and t -1 is 2000. dif f d,t-1 is the dierence between the share of votes for the NPP and the NDC in district d at the last presidential elections 15 : at the 1996 election for period 1 (1998)(1999)(2000) and at the 2000 election for period 2 (2000)(2001)(2002)(2003). dif f d,t-1 takes positive values when the NPP is the majority party in the district and negative values when the NDC is the majority party.

δ(t) is a time dummy variable that takes value 1 if the NDC is in power at time t (period 1) and 0 if the NPP rules at time t (period 2). Coecient α captures whether or not the government in power provides its supporters' districts with more public goods.

In actual fact, α measures the double dierence between NPP voters and NDC voters, and between period 1 (1998)(1999)(2000) and period 2 (2000)(2001)(2002)(2003). 16 It is the main coecient in this paper, as it points up the pork barrel mechanisms. α should be negative under the party machine model: the NDC was in charge during period 1, the NPP was in charge during period 2, so the NPP voters should be relatively deprived during period 1. α can be positive only under the post-conict literature model and the natural order model, where the incumbent helps its opponents.

The empirical validity of our strategy is based on the double dierence between districts voting for the NPP and for the NDC, and between period 1 and period 2. Therefore, we need to nd the districts' unobservable characteristics that cause the accumulation of public goods to be constant over the ve years of our panel. In particular, the correlation between the districts' political preferences and the accumulation of public goods changes between the periods 1 and 2. This should be exclusively ascribed to a pork barrel mechanism.

Coecient γ in model ( 1) is the coecient of the square of the dierence between the 15 We use solely the results of the presidential elections in this paper. However, the patterns are the same when we look at the results of the parliamentary elections. 16 The covariates X d,t-1 include time dummies and dif f d,t-1 . The complete list is given below.

NPP and the NDC. It is expected to be negative under the swing voter model: political competition may increase investment in public goods.

A vector of covariates X d,t-1 is added, including dif f d,t-1 , proxies for the district's wealth and education, ethnic structure, and region-year dummies (there are 10 regions in Ghana, the 110 districts are nested in the regions). The covariates are measured at the beginning of the period, since investment over the period may aect the covariates at the end of the period. The estimations are made by pooling all the types of public goods by year and survey. All the specications consequently contain type of public good-survey xed eects.

Some public goods are measured on the same date by two dierent surveys. For example, the share of households connected to the electricity grid and to piped water in 2003 is measured by the 2003 DHS survey and by the CWIQ survey (Figure 6). In our data, all this information is pooled, as two observations of the same good in the same district from two surveys are far from independent. We therefore have to control in detail for the correlation between those two observations. So error term µ s (G g,d,t ) is included in the equation. All the standard errors are then corrected for an arbitrary correlation between dierent observations for the same district. The variance-covariance matrix between dierent observations for the same district is given by the data. The estimated standard errors are hence corrected for the fact that two observations of the same good in the same district from two surveys are strongly correlated.

The model (1) pools dierent types of public goods (schools, health centers, etc.).

Hence, the information on each public good is normalized: the observations for dierent districts in the same survey for the same good g have a mean of 0 and a standard deviation of 1. We interpret our normalized variable G g,d,t,s as the relative position in the country of district d for public good g at time t. The relative position is comparable across goods and dates.

Interacted model

The post-conict literature model and the natural order model do not predict the government will target any opponent district. Conversely, however, the post-conict literature model predicts that the government will target opponents with enough political power to lead a coup (bribing them in peace time increases the opportunity cost of a coup). The natural order model predicts the government will target the elite among its opponents. Both may obviously be correlated. Let's assume we can measure political power pp, then this heterogeneity is measured in model ( 2) by coecient κ > 0:

G g,d,t,s = ρG g,d,t-1 + αδ(t)dif f d,t-1 + κδ(t)dif f d,t-1 pp +γdif f 2 d,t-1 + X d,t-1 β 1 + β 2 pp + g,d,t,s + µ s (G g,d,t ) (2)

Fixed-eect model

The coecient ρ of G g,d,t-1 is expected to be positive. Note, however, that in this equation, the residuals g,d,t,s may well be serially correlated. A serial correlation of these residuals would induce a correlation between G g,d,t,s and G g,d,t-1,s due to the correlation between g,d,t,s and g,d,t-1 . This would mean that ρ would then be biased. It should be positive for two reasons: because there is some inertia in public goods availability, and because the unobservable characteristics causing G g,d,t,s are persistent. ρ would be the sum of these two eects. This has a repercussion for the other coecients: the control for G g,d,t-1,s is imperfect. To see the extent to which the empirical results of model (1) and model ( 2) may be biased, we estimate a xed-eect specication for model (1) and model

(2), which controls for the constant district unobservable characteristics in equation ( 3) and ( 4). (Note that dif f d,1996 is taken from the 1996 elections for periods 1 and 2 to ensure strict exogeneity in this specication.)

G g,d,t,s = αδ(t)dif f d,1996 + λ d + g,d,t,s + µ s (G g,d,t ) (3) G g,d,t,s = αδ(t)dif f d,1996 + κδ(t)dif f d,1996 pp +λ d + g,d,t,s + µ s (G g,d,t ) (4)

Fully interacted model

Lastly, the political power of a district pp may be correlated with observable characteristics X d,t-1 or with unobservable characteristics g,d,t,s . This can make the identication of equation ( 2) questionable. If coecient α is heterogeneous between districts with different (X d,t-1 , g,d,t,s ) and pp is correlated with (X d,t-1 , g,d,t,s ), then the estimation of κ in equation ( 2) is biased. The estimation of equation ( 5) controls for the interaction δ(t)dif f d,t-1 X d,t-1 , assuming α = α 0 + β 3 X d,t-1 . Therefore, it assesses whether the estimation of κ in equation ( 2) may be subject to an omitted variable bias, if the omitted variable is included in X d,t-1 or correlated with X d,t-1 .

G g,d,t,s = ρG g,d,t-1 + α 0 δ(t)dif f d,t-1 + κδ(t)dif f d,t-1 pp +γdif f 2 d,t-1 + X d,t-1 β 1 + β 2 pp +β 3 δ(t)dif f d,t-1 X d,t-1 + g,d,t,s + µ s (G g,d,t ) (5)

Results

Table 1 shows the results of the estimation of three dierent specications of model (1). The rst specication does not include any control for the districts' characteristics, whereas specications 2 and 3 take in dierent vectors of covariates. The last two specications are the estimations of model ( 2). Region-year dummies and survey-public good dummies are included in all specications, but their coecients are not shown. The estimated standard errors are robust to the correlation of dierent observations of the same district. Table 2 shows the district xed eect specication.

In each specication, the public good index at time t -1 is a predictor of the public good index at time t. The coecient is positive and signicant, as expected.

In the rst specication (column 1, Table 1), the dierence between votes for the NPP and the NDC is correlated with the increase in infrastructure availability. However, the coecient becomes much smaller and not signicant when controlling for the covariates, especially the district's mean wealth level (column 2 and following). The fact that the coecient of the dierence in votes between the NPP and the NDC is halved when controlling for urbanization and education can be explained by the fact that the NPP is the right-wing party in Ghana. The districts that vote for the NPP are wealthier on average, and wealthier districts accumulate more public goods. The correlation between votes and infrastructure availability diminishes when controlling for our proxies for wealth, education and urbanization.

