Do political institutions improve the diminishing effect of financial deepening on growth? Evidence from developing countries

Accepted Manuscript Title: Do political institutions improve the diminishing effect of financial deepening on growth? Evidence from developing countries Author: Kevin Williams PII: DOI: Reference:

S0148-6195(18)30090-0 https://doi.org/10.1016/j.jeconbus.2018.11.003 JEB 5830

To appear in:

Journal of Economics and Business

Received date: Revised date: Accepted date:

24 April 2018 10 September 2018 19 November 2018

Please cite this article as: Williams K, Do political institutions improve the diminishing effect of financial deepening on growth? Evidence from developing countries, Journal of Economics and Business (2018), https://doi.org/10.1016/j.jeconbus.2018.11.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Do political institutions improve the diminishing effect of financial deepening on growth? Evidence from developing countries

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Kevin Williams

The University of the West Indies, Kingston, Jamaica [email protected]

Highlights

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Credit market development impedes economic growth in emerging and developing countries Democratic institutions reduce the diminishing effect that credit market development has on economic growth These results advance economic and political debate in emerging and developing countries

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Abstract

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This paper studies the effect that credit market deepening has on economic growth in emerging and developing economies over the 1970-2014 period. The paper further examines whether political institutions intermediate the relationship between credit market deepening and economic growth. Two main findings have been uncovered in the empirical analysis. The first key finding suggests that credit market deepening reduces economic growth in the panel of emerging and developing economies. The second central finding indicates that democratic institutions reduce the diminishing effect of credit market deepening on economic growth. Overall, these findings advance economic and political debate in emerging and developing economies.

JEL Classification: G21, O11, P16

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Keywords: Democratic institutions; credit market development; economic growth

1. Introduction Going back to the late 19th century, economists argued that financial development is an important driver of economic growth (Bagehot, 1873; Schumpeter, 1911). They provide several reasons why a sound financial sector is central to economic growth. As emphasized by McKinnon (1973) and Shaw (1973), financial repression undermines the capacity of the financial sector to 1

mobilize savings and to intermediate between agents who want to save and agents who want to invest in high-return projects. More recently, Levine (2005) argues that a well-functioning financial sector facilitates transactions in markets, generates information about investments, channels resources to their most profitable uses, and diversifies and manages risks.

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A large empirical literature, starting with King and Levine (1993), supports the idea that financial development is an important determinant of economic growth. Consistent with this positive link in the literature, a wave of financial liberalization takes hold in developing countries in the 1990s. The disruption in economic growth caused by the 2007-2008 global financial crisis casts doubt, however, on the positive relationship between financial development and economic growth, starting a lively debate that if financial development becomes too large it will generate inefficient allocation of resources, which in turn can be a drag on economic growth.

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Recent evidence highlights the fact that beyond a certain limit, financial development can be harmful to economic growth. Using a sample of 133 developed and developing countries, Arcand et al. (2015) show that financial deepening has a negative effect on economic growth when credit to the private sector exceeds 100% of GDP. Law and Singh (2014) also find evidence, in a sample of 87 developed and developing countries, that financial development reduces economic growth when credit to the private sector reaches in the range of 90% of GDP. In a novel contribution, Fufa and Kim (2017) examine the effect of financial development on economic growth in various groups of homogeneous panel of countries. The authors document that private sector credit and stock market liquidity have differential effect on growth in middle-income and high-income countries. They conclude that the effect of financial development on economic growth depends critically on the stages of economic development. In their seminal work, Ibrahim and Alagidede (2017) use data on sub-Saharan Africa to demonstrate that the impact of financial development on economic growth is mediated by whether countries reach a certain level of per capita income, human capital development, and financial development. Using the system GMM approach, Inoue (2018) examines the interplay between remittances, financial development, and poverty in developing countries. The author finds that remittances and financial development reduce poverty, while remittances play a substituting role in reducing poverty in developing countries with poor financial development.

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This paper makes two central contributions to the literature on the finance-growth debate. First, using a rich panel comprising 81 emerging and developing economies over the 1970-2014 period, the paper examines whether too much credit market deepening reduces economic growth. The paper focuses on emerging and developing economies for several reasons. There is not much systematic evidence whether credit market development is harmful to economic growth in emerging and developing economies. This is surprising, given their poor regulatory framework and low levels of institutional development, as emerging and developing economies are more susceptible to economic and financial shocks and many of them perform poorly on key economic indicators. Thus, understanding whether credit market deepening harms economic growth in emerging and developing economies will inform debates about the appropriate policy to mitigate economic and financial risks.

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In the second contribution, the paper further investigates whether democratic institutions as captured by political rights and the Polity index mediate the relationship between credit market development and economic growth. In countries with strong democratic institutions credit markets are more likely to allocate credits to more productive investments, as political elites faced more constraints to directing resources to unproductive politically favored investments. Strong democratic institutions should therefore make credit market development more effective in promoting economic growth. By contrast, in countries with weak democratic institutions, political elites faced fewer constraints to influencing which projects can access credits. To the best of our knowledge, this paper is the first to explore the intermediating role of political institutions on the relationship between too much credit market deepening and economic growth.

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To estimate the effect that too much credit market deepening has on economic growth in emerging and developing economies, the paper implements the Blundell and Bond (1998) dynamic system generalized method of moments (GMM) estimator that controls for endogeneity arising from reverse causality between credit market deepening and economic growth. The empirical evidence from the panel data analysis suggests that too much credit market deepening reduces economic growth in emerging and developing economies. Further, democratic institutions moderate the effect that too much credit market deepening has on economic growth. Specifically, democratic institutions improve the diminishing effect that too much credit market deepening has on economic growth. These findings are robust to a range of sensitivity checks.

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2. Related literature

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The rest of the paper is structured as follows. The next section discusses the literature on financial development and economic growth. Section 3 discusses the empirical strategy and data. Section 4 discusses the results on the impact of too much credit market deepening on economic growth. Section 5 discusses the results on the intermediating effect of political institutions. And concluding remarks are contained in Section 6.

