Journal Issue
Share
Article

Democracy and Reforms

Author(s):
Antonio Spilimbergo, Paola Giuliano, and Prachi Mishra
Published Date:
July 2010
Share
  • ShareShare
Show Summary Details

I. Introduction

Political and economic freedoms go hand in hand … or do they not? This is one of the oldest questions in economics and in political science, which is still largely unanswered. This paper answers this question using a novel dataset on economic reforms, which is the most exhaustive in the literature in terms of countries, years, and range of reform coverage.

This question is still open because there are very good theoretical arguments and numerous examples as to why political freedom can either hinder or facilitate economic reforms. Take the historical examples of Chile under Pinochet, or South Korea under Park. In both cases, important economic reforms were undertaken under dictatorial regimes. The majority of the contemporary industrialized countries were not democracies when they took off (Schwarz, 1992). In most cases, East Asian economies did develop under undemocratic regimes. In addition to these historical examples from every region of the world and different historical periods, there are compelling theoretical reasons as to why less democratic regimes may favor economic reforms and growth.

A fully democratic regime can fall prey to interest groups, which put their goals before general well being. Sometimes, capitalists entrenched in their rent-seeking positions are the main opponents of economic reforms. In a newly independent country only a ‘benevolent dictator’ can shelter the institutions, avoid that the state becomes captive of any specific interest group, and allow the state to perform its function in an efficient way.1 In particular, interest groups can block reforms if there is uncertainty about the distribution of the benefits (Fernandez and Rodrik, 1991). In addition to pressure from interest groups, democracy can lead to excessive private and public consumption and lack of sufficient investment (Huntington, 1968); so dictatorial regimes can rely on financial repression to increase the domestic saving rate. Wages are typically higher under democracy (Rodrik, 1999). Several countries, including the Soviet Union and many East Asian countries, have been able to increase savings, and ultimately achieve high economic growth rate, thanks to a repressive political system and an attendant highly regulated financial system. In conclusion, do the historical examples and the theoretical arguments provide a compelling case against the role of democracy in fostering economic reforms? The answer to this question is a resounding no.

The alternative view that democracy often accompanies economic reforms is also based on strong theoretical arguments and solid empirical evidence. Secured property rights, as guaranteed by a democracy, are considered key to economic development. In general, dictators cannot credibly make commitments because of time-inconsistency; so no reform can be undertaken (McGuire and Olson, 1996). Autocratic rulers tend to be predatory, disrupting economic activity and making any reform effort meaningless; autocratic regimes have also an interest in postponing reforms and maintaining rent-generating activities for a restricted number of supporting groups. On the opposite, democratic rulers should be more sensitive to the interest of the public, and so more willing to implement reforms, which destroy monopolies in favor of the general interests. In addition to these theoretical arguments, there is strong empirical evidence that reforms are highly correlated with democracy.

The correlation between democracy and economic reforms is very strong both across time and in a cross section. Figure 1 shows the correlation over time between the indices of democracy (measured as polity IV and normalized between 0 and 1) and reform (all the indices are normalized between 0 and 1, with 0 corresponding to the least reformed and 1 to the most reformed) in the following six sectors (or areas)2—(i) domestic financial, (ii) capital account, (iii) product markets (electricity and telecommunications), (iv) agriculture, (v) trade (based on tariffs) and (vi) current account transactions—over time.3 All the cases show a strong correlation between democracy and regulation, with democracy usually preceding the deregulation process. Figure 2 shows that the correlation holds very strongly also when we take a cross section: countries that are more democratic are also more reformed. However, these correlations in themselves do not show that democracy necessarily causes economic reforms. The correlation could run in the opposite direction, or both democracy and economic reforms could be driven by a common third factor.

Figure 1.Regulation and Democracy over Time

Notes to Figure 1: This figure shows the correlation over time between the indices of democracy on the y-axis (measured as polity IV and normalized between 0 and 1) and reforms on the x-axis (all the indices are normalized between 0 and 1, with 0 corresponding to the least reformed and 1 to the most reformed) in the following eight sectors (or areas) – (i) domestic financial, (ii) capital account, (iii) product markets (electricity and telecommunications), (iv) agriculture, (v) labor, (vi) trade (based on tariffs) and (vii) current account transactions.

Figure 2.Democracy and Reforms, 2000

Notes: This figure shows the correlation in 2000 between the indices of democracy on the y-axis (measured as polity IV and normalized between 0 and 1) and reforms on the x-axis (all the indices are normalized between 0 and 1, with 0 corresponding to the least reformed and 1 to the most reformed) in the following eight sectors (or areas) – (i) domestic financial, (ii) capital account, (iii) product markets (electricity and telecommunications), (iv)agriculture, (v) labor, (vi) trade (based on tariffs) and (vii) current account transactions. The country codes and groups used in this figures are described in Tables A2 and A3.

The sharp contrast between these opposing views has left the question of the effects of democracy on economic reforms largely unanswered. The goal of this paper is to address again this issue using a novel database, which covers almost 150 countries, 6 sectors and spanning more than 40 years of data.

The main findings are that an increase in the quality of democratic institutions is significantly correlated with the adoption of economic reforms but there is no evidence of a feedback effect from economic to political liberalization. These results are robust to controlling for country, reform-specific effects and any possible interaction among them. Global reform waves and possible country-time varying determinants of reforms (including crises, reforms in neighboring countries, existence of compensation for losers, human capital and bureaucratic quality, and several political variables) do not weaken these results, which are also robust to using an instrumental variable strategy.

The remainder of the paper is organized as follows. Section 2 reviews the existing literature on economic reforms and democracy; Section 3 presents the data; Section 4 presents the results on the effects of democracy on reforms, controlling for other possible determinants of reforms and the possibility of reverse causality and omitted variables; Section 5 concludes.

II. Democracy and Reforms: Theory and Empirics

While there is a vast theoretical and empirical literature that considers the determinants of economic reforms in general, there is scarce evidence, particularly empirical, on the relationship between democracy and reforms.4

Economic theory does not give a clear answer on whether political liberalizations favor or hinder economic reforms or if the relationship could go both ways. Democratic regimes could lead to more reforms if reforms create more winners than losers (Giavazzi and Tabellini, 2005). Democratically elected governments may also have greater legitimacy to implement and sustain policies bearing high short-term costs; similarly institutional changes—e.g., strengthening an independent legal system or a professional civil service required to ensure political freedom and democracy—could lead also to successful market reforms. Finally, democracy could create an environment conducive to economic reforms by limiting rent-seeking and putting in place a system of checks and balances (Dethier, Ghanem and Zoli, 1999).