The coecient of the dierences in votes interacted with the dummy for the rst period (fourth line of Table 1) is positive and signicant in each specication (columns 1, 2 and 3). It is the estimation of coecient α in equation ( 1): the double dierence between NPP voters and NDC voters, between period 1 and period 2. The xed eect specication renders the same positive and signicant coecient (Column 1 in Table 2). This positive coecient means that the NPP voters were relatively favored in period 1, when the NDC was in charge. The standard democratic competition theories are therefore useless when it comes to explaining this pattern in the relation between votes and public investment. The machine politics model does not t the data, since the districts supporting the parties in power did not receive more public goods and the districts supporting the opposition actually received more public goods between 1998 and 2000. In addition, the swing voter model produces no prediction for coecient α, but does provide a prediction for coecient γ. It is therefore unable to explain why α is positive. This paper gives a plausible explanation for this fact, based on the estimation of model ( 2). Specications 4, 5, Table 1 and specication 2, Table 2 interpret the counterintuitive relationship between votes and the allocation of public goods, by estimating coecient κ in equation ( 2) in column 4 and column 5, Table 1. Column 2, Table 2 shows the corresponding district xed-eect specication (equation ( 4)). These specications focus on the relationship between votes and public goods allocation in dierent contexts. They single out districts with dierent kinds of political power, as found by equation ( 2).

First, we single out districts in which a candidate standing for the 1996 parliamentary elections became minister after 2000 (under NPP rule). These districts were probably the constituency of a leader of the opposition party before 2000. In these 15 districts, the coecient of the correlation between voting for the NPP and public goods in the rst period is positive and signicant (2.71, line 6, column 4 Table 1). By comparison, it is not signicant in the other districts (0.30, line 4, column 4 Table 1). Our interpretation of this result is as follows: in addition to pursuing its electoral objectives, the NDC government wants to govern a peaceful country. Therefore, sensitive districts are rewarded to ensure the country's stability. The districts with an opposition leader may be considered to be sensitive mainly when they are opposition strongholds. This would explain the positive coecient of the interaction between our proxy for politicians and votes under the NDC government.

We also single out the districts where the 1996 parliamentary election candidate was a minister before 2000, under NDC rule. The coecient of this dummy variable and its interaction with votes is not signicant, from 1998 to 2000 (line 8, column 4 Table 1).

The districts with an NDC leader did not receive more public goods than others during Rawlings' government, whatever their election results. Again, this is not in line with the party machine model. However, column 4, Table 1, shows that after 2000, the districts with an opposition (NDC) leader had more public goods. The coecient of the interaction between votes and the dummy variable for districts with an NDC minister is signicant and positive (0.46, line 7). Notes: OLS with standard errors given beneath the coecients. The standard errors are corrected for an arbitrary correlation between dierent observations for the same district. The public goods included in the specication are: the share of households connected to the electricity grid, the share of households with access to piped water, the share of civil servants in the labor force, the share of the rural population with access to a primary school in the community, the share of the rural population with access to a secondary school in the community, and the share of the rural population with access to a health clinic in the community. All the specications include region-year xed eects and type of public good-survey xed eects. Notes: OLS with standard errors given beneath the coecients. The standard errors are corrected for an arbitrary correlation between dierent observations for the same district. The public goods included in the specication are: the share of households connected to the electricity grid, the share of households with access to piped water, the share of civil servants in the labor force, the share of the rural population with access to a primary school in the community, the share of the rural population with access to a secondary school in the community, and the share of the rural population with access to a health clinic in the community. All the specications include region-year xed eects and type of public good-survey xed eects.

We then generate a political index that takes the value of 1 if one of the parliamentary election candidates was a minister under NPP rule and -1 if one of the parliamentary election candidates was a minister under NDC rule. 17 As expected, the coecient for the interactions between votes and this index is positive and signicant from 1998 to 2000 in column 5, Table 1, and negative and signicant from 2000 to 2003 in column 5. The same result is found with the xed eect specication (column 2 in Table 2).

The correlation between support for the NPP and the dierences in votes is also positive in the Accra region in the rst period. This is also compatible with our theory of sensitive districts, as the capital's regions are well known for being a good place for demonstrations and they take in many members of the elite.

Column 4, Table 1 also presents a negative coecient for votes in the Accra region under NPP rule. This means that the districts voting for the NPP in Accra received fewer public goods after 2000. This coecient is intuitive: Accra is a sensitive place for both parties.

Overall, the validity of model ( 2) (κ > 0) means that the government curries favor with its opponents' elite. This does not mean it does not help its own supporters' elite. In fact, we only observe transfers through public goods allocation in the districts. Transfers to the supporters' elite may go via a dierent channel, and some of the potential channels cannot be observed by the social scientist (such as informal cash transfers).

In line three of Table 1, the coecients for the square of the dierence between NPP and NDC votes are always positive and signicant. This coecient appears to invalidate the swing voter model, or at least the version put forward by [START_REF] Levitt | The impact of federal spending on House election outcomes[END_REF], wherein politically centre districts receive more public funds because of MPs' incentives.

The politically centre districts in the electoral competition do not benet from particularly generous investment in public goods.

The coecients of the log of population density and mean education in the district are positive in columns 2 and 3. The coecient for wealth (as measured by our household amenities index) is not signicant, but wealth is strongly correlated with urbanization and education. This means that urban districts receive more public goods, which may be due to cost-recovery policies and community-driven approaches or national political targeting. The coecients for the other covariates are not signicantly dierent from zero at the 5% level. For instance, the coecient for the ethnic heterogeneity variable is not signicant. This result diers from the ndings of [START_REF] Banerjee | The political economy of public goods: Some evidence from India[END_REF] in India, where ethnic heterogeneity prevents an increase in public goods availability from 1971 to 1991. This result may be partly explained by the fact that Ghana's system of public goods allocation is centralized, rather than decentralized.

The Akan districts, and especially the Ashanti districts, receive fewer public goods than the others, but these results are signicant only at the 10% level. This is true only after controlling for the other covariates. The same regressions without controlling for votes would paint a totally dierent picture of ethnicity, as votes are strongly correlated with ethnicity in Ghana. Once ethnic pork barreling has been disentangled from electoral pork barreling, the eect of ethnic pork barreling is small and rarely signicant.

Robustness checks

This section assesses the validity of the interpretation of the coecients in Table 1.

It focuses on the link between the allocation of public goods and votes. Section 5 shows that investment in infrastructures under NDC rule was particularly high in the sensitive districts 18 that voted for the NPP. The OLS estimates could be biased by two dierent mechanisms: reverse causality and omitted variables. Reverse causality does not seem plausible in this case. The allocation of public goods from 1998 to 2000 causes neither the votes in 1996 nor the fact that a given district is in the Accra region. Moreover, it seems implausible for the ministers in the NPP government after 2000 to have been chosen because they obtained public goods from the NDC before 2000.

As regards the omitted variables bias, we identify the coecient κ with the heterogeneity of the correlation between the votes for the NPP and public goods between districts with and without political power. However, political power is probably correlated with other characteristics X it . In equation ( 5), we assume these characteristics X it may be correlated with the heterogeneity of coecient α. Table 3 assesses whether such heterogeneity biases the coecients in Table 1. In other words, the correlation between votes for the NPP and public goods is bigger in the districts with political power. We check whether some heterogeneity of the correlation between votes for the NPP and public goods based on other observable characteristics can change our results.

To do so, the dierence in votes is interacted with a number of other characteris-18 In other words, districts with a national NPP politician or in the Accra region.

tics (plus an interaction with the dummy for the 1998-2000 period), as in equation ( 5).

The variables included are: the district's population density, share of urban population, education index, household amenities index and ethnic variables. Column 2 of Table 3 presents the results of this specication, and the rst column of this table reproduces the estimates from Table 1, specication 5. In columns 1 and 2, the sign and signicance of the coecients interacted with the dierence in votes are the same, which indicates that the omitted variable bias is probably moderate.

The coecient for the interaction between the dierence in votes and the log of population density and the dierence in votes for the 1998-2000 period is positive and signicant (0.54). Again, this is compatible with our theory of a targeting of "sensitive districts", as urban districts may be harder to control.

The coecient for the interaction between the dierence in votes and the share of Akan for period 1 (1998)(1999)(2000) is positive and signicant (2.24). Again, Akan might be a proxy for strong opposition to the ruling party before 2000. Indeed, it is the majority ethnic group in Ghana, and Akans tend to vote for the NPP, which was the opposition party prior to 2000. The other coecients interacted with the dierence in votes for the 1998-2000 period in column 2 are not signicant at the 5% level, and do not change the column 1 coecients.