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King and Levine (1993) are the first study to provide empirical evidence on the effect of financial development on economic growth. The authors use a cross-section of 80 countries from 1960-1989 to show that financial development improves economic growth. Following this contribution, other papers using more robust econometric techniques also corroborate the evidence in King and Levine (1993). Levine at al. (2000), for example, use a panel data approach that isolates the exogenous variation of financial development. Their system GMM instrumental variables estimates are in line with a positive effect of financial development on economic growth. Beck and Levine (2004) extend the empirical model in Levine et al. (2000) by including the effect of the stock market. Using data for 40 countries over the 1976-1998 period, they further find that both financial institutions and financial markets induce economic growth. More recent studies contradict previous finding of a positive association between financial development and economic growth. Demetriades and Rousseau (2016), using a sample of 84 developed and developing countries, explore the changing nature of the effect of financial development on economic growth. They show that financial development is positively associated

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with economic growth over the 1975-1989 period, but reforms of financial institutions are more important in explaining economic growth for the period 1990-2004.

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A distinguishing feature of this paper is that the above studies do not consider the impact that too much credit market deepening has on economic growth in emerging and developing economies. The current paper is most closely related to an emerging literature, following the 20072008 global financial crisis, which shows that there can be a threshold beyond which financial development reduces economic growth. The key contributions are Cecchetti and Karroubi (2012), Law and Singh (2014), and Arcand et al. (2015). Cecchetti and Karroubi (2012) use a sample of 50 developed and emerging economies to estimate the effect of financial development on economic growth from 1980-2009. They find that when financial deepening is too large it has an inverted U-shaped impact on economic growth. The point at which financial development starts hurting economic growth, 98% of private sector credit to GDP, is close to Law and Singh (2014) and Arcand et al. (2015), 90% and 100%, respectively. A major advantage of this paper that sets it apart from these contributions is that, in addition to focusing on emerging and developing economies, the current paper also examines whether and how political institutions affect the impact that too much credit market deepening has on economic growth and finds that democratic institutions reduce the negative response of economic growth to too much credit market deepening. None of the above studies examine the interplay between political institutions, credit market development, and economic growth in emerging and developing economies, which is the heart of the analysis.

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This paper is also related to the literature that examines the effects of democratic institutions on credit market development. Drawing on historical experiences of Germany and the U.S., Pagano and Volpin (2001) suggest that politicians respond to incentives of being elected by directing credits to their constituents, with negative effects on economic growth. Khwaja and Mian (2005) reported that over the 1996-2002 period, politically connected firms in Pakistan have greater access to credit and higher default rates, which harms economic growth. The effect is stronger for government banks. Under strong democratic institutions, this clientelistic approach to allocating credit will be moderated, because of more political constraints.

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Rajan and Zingales (2003) develop a theory of the effects of interest group politics on financial development. Using data for developed countries spanning the 20th century, they show that political interests, when they are threatened, will block financial development because financial development introduces competition, which reduces their rents. They further show that special interest politics are less likely to impede financial development in countries exposed to cross-border capital flows. Democracies conduct more cross-border trade and hence will improve the growth effects of financial development by encouraging competition in credit markets through more openness to international capital flows. Clague et al. (1996) develop a theory which predicts that under strong democratic institutions, better property rights and contract enforcement are likely to emerge to support more financial development. They present evidence consistent with this theory. Beck et al. (2003) explore the historical determinants of financial development. In colonies where 4

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Europeans settled, the authors find that Europeans established democratic institutions that protect private property and creditor rights, two key elements that support credit and capital markets development. Another strand of the literature explores the effects of democratic institutions on economic growth. The weight of the evidence in this literature indicates that democratic institutions improve economic growth. Using various econometric approaches, Acemoglu et al. (2016) document a 20% increase in economic growth in the long run in democracy. The channels through which this occurs are investments, education, economic reforms, better provision of public goods, and less social unrest. Similar evidence is reported by Papaioannou and Siourounis (2008) using different sample and econometric techniques.

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By examining the effects of the interaction between credit market deepening and democratic institutions on economic growth, the current paper contributes to the literature by bridging the gap between two different literatures: the relationship between democratic institutions and credit market deepening; and the relationship between democratic institutions and economic growth. The paper further advances our understanding by presenting evidence suggesting that democratic institutions moderate the negative effects that credit market deepening has on economic growth.

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3. Estimation framework and data

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This section discusses the estimation strategy and the data used to estimate the relationship between too much credit market deepening and economic growth in emerging and developing economies. The paper uses non-overlapping 5-year averaged panel data for 81 emerging and developing economies covering the 1970-2014 period. 5-year averages smooth cyclical variations associated with annual data and thus makes the estimates more precise. The paper estimates the following reduced-form dynamic econometric model that relates economic growth to our measures of credit market development and a set of growth determinants:

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Growthit = γi + δt + πlnYit-1 + βFDit + µFDsquaredit + αlnXit + εit.

(1)

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Growthit is real per capita GDP growth in country i and reference time t. γi is a full set of country fixed effects that control for time-invariants country-level characteristics, for example colonial heritage, ethnic background, geography, and other country-level factors that affect credit market development and economic growth differently across countries. δt is a full set of time fixed effects that control for time-specific shocks that jointly affect economic growth and credit market development, such as global financial crises and other global political shocks such as the fall of the Berlin Wall and the collapsed of the Soviet Union. The natural logarithm of initial real per capita GDP lnYit-1 reflects convergence in economic growth. To capture the effect of too much credit market deepening on economic growth, following Arcand et al. (2015), the paper includes a linear measure FDit and a squared measure FDsquaredit 5

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of credit market development in equation (1). Although the squared term FDsquaredit imposes a curvature on the estimated coefficient, it does not impose statistical significance, that is, the estimated coefficient can turn out statistically insignificant. The main measure of credit market development is GDP share of domestic credit to the private sector. Arcand et al. (2015), King and Levine (1993), and Law and Sing (2014) use GDP share of domestic credit to the private sector as their main measure of credit market development. As robustness checks against the main measure, the paper also employs two commonly used measures of credit market development: total domestic credit and liquid liabilities, both expressed as a share of GDP. These bank-based indicators are preferred over alternative indicators because the banking sector is the most important source of intermediation between savers and investors in emerging and developing economies (Law and Singh, 2014).

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The vector Xit contains the main control variables that the literature shows are correlated with economic growth: the natural logarithm of trade openness measured as the sum of exports and imports expressed as a ratio of GDP; the natural logarithm of life expectancy at birth; the natural logarithm of inflation measured by the consumer price index; the natural logarithm of the ratio of government consumption to GDP; and population growth. εit is the error term. The data are from the World Bank World Development Indicators and the Financial Development Structure Database.