Alternatively, political liberalization could lead to less economic reforms if the electoral system creates a pivotal voter with veto power. For instance, it has been argued that Chile in the late 70s and the 80s implemented several forward-looking economic reforms because the military regime did not have to respond to a short-sighted electorate. At the same time, it has been argued that Costa Rica has been a laggard in economic reforms because the democratic system gives veto power to groups that can lose from reforms. Democratic legislators are more likely to adopt time-inconsistent policies (Quinn 2000). In fact, uncertainty about the impact of economic reforms at the individual level could also lead a rational electorate to vote against reforms even if they are known ex ante to benefit a majority of them (Fernandez and Rodrik, 1991).

The theoretical predictions about the feedback effect from economic reforms to democratization are ambiguous as well. For example, economic liberalizations could be associated with higher quality of democratic institutions if they increase the power of the middle class (Rajan and Zingales, 2003). On the other hand, liberalization could lower democracy through increases in income inequality and the associated political strife and violence (Quinn, 1997, Dixon and Boswell, 1996).

On the empirical side, only a few empirical papers have looked at the relationship between democracy and reforms. Among the available evidence, Giavazzi and Tabellini (2005) study the feedback effects between economic and political liberalizations. Economic liberalization is defined as the event of becoming open, where openness is defined as in Wacziarg and Welch (2008). Political liberalization is the event of becoming a democracy; where democracy is defined by strictly positive values of polity2. Using a panel of 140 countries over 1960–2000 (with country and year fixed effects), Giavazzi and Tabellini (2005) find evidence of a positive and significant relationship between democratizations and trade reforms; they find that the feedback effect could run in both directions although the causality is more likely to run from political to economic reforms. In comparison, we find little evidence of feedback effects from reforms to democracy.5 Similarly, Persson (2005) shows that the forms of democracy (parliamentary, proportional and permanent ones) are important in explaining variation in trade reforms (measured by the Wacziarg and Welch index) and an index protection of property rights.6Amin and Djankov (2009) show that democracy (measured by Freedom House or PolityIV scores) is good for micro-reforms (as defined in the World Bank’s Doing Business Database).7Eichengreen and Leblang (2008) find evidence of a positive two-way relationship between democracy and globalization defined as trade and capital account liberalization.8 They, however, find that these effects are not uniform across time and space.

Quinn (2000) examines the relationship between democracy and international financial liberalization. He measures international financial regulation through changes in current and capital account openness created using the Exchange Arrangements and Exchange Restrictions from the IMF. Democracy is measured by changes in polity2. Quinn uses both panel data techniques and individual country VARs for 40–50 countries over 1950–97 and finds evidence that democracies liberalize international finance, especially capital accounts. Unlike this paper, he also finds evidence of feedback effects from financial liberalization to democratizations whereby capital account liberalization is associated with decreases in democracy 6 to 15 years later.9 Finally, Olper, Falkowski and Swinnen (2009) study the effect of regime transitions from autocracy to democracy on agricultural policy distortions, measured by indicators of government transfers to the agriculture sector. They find that while agriculture protection increases after a country’s transition to democracy, there is no effect when the regime shifts from democracy to autocracy.

Other papers examine the relationship between economic and political liberalizations in the context of post-communist countries. For example, Fidrmuc (2003) in a sample of 25 transition countries over 1990-2000 finds a positive relationship between the indices of liberalization and democracy. Liberalization is measured by an average of various reform indicators developed by the European Bank for Reconstruction and Development covering privatization, governance and enterprise restructuring, price liberalization, trade and foreign exchange, competition policy, and banking and securities markets. Democracy is measured by an average of the indicators of political rights and civil liberties reported by the Freedom House. In a similar vein, Dethier, Ghanem, and Zoli (1999) also find that political freedom and civil liberties facilitated economic liberalization in the 25 post-communist countries between 1992 and 1997. Milner and Mukerjee (2009) find evidence that democracy fosters trade and capital account liberalization, but also that the impact of openness of democracy is quite weak in developing countries. Grosjean and Senik (forthcoming) using a survey conducted in 2006 by the European Bank for Reconstruction and Development and the World Bank in 28 post-transition countries find a significant effect of democracy (measured by the Freedom House democracy score) on market liberalization, but no evidence of a feedback effect. In addition to the statistical analysis, some papers (Bates and Krueger, 1993) have focused on case studies. This approach takes into account the complexity and the country specificity of the interaction between democracy and economic reforms.

To summarize, while there are many theoretical predictions about the relationships between political and economic liberalizations, empirical evidence on the subject is limited to reforms in particular sectors, in particular international trade and finance, micro-reforms, or specific countries over a short period.

Our study is the first one to combine a comprehensive coverage of reforms in different sectors, a significant coverage of countries and a long time period. In particular, the dataset used in this paper spans six sectors, and both developing and developed countries from the 1960 up until 2004.

III. Data

A. Data on reforms

Our analysis is based on a completely new and extensive dataset, compiled by the Research Department of the IMF, describing the degree of regulation for a sample of 150 industrial and developing countries. The new dataset thus has significant advantages over existing data sources, which cover a narrower set of reforms and countries. Reform indicators cover six sectors, including both financial and real sectors. Financial sector reform indicators include reforms pertaining to domestic financial markets and the external capital account, while real sector structural reform indicators include measures of product and agriculture markets, trade, and current account reforms. Each indicator contains different sub-indices summarizing different dimensions of the regulatory environment in each sector. The sub-indices are then aggregated into indices and normalized between 0 and 1. We construct all the measures of reform in each sector so that higher values represent greater degrees of liberalization.

Table 1 presents a brief definition and sources of the reform indicators used in this paper. IMF (2008) describes all data sources and full details of the construction of the indicators.