Column 3 tests for an omitted variable bias due to other political considerations.

Asante and Gyimah-Boadi (2004) explain that Rawlings' government made an eort in the Ashanti region. Two explanations are possible. The rst is the will to win votes from the Ewe, who migrated to the region to produce cocoa. The second ties in with the traditional Ashanti kingdoms, which may still wield power and compel certain public transfers from central government. So we control for a specic eect of the share of Ewe in the Ashanti region. One of the two variables for this eect appears to be signicant at the 1% level. In addition, we control for the same particularity tying in with the Ashanti kingdoms. These kingdoms are in the Ashanti region, and the best proxy we have for the districts within these kingdoms is the share of the Ashanti ethnic group in the population.

So we control for a specic eect of the Ashanti ethnic group in the Ashanti region, which does not appear to be signicant. Overall, the coecients of interest in column 3 are very similar to those in column 1. Notes: OLS with standard errors given beneath the coecients. The standard errors are corrected for an arbitrary correlation between dierent observations for the same district. The public goods included in the specication are: share of households connected to the electricity grid, share of households with access to piped water, share of civil servants in the labor force, share of the rural population with access to a primary school in the community, share of the rural population with access to a secondary school in the community, and share of the rural population with access to a health clinic in the community. All the specications include region-year xed eects and type of public good-survey xed eects, and the same covariates as specication 5 in Table 1, but all covariates are interacted with time in specication 2.

dierent parts. Nevertheless, the signs of the coecients remain similar for each public good.

Conclusion

This paper sets out to shed light on the mechanisms of political competition in semidemocratic African countries. The Ghanaian democratization process presents an opportunity to analyze how the political economy aects the allocation of public infrastructure in Ghana.

Most empirical and theoretical papers posit that the government should either target central districts in the electoral competition (swing districts) or its supporters. We nd the opposite to be true in Ghana. When the NDC was in power from 1998 to 2000, the districts that voted for the opposition received more public goods. This was particularly true when the districts had a leading opposition party politician. We assert that this nding is partially driven by a sense of need to curry favor with opposition party politicians.

These results were observed, at the end of the 1990s, in most particular circumstances.

Ghana was politically unstable from independence to the 1980s, when Jerry Rawlings took over as dictator. By the end of the 1990s, Ghana was an emerging democracy with Jerry Rawlings as the rst democratic president. A promising future paper could therefore be to identify the emergence of these political mechanisms before 1992 when Ghana was a dictatorship, and to check the persistence of these political patterns since 2004, following two peaceful general and presidential elections in Ghana. Notes: OLS with standard errors given beneath the coecients. The standard errors are corrected for an arbitrary correlation between dierent observations for the same district. The public goods included in the specication are: share of households connected to the electricity grid, share of households with access to piped water, share of civil servants in the labor force, share of the rural population with access to a primary school in the community, share of the rural population with access to a secondary school in the community, and share of the rural population with access to a health clinic in the community.

All the specications include region-year xed eects and type of public good-survey xed eects, and the same covariates as specication 5 of Table 1.

1994, Ghana launched the national Community Water and Sanitation Program (1994[START_REF] Schady | Seeking votes: The political economy of expenditures by the Peruvian social fund (FONCODES)[END_REF]CWSP-1 and 1999-2004 CWSP-2) based on a demand-and community-driven approach.

The underlying principle is that a 5% community contribution normally has to be applied to capital costs for water facilities for every investment in the water sector. However, the World Bank (2008) reports that there are variations in the interpretation and application of the policy.

Electricity Supply 20

Two main operators generate electricity: the Electricity Company of Ghana and the Volta River Authority (VRA) in charge of the hydroelectric plants in the Volta Basin.

  One candidate represented the Danquah/Busia movement 5 (right wing), on behalf of the New Patriotic Party (NPP). Three candidates represented the Nkrumahist movement and the most credible of them struck an electoral alliance with the NPP. The splintering of the Nkrumahist movement and its paradoxical alliance with the right-wing party left the door wide open for Rawlings to move into their traditional political arena: like Kwame Nkrumah, Rawlings was a charismatic leader and presented a populist platform

Figure 1 :

 1 Figure 1: Presidential elections, % of votes for the NPP party in 1996, 2002 and 2000 1996 2000 2004

Figure 2 :

 2 Figure 2: GDP at constant prices and public expenditure per capita (Cedis), 1987 -2004

Figure 3 :

 3 Figure 3: Public goods provision (% of people with access to public facilities), 1988-2003

  household datasets, namelyGLSS4 (1998),DHS (1998 and[START_REF] Asante | Economic Analysis of Decentralisation in Rural Ghana[END_REF], the 2000 national household and facility survey, and the 2003 CWIQ survey. 11 Together, these surveys provide information on the availability of public goods in Ghanaian districts at three points in time: 1998, 2000 and 2003. Figure 6 presents an overview of the national survey we use and compares their dates with the dates of national elections. They include information on the share of households with access to electricity and piped water

Figure 4 :

 4 Figure 4: Normalized public goods aggregate, 2000

Figure 6 :

 6 Figure 6: National elections and national household surveys in Ghana between 1996 and 2004

  The VRA is also mandated to distribute electricity in the North of Ghana. This led to the creation of the Northern Electricity Department in 1987. By the end of 1997, two key regulatory institutions had been created by acts of Parliament: the Public Utilities Regulatory Commission (PURC) and the Energy Commission (EC). The Ministry of Energy is responsible for broad policy direction while the PURC is in charge of economic regulation, fair competition among utilities and monitoring service quality. The EC is responsible for national indicative planning, licensing electricity utilities and technical standards.These two regulatory bodies were established to create the conditions required by the World Bank to improve the electricity sector's operational eciency, transparency and independence from government. The two government-owned generation and distribution utilities (ECG and VRA) have been granted signicant debt relief by both government and international donors. Despite structural reforms and government and international support, Ghana's electricity distribution sector is plagued with problems including poor infrastructure, managerial failings that have led to high system losses, and severe liquidity problems. Limitations on electricity services reportedly check economic growth and can play a part in social unrest. 20 All the information in this paragraph comes from RCEER (2005).

  14 We took the names of each minister in Kufuor's government from 2001 to 2005 and the names of each minister in Rawlings' government from 1993 to 2000. The 1996 parliamentary election results provide information on whether they were candidates and, if so, in which district. Of the 37 Kufuor's ministers, 15 were NPP candidates in the 1996 parliamentary election and 14 were elected. Eight of the corresponding 15 districts were urban (proportion of urban population greater than 50%)

Table 1 :

 1 Determinants of the allocation of public goods in Ghana

	(1)	(2)	(3)	(4)	(5)

Table 2 :

 2 Determinants of the allocation of public goods in Ghana, xed eects specica-

	tions
		(1)	(2)
	(Votes NPP -Votes NDC) (1996 elections) * (1998 -2000) 0.28+	0.09
		(0.16)	(0.15)
	(Votes NPP -Votes NDC) (1996 elections) * (1998 -2000)		0.58*
	* political index		(0.27)
	(Votes NPP -Votes NDC) (1996 elections) * (1998 -2000)		1.79**
	* District in Accra region		(0.36)
	(Votes NPP -Votes NDC) (1996 elections) * (1998 -2000)		0.09
	*NPP parliamentary candidate, minister after 2000		(0.14)
	(Votes NPP -Votes NDC) (1996 elections) * (1998 -2000)		-0.29+
	*NDC parliamentary candidate, minister before 2000		(0.16)
	Observations	1480	1480
	R 2	0.575	0.580

**, * and + mean respectively that the coecients are signicant at the 1%, 5% and 10% levels.

Table 4

 4

presents specication 5 for Table

1

disaggregated by type of public good. The estimation of the coecients is imprecise here, as the sample has been broken down into

Table 3 :

 3 Endogeneity checks: control for omitted variables

	(1)	(2)	(3)

Table 4 :

 4 Disaggregation between dierent types of public goods

	(7)	health	centres
	(6)	secondary	schools
	(5)	primary	schools
	(4)	civil	servants
	(3)	electricity
	(2)	water
	(1)	All

**, * and + mean respectively that the coecients are signicant at the 1%, 5% and 10% levels.

See, for instance,[START_REF] Levitt | Political parties and the distribution of federal outlays[END_REF] and[START_REF] Joanis | The road to power: Partisan loyalty and the centralized provision of local infrastructure[END_REF] for empirical evidence of public funds targeting the government's core support group in developed countries.

and if at least one parliamentary election candidate was a minister for either party.