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There are two econometric concerns when estimating equation (1). The first issue is endogeneity bias arising from the reverse effect of economic growth itself affecting credit market development. Robinson (1952) argues, for example, that economic growth fosters opportunities for financial institutions and financial services to be emerged. Greenwood and Jovanovic (1990) also show in an endogenous growth model that financial development supports economic growth and economic growth itself provides resources for financial institutions to be created. Controlling for the reverse effect of economic growth alleviates concern that credit market development is responding to economic growth. The second concern is the correlation between the lagged dependent variable Yit-1 and the error term, the socalled Nickell (1981) bias.

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To overcome these econometric challenges, the paper uses the Blundell and Bond (1998) dynamic system GMM that models the dynamic effect of the lagged dependent variable and that controls for the reverse effect of economic growth on credit market development. The dynamic system GMM uses lagged levels as instruments for the equation in first differences and lagged differences as instruments for the level equation. With these additional internal instruments, the system GMM is more efficient than the first-difference GMM and OLS estimators (Roodman, 2009). Validity of the instruments, however, in the dynamic system GMM rests on the Hansen test and the AR(2) test. The paper reports the p-values of these tests to check the reliability of the dynamic system GMM estimates. In the empirical section, the Hansen test and the AR(2) test support the reliability of the dynamic system GMM estimates. Although the system GMM is used in many previous studies, it is not without limitations. The system GMM suffers from the weak instrument problem that can make inferences

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problematic (Bun and Windmeijer, 2010).1 To improve the precision of the dynamic system GMM estimates, robust standard errors are computed with the Windmeijer (2005) finite sample correction. Also, the additional moment conditions generated by the system GMM can cause instrument proliferation and hence weakens the diagnostic tests to detect unreliable estimates (Roodman, 2009). Moreover, though we control for a large set of growth determinants that are commonly used in the literature, given the range of factors that could affect economic growth, the empirical model could still be affected by omitted variables bias. We reduce omitted variables bias by include country fixed effects in the regressions. Notwithstanding, caution must be applied when interpreting the system GMM estimates. Descriptive statistics are reported in Table 1. [Table 1 here] 4. Results

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Table 2 presents the main estimates of the average effect that too much credit market deepening has on economic growth in the panel of 81 emerging and developing economies, over the 1970-2014 period. These estimates, as in subsequent tables, are based on the dynamic system GMM estimator that alleviates concern of the potential reverse effect of economic growth on credit market development. Table 2 uses domestic private sector credit as a percentage of GDP as the main measure of credit market development. Column 1 includes this linear measure of credit market development. Column 2 begins to examine the effect of too much credit market deepening by including in the model specification domestic private sector credit squared. Columns 3 to 8 include, sequentially, the growth determinants to check whether the relationship between domestic private sector credit and economic growth is affected by omitted variable bias. The main message emerging from Table 2 is that if credit market development gets too large it can reduce economic growth in emerging and developing countries.

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With country and time fixed effects as the only control variables in column 1, the estimated coefficient of 0.173 (standard error = 0.000) on domestic private sector credit is positive and statistically significant at the 5% significance level, indicating that private sector credit promotes economic growth in the panel of emerging and developing countries. This finding is consistent with research conducted in the 1990s (King and Levine, 1993; Levine and Zervos, 1998; Rousseau and Wachtel, 1998) and early 2000s (Levine et al., 2000; Beck and Levine, 2004). To capture the impact of too much credit market deepening, column 2 adds in domestic private sector credit squared. The estimated coefficient on domestic private sector credit squared is negative and highly statistically significant at the 1% significance level and the estimated coefficient on the linear term remains positive and now significant at the 1% level, together suggesting that credit market development has an inverted U-shaped effect on economic growth. To put these estimates into perspective, quantitatively, credit market development yields a negative effect on economic growth when credit to the private sector exceeds 87% of GDP. The size of this impact is close to other studies that focus on developed countries, or do not distinguish between developed and developing countries (Arcand et al., 2015; Law and Singh, 2014; Cecchetti and Karroubi, 2012). 1

See Bun and Windmeijer (2010) for a detail derivation of the weak instrument problem.

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As noted above, the rest of Table 2 assesses the impact of the growth control variables on the inverted U-shaped effect of domestic private sector credit on economic growth. Column 3 includes the sum of imports and exports divided by GDP to capture trade openness. This measure of trade reflects one aspect of globalization. Trade openness has a significant positive effect on economic growth. Importantly, the quantitative magnitude (86% of GDP) and significance (at the 1% level) of the inverted U-shaped effect of credit market development are not affected by the inclusion of this growth covariate.

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Life expectancy is added to the model specification in column 4. This control variable measures the level of development in a country. As expected, life expectancy has a positive and significant effect on economic growth. Notice that the size of the estimated coefficient on the linear term of domestic private sector credit, 0.316 (standard error = 0.000), and on domestic private sector credit squared, -0.002 (standard error = 0.000), both reduced by about 50% in absolute values. These smaller estimates notwithstanding, credit market development starts reducing economic growth when credit to the private sector exceeds 79% of GDP. Moving to column 5 that includes population growth, which captures aspects of economic development. In developing countries, higher population growth rates reduce the flow of capital for savings and investment (Birdsall and Sinding, 2003), two key ingredients for economic growth, other things being equal. Population growth is negatively associated with economic growth and statistically significant at the 1% significance level.

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Column 6 includes inflation as a measure for macroeconomic stability. Inflation has a negative effect on economic growth. GDP share of government consumption is included in column 7 to capture the size of the public sector. Large government is negatively associated with economic growth;2 the estimated coefficient on government consumption is negative and significant. Lagged per capita GDP is included as an additional regressor in column 8 to measure convergence in economic growth across countries. The estimated coefficient on the convergence term is negative and significant at the 1% significance level. Reassuringly, in all model specifications the inverted U-shaped effect of credit market development is precisely estimated. Using column 8 with the full set of control variables as the preferred model specification, quantitatively, credit market deepening starts stunting economic growth when domestic private sector credit exceeds 140% of GDP. Note that the Hansen test of instrument relevance and the AR(2) test of no-second order serial correlation – two important criteria for reliable estimates – support the system GMM estimates. [Table 2 here]

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Tables 3 and 4 repeat the exercise in Table 2 using 2 alternative measures of credit market development: total domestic credit and liquid liabilities expressed as ratios of GDP. These are useful checks that help determine whether the inverted U-shaped effect of credit market development is sensitive to any particular measure of credit market development. Domestic credit includes credit both to the private sector and to the public sector. It therefore provides a 2

This negative effect could reflect counter cyclical fiscal policy, which does not suggest that large government hurts economic growth. I thank an anonymous referee for this interpretation.