Table 1.Reform Indicators
Financial sector
The index of domestic financial liberalization is an average of six subindices, five related to banking and one related to the securities market.
BankingThe banking subindex is an average of the following 5 indicators: (i) interest rate controls, such as floors or ceilings; (ii) credit controls, such as directed credit and subsidized lending; (iii) competition restrictions, such as limits on branches and entry barriers in the banking sector, including licensing requirements or limits on foreign banks; (iv) the degree of state ownership; and (v) the quality of banking supervision and regulation, including power of independence of bank supervisors, adoption of Basel capital standards, and a framework for bank inspections.
Securities marketThe sixth subindex relates to securities markets and covers policies to develop domestic bond and equity markets, including (i) the creation of basic frameworks such as the auctioning of T- bills, or the establishment of a security commission; (ii) policies to further establish securities markets such as tax exemptions, introduction of medium- and long-term government bonds to establish a benchmark for the yield curve, or the introduction of a primary dealer system; (iii) policies to develop derivative markets or to create an institutional investor’s base; and (iv) policies to permit access to the domestic stock market by nonresidents. The subindices are aggregated with equal weights. Each subindex is coded from zero (fully repressed) to three (fully liberalized).
Data sourcesAbiad and others (2008), following the methodology in Abiad and Mody (2005), based on various IMF reports and working papers, central bank websites, and others.
Coverage1973–2005; Minimum and maximum number of countries in any year are 72 and 91 respectively.
Capital account
Qualitative indicators of restrictions on financial credits and personal capital transactions of residents and financial credits to nonresidents, as well as the use of multiple exchange rates. Index coded from zero (fully repressed) to three (fully liberalized).
Data sourcesAbiad and others (2008), following the methodology in Abiad and Mody (2005), based on various IMF reports and working papers, central bank websites, and others.
Coverage1973–2005; Minimum and maximum number of countries in any year are 72 and 91 respectively.
Product markets
The electricity indicators capture (i) the degree of unbundling of generation, transmission, and distribution; (ii) whether a regulator other than government has been established; and (iii) whether the wholesale market has been liberalized; and (iv) privatization. Each subindex is coded from 0 to 1 or from 0 to 2.
ElectricityThe telecommunication indicator captures (i) the degree of competition in local services; (ii) whether a regulator other than government has been established; (iii) the degree of liberalization of interconnection changes; and (iv) privatization. Each subindex is coded from 0 to 1 or from 0 to 2.
TelecommunicationElectricity: Based on various existing studies and datasets as well as national legislation and other official documents.
Data sourcesTelecommunication: Based on IMF commodities data, various existing studies and datasets, and national legislation and other official documents.
Coverage1960–2003; Minimum and maximum number of countries in any year are 106 and 108 respectively.
Agriculture market
The index captures intervention in the market for the main agricultural export commodity in each country. The index can take four values (i) zero (public monopoly or monopsony in production, transportation, or marketing, e.g., export marketing boards); (ii) one-third (administered prices); (iii) two-thirds (public ownership of relevant producers or concession requirements); and (iv) one (no public intervention).
Data sourcesBased on IMF commodities data, various existing studies and datasets, and national legislation and other official documents.
Coverage1960–2003; Minimum and maximum number of countries in any year are 96 and 104respectively.
Trade
Trade liberalization is defined by looking at average tariff rates, with missing values extrapolated using implicit weighted tariff rates. Index normalized to be between zero and unity: zero means the tariff rates are 60 percent or higher, while unity means the tariff rates are zero.
Data sourcesVarious sources, including IMF, World Bank, WTO, UN, Clemens and Willamson, 2004.
Coverage1960-2005; Minimum and maximum # of countries in any year are 47 and 142 respectively.
Current account
Current account liberalization is defined with an indicator describing how compliant a government is with its obligations under the IMF’s Article VIII to free from government restriction the proceeds from international trade in goods and services. The index represents the sum of two subcomponents, dealing with restrictions on trade in visibles, as well as in invisibles (financial and other services). It distinguishes between restrictions on residents (receipts for exports) and on nonresidents (payments for imports). Although the index measures restrictions on the proceeds from transactions, rather than on the underlying transactions, many countries in practice use restrictions on trade proceeds as a type of trade restriction. The index is scored between zero and 8 in half-integer units, with 8 indicating full compliance.
Data sourcesBased on the methodology in Quinn (1997) and Quinn and Toyoda (2007), drawing on information contained in the Fund’s AREAER database (Annual Reports on Exchange Arrangements and Exchange Restrictions).
Coverage1960–2005; Minimum and maximum number of countries in any year are 50 and 65 respectively.
This table presents brief description of the reform indicators used in the paper. For a full description of all variables, data and sources refer to IMF (2008).
This table presents brief description of the reform indicators used in the paper. For a full description of all variables, data and sources refer to IMF (2008).

a. Financial sector reforms in the domestic financial market

The dataset contains two measures of financial sector reforms, one for the domestic financial sector and the other regarding the extent of capital account liberalization. The domestic financial sector liberalization indicator in turn includes measures of securities markets and banking sector reforms. The securities markets subindex assesses the quality of the market framework, including the existence of an independent regulator and the extent of legal restrictions on the development of domestic bond and equity markets. The banking subindex captures reductions or removal of interest rate controls (floors or ceilings), credit controls (directed credit and subsidized lending), competition restrictions (limits on branches and entry barriers in the banking market, including licensing requirements or limits on foreign banks), and public ownership of banks. The banking index also captures a measure of the quality of banking supervision and regulation, including the power and independence of bank supervisors, the adoption of Basel capital standards, and the presence of a framework for bank inspections.

b. Capital account liberalization

The second measure of reform in the financial sector pertains to the extent of the external capital account liberalization. The index contains information on a broad set of restrictions including, for example, controls on external borrowing between residents and non-residents, as well as approval requirements for foreign direct investment (FDI).

c. Product market reforms

Turning to the real sector, the product market indicator covers the degree of liberalization in the telecommunication and electricity markets, including the extent of competition in the provision of these services, the presence of an independent regulatory authority, and privatization.

d. Agricultural market reforms

The agricultural sector indicator captures intervention in the market for the main agricultural export commodity in each country. It measures the extent of public intervention in the market going from total monopoly or monopsony in production, transportation or marketing (i.e., the presence of marketing boards), the presence of administered prices, public ownership of relevant producers or concession requirement to free market.

e. Trade reforms

Trade reforms are captured by using two different indicators: one based on tariffs and the other measuring the extent of current account liberalization. The indicator based on tariff liberalization is meant to capture distortions in international trade and is measured by average tariffs.

f. Current account liberalization reforms

The second indicator for measuring reform in the trade sector broadly measures the extent of current account liberalization. It captures the extent to which a government is compliant with its obligations under the IMF’s Article VIII to free from government restriction the proceeds from international trade in goods and services.