* We thank the AFD (Agence Française de Développement) for its contribution towards the research for this paper. We also thank Thomas Bossuroy for the election data he collected in Ghana and

Civil servants: Share of civil servants in the labour force.

District education: District average of an education variable for individuals aged 25 and over. This variable takes the value of 0 if the individual has never been to school (but possibly pre-school), 1 if he started primary school, 2 if he completed primary school, 3 if he went to lower secondary school, 4 if went to upper secondary school, and 5 if he went to university.

Electricity supply: Share of households with access to electricity in the household.

Ethnic heterogeneity in the district: Sum of the squares of the shares of Akan, Ewe, Ga-Adangbe and Others in the district. Included in the [0, 1] interval.

Health centres: Share of the rural population with access to a hospital, health clinic or health centre. The 2000 facility census denes areas with a hospital, health clinic or health centre less than 4 km away as having a health centre. The CWIQ 2003 survey denes clusters in which more than 60% of households report access to a hospital or health clinic less than 45 minutes away on foot as having a health centre.

Household amenities index: Synthetic variable measuring the comfort of the dwelling.

It is the sum of four variables, averaged at district level. The rst variable takes the value of 1 if the cooking energy is charcoal, 2 if the cooking energy is electricity, gas or kerosene, and 0 otherwise. The second variable takes the value of 1 if the roof is made of metal, concrete or asbestos, and 0 otherwise. The third variable takes the value of 1 if the wall is in stabilised or made of burnt bricks, concrete or metal. The last variable takes the value of 0 if the oor is made of earth, and 1 otherwise.

Log (population density): The population density is calculated from the 2000 census. Of the 37 ministers, 15 were NPP candidates in the 1996 parliamentary election and 14 were elected. Eight of the corresponding 15 districts were urban (proportion of urban population greater than 50%) and six of these were district capitals.

Public goods aggregate: All six types of public goods (civil servants, electricity supply, health centres, primary schools, secondary schools and water supply) are transformed by linear transformation to have a mean of 0 and a standard error of 1, so as to ensure comparability between public goods. The public goods aggregate is the sum of these six variables.

Primary schools: Share of the rural population with access to a primary school. The 2000 facility census denes areas with a primary school less than 4 km away as having a primary school. The CWIQ 2003 survey denes clusters in which more than 60% of households report access to a primary school less than 45 minutes away on foot as having a primary school.

Political index: Takes value 1 if one of the legislative candidates was minister after 2000 (under the NPP), -1 if one of the legislative candidates was minister before 2000 (under the NDC), and 0 if neither or both.

Secondary schools: Share of the rural population with access to a secondary school.

The 2000 facility census denes areas with a secondary school less than 4 km away as having a secondary school. The CWIQ 2003 survey denes clusters in which more than 60% of households report access to a secondary school less than 45 minutes away on foot as having a secondary school.

Share of Akan in the district

Share of Ashanti in the district: This is calculated from the 2000 census.

Share of Ewe in the district

Share of urban population: This is calculated from the 2000 census. The denition of an urban area in Ghana is one with a population of more than 5,000 inhabitants.

Water supply: Share of households with access to piped water in the district.

B Data sources


Laura Turner

Hervé Boulhol
email: herve.boulhol@oecd.org

Laure Turner
email: laure.turner@insee.fr

Laure Turner
email: laure.turner@insee.fr.

Laure Turner

Recent trends and structural breaks in US and EU15 labour productivity growth

Keywords: JEL classification codes: E30, O47, O51, O52 labour productivity growth, structural break tests, ICT 1

This paper examines shifts in labour productivity growth in the United States and in Europe between 1970 and 2007 based on econometric tests of structural breaks. Additionally, it makes use of time-series-based projections of labour productivity growth up to 2009 in order to detect breaks depending on confidence intervals of the projections. The identification of structural breaks in US labour productivity growth is far from obvious. A statistically significant break is found in the late 1990s only if at least the 97.5th percentile of forecasts materialises in the future, which means that despite a clear pick-up in productivity growth in the second half of the 1990s, the size of the hump is not large enough compared with past variations to make this change a statistically significant break. However, a significant breakpoint is detected in the mid-1990s for the difference in labour productivity growth between the United States and the EU15, even when controlling for the convergence of Europe towards US productivity levels that has contributed to higher European performance in the early catch-up phase. Finally, within Europe, the accumulation of ICT capital seems to be related to differences in the shifts in structural labour productivity growth across countries.

Introduction

The gap in hourly labour productivity growth between the United States and the EU15 was nearly closed by the second half of the 1990s. Since then, there has been a sharp turnaround, with labour productivity growing faster in the United States than in Europe. However, productivity growth in the United States has slowed since 2003, to reach 1.4% in 2007. In contrast, in conjunction with the cyclical recovery, a small acceleration in labour productivity occurred in the EU15 between 2004 and 2006, before decelerating to a growth rate of 1.2% in 2007. 2 This paper aims at assessing the extent to which the recent changes in labour productivity growth in the United States and in Europe are structural as opposed to cyclical. First, for descriptive purposes, filtering techniques are employed on observed data to calculate the underlying trends in labour productivity growth between 1970 and 2007. Then, time series modelling is used to get forecasts of labour productivity growth up to 2009 as well as a high and a low scenario. Identifying the trends of those scenarios gives an insight on the conditions under which structural changes might have recently taken place. Finally, the statistical significance of the breaks in labour productivity growth is assessed. Throughout the paper, "breaks" should be understood as induced by sudden shifts rather than by gradual changes or drifts.

2.

Since the analysis was carried out, the published data has been extended by almost one year. However, it has been checked that growth rate trends have been little affected, such that the results are not altered by the extension of the available data.

The paper takes into account the heterogeneity between European countries. The paper investigates whether this heterogeneity in recent performance is due to different propensities of being intensive in Information and Communication Technology (ICT).

Well-known stylised facts are highlighted by the descriptive analysis:

a. Until the second half of the 1990s, the EU15 outperformed the United States in terms of labour productivity growth. 3 As from then, the United States experienced an increase in productivity growth, whereas EU15 labour productivity growth kept on decreasing. The trend in the productivity growth gap between the United States and the EU15 reached a peak in the early years of the 2000s, and has decreased since then.

b. Over 2000-2007, the United Kingdom, Ireland, Finland and Sweden were in the upper range of labour productivity growth performance in Europe, whereas Italy, Spain, Portugal and the Netherlands were in the lower range (Table 1).

c. During the 1996-2007 decade, European countries with high intensity of Information and Communication Technology (ICT) have been performing better in terms of structural labour productivity growth than the others.

This paper contributes to the literature that both identifies and dates breaks in labour productivity growth in the United States and in Europe, using statistic and econometric techniques, as in [START_REF] Benati | Drift and Breaks in Labor Productivity[END_REF], European Commission (2007), [START_REF] Gomez-Salvador | Labour Productivity Developments in the Euro Area[END_REF], [START_REF] Hansen | The New Econometrics of Structural Change: Dating Changes in U.S. Labor Productivity[END_REF] and [START_REF] Stiroh | Information Technology and the US Productivity Revival: What Do The Industry Data Say? Federal Reserve Bank of New York[END_REF]. It also brings in new elements. First, it extends data time coverage and makes use of various scenarios of labour productivity growth forecasts up to 3. EU15 is defined as a weighted average based on each country's GDP at PPP. Throughout the paper EU15 is without Austria because of the lack of data on hours worked before 1990 for this country.