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broader measure of credit market development relative to private sector credit. Liquid liabilities on the other hand measures the size of the banking system. The main disadvantage of liquid liabilities as a measure of credit market development is that it captures financial transactions instead of the banking sector intermediating between savers and investors (Ang and McKibbin, 2007). Nevertheless, liquid liabilities allow an important check against the main measure and it has been used to measure credit market deepening by King and Levine (1993) and Beck and Levine (2004).

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Looking down each column of Table 3, we see that the estimated coefficients on domestic credit are positive and statistically significant and negative and statistically significant for domestic credit squared. These findings are consistent with those in Table 2. Using the preferred model specification in column 8, quantitatively, the inverted U-shaped effect of domestic credit reaches 102% of GDP, after which economic growth starts responding negatively to credit market development, smaller than that of column 8 of Table 2. The picture does not change even when using liquid liabilities that does not capture the allocation of credit in the economy. In this case the inverted U-shaped effect approaches 85% of GDP, column 8 of Table 4. The control variables have the expected sign and are in general statistically significant. Overall, the main conclusion from this section is that the size of credit market development matters for economic growth in emerging and developing economies: if it gets too large it can hamper economic growth.

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[Table 3 here]

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[Table 4 here] 4.1. Additional results

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The evidence above shows that credit market development can lean against economic growth in emerging and developing countries. In this subsection, the paper conducts additional checks of the robustness of the main finding. To this end, the paper estimates a specification that includes the full set of growth control variables. Column 1 of Table 5 drops all countries from Latin America and the Caribbean (LAC). This region consists of middle income countries. Column 2 excludes all countries from the Middle East and North African (MENA) region. These are mainly Muslim states that have both traditional banking system alongside Islamic banking, and it has been shown that Islamic banking development promotes economic growth. Column 3 excludes all countries from Sub-Saharan Africa (SSA). Except for South Africa, SSA is comprised of low income countries and the financial sector is in general underdeveloped. Column 4 drops all countries from Asia, and column 5 excludes the four countries that have on average the largest GDP share of credit to the private sector over the sample period. These countries are: China (91%), Malaysia (88%), South Africa (100%), and Thailand (83%). These checks will help determine the extent to which the inverted U-shaped effect of credit market development is influenced by any particular region or by the handful of countries that have a more developed credit market. As displayed in Table 5, columns 1-5, in all specifications the estimated coefficient on private sector credit and on private sector credit squared is significantly positive and significantly negative, respectively, at least at the 5% level of significance.

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The results in columns 1-5 may still differ however based on the economic structure of each country. Following the CIA World Factbook classifications, we split the sample into three subsamples – commodity-, services-, and industrial-based economies – and test whether the main results vary with the economic structure of the subsamples. 3 The results reported in columns 6-8 show that the estimated coefficients on private sector credit and private sector credit squared retain their signs and significance, though not as strong as columns 1-5. Nevertheless, we can therefore reject the hypothesis that too much credit market deepening does not significantly reduce economic growth. Though not reported to save space, but are available upon request, these results are also confirmed with domestic credit and liquid liabilities. [Table 5 here]

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In Table 6, the paper further checks whether these results are different across low and middle income countries. We group countries based on the World Bank income classifications. Columns 1-3 and 4-6 present estimates for low income countries and middle income countries, respectively. Regardless of whether countries are low or middle income and regardless of the measure of credit market development, the evidence still points to an inverted U-shaped relationship between credit market development and economic growth. In sum, the results from Tables 5 and 6 support the baseline results in Table 2. [Table 6 here]

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5. Political institutions, credit market development, and economic growth

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Do political institutions influence the impact that too much credit market deepening has on economic growth? The paper attempts to answer this question in this section. As discuss in Section 2, democratic institutions prevent political elites from using the weight of their office to influence the allocation of credit in the economy. A democratic environment creates the rules for credit market to generate optimal efficiency. In other words, democratic political institutions do not obstruct the allocation of credit to its most productive uses. Moreover, because democratically elected political elites face the electorate at regular intervals they have stronger incentives to pursue growth-enhancing policies. Their autocratic counterparts on the other hand do not face the same incentives.

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Credit markets interact with political institutions to affect economic outcomes. This section both complements and extends studies that explore how political institutions shape financial development. Huang (2010) and Girma and Shortland (2008) use panel data to study the effect of political institutions on financial development. These authors find that democratic institutions improve financial development. Huang (2009) also shows that democracy is an important driver of financial forms. Pagano and Volpin (2001) and Rajan and Zingales (2003) shed light on the role of the political process in shaping financial development.

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I thank an anonymous referee for suggesting these additional checks.

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To test for the effect of democratic institutions on the relationship between too much credit market deepening and economic growth, we modified equation (1) and estimate the following specification:

Growthit = γi + δt + πlnYit-1 + βFDit + µFDsquaredit + ψ(FDit × Demit)+ (2)

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µ(FDsquaredit × Demit ) + λDemit + αlnXit + εit .

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We include 3 new variables in equation (2): Demit represents political rights as the main measure of democratic institutions from Freedom House. The political rights score ranges from 1 to 7, where 1 indicates more political rights. This score is normalized between 0 and 1, with 1 indicating more political rights. Freedom House codes political rights based on a set of criteria: free and fair elections; competitive political parties, existence of opposition parties; participation of minority in the political process; acceptance of elected government. As robustness check, the paper also uses the Polity index from the Polity IV dataset. Political rights and the Polity index are two of the most widely-used measures of democratic institutions (Acemoglu et al.2008; Williams, 2017). (FDit × Demit) is an interaction between the linear measure of credit market development and democratic institutions. (FDsquaredit × Demit) is an interaction between the squared measure of credit market development and democratic institutions. These two interaction terms capture the intermediating effect of democratic institutions. All the other variables in the vector Xit remain unchanged. Notice that we include the linear measure of credit market development FDit, credit market development squared FDsquaredit, and the linear measure of democratic institutions Demit to ensure that the estimates on the intermediating effect of democratic institutions do not pick-up the effects of these variables.