Additional details on the sources and specifics of each indicator can be found in IMF (2008) and Table 1.

A. Aggregation and normalization

For each of our six sectors, we construct an aggregate index by averaging the sub-indices for that particular sector (for the cases in which we do have multiple sub-indices, like product market or the financial sector). Each sectoral indicator is then normalized between 0 and 1, where 1 indicates a higher degree of liberalization. “Reform” in any sector is then defined as an annual change in the index. Table 2 reports the pair wise correlations between different types of reforms. Financial sector, trade, current, and capital account reforms are strongly correlated among themselves, and less so with agricultural and product market reforms (with the exception of the financial sector reform which is strongly correlated to product market reforms). Overall the correlations indicate that once the process of reform in a country starts, it probably spreads over to several sectors.10 We run most of our regressions at the sector-country and year level; however as one of our robustness checks we also aggregate the six reform indicators using a principal component analysis.

Table 2.Correlation between Reform Indicators
AgricultureProd. MktTradeCap. Acc.Curr. Acc.Finance
Agriculture1
Prod. Mkt0.30***1
Trade0.32***0.35***1
Cap. Acc.0.40***0.46***0.57***1
Curr. Acc.0.42***0.47***0.63***0.77***1
Finance0.44***0.63***0.62***0.73***0.71***1

denotes statistical significance at the 1 percent level.

denotes statistical significance at the 1 percent level.

B. Other data

Democracy is measured using the standard, well-established measure of democracy taken from the Polity IV database. In particular, we use the combined polity2 index ranging from -10 to 10 (-10=high autocracy; 10=high democracy).11 We normalize the index so that 1 indicates the most democratic country and 0 the least democratic regime.

We also include in our specifications the following controls:

  • Initial level of regulation (as measured by the lagged level of the regulation index): this variable can be a proxy for important incentives in favor and against the implementation of structural reforms. Excessive government regulation and/or market failures may be perceived as more costly when the economy is least reformed. At the same time, the beneficiaries of existing large rents may oppose reforms.
  • Economic crisis: According to a widely held view, economic crises foster economic reforms by making evident the cost of stagnation and backwardness. The opposite view maintains that it is easier to implement reforms during periods of economic growth when potential losers can find other opportunities in a booming economy or when countries become richer and have more resources to compensate the losers. In order to test this hypothesis, we use several measures of crisis: a dummy equal to 1 if the country is experiencing inflation larger than 40 percent in that year, a measure for recession (as summarized by a dummy indicating negative growth in per-capita GDP), terms of trade shocks, and banking and debt crisis.12
  • Public expenditures/GDP and real devaluation: Compensation schemes can offset costs associated with reforms. A large government may compensate losers from reforms than a very lean government with a small budget. We use public expenditures/GDP as a proxy of the size of social safety nets. As an alternative measure of compensation, we also control for real devaluation, which could promote exports and therefore help compensate losers from reforms.13
  • Human capital and effectiveness of bureaucracy could also facilitate reforms (Besley and Personn, 2007). We use enrollment in tertiary education from Barro and Lee (2001) as a measure of human capital and bureaucratic quality from the International Country Risk Guide.14
  • Reforms in neighboring countries or in trading partners may affect the adoption of domestic reforms through peer pressure and imitational effects. We use the weighted average of reforms in neighboring countries, where the weights are given by two concepts of distance defined by geography and trade.15
  • The ideology of the ruling government and the form of government may determine the adoption of reforms.16 We capture the ideological orientation of the executive with the indicator left, which is equal to 1 if the executive belongs to a party of the left and 0 if it belongs to a right-wing, centrist or other party. The form of government is proxied by the variable presidential, which takes the value of 1 if the system is directly presidential and 0 if the president is elected by the assembly or parliamentary. The source for these two variables is the Database of Political Institutions from the World Bank.17

Table A1 provides the summary statistics for the key variables used in the empirical analysis.

IV. Empirical strategy

The unit of analysis is a sector-country-year observation (there are 6 sectors, 150 countries, and 45 years); the resulting dataset is a panel of 20,123 observations. We define reform as a change over time in the index of regulation for each of the six sectors, s, in country c at time t:

Our baseline specification is as follows:

where

δs, γc and χt are sector, country, and year fixed effects, respectively, and Xct-1 are country-specific and time-varying controls to be described below. δsγc and δsχt represent the interactions between country and sector; and sector and time fixed effects respectively. We also control for the lagged level of the index to identify the existence of convergence toward some possible country specific levels of regulation.

The dependent variable (reform) is highly persistent; for this reason the error terms in specification (1) may also exhibit serial correlation.18 We allow for first-order serial correlation in the error terms: εct = ρεct-1+ uct.19 In specifications (2) and (4), we allow the serial correlation coefficient in the error term to be country-sector specific.20 In specification (3), we allow the serial correlation coefficient to be country specific. In Table 7b we also test the robustness of our results by clustering the error terms at the country level.

Our first specification includes only sector, country, and time fixed effects (Table 3, column 1). The coefficient on the lagged level of the index is negative and significant at the 1 percent level, indicating convergence toward country specific levels of regulation. The coefficient on the lagged level of democracy is significant at the 1 percent level. The magnitude of the estimated effect implies that a one standard deviation increase in the democracy index explains 7 percent variability in reforms. In addition, moving to a complete democracy in the long-run is associated with a 0.22 (=βα) increase in the index of reform (using the coefficients of column 1).