2009 based on confidence intervals. 4 Second, whereas few studies have concerned individual

European countries, the current paper estimates the structural breaks in labour productivity growth on a country-by-country basis. It also provides the test and dating of structural breaks in the difference between US and EU15 labour productivity growth rates. Finally, it sheds some light on the contrasted patterns of labour productivity growth developments of the countries with high, medium and low intensity of ICT.

The main findings of the paper are the following: f. In the United States, a structural increase of growth in ICT capital services is estimated to have taken place after 1995, followed by a strong fall after 2001. These breaks do not translate into breaks at the total economy level.

The paper is organised as follows. The next section presents a brief review of the literature.

Overview of the literature

The focus of this paper is the timing and extent of breaks in labour productivity growth rather than the identification of the determinants of labour productivity growth. An initial literature predominantly made use of growth decomposition techniques to document the sources of the shifts in labour productivity growth with specific attention placed on the role of ICT. 5 These studies have two shortcomings concerning the identification of the structural trends in productivity. First, they presume a breakpoint in 1995 in US labour productivity growth. While the average annual labour productivity growth has strongly increased after 1995, an a priori selection of the break date is not satisfactory from a statistical point of view. The break date should be estimated as the one for which the shift in trend is statistically significant. Secondly, as [START_REF] Hansen | The New Econometrics of Structural Change: Dating Changes in U.S. Labor Productivity[END_REF] underlines, structural change has a meaning only in the context of a model, and occurs when the model's parameters change over time at some breakpoints.

The current paper overcomes these issues by relying on the econometrics of structural change, which allows for both the identification of multiple structural shifts in series and their dating with confidence intervals. The amount of work in this field is voluminous and surveyed by [START_REF] Bai | Multiple Structural Change Models: A Simulation Analysis[END_REF]. In particular, substantial advances have been made by [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) to cover models at a high level of generality. Their methodology, used in the current paper, is now widely implemented in applied studies covering a wide range of domains. For example, it is used to test for changes in the pattern of different series, such as aggregate employment growth in the euro area in the late 1990s [START_REF] Mourre | Did the pattern of aggregate employment growth change in the euro area in the late 1990s?[END_REF]. 6 The break tests are adequate for detecting sudden shifts. Conversely, such tests might have a low power to identify drifts when the underlying series is driven by too gradual changes [START_REF] Benati | Drift and Breaks in Labor Productivity[END_REF].

For the United States, the results obtained in this literature depend upon the sectoral coverage (non-farm business, manufacturing, total economy) and the period under study (Table 2). For 5. [START_REF] Gordon | Does the 'New Economy' Measure Up to the Great Inventions of the Past[END_REF][START_REF] Gordon | Five Puzzles in the Behavior of Productivity, Investment, and Innovation[END_REF], [START_REF] Jorgenson | Raising the Speed Limit: U.S. Economic Growth in the Information Age[END_REF], [START_REF] Jorgenson | Projecting Productivity Growth: Lessons from the U.S. Growth Resurgence[END_REF][START_REF] Mourre | Did the pattern of aggregate employment growth change in the euro area in the late 1990s?[END_REF], 2007), and Oliner andSichel (2000, 2002). See [START_REF] Jorgenson | Retrospective Look at the U.S. Productivity Growth Resurgence[END_REF] for a comprehensive survey of this literature for the United States, as well as [START_REF] Gordon | Why Did Europe's Productivity Catch-up Sputter Out? A Tale of Tigers and Tortoises[END_REF] for a complementary analysis; see also [START_REF] Gust | Productivity Developments Abroad[END_REF] for the other main industrialised countries. 6 .

It has also been applied in such domains as budget deficits (Bajo-Rubio, Díaz-Roldán and Esteve, 2008), export performance [START_REF] Rodríguez | Analysing the effects of labour standards on US export performance. A time series approach with structural change[END_REF] and inflation [START_REF] Santos | Assessing French inflation persistence with impulse saturation break tests and automatic general-to-specific modelling[END_REF].

the non-farm business sector, [START_REF] Benati | Drift and Breaks in Labor Productivity[END_REF] investigates changes in the growth of labour productivity using data from the Bureau of Labor Statistics (BLS) over 1947:1-2005:4. The [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) test for structural change fails to identify any statistical break for growth in output per hour. In an earlier paper, [START_REF] Stiroh | Information Technology and the US Productivity Revival: What Do The Industry Data Say? Federal Reserve Bank of New York[END_REF] uses one of the methodologies that served as a basis for the [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) 1983:2 (upwards) and1997:2 (downwards), and Spain three breaks in 1985:1 (downwards), 1991:1 (upwards) and 1994:4 (downwards).

Standard Hodrick-Prescott filtering of the trends

The

7.

The methodology differs in that the series are first filtered before the [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) test for structural breaks are run on the extracted trend. Moreover, the criteria employed to select the number of breaks is the Bayesian information criteria (BIC) which is weaker than the sequential procedure of Bai and Perron (see simulation analysis in [START_REF] Bai | Multiple Structural Change Models: A Simulation Analysis[END_REF]. Model selection procedure based on information criteria cannot take into account potential heterogeneity across time segments unlike the sequential method and shows limits when serial correlation is present.

However, it can be noted from Table 3 that much of the decrease in US labour productivity growth over 2004-2007 could be cyclical.

To gain further insight into possible shifts in labour productivity growth in recent years, both in the United States and in Europe, a forecast for US and EU15 labour productivity growth up to 2009:Q4 is made using time series analysis methods, as well as a confidence interval for the forecast consisting of an upper and a lower scenario at the 95% confidence level. That is, the upper scenario is defined by the 97.5 th percentile of the forecasts and the lower scenario by the 2.5 th percentile. This gives three series of labour productivity growth consisting of the observed data supplemented by the forecasts, namely the central, the upper and the lower scenarios. All scenarios are then decomposed into structural and cyclical parts, in order to compute three alternatives in labour productivity growth. Figure 2A and 2B show the central, upper and lower trend scenarios obtained for the EU15 and United States. 8,9 The robustness of the identified trends is subjected to two limitations that the tests reported in Section 4 partly overcome.

-One of the well documented drawbacks of the HP filter is that at the end of the sample, the filter becomes one-sided and the contemporaneous data are given a weight that is much greater than in the middle of the sample. This effect can be seen on Figures 2A andB: the upper and lower scenarios are diverging from the central 8.

These scenarios are based on ARIMA forecasts of the labour productivity series. The model that fits the EU15 is an ARIMA with differentiation parameter d=1, AR parameters p=9, 10, 11, 21, 22, 23 and MA parameter q=0, whereas the model for the USA is an ARIMA where d=1, p=9, 12 and q=0. The trends are robust to various specifications.

9.

The HP trends based on the OECD Economic Outlook 84 projections for the US and EU15 labour productivity growth up to 2009:4 are shown in Figure 2 as well. The trend based on these projections is close to the central scenario based on ARIMA forecasts, albeit slightly below. The purpose of using time-series-based forecasts is to get the upper and the lower scenarios.

scenario as soon as 2003:Q4, even though all scenarios are based on the same observed data covering four additional years.