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Table 7 presents estimates using Freedom House political rights index as the measure of democratic institutions. All specifications include the full set of growth control variables, though, to prevent clutter, they are not reported.4 As indicated at the top of each column, column 1 uses private sector credit to measure credit market development, column 2 uses total domestic credit, and column 3 uses liquid liabilities. In column 1, the estimated coefficient on private sector credit and private sector credit squared is statistically insignificant at the conventional significance level. This continues to be the case in columns 2-3 with domestic credit and liquid liabilities. Democratic institutions is positive and significantly associated with economic growth. This finding is consistent with evidence presented by Barro (1999) but contradicts that presented by Acemoglu et al. (2008) when country fixed effects are accounted for. Importantly, the estimated coefficient, 2.755 (standard error = 0.001), on the interaction between private sector credit and political rights has a significant (5% level) negative effect on per capita GDP growth. Also, the estimated coefficient, 0.017 (standard error = 0.000), on the interaction between private sector credit squared and political rights is positive and statistically significant at the 5% significance level. 4

These control variables are generally statistically significant at the conventional significance level and are available upon request.

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The insignificant estimated coefficients on private sector credit and private sector credit squared, together with the significant negative estimated coefficient on the interaction between private sector credit and political rights on the one hand and the significant positive estimated coefficient on the interaction between private sector credit squared and political rights on the other hand, indicate that democratic institutions mediate the effect that too much credit market deepening has on economic growth. Specifically, the interaction terms have a U-shaped effect on per capita GDP growth, suggesting that democratic institutions reduce the negative effect that too much credit market deepening has on economic growth. Quantitatively, democratic institutions improve the effect of too much credit market deepening on economic growth when credit to the private sector exceeds 81% of GDP (column 1).

[Table 7 here] [Table 8 here]

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A further implication of the main finding is that democratic institutions can also overturn the positive effect that credit market development has on economic growth when credit market is shallow.5 Looking across all model specifications, the inclusion of the interaction terms renders the estimated coefficient on the linear and on the squared measures of credit market development statistically insignificant.6 These results are confirmed in Table 8 using the Polity index measure of democratic institutions, except now the linear measures of credit market development in columns 1 (private sector credit) and 3 (liquid liabilities) are statistically significant and positive.7 Notice that the estimated coefficient on the measures of democratic institutions turns negative in column 2 of Table 7 and insignificant in column 2 of Table 8, after the inclusion of public sector credit. One possible reason is that, though political rights and the Polity index are widely used in the literature they may not be accurate measures of democratic institutions and thus picking-up other factors. The main conclusion however from Tables 7 and 8 is that democratic institutions can potentially shield emerging and developing economies from the harmful effects of too much credit market deepening, as well as retard economic growth if credit market development is low.

6. Conclusion

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The 2007-2008 global financial crisis generates an active debate on the role of the financial sector in economic development. A central argument in this debate is whether a large financial 5

One explanation for this finding is that during the early stages of development, a central planner could mandate how much of society’s income should be saved. I thank an anonymous referee for this interpretation and possible reason. Or it could be that even with more political rights, if credit market development is low it creates competition for the limited credit; corruption could emerge with adverse effect on economic growth. 6 The interaction terms capture the channels through which credit market development affects economic growth. Hence econometrically they explain most of the variation in economic growth. 7 The polity index is a composite measure of democracy based on a -10 to 10 scale, with 10 indicating more democracy and -10 more autocracy. The polity index coding is based on competitiveness of political participation; constraints on the executive; openness and competitiveness of executive recruitment. As with political rights, we rescaled the polity index to lie between 1 and 0, with 1 indicating more democracy.

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sector is bad for economic growth. This paper contributes to that debate by investigating the effect that too much credit market deepening has on economic growth in emerging and developing economies, a question that has not been systematically addressed before in the context of emerging and developing economies. The study further advances the literature by examining the role of political institutions on the effect that too much credit market deepening has on economic growth. To answer these questions, the paper employs the Blundell and Bond (1998) dynamic system GMM estimator that controls for the possibility of economic growth driving credit market development. Two main findings have been uncovered in the empirical analysis.

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The first key finding indicates that too much credit market deepening hurts economic growth in emerging and developing countries. This finding is robust to different ways of measuring credit market development, to sequentially including a range of growth covariates, to static and dynamic model specifications, and to various subsamples. The second central finding suggests that democratic institutions reduce the negative impact that too much credit market deepening has on economic growth. This result is robust to alternative measures of democratic institutions, to a full set of growth determinants, and to alternative measures of credit market development. The findings advance economic and financial policy debate in emerging and developing economies.

References

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Blundell, R. & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel models. Journal of Econometrics, 87 (1), 115-143. Birdsall, N. & Sinding, W. S. (2003). How and why population matters: new findings, new issues. In N. Birdsall, A. C. Kelly, & S. W. Sinding (Eds.), Population Matters: Demographic Change, Economic Growth, and Poverty in the Developing World (pp. 3-23). New York: Oxford University Press Inc.

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Bun, M. J. G. & Windmeijer, F. (2010). The weak instrument problem of the system GMM estimator in dynamic panel data models. Econometrics Journal, 13, 95–126. Cecchetti, S. and Kharroubi, E. (2012). Reassessing the impact of finance on growth. Bank for International Settlements, Working Paper No. 381. Clague, C., Keefer, P., Knack, S. & Olson, M. (1996). Property and contract rights in autocracies and democracies. Journal of Economic Growth, 1(2), 243-276.

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Demetriades, P. & Rousseau, P. (2016). The changing face of financial development. Economics Letters, 141, 87–90.

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Girma, S. & Shortland, A. (2008). The political economy of financial development. Oxford Economic Papers, 60: 567-596.

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Greenwood, J. & Jovanovic, B. (1990). Financial development, growth and the distribution of income. Journal of Political Economy 98 (5), 1076-1107.

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Huang, Y. (2009). The political economy of financial reform: Are Abiad and Mody right? Journal of Applied Econometrics, 24(7), 1207-1213.