Table 3.Reforms and Democracy
Dependent variable: reform in country, sector, year
(1)(2)(3)(4)
Lagged democracy0.016***0.017***0.033***0.017***
Lagged level of index-0.073***-0.124***-0.047***-0.131***
Country FEYYYY
Sector FEYYYY
Year FEYYYY
Country*Sector FEYY
Sector*Year FEYY
Observations20,12319,52120,07119,521
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term.***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term.***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

We then add country-sector specific effects, and sector-year specific effects and both of them (column 2, 3 and 4 respectively). The interactions between country and sector fixed effects take into account that reforms are inherently different across countries, e.g., trade sector reforms in India have different characteristics than banking reforms in Brazil (Specification 2). The interactions between sector and year effects account for the possibility of global reform waves across all countries (Specification 3). Specification 4 is the most demanding because it includes all the individual fixed effects and possible two-way interactions. Notice that we cannot control for country-time effects, since the main variable of interest, which is democracy, tends to be country-time varying. The results are very similar across specifications. The magnitude of the coefficients on the democracy variable ranges from 0.02 to 0.03 in columns 2-4.

The results in Table 3 show that the correlation between (past) democracy level and the adoption of reforms is not driven by country or sector-fixed characteristics or by the fact that there was a worldwide movement toward reforms and democracy, or any interactions between country-sector and sector-time fixed characteristics.

If the correlation between economic reforms and democracy is not due to spurious correlation owing to a common trend, could it be driven by other country-time varying omitted variables? The next subsection checks whether this correlation is robust to the inclusion of several variables, which (current theories suggest) may explain both economic reforms and democracy, i.e., the possible bias deriving from country-sector-time varying omitted variables.

A. Additional controls

Reforms may be triggered by a wide range of factors other than democracy. Following the theoretical literature reviewed above, in Table 4 we control for the following possible determinants of reforms: a measure of crisis (a dummy equal to 1 if the country experiences inflation larger than 40 percent)21, public expenditure/GDP and real devaluation, human capital and bureaucratic quality, reforms in neighbors, and political variables (columns 1-5).

Table 4.Reforms and Democracy: Robustness to Controls
Dependent variable: reform in (country, sector, year)
(1)(2)(3)(4)(5)(6)
Lagged democracy0.011***0.014**0.048***0.011***0.014***0.045***
Lagged level of index-0.149***-0.205***-0.401***-0.135***-0.173***-0.412***
Lagged crisis (inflation>40)-0.005*-0.003
Lagged real devaluation0.007-0.009
Lagged public expenditure to GDP0.000-0.001*
Lagged bureaucratic quality0.0030.006*
Lagged tertiary enrollment0.006-0.003
Lagged reforms in geographical neighbor0.055***0.044
Lagged dummy for left0.003-0.004
Lagged dummy for presidential-0.0010.006
Observations16,6489,6275,56417,80414,1754,784
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. All regressions control for country sector, year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. All regressions control for country sector, year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

In many countries, difficult fiscal situations were associated with monetization of deficit and high inflation. For this reason, we take hyperinflation (defined as inflation larger than 40 percent) as an indicator of (unresolved) fiscal crisis. Not surprisingly, episodes of hyperinflation appear to reduce the probability of reforming (Column 1), although the effect is small and significant only at the 10% level. Moreover, when we include all the controls in column (6), only initial structural conditions and democracy appear to be significant in explaining reforms22. Bureaucratic quality and public expenditure/GDP also appear to matter but with coefficients which are low and only significant at the 10% level.

Of all the variables, reforms in neighboring countries appear to spur domestic reforms.23 This result, which extends the results of IMF (2004) on OECD countries, is also in line with Buera, Monge, and Primiceri (2008), who find a spillover effect from beliefs in neighboring countries. The inclusion of these variables does not decrease the significance of democracy in explaining the adoption of reforms.

B. Endogeneity

Another source of bias derives from the fact that reforms themselves may have an effect on democracy. In order to deal with this issue we have two approaches: 1) we use instrumental variables, and 2) we check if reforms cause democracy (in the final section of the paper).

While an ideal source of exogenous variation of democracy is difficult to find, we use democracy in neighboring countries as an instrument where we introduce the concept of political distance to define the neighbors. The idea behind this instrument is that democracy in political allies has influence on domestic democracy but no direct impact on a country’s ability to reform. For instance, the political alliance between the U.S. and Western Europe had surely an effect on democracy in Western Europe but not a direct effect on the reform level in Europe.24

Table 5A shows the regressions using lagged democracy in political neighbors as an instrumental variable. As expected, the first-stage F statistics confirm the relevance of democracy in neighbors in promoting the democratic process in the domestic economy (the first stage of our IV regression is presented in Table 5B). The results in our second stage show that, consistent with the OLS specification, there is evidence for a strong and positive effect of democracy on reforms. Notice that the estimated effect is not statistically significant in the specification which includes all the controls (column 1c). The magnitude of the estimated effect is, however, not significantly different from Column 1b, which uses a larger sample and a restricted set of controls suggesting that the statistical insignificance in specification 1c is likely to be driven by the large standard errors from the smaller sample. The regression in column 1d, where the sample is the same as column 1c but without the inclusion of controls, indeed confirms that this is the case.

Table 5a.Reforms and Democracy: Instrumental Variables Second Stage
Dependent variable: reform in (country, sector, year)
(1a)(1b)(1c)(1d)
Lagged democracy0.078***0.151***0.190.141
Lagged level of index-0.135***-0.180***-0.281***-0.281***
Lagged crisis (inflation>40)-0.005-0.01
Lagged real devaluation0.0080.003
Lagged public expenditure to GDP0.000-0.001
Lagged bureaucratic quality0.004
Lagged tertiary enrollment0.023
Lagged reforms in geographical neighbors0.0560.053
Lagged dummy for left-0.001-0.001
Lagged dummy for presidential0.029**0.049
Observations18,97010,0075,2445,244
First stage F-stat764.59229.0936.4750.77
p-value of F test0.0000.0000.0000.000
Note. Lagged democracy is instrumented by (lagged) democracy in neighboring countries. All regressions control for country sector, year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. Lagged democracy is instrumented by (lagged) democracy in neighboring countries. All regressions control for country sector, year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Table 5b.Reforms and Democracy: Instrumental Variables First Stage
Dependent variable: reform in (country, sector, year)
(1a)(1b)(1c)(1d)
Lagged democracy in neighboring countries0.014***0.009***0.005***0.006***
Lagged level of index0.022-0.016-0.008-0.005
Lagged crisis (inflation>40)-0.0150.013
Lagged real devaluation-0.0110.020**
Lagged public expenditure to GDP0.001-0.002
Lagged bureaucratic quality-0.003
Lagged tertiary enrollment-0.199***
Lagged reforms in geographical neighbors0.0520.198***
Lagged dummy for left0.001-0.009*
Lagged dummy for presidential-0.226***-0.238***
Observations18,97010,0075,2525,252
Note. All regressions control for country sector, year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. All regressions control for country sector, year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