-Trends are to some extent sensitive to the filtering parameter. 10 When using the lambda=1600 filter, the central prediction is that the post-1995 gap between US and EU15 labour productivity growth is shrinking quicker and reaching a lower level in 2009 than when using the lambda=7000 filter (Figure 3). A filter should include around 90% of the short cycles amplitude in the cyclical component, and under this constraint, the percentage of the long cycles amplitude included in the cyclical component should be as low as possible. On this basis, HP filtering on annual data requires lambda=30 [START_REF] Bouthevillain | Filtre de Hodrick-Prescott et choix de la valeur du paramètre lambda[END_REF]. Lambda=30 leads to a value of 91% of the short cycles amplitude included in the cyclical component and 41% of the long cycles amplitude included in the cyclical component. Lambda=100 -the value suggested by Hodrick and Prescott-leads to a value of 97% of the short cycles amplitude included in the cyclical component but to 70% of the long cycles amplitude included in the cyclical component. On quarterly data, lambda=7000 corresponds to lambda=30 on annual data. However, the usual value for international comparisons is lambda=1600 (which would correspond to lambda=7 on annual data). The different parameter specifications lambda=30 and lambda=100 have been studied on annual data as well as lambda=7000 and lambda=1600 on quarterly data.

11.

No data on capital services in the ICT sector being available for Luxembourg, it is excluded from this country classification.

1990s, recording a growth rate of both observed and trend labour productivity that is twice as large as that of the EU15.

An econometric assessment of structural breaks in labour productivity growth

This section investigates the existence and importance of multiple breaks in labour productivity growth since 1970 using the segmented trend approach developed in the context of the econometrics of structural change and more specifically the [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) test. This section is organised as follows. The next subsection describes briefly the methodology. Subsection 4.2 presents the results from the Bai and Perron sequential procedure for the EU15. Subsection 4.3 focuses on the United States, and subsection 4.4 gives the results

for the difference between the United States and EU15. The last subsection deals with the European countries and groups of countries based on their ICT intensity.

Methodology

The econometrics of structural change provides statistical answers to the questions of the existence, number and dates of structural shifts in labour productivity growth. Compared with HP filtering, this method has the critical advantage of dating the breaks without any a priori hypothesis about the length of the economic cycles. It also indicates how statistically significant the shifts are. Therefore it overcomes these two limits of HP filtering.

The estimation focuses on the identification of breaks in the mean of the labour productivity growth between different periods. The model used for testing structural change and estimating the number of break dates is the following, for m breaks at dates T m :

t k m k k t v T t I y + > + = ∆ ∑ = + ) ( 1 1 1 β β
where t y ∆ is labour productivity growth, (β 1 , …, β m ) the parameters, and t v the error term.

The [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) method of estimation of the candidate break dates is based on the least-squares principle and uses grid-search. 12 The methodology covers models at a level of generality that permits numerous practical applications. In particular, it allows for autocorrelation and heteroskedasticity in the residuals and different distribution for the data and for the errors across segments. The results of the test are reported at conventional test sizes of 5% or 10%.

Results for the EU15

Testing for structural change on quarterly data for the EU15 gives two break dates in 1979:Q2, and in 2000:Q2 in the central scenario (Table 4). 13 After each break, the estimated average annual labour productivity growth rate is lower, decreasing from 4.1% to 1.3% over the whole period. These results are in line with the literature reviewed above. The breaks, however, could be due to a convergence effect towards the steady state having fostered growth in the catch-up phase. Indeed, Figure 4 displays the strong EU15 labour productivity growth until the mid-1990s, while the United States evolved on a more steady growth path at higher labour productivity levels. 14 To investigate whether such breaks might be explained by convergence, the difference between the EU15 and US productivity levels is added as a control variable.

12.

For each m-partition (T1, …, Tm), the associated least squares estimates of the parameters (β1, …, βm) are obtained by minimising the sum of squared residuals. Substituting the resulting estimates in the objective function and denoting the resulting sum of squared residuals S(T1, …, Tm), the estimated break points ( ) m T T ,..., ˆ1 are the solution of the minimisation of S(T1, …, Tm) over all partitions. Then, the stability tests are implemented. The procedure is sequential. First, stability of the trend is tested against the hypothesis of one break. If stability is rejected, then one break date is imposed on the model, and the hypothesis of one break is tested against the hypothesis of two breaks. The second break date is obtained by testing all the possible models with two breaks knowing the first break date against the one break model. The procedure is repeated until the number of breaks and the corresponding break dates are determined. A maximum of 5 breaks have been allowed for this study. In the remaining of the text, the results of the sequential procedure are reported at the 5% or 10% significance level.

13.

Results limited to observed data, i.e. without the forecasts up to 2009:Q4 give the same results.

14.

Convergence has remained incomplete though as the catch-up stopped in the mid-1990s.

Estimates indeed point to convergence towards the US level at an annual pace of 7.8%. When this convergence effect is taken into account, the break in 2000:Q2 is still identified, but the one in 1979:Q2 disappears, suggesting that it actually reflects the convergence process. Subsection 4.4 comes back on the convergence effect in greater detail whereby additional tests are applied to the difference in the US and EU15 series.

It is interesting to investigate the extent to which the departure from the central scenario affects the results. Testing multiple structural breaks in the lower scenario (2.5 th percentile), as defined in Section 3, does not modify the results, whereas it does in the upper scenario (97.5 th percentile). More precisely, a break is always found in 1979. Another break is found at the end of 2000 in the lower scenario, as in the central one. However, if future productivity growth were consistent with the upper scenario, the slowdown after 2000 would not be identified as a structural break. A less stringent characterisation of the upper scenario, the 75 th percentile, rejects also the structural break in 2000, such that the 2000 break cannot be considered as being robust to possible future productivity developments.

In sum, the only robust break for EU15 labour productivity growth is in 1979 and disappears once convergence towards US productivity levels is controlled for, as convergence explains the faster growth in the (incomplete) catch-up phase.

Results for the United States

For the US non-farm business sector (Table 5), the test on data covering 1970-2007 as well as in the central or lower scenario up to 2009:Q4 gives no statistically significant break dates in US labour productivity growth even at the 10% level. It is only if high growth rates of labour productivity were reached in the future, i.e. consistent with the upper scenario, that the structural break of the mid-1990s, presumably due to ICT, would be confirmed. With the upper scenario, a statistically significant break date is found in 1998:Q3. However, with a less stringent definition of the upper scenario, the 95 th percentile instead of the 97.5 th percentile, the break is not identified. Despite the clear pick-up in productivity growth in the second half of the 1990s, the size of the hump is not large enough compared with past variations to make this change a statistically significant break.

In order to gain more insight on the structural evolution of labour productivity in the

Results for the difference in the US and EU15 growth rates

One advantage of looking at the difference between the US and EU15 series of labour productivity growth is to control for the effect of global shocks affecting both zones. Studying the difference in the US and EU15 series of labour productivity growth over 1970:Q1-2007:Q4

15.

As discussed earlier, for the total economy, using the Groningen Growth and Development Centre (GGDC) Total Economy Database over 1950[START_REF] Mourre | Did the pattern of aggregate employment growth change in the euro area in the late 1990s?[END_REF][START_REF] Gomez-Salvador | Labour Productivity Developments in the Euro Area[END_REF] finds two break dates in the United States labour productivity growth in 1973 and in 1995. Those breaks are not found using the BLS data at the non-farm business sector level over the same period. In order to understand the result of [START_REF] Gomez-Salvador | Labour Productivity Developments in the Euro Area[END_REF], the structural change test was ran for the same sectoral coverage of data, i.e. the total economy, using the OECD Economic Outlook 84 database. The period covered could only start in 1960 due to data availibility. The result of the test gives a break date in 1968. Over the same period of 1960-2006, the GGDC data also support a similar unique break date in 1966. This means that the results of [START_REF] Gomez-Salvador | Labour Productivity Developments in the Euro Area[END_REF] depend both on the sectoral coverage (total economy versus non-farm business) and the starting date (1950 versus 1960).

leads to the identification of a structural shift in the gap in labour productivity growth between the two areas after 1995:Q2 (Table 6). Until 1995, the structural EU15 labour productivity growth rate is estimated to exceed the US one by 1.6 percentage points annually (significant at the 99% confidence level), while EU15 is estimated to underperform the United States by 0.6 percentage point per annum after 1995 (this difference after 1995 is not significant). 16 This result is robust to whether the central, upper or lower scenario is considered.