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Huang, Y. (2010). Political institutions and financial development: An empirical study. World Development, 38(12), 1667-1677.

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Inoue, T. (2018). Financial development, remittances, and poverty reduction: Empirical evidence from a macroeconomic viewpoint. Journal of Economics and Business, 96, 59–68. Khwaja, A. & Mian, Atif (2005). Do lenders favor politically connected firms? Rent provision in an emerging financial market. Quarterly Journal of Economics, 120(4), 1371–1411. King, R. G. & Ross, Levine (1993). Finance and growth: Schumpeter might be right. Quarterly Journal Economics, 103(3), 717-737. Law, S. H. & Singh, N. (2014). Does too much finance harm economic growth? Journal of Finance and Banking, 41, 36-44. 14

Levine, R. (2005). Finance and growth: theory and evidence: In P. Aghion & S. Durlauf (Eds.), Handbook of Economic Growth (pp. 865-934). Amsterdam: Elsevier Publisher. Levine, R., Loayza, N. & Beck, T. (2000). Financial intermediation and growth: Causality and causes. Journal of Monetary Economics, 46, 31-77.

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Levine, R. & Zervos, S. (1998). Stock market, banks, and economic growth. American Economic Review, 88(3), 537-558. McKinnon, R. I. (1973). Money and capital in economic development. Washington: Brookings Institutions Press. Nickell, Stephen (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 3146. Pagano, M. & Volpin, P. (2001). The political economy of finance. Oxford Review of Economic Policy, 17(4), 502-519.

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Papaioannou, E. & Gregorios S. (2008). Democratisation and Growth. Economic

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Journal, 118(532), 1520–1551.

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Rajan, R. G. & Zingales, L. (2003). The great reversals: The politics of financial development in the twentieth century. Journal of Financial Economics, 69, 5-50.

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Robinson, J. (1952). The generalization of the general theory and other essays. London: Macmillan.

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Roodman, D. (2009). How to do xtabond2: an introduction to difference and system GMM in Stata. Stata Journal, 9, 86-146.

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Rousseau, P. & Wachtel, P. (1998). Financial intermediation and economic performance: Historical evidence from five industrial countries. Journal of Money, Credit and Banking, 30(4), 657-678. Schumpeter, J. A. (1911). A history of economic development. Cambridge, Massachusetts: Harvard University Press.

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Shaw, E. S. (1973). Financial deepening in economic development. New York: Oxford University Press.

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Williams, K. (2017). Do remittances improve political institutions? Evidence from Sub-Saharan Africa. Economic Modelling, 61, 65–75. Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators,” Journal of Econometrics, 126, 25-51.

15

Std. Dev. 23.977 31.974 25.893 3942.763 7.975 37.778 9.398 441.463 1.044 0.329 0.335

A

CC

EP

TE

D

M

A

N

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Mean 31.013 45.236 40.933 3775.055 14.842 72.441 62.489 51.385 1.920 0.539 0.558

16

Obs. 677 668 680 677 634 663 719 657 729 700 585

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Table 1: Descriptive statistics Variables Credit to the private sector (% of GDP) Total domestic credit (% of GDP) Liquid liabilities (% GDP) Per capita GDP (constant 2010 US$) Gov. consumption (% of GDP) Trade (% of GDP) Life expectancy Inflation Population growth Political rights Polity

N U SC RI PT

PT

Log Gov. consumption

ED

M

A

Table 2: Estimating the effect of private sector credit on economic growth Dependent variable: Per capita GDP growth (1) (2) (3) (4) (5) Private sector credit 0.173** 0.696*** 0.689*** 0.316*** 0.263*** (0.000) (0.000) (0.000) (0.000) (0.000) 2 Private sector credit -0.004*** -0.004*** -0.002*** -0.001*** (0.000) (0.000) (0.000) (0.000) Log Trade 0.005*** 0.004*** 0.003*** (0.001) (0.001) (0.001) Log Life expectancy 0.054*** 0.045*** (0.005) (0.004) Population growth -0.003*** (0.000) Log Inflation

(6) 0.268*** (0.000) -0.001*** (0.000) -0.001 (0.001) 0.035*** (0.004) -0.004*** (0.000) -0.021*** (0.001)

(7) 0.334*** (0.000) -0.002*** (0.000) 0.001 (0.001) 0.037*** (0.005) -0.003*** (0.001) -0.020*** (0.001) -0.012*** (0.002)

Yes Yes 0.000 0.986 0.931 603

Yes Yes 0.000 0.615 0.950 581

Log Per capita GDP, t-1

CC E

Year FE Country FE AR(1) test, p-value AR(2) test, p-value Hansen test, p-value Observations

Yes Yes 0.000 0.953 0.141 660

Yes Yes 0.000 0.829 0.916 660

Yes Yes 0.000 0.929 0.908 642

Yes Yes 0.000 0.888 0.948 635

Yes Yes 0.000 0.864 0.957 635

(8) 0.280*** (0.000) -0.001*** (0.000) -0.001 (0.001) 0.080*** (0.007) -0.007*** (0.001) -0.018*** (0.001) -0.007*** (0.003) -0.012*** (0.001) Yes Yes 0.000 0.797 0.901 531

A

Notes: This table reports system GMM estimates of the effect of too much credit market deepening on per capita GDP growth (constant 2010 US$). Private sector credit is the measure of credit market development. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. *** and ** indicate significance at the 1 and 5% level, respectively.