C. Regressions by sector

Does democracy have a differential effect across sectors? Alternatively, are the results presented above driven by a particular sector? We explore this possibility by looking at the impact of democracy on different sectors. The results in Table 6 show that, with the exception of product markets (electricity/telecommunication), democracy promotes reforms in all other sectors, with the estimated effect being statistically significant at the one percent level in all sectors. The fact that democracy is not significant in explaining reforms in electricity/telecommunications may be due to the fact that global waves (which are captured by year effects) drive the adoptions of reforms in these sectors.

Table 6.Reforms and Democracy: By Reform
Dependent variable: reform in (country, year)
(1)(2)(3)(4)(5)(6)
FinanceCap. Acc.Prod. MktAgricult.TradeCurr. Acc.
Lagged democracy0.067***0.182***-0.0260.202***0.075***0.179***
Lagged level of index-0.379***-0.521***-0.278***-0.558***-0.420***-0.554***
Lagged crisis (inflation>40)0.019*-0.042*0.006-0.0160.0020.021
Lagged real devaluation-0.0070.024-0.01-0.039*0.006-0.012
Lagged public expenditure to GDP0.0020.0020.0010.000-0.003***-0.001
Lagged bureaucratic quality0.014***0.022*0.014*-0.010.012**0.021**
Lagged tertiary enrollment-0.0380.0570.109-0.145-0.0070.053
Lagged reforms in geographical neighbors-0.010.257*-0.188-0.1470.228**0.013
Lagged dummy for left-0.003-0.008-0.006-0.005-0.0010.000
Lagged dummy for presidential0.037*0.0260.0410.0420.046**-0.005
Observations786786888807857660
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. All regressions control for country and year fixed effects. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. All regressions control for country and year fixed effects. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

We prefer the general specification that encompasses all sectors in order to maximize the number of observations so that we can control for country, reform, and year fixed effects and (most importantly) their interactions as shown in Table 3.

D. Other robustness checks

In Table 7a, we carry out several robustness checks.25 In columns 1a–1b and 2a–2b, the sample is restricted to communist and developing countries respectively (we estimate two regressions for each subsample with and without the inclusion of controls). In columns 3a-3b, we use a zero-one definition of democracy (as in Giavazzi and Tabellini, 2005), where democracy=1 if polity2 has positive values. Using a zero-one definition of democracy does not change our results (the results are weaker when we include all the controls, but this is driven by the fact that the sample size is much smaller, in column 3c we indeed show that the impact of democracy on reform on the restricted sample but without the inclusion of controls is also not significant). Table 7b shows that the results are also robust to different standard error corrections (instead of explicitly allowing for an AR(1) term in the model, the standard errors are clustered at the country-reform level) (column 1). Reforms in trading partners (column 2) and reforms in other sectors (column 3) also do not alter our main conclusion, and the results are also robust to a variety of crisis definitions (negative per-capita GDP growth, banking and debt crises and terms-of-trade shocks-columns 4 to 7). We also find very similar results when we follow Giavazzi and Tabellini (2005) and include a political reform variable defined as a dummy taking the value of 1 in the years after democratization (where democratization is defined as the event of becoming a democracy, given that a country was not a democracy in the previous year)26.

Table 7a.Reforms and Democracy: Robustness Checks
Dependent variable: reform in (country, sector, year)
(1a)(1b)(2a)(2b)(3a)(3b)(3c)
Lagged democracy0.007**0.070***0.014***0.063***
Lagged level of index-0.130***-0.463***-0.149***-0.565***-0.135***-0.495***-0.497***
Democracy dummy (polty2>0)0.010***0.0130.013
Lagged crisis (inflation>40)-0.002-0.002-0.0020.009
Lagged real devaluation-0.006-0.009-0.009
Lagged public expenditure to GDP0.000-0.001-0.001
Lagged bureaucratic quality0.009**0.0070.010**
Lagged tertiary enrollment-0.0220.0240.011
Lagged reforms in geographical neighbors0.0630.0120.025
Lagged dummy for left-0.005-0.003-0.004
Lagged dummy for presidential0.0100.023-0.007
Observations16,8164,34715,1883,33819,5214,7844,784
Note. In Columns 1a-1b and 2a-2b, the sample is restricted to communist and developing countries respectively. In Columns 3a-3b, we use a zero-one definition of democracy (as in Giavazzi and Tabellini, 2005), where democracy=1 if polity2 has positive values. The estimators are within estimators and allow for first-order autoregressive disturbance term. All regressions control for country and year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. In Columns 1a-1b and 2a-2b, the sample is restricted to communist and developing countries respectively. In Columns 3a-3b, we use a zero-one definition of democracy (as in Giavazzi and Tabellini, 2005), where democracy=1 if polity2 has positive values. The estimators are within estimators and allow for first-order autoregressive disturbance term. All regressions control for country and year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Table 7b.Reforms and Democracy: Additional Robustness Checks
Dependent variable: reform in (country, sector, year)
(1)(2)(3)(4)(5)(6)(7)(8)(9)
Lagged democracy0.016***0.065***0.062***0.061***0.066***0.066***0.069***0.011***
Lagged level of index-0.125***-0.495***-0.510***-0.479***-0.494***-0.523***-0.520***-0.128***
Lagged crisis (inflation>40)-0.003-0.001
Lagged real devaluation-0.009-0.008-0.007-0.009-0.011-0.010
Lagged public expenditure to GDP-0.001-0.0010.000-0.001-0.001-0.001
Lagged bureaucratic quality0.010**0.009**0.010***0.010**0.007*0.008**
Lagged tertiary enrollment0.0060.0110.0000.0070.0100.010
Lagged reforms in geographical neighbors0.0380.0290.0360.0260.0630.058
Lagged dummy for left-0.004-0.004-0.005-0.005-0.007-0.008
Lagged dummy for presidential0.0000.0020.0010.002-0.0010.003
Lagged reform in trade neighbors-0.043
Lagged average reform in other sectors0.122***
Lagged crisis (growth<0)-0.007**
Terms of trade shocks-0.004
Lagged crisis (debt)0.010
Lagged crisis (bank)-0.016***
Political reform - Giavazzi and Tabellini (2005)0.015***
Observations20,1234,7844,7844,7694,7844,2654,26521,29219,521
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. In Column (1), instead o f explicitly allowing for an AR(1) term in the model, the standard errors are clustered at the country-reform level. In Column (8), political reform is a dummy variable taking a value of 1 in the years after democratization. Democratization is defined as the event of becoming a democracy, given that a country was not a democracy in the previous year. All regressions control for country and year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. In Column (1), instead o f explicitly allowing for an AR(1) term in the model, the standard errors are clustered at the country-reform level. In Column (8), political reform is a dummy variable taking a value of 1 in the years after democratization. Democratization is defined as the event of becoming a democracy, given that a country was not a democracy in the previous year. All regressions control for country and year fixed effects and country*sector and sector*year interactions. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