One weakness of the above analysis is the lack of a structural model for the productivity growth rates. The over-performance of Europe in terms of labour productivity growth before 1995 might be due to a convergence effect towards the US level as discussed above. In order to explore this hypothesis further, the test for structural change is run controlling for the difference in the levels of labour productivity (in logarithms). Within the [START_REF] Bai | Estimating Multiple Break Dates at One Time[END_REF]Perron (1998, 2003) framework, the model used is the following:

t US t EU t m k k k t US t EU t v y y T t I y y + - + > + = - ∆ - - = + ∑ ) ( ) ( ) ( 1 1 1 1 α β β
where US t y and EU t y are US and EU15 labour productivity levels (in logarithms), (β 1 , …, β m ) the usual parameters, α the convergence effect, and t v the error term.

When controlling for the difference in levels, the sequential test confirms the break in 1995:Q2 with a significant change in the growth-rate difference from +0.8 before 1995 to -1.1 percentage points after 1995, and an annual speed of convergence of 3.1%. In order to discriminate between a break in the steady-state growth rate (the β 's) and a break in the convergence process (the α 's) regressions conditional on the 1995:Q2 break date were made.

16.

The identified structural break means that the difference between the two sub-periods of the growth rate differential (from +1.6 to -0.6) across the two areas is significant at the 95% confidence level.

Results are reported in Table 7. According the first regression (first column) which does not distinguish between the two sub-periods (before and after 1995:Q2), the difference in growth rates between the two areas is partly explained by convergence at an annual pace of 7.8%.

Column (2) allows for different speeds of convergence between sub-periods. 17 The speed of convergence is estimated to have diminished from an annual rate of 6.8% before 1995 to no convergence afterwards. Column (3) controls for overall convergence, but allows for different levels of growth rate differentials (the β 's): it is therefore entirely consistent with the results of the sequential Bai and Perron's testing procedure reported above. Column ( 4) is the most general as it replicates column (3) while allowing for different speeds of convergence. Both cases are consistent with the break in growth rates and with a non-significant convergence parameter. However, multicollinearity might be problematic, and the last two columns replicate (3) and ( 4), respectively, but drop the non significant growth-rate difference in the first sub-period. These last estimates suggest that there was a break in both the speed of convergence from 5.7% to zero, and the structural growth rate differential after 1995:Q2, the latter being favourable to the United States by 0.6 percentage point annually after the break.

Results for the European countries and the ICT groups of countries

Finally, heterogeneity in Europe across countries and across ICT groups of countries has been taken into account. The results are summarised in Tables 8 and9. The European countries that have similar timing of the structural shifts in their labour productivity growth are also part of the same ICT group. This suggests that in Europe the accumulation of ICT capital is correlated to structural shifts in labour productivity.

17.

Given possible collinearity issues, to be consistent with the idea of convergence, the convergence parameters (the α 's) have been constrained to be no greater than zero.

a. As for the United States, no significant break is found for the United Kingdom, Sweden, and Ireland.

  Figures1A and 1B show the inversion in labour productivity growth trends that occurred in the

Figure 1A .

 1A Figure 1A. US and EU15 labour productivity growth rates, observations and trends, quarterly data, 1970:1 -2007:4

Figure 1B .

 1B Figure 1B. Zoom on US and EU15 labour productivity growth rate trends, quarterly data, 1995:1 -2007:4

Figure

  Figure 2A. EU15 growth rate trends in labour productivity, quarterly data 1970:1 -2007:4, and arima forecast to 2009:4 Central, upper and lower projected trends in labour productivity growth

Figure 4 .

 4 Figure 4. Labour productivity levels in the United States and in Europe, 1970:1 -2007:4 at 2000 PPP, USD

  point over 1996-2007. This breakpoint holds when controlling for the difference in lagged productivity levels. The latter finding suggests that the 1995 breakpoint is due both to the catch-up of Europe, which has stopped since the mid-1990s, and to different ICT performances. e. European countries that have similar timing of the structural shifts in their labour productivity growth are devoting comparable effort to ICT. This suggests that in Europe the accumulation of ICT capital is correlated to structural shifts in labour productivity.

  United States, breaks in some of the series related to labour productivity growth -capital deepening growth, multifactor productivity growth, labour quality growth and ICT capital accumulation -have been studied between 1970 and 2006. The results are reported in Annex 3. The main finding is a structural increase in the growth rate of ICT capital services after 1995, followed by a sharp fall after 2001. This analysis implies that these breaks do not

translate into breaks at the total economy level. Finally, for the manufacturing sector over 1987:2 to 2007:4, a break is found in 1993:3 at the test significance level of 10%, but not at he 5% level.

15

ANNUAL GROWTH RATE OF TOTAL CAPITAL SERVICES IN THE ICT SECTOR, IN THE UNITED STATES AND EUROPE Figure. Annual growth rate of total capital services (in %), ICT sector, United States and Europe, 1985-2005

  Those countries are all ICT-intensive. . The break (downwards) in France and Spain is estimated to have occurred around the late 1980s. Both countries are part of the intermediary ICT group.The study of the difference in labour productivity growth between Europe high ICT and Europe medium-lowICT over 1970ICT over :1-2007:4 :4 gives a break point at the end of 1990, indicating that labour productivity has structurally grown faster in Europe high ICT than in Europe medium-low ICT after this point. Second, the pick-up in United States labour productivity growth, presumably due to ICT, would be statistically measured as a break only if high growth rates of labour productivity, consistent with the 97.5 th percentile of forecasts, were reached in the future. Third, a clear breakpoint is found in 1995 for the difference in labour productivity growth between the United States and the EU15. This breakpoint holds when controlling for a convergence effect of Europe towards United States levels, suggesting further that there has been a structural change in both the speed of convergence and the structural growth rate differential after 1995:Q2, the latter becoming favourable to the United States after the break. Labour productivity is defined as GDP per hour. Annual data for the European countries come from the OECD Productivity Database and cover 1970 to 2007. Quarterly data come from the OECD Economic Outlook 84 database and cover 1970:1 to 2007:4. The data are available at the aggregate country level. They cover the total economy. For the United States, the data sources are the OECD Economic Outlook 84 database and the Bureau of Labour Statistics (BLS) databases. The non-farm business sector is the one studied.However, the BLS also provides historical series of annual labour productivity growth for the non-farm business sector from 1948 as well as a quarterly series for manufacturing from 1987. Two series of data were used to study the ICT capital trends over1970[START_REF] Mourre | Did the pattern of aggregate employment growth change in the euro area in the late 1990s?[END_REF]. Jorgenson and Stiroh (2007) have built a dataset which contains IT capital services' values and prices from 1948 to 2006. The ratio of these series, which approximate the quantity of IT capital services, is taken as the first series. The second data series considered is the BLS calculation of the contribution of IT capital intensity to aggregate productivity growth (growth rate of information processing equipment and software capital services per hour times its share in total costs) available also from 1948 to 2006.