17

N U SC RI PT

(6) 0.954* (0.000) -0.007** (0.000) -0.0003 (0.003) 0.021 (0.017) -0.004** (0.002) -0.018*** (0.005)

(7) 0.570** (0.000) -0.003** (0.000) 0.003 (0.002) 0.024** (0.010) -0.003* (0.001) -0.017*** (0.003) -0.014*** (0.003)

Yes Yes 0.000 0.916 0.189 598

Yes Yes 0.000 0.608 0.228 576

PT

Log Gov. consumption

ED

M

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Table 3: Estimating the effect of domestic credit on economic growth Dependent variable: Per capita GDP growth (1) (2) (3) (4) (5) Domestic credit -0.018 0.221*** 0.216*** 0.034** 0.041*** (0.000) (0.000) (0.000) (0.000) (0.000) 2 Domestic credit -0.001*** -0.001*** -0.0001* -0.0002*** (0.000) (0.000) (0.000) (0.000) Log Trade 0.006*** 0.004*** 0.003*** (0.001) (0.001) (0.001) Log Life expectancy 0.074*** 0.054*** (0.008) (0.005) Population growth -0.004*** (0.000) Log Inflation

CC E

Log Per capita GDP, t-1

A

Year FE Country FE AR(1) test, p-value AR(2) test, p-value Hansen test, p-value Observations

Yes Yes 0.000 0.945 0.258 655

Yes Yes 0.000 0.981 0.853 655

Yes Yes 0.000 0.908 0.888 637

Yes Yes 0.000 0.784 0.947 630

Yes Yes 0.000 0.762 0.891 630

(8) 0.617*** (0.000) -0.003** (0.000) -0.002 (0.002) 0.063*** (0.009) -0.006*** (0.001) -0.015*** (0.003) -0.011*** (0.003) -0.012*** (0.001) Yes Yes 0.000 0.887 0.282 526

Notes: This table reports system GMM estimates of the effect of too much credit market deepening on per capita GDP growth (constant 2010 US$). Domestic credit is used to measure credit market development. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. ***, **, and * indicate significance at the 1, 5, and 10% level, respectively.

18

N U SC RI PT

Log Inflation

PT

Log Gov. consumption

(5) 0.447* (0.000) -0.003* (0.000) 0.001 (0.003) 0.037*** (0.009) -0.003*** (0.001)

(6) 1.544*** (0.000) -0.010*** (0.000) -0.004 (0.003) 0.017 (0.012) -0.002* (0.001) -0.013*** (0.004)

(7) 1.724*** (0.000) -0.011*** (0.000) -0.002 (0.003) 0.011 (0.012) -0.002 (0.002) -0.012 (0.004) -0.014 (0.005)

Yes Yes 0.000 0.992 0.249 635

Yes Yes 0.000 0.986 0.324 603

Yes Yes 0.000 0.716 0.478 581

ED

M

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Table 4: Estimating the effect of liquid liabilities on economic growth Dependent variable: Per capita GDP growth (1) (2) (3) (4) Liquid liabilities 0.109** 0.643*** 0.601*** 0.413* (0.000) (0.000) (0.000) (0.000) 2 Liquid liabilities -0.003*** -0.003*** -0.003 (0.000) (0.000) (0.000) Log Trade 0.002 0.002 (0.002) (0.003) Log Life expectancy 0.046*** (0.009) Population growth

Log Per capita GDP, t-1

CC E

Year FE Country FE AR(1) test, p-value AR(2) test, p-value Hansen test, p-value Observations

Yes Yes 0.000 0.823 0.370 657

Yes Yes 0.000 0.766 0.936 657

Yes Yes 0.000 0.840 0.975 642

Yes Yes 0.000 0.979 0.233 635

(8) 1.364*** (0.000) -0.008*** (0.000) -0.004 (0.003) 0.052*** (0.016) -0.007*** (0.002) -0.009** (0.004) -0.006 (0.004) -0.012*** (0.002) Yes Yes 0.000 0.971 0.690 531

A

Notes: This table reports system GMM estimates of the effect of too much credit market deepening on per capita GDP growth (constant 2010 US$). Liquid liabilities is used to measure credit market development. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. ***, **, and * indicate significance at the 1, 5, and 10% level, respectively.

19

N U SC RI PT

Table 5: Additional robustness checks I Dependent variable: Per capita GDP growth

Private sector credit2 Log Trade Log Life expectancy

CC E

Log Inflation

PT

Population growth

Log Gov. consumption

A

Year FE Country FE AR(1) test, p-value AR(2) test, p-value Hansen test, p-value Observations

Excluding SSA (3) -0.018*** (0.002) 1.525** (0.001) -0.009** (0.000) -0.009** (0.004) 0.092*** (0.031) -0.008*** (0.002) -0.008*** (0.004) -0.005 (0.005) Yes Yes 0.000 0.195 0.068 376

A

Excluding MENA (2) -0.016*** (0.004) 4.332*** (0.001) -0.022*** (0.000) -0.018*** (0.007) -0.030 (0.043) 0.002 (0.004) -0.011*** (0.004) -0.007 (0.007) Yes Yes 0.000 0.189 0.427 471

M

Private sector credit

ED

Log Per capita GDP, t-1

Excluding LAC (1) -0.012*** (0.002) 0.369** (0.000) -0.002** (0.000) 0.001 (0.004) 0.058*** (0.008) -0.008*** (0.002) -0.027*** (0.003) -0.007* (0.004) Yes Yes 0.000 0.068 0.406 332

Excluding ASIA (4) -0.017*** (0.003) 2.617*** (0.001) -0.015*** (0.000) -0.010** (0.005) 0.034 (0.025) -0.005** (0.002) -0.014*** (0.004) -0.021*** (0.007) Yes Yes 0.000 0.759 0.396 441

Excluding: Ch., Mala., S. Afr., Commodity Thailand Economy (5) (6) -0.007*** -0.011*** (0.003) (0.002) 0.557*** 0.979* (0.000) (0.000) -0.006*** -0.006* (0.000) (0.000) -0.0004 -0.002 (0.001) (0.006) 0.049*** 0.051*** (0.011) (0.017) -0.008*** -0.004 (0.001) (0.002) -0.020*** -0.018*** (0.002) (0.005) -0.007*** -0.011 (0.003) (0.007) Yes Yes Yes Yes 0.000 0.000 0.989 0.949 0.973 0.248 501 281

Services Economy (7) -0.012*** (0.004) 2.712* (0.001) -0.027** (0.000) 0.004 (0.008) 0.016 (0.041) -0.006** (0.002) -0.086** (0.033) 0.001 (0.011) Yes Yes 0.011 0.432 0.788 126

Industrial Economy (8) -0.092* (0.052) 4.865* (0.002) -0.017* (0.000) -0.032 (0.021) 0.130 (0.202) 0.147 (0.098) 0.015 (0.042) -0.038 (0.080) Yes Yes 0.257 0.471 1.000 124

Notes: This table reports system GMM estimates of the effect of too much credit market deepening on per capita GDP growth (constant 2010 US$). Private sector credit is used to measure credit market development. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. ***, **, and * indicate significance at the 1, 5, and 10% level, respectively.