By including the lagged level of reform, the specifications so far have assumed that there is (conditional) convergence in the reform adoption.27 However, unlike growth regressions, there is no theoretical reason why we should expect convergence in the level of regulation. In order to test if our results depend on this assumption, we replicate the specification in Table 3 without the lagged reform index using the following specification:

Column (9) in Table 7b reports the results from estimating Equation (2). The estimated coefficient on lagged (democracy) is positive and statistically significant at the 1 percent level. The magnitude of the estimated coefficient (β= 0.011) is smaller than in Table 3.28 This coefficient, however, is not exactly comparable to the coefficient in the previous regressions in Table 3 given that the magnitude of the estimated coefficient on democracy in this regression can be interpreted only as the effect of democracy on the rate of adoption of structural reforms rather than on the steady-state level.29

Finally, in Table 8, we find some evidence for non-linear effects of democracy on reforms: the more democratic the country is initially, the easier it is to reform.30

Table 8.Reforms and Democracy: Flexible Functional Form
Dependent variable: reform in (country, sector, year)
(1)(2)(3)(4)
Lagged democracy (polity2<0.15)0.0140.011-0.0050.014
Lagged democracy (0.15<=polity2<0.75)0.012**0.0090.036***0.01
Lagged democracy (polity2>=0.75)0.015***0.016***0.038***0.016***
Lagged level of index-0.073***-0.129***-0.036***-0.135***
Country FEYYYY
Sector FEYYYY
Year FEYYYY
Country*Sector FEYY
Sector*Year FEYY
Observations20,12319,52119,98019,521
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

E. The feedback effect

In this section, we check whether economic reforms could foster the democratic process in a country. Giavazzi and Tabellini (2005) find evidence of a possible feedback effect from economic liberalization (when looking only at the trade sector) and the democratic process. We test for the possibility of a feedback effect from reforms to democracy by estimating the following regression

Overall, we find that democracy promotes reform, while we do not find any evidence that reforms promote the democratic process (Table 9a).31 Our results therefore do not support a reverse causality story.32 We also repeat the same exercise reform by reform and find little evidence of feedback for most reforms with the exception of reforms in domestic financial sector and current account. Reforms in these sectors seem to reduce the probability of democratization. The results are qualitatively similar to Giavazzi and Tabellini (2005), who argue that for trade reforms, “causality is more likely to run from political to economic liberalizations rather than vice versa”.

Table 9a.Reforms and Democracy: Feedback Effects
Dependent variable: change in democracy (country, year)
(1)(2)(3)(4)
Lagged democracy-0.135***-0.157***-0.112***-0.157***
Lagged reform in (country, sector, year)-0.009-0.0110.004-0.010
Country FEYYYY
Sector FEYYYY
Year FEYYYY
Observations19,04318,44119,26218,441
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Table 9b.Reform and democracy: Feedback Effects
Dependent variable: change in democracy (country, year)
(1)(2)(3)(4)(5)(6)
FinanceCap. Acc.Prod. MktAgricult.TradeCurr. Acc.
Lagged democracy-0.177***-0.177***-0.161***-0.167***-0.181***-0.167***
Lagged reform in (country, year)-0.088**-0.016-0.0180.0170.011-0.038*
Country FEYYYYYY
Year FEYYYYYY
Observations3,0153,9133,1952,1602,4312,160
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively.

F. Factor analysis

In this section, we implement a different approach from the panel analysis presented above. To take into account the possibility that the reform process is one unique process common to all sectors, we undertake a factor analysis of our measures of reforms in the six sectors. In particular, we extract the first principal component from the whole dataset with all the data on reforms for each sector.33 The results are reported in Table 10. The impact of democracy seems to be relevant for the overall tendency of a country to reform (the coefficient on the lagged level of democracy is significant at the 1 percent level): moving to a complete democracy in the long-run is associated with a 0.03 increase in the index of reform (the magnitude doubles when we instrument for lagged democracy using lagged democracy in neighboring countries). On the other hand, we do not find any evidence of a feedback effect from the impact of the overall tendency of a country to reform on democracy.

Table 10.Reforms and Democracy: Principal Component
Dependent variable: change in reform

index (country, year)
Dependent variable: change in

democracy (country, year)
(1)

OLS
(2)

IV
(3)
Lagged democracy0.001***0.006***-0.218***
Lagged level of index (country, year)-0.029***-0.096***
Lagged reform in (country, year)-1.775
Country FEYYY
Year FEYYY
Observations1,4181,4181,303
First stage F-stat41
p-value of F-stat0.000
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively. In Column (2), lagged democracy is instrumented by (lagged) democracy in neighboring countries.
Note. The estimators are within estimators and allow for first-order autoregressive disturbance term. ***, ** and * denote statistical significance at 1, 5 and 10 percent respectively. In Column (2), lagged democracy is instrumented by (lagged) democracy in neighboring countries.

V. Conclusions

The question of whether democratic countries favor economic reforms is central to the political economy literature. Political economists study why apparently welfare-enhancing reforms are postponed or adopted with long delays and the presence (or the absence) of democracy is one of the main causes investigated. Unfortunately, despite the vast theoretical literature and limited empirical evidence (restricted to some set of countries, to some reforms and to some periods), the answer to this question has been tentative because of data limitations, which has also limited the techniques that can be used.

This paper answers this question using a novel dataset on structural reforms, which encompasses several sectors and many countries for several years. This dataset allows us to control for a set of possible omitted variables, including country and reform fixed effects, possible two-way interactions between the fixed effects and waves of reforms.

The main conclusions of the papers are that 1) democracy and economic reforms are positively correlated (after controlling for country and reform-specific characteristics, any interaction between country and reform characteristics, and global reform waves); 2) this correlation is robust even after we control for standard factors, which are usually correlated with reforms and democracy, including bureaucratic quality and education, and political stability; 3) the correlation is also robust to the variables that are usually associated with reforms (but not necessarily with democracy) such as crises, neighboring country effects, and compensation schemes; and 4) there is no evidence that economic reforms pave the way for political reforms.

The strong correlation between (lagged) democracy and the adoption of economic reforms, even controlling for many possible omitted factors as well as the finding that past economic reforms are not associated with the adoption of democracy, point to the fact there is probably a causal link from democracy to reforms.

These strong results call for an effort to study the precise mechanisms through which democracy has an impact on economic reforms.

References

    AbiadAbdul and AshokaMody2005Financial Reform: What Shakes It? What Shapes It?American Economic ReviewVol. 95 pp. 6688.

    AbiadAbdulEnricaDetragiache and ThierryTressel2008Do Financial Reforms Boost the Development of Financial Systems? Evidence from a New Database on Financial ReformsIMF Working Paper 08/266 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

    AcemoglouDaron and James A.Robinson2006Economic Origins of Dictatorship and Democracy (Cambridge University Press).

    • Export Citation

    AcemogluDaronSimonJohnsonJames A.Robinson and PierreYared2008Income and DemocracyAmerican Economic ReviewVol. 98No. 3 pp. 808-842.

    • Crossref
    • Search Google Scholar
    • Export Citation

    AlesinaAlberto and NourielRubini1992Political Cycles in OECD EconomiesReview of Economic StudiesOctoberVol. 59 pp. 66388.

    AlbertoAlesinaSilviaArdagna and FrancescoTrebbi2005IMF Staff PapersVol. 53: Special Issue pp. 129 (2005Mundell Fleming lecture)

    • Search Google Scholar
    • Export Citation

    Amin and Djankov2009Democracy and ReformsCEPR Discussion Paper No. 7151.

    BanerjiA. and GhanemH1997Does the Type of Political Regime Matter for Trade and Labor Market Policies?World Bank Economic ReviewVol. 11171-194.

    • Crossref
    • Search Google Scholar
    • Export Citation

    BarroRobert. J. and Jong-WhaLee2001International Data on Educational Attainment: Updates and ImplicationsOxford Economic Paper No. 53 pp. 54163.

    • Crossref
    • Search Google Scholar
    • Export Citation

    BassaniniAndrea and RomainDuval2006Employment Patterns in OECD Countries, Reassessing the Role of Policies and InstitutionsOECD Economics Department Working Papers No. 486.

    • Search Google Scholar
    • Export Citation

    BatesRobert H. and Anne O.Krueger1993Political and Economic Interactions in Economic Policy Reform: Evidence from Eight CountriesBasil Blackwell LimitedCambridge, USA.

    • Export Citation

    BesleyTimothy J. and TorstenPersonn2007The Origins of State Capacity: Property Rights, Taxation, and PoliticsCEPR Discussion Paper No. 6370.

    • Search Google Scholar
    • Export Citation

    BueraPacoAlexMongeGiorgioPrimiceri2008Learning the Wealth of NationsCambridge, MA: NBER working paper No. 14595.

    ClemensMichael A. and Jeffrey G.Williamson2004Why Did the Tariff-Growth Correlation Reverse after 1950?Journal of Economic GrowthVol. 9No. 1 pp. 5-46.

    • Crossref
    • Search Google Scholar
    • Export Citation

    DaveriFrancescoGuidoTabelliniSamuelBentolila and HarryHuizinga2000Unemployment, Growth and Taxation in Industrial CountriesEconomic PolicyVol. 15No. 30 pp. 47-104.

    • Crossref
    • Search Google Scholar
    • Export Citation

    DebreuG.1951The Coefficient of Resource UtilizationEconometricaVol. 19 pp. 273-92.

    DethierJean-JacquesGhanemHafez and ZoliEdda1999Does Democracy Facilitate the Economic Transition? An Empirical Study of Central and Eastern Europe and the Former Soviet Union”. World Bank Policy Research Working Paper No. 2194.

    • Search Google Scholar
    • Export Citation

    DixonW. J. and T.Boswell1996Dependency, Disarticulation and Denominator Effects: Another Look at Foreign Capital PenetrationAmerican Journal of SociologyVolume 102No. 2 September pp. 543-62.

    • Crossref
    • Search Google Scholar
    • Export Citation

    DrazenA. and WilliamEasterly2001Do Crises Induce Reform? Simple Empirical Tests of Conventional WisdomEconomics and PoliticsVol. 13No. 2 pp. 129-157.

    • Crossref
    • Search Google Scholar
    • Export Citation

    EichengreenB. and M.Bordo2003Crises Now and Then: What Lessons from the Last Era of Financial Globalization?” in PaulMizen(ed.) Monetary History Exchange Rate and Financial Markets: Essays in Honor of Charles GoodhardCheltenham: Edward Elgarvol. 2. pp. 52-91

    • Crossref
    • Search Google Scholar
    • Export Citation

    EichengreenB. and D.Leblang2008Democracy and GlobalizationEconomics and Politicsvol. 20 (3) 289-334.

    FäreR.S.Grosskopf and C. A. K.Lovell1994Production Frontiers (Cambridge: Cambridge University Press).

    • Export Citation

    FarrellM. J.1957The Measurement of Productive EfficiencyJournal of the Royal Statistical Society pp. 25381.

    FernandezRaquel and DaniRodrik1991. “Resistance to reform: Status Quo bias in the Presence of Individual Specific UncertaintyAmerican Economic ReviewDecemberVol. 81No. 55 pp. 114655.

    • Search Google Scholar
    • Export