	b. Italy and Germany experienced a structural change (downwards) in the labour productivity growth around the end of 1979 according to the tests. Both countries have a low intensity of ICT. Conclusion This paper aimed at assessing the existence and extent of structural shifts in US and EU15 5 labour productivity growth since 1970. Four main conclusions emerge from the econometric tests. First, the analysis of the EU15 series points to a structural slowdown in productivity growth around 1979 and again around 2000. However, the 2000 break is not robust to likely scenarios of future productivity growth, while the 1979 break disappears when convergence Section 4 makes use of those data in order to allow comparison of results with the existing literature. Also, in Section 4, in order to gain more insight about the structural evolution of labour productivity in the United States, capital deepening, multifactor productivity growth and labour quality have been studied, as well as ICT capital trends. The data on capital deepening (capital services divided by hours) are the annual data of the BLS between 1970 and 2006, and the quarterly data of the OECD Economic Outlook 84 database on capital stock in volume 1.8 1.8 0.4 1.7 1.1 1.7 1.2 1.0 1.4 0.7 1.6 1.0 1.1 1.8 1.8 1.8 1.8 1.2 1.2 USA SWE GBR IRL DNK PRT BEL NLD FRA FIN GRC ESP ITA DEU towards US levels is controlled for. Fourth, looking at individual European countries, the paper shows that ICT-intensive countries have been structurally performing better in terms of labour productivity growth since the nineties. ANNEX 1: DATA 3.2 3.0 2.6 2.6 2.2 2.2 2.2 2.0 determine weights. ANNEXE 2 : 2.0 average 1985-1995 average 1996-2005
	divided by hours between 1970:1 and 2006:4. Multifactor productivity growth is provided by
	the BLS on an annual basis between 1970 and 2006. Finally, the BLS provides annual data on
	labour composition between 1970 and 2006. Labour composition measures the effect of shifts
	in the experience, education, and gender composition of the work force. It is the ratio of labour
	input to hours of all persons, where labour input is a Tornquist aggregate of hours of all
	persons (classified by education, work experience and gender) using hourly compensation to

cSource: OECD Capital-Services Database. No data are available for Luxembourg.

Table 1 . Average growth rate labour productivity (quarterly annualised)

 1 Source: OECD Economic Outlook 84 Database. Hodrick-Prescott filtering (lambda=7000).Reading note: the ICT high-intensive group of countries includes Sweden, United Kingdom, and Ireland. It was defined considering the countries' average growth in total capital services over 1996-2005 in the ICT sector (see section 3)

			1985-1995			1996-2007			2000-2007
		LP	Trend	Cycle	LP	Trend	Cycle	LP	Trend	Cycle
	BEL	2.2	2.2	0.0	1.4	1.4	0.0	1.1	1.2	-0.1
	DEU	2.7	2.7	0.0	1.6	1.6	0.0	1.5	1.4	0.1
	DNK	2.6	2.3	0.3	1.0	1.1	-0.1	1.0	1.0	0.0
	ESP	1.8	1.8	-0.1	0.5	0.6	-0.1	0.7	0.5	0.2
	FIN	3.2	3.2	0.1	2.5	2.4	0.1	2.5	2.3	0.2
	FRA	2.4	2.4	0.0	1.6	1.6	0.0	1.6	1.5	0.1
	GBR	2.0	1.9	0.1	2.2	2.5	-0.3	2.0	2.7	-0.7
	GRC	1.7	1.0	0.7	3.1	3.2	-0.1	3.7	3.4	0.3
	IRL	3.6	4.0	-0.4	4.2	4.0	0.2	3.1	3.4	-0.3
	ITA	2.2	1.9	0.3	0.6	0.7	-0.1	0.5	0.4	0.1
	LUX	3.0	3.0	0.0	1.9	1.7	0.2	1.7	1.7	0.0
	NLD	1.5	1.7	-0.2	1.3	1.4	-0.1	0.9	1.0	-0.1
	PRT	3.0	2.6	0.4	1.9	1.7	0.2	1.2	0.8	0.3
	SWE	1.6	1.6	0.0	2.3	2.3	0.0	2.2	2.0	0.2
	EU15	2.1	2.1	0.0	1.5	1.5	0.0	1.2	1.4	-0.1
	ICT high-
	intensive	2.4	2.5	-0.1	2.9	2.9	0.0	2.4	2.7	-0.3
	countries

Table 2 . Overview of the previous results

 2

	Paper	Data		Data	Statistical	Break(s)
		source and	period	frequenc	approach	identified
		scope		y
			UNITED STATES
	Benati	USA	1947:1-	quarterly	Bai and Perron	No break
	(2007)	Non-farm	2005:4		(1998, 2003)
		business, BLS
	Stiroh	USA	1974:1-	quarterly	estimation of one	No break
	(2001)	Non-farm	2000:3		break date
		business, BEA
	Stiroh	USA,	1974:1-	quarterly	estimation of one	1993:3
	(2001)	Manufacturing,	2000:3		break date
		BEA
	Hansen	USA	1947:1-	quarterly	Bai and Perron	1997
	(2001)	Manufacturing/	2000:4		(1998) among
		durables, BLS			others
	Gomez-	USA,	1950-	annual	Bai and Perron	1973, 1995
	Salvador	Total Economy,	2006		(1998, 2003)
	et al. (2006)	GGDC Database
			EUROPE
	Benati	Euro-zone,	1970:1	quarterly	Bai and Perron	2001:1
	(2007)	Total Economy,	-		(1998, 2003)
		European Central	2006:2
		Bank Area Wide
		Model Database
	Gomez-	Euro-zone,	1950-	annual	Bai and Perron	1973, 1979,
	Salvador et	Total Economy,	2006		(1998, 2003)	1995
	al. (2006)	GGDC Database
	EC (2007)	Euro-zone,	1980:1	quarterly	Bai and Perron	1998:1
		Total Economy,	-		(1998, 2003) on
		Eurostat	2006:4		trend extracted by
					filter. BIC criteria.

Table 3 . Trend/cycle breakdown of labour productivity growth

 3 Source: OECD Productivity Database and BLS for 2007 US labour productivity growth rates in the non-farm business sector. Hodrick-Prescott filtering (lambda=30).

	(annual data, Hodrick-Prescott filtering with lambda=30)
		EU15
		Labour	Trend	Cycle
		productivity
		growth
	1985-1995	2.1	2.1	0.0
	1996-2006	1.5	1.5	0.0
	2000-2006	1.2	1.4	-0.1
	2000-2003	1.2	1.5	-0.2
	2004-2007	1.3	1.3	0.0
		United States
		Labour	Trend	Cycle
		productivity
		growth
	1985-1995	1.2	1.4	-0.2
	1996-2006	2.1	2.1	0.0
	2000-2006	2.2	2.2	-0.1
	2000-2003	2.7	2.3	0.3
	2004-2007	1.3	2.1	-0.8

Table 8 . Results of the Bai-Perron sequential test at significance level of 5% for selected countries

 8

	Countries	Periods identified by the	Estimated average growth rate of
		BP test	labour productivity
	FRA	1970:Q1-1989:Q4	3.5***
		1990:Q1-2007:Q4	1.7***
	ESP	1970:Q1-1986:Q2	4.4***
		1986:Q3-2007:Q4	0.9***
	DEU	1970:Q1-1979:Q2	4.6***
		1979:Q3-2007:Q4	2.0***
	ITA	1970:Q1-1979:Q4	4.3***
		1980:Q1-2007:Q4	1.2***
	GBR	non significant	_
	SWE	non significant	_
	IRL	non significant	_

*** indicates that estimates are significant at the 1% level Reading note: see Table

4

.

Table 9 . Results of the Bai-Perron sequential test at significance level of 5 % - Difference between high ICT Europe and medium-low ICT Europe

 9 * indicates that estimates are significant at the 5% level, * at the 10% level."Europe high ICT" and "Europe medium-low ICT" labour productivities are unweighted averages. The ICT groups of countries are defined looking at the average growth in total capital services over 1996-2005 in the ICT sector (see section 3).Reading note: see table 4.

	Periods identified by	Estimated difference in growth
	the BP test	rates
	1970q1-1990q4	-0.5*
	1991q1-2006q4	1.0**

*

Source: OECD Economic Outlook 84 Database, and BLS for 2007 US labour productivity growth rates in the non-farm business sector. Hodrick-Prescott filtering (lambda=7000). Scenarios are based on ARIMA projection (see Section 3).

The results reported for the ICT capital services growth rely on Jorgenson and Stiroh (2007) dataset.

They were confirmed using the BLS dataset. Note. To be consistent with convergence, the parameter for the difference in levels (first three rows in the table) is restricted to be negative. The constraint is binding for the difference in levels after 1995:Q2. Standard errors in parenthesis are robust to heteroskedasticity and autocorrelation.