20

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Table 6: Additional robustness checks II Dependent variable: Per capita GDP growth Low Income Countries Only Middle Income Countries Only (1) (2) (3) (4) (5) (6) Log Per capita GDP, t-1 -0.017*** -0.015*** -0.018*** -0.017*** -0.018*** -0.015*** (0.003) (0.002) (0.004) (0.002) (0.002) (0.002) Private sector credit 0.823** 0.642* (0.003) (0.000) Private sector credit2 -0.008* -0.004* (0.000) (0.000) Domestic credit 0.506* 0.902** (0.000) (0.000) Domestic credit2 -0.004* -0.004* (0.000) (0.000) Liquid liabilities 0.307** 1.331*** (0.000) (0.000) 2 Liquid liabilities -0.002** -0.008*** (0.000) (0.000) Log Trade 0.002 0.005* -0.005 -0.005 -0.003 -0.003 (0.006) (0.003) (0.004) (0.003) (0.003) (0.003) Log Life expectancy 0.050*** 0.069*** 0.059*** 0.033 0.015 0.154** (0.015) (0.007) (0.016) (0.032) (0.039) (0.074) Population growth -0.005** -0.007*** -0.006*** -0.008*** -0.007*** -0.006*** (0.002) (0.001) (0.002) (0.002) (0.001) (0.002) Log Inflation -0.022*** -0.022*** -0.018*** -0.014*** -0.010** 0.003 (0.004) (0.004) (0.002) (0.004) (0.005) (0.007) Log Gov. consumption -0.009 -0.006 -0.003 -0.017*** -0.025*** -0.017*** (0.006) (0.004) (0.007) (0.005) (0.006) (0.004) Year FE Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes AR(1) test, p-value 0.000 0.000 0.000 0.000 0.001 0.001 AR(2) test, p-value 0.319 0.493 0.499 0.643 0.556 0.857 Hansen test, p-value 0.402 0.689 1.00 0.023 0.137 0.548 Observations 243 268 272 259 258 259

A

CC

Notes: This table reports system GMM estimates of the effect of too much credit market deepening on per capita GDP growth (constant 2010 US$) in two subsamples. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. ***, **, and * indicate significance at the 1, 5, and 10% level, respectively.

21

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Table 7: Intermediating effect of democratic institutions using Political rights Dependent variable: Per capita GDP growth Private sector Domestic credit credit Liquid liabilities (1) (2) (3) Log Per capita GDP, t-1 -0.009*** -0.010*** -0.011*** (0.002) (0.001) (0.001) Private sector credit 0.996 (0.001) 2 Private sector credit -0.005 (0.000) Private sector credit × Political -2.755** rights (0.001) 2 Private sector credit × 0.017** Political rights (0.000) Political rights 0.075** -0.010** 0.032*** (0.037) (0.004) (0.011) Domestic credit 0.045 (0.000) Domestic credit2 0.00002 (0.000) Domestic credit × Political rights -0.406*** (0.000) Domestic credit2 × Political 0.002*** rights (0.000) Liquid liabilities 0.117 (0.000) 2 Liquid liabilities 0.001 (0.000) Liquid liabilities × Political -0.812*** rights (0.000) 2 Liquid liabilities × Political 0.002** rights (0.000) Controls Yes Yes Yes Year FE Yes Yes Yes Country FE Yes Yes Yes AR(1) test, p-value 0.000 0.000 0.000 AR(2) test, p-value 0.438 0.799 0.615 Hansen test, p-value 0.027 0.489 0.524 Observations 525 522 525

Notes: This table reports system GMM estimates of the intermediating effect of democratic institutions. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. *** and ** indicate significance at the 1 and 5% level, respectively.

22

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Table 8: Intermediating effect of democratic institutions using the Polity index Dependent variable: Per capita GDP growth Private sector credit Domestic credit Liquid liabilities (1) (2) (3) Log Per capita GDP, t-1 -0.009*** -0.011*** -0.008*** (0.000) (0.002) (0.002) Private sector credit 0.384*** (0.000) 2 Private sector credit -0.001 (0.000) Private sector credit × -1.208*** Polity (0.000) 2 Private sector credit × 0.006*** Polity (0.000) Polity 0.028*** 0.004 0.152*** (0.000) (0.011) (0.043) Domestic credit -0.148 (0.000) Domestic credit2 -0.003 (0.000) Domestic credit × Polity -0.280** (0.000) Domestic credit2 × Polity 0.005*** (0.000) Liquid liabilities 1.800** (0.001) 2 Liquid liabilities -0.006 (0.000) Liquid liabilities × Polity -4.475*** (0.001) 2 Liquid liabilities × 0.021*** Polity (0.000) Controls Yes Yes Yes Year FE Yes Yes Yes Country FE Yes Yes Yes AR(1) test, p-value 0.000 0.000 0.000 AR(2) test, p-value 0.931 0.991 0.786 Hansen test, p-value 0.384 0.306 0.710 Observations 453 453 456

Notes: This table reports system GMM estimates of the intermediating effect of democratic institutions. Robust standard errors in parenthesis are computed with the Windmeijer (2005) finite sample correction. AR(1) and AR(2) are, respectively, first and second order serial correlation tests. Hansen test checks instruments relevance. *** and ** indicate significance at the 1 and 5% level, respectively.

23

Appendix

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Dominican Republic Ecuador Egypt El Salvador Fiji Gabon Gambia Ghana Grenada

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Guatemala Guinea-Bissau Guyana Haiti Honduras India Indonesia Iran Ivory Coast Jamaica Jordan

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Vanuatu Venezuela Vietnam Zambia Zimbabwe

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Kenya Malawi Malaysia Mali Maldives Mauritius Mexico Morocco Niger Nigeria Pakistan Papua New Guinea Paraguay Peru Philippines Russia Samoa Sao Tome and Principe Senegal Seychelles Sierra Leone Solomon Islands South Africa Sri Lanka St. Kitts and Nevis St. Lucia St. Vincent and the Grenadines Sudan Suriname Syria Thailand Timor-Leste Trinidad and Tobago Togo Tonga Tunisia Turkey Uruguay

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List of countries Algeria Antigua Argentina Bangladesh Bahamas Barbados Belize Brazil Bolivia Cabo Verde China Colombia Comoros Cameroon Costa Rica Congo, DR Congo, Republic Dominica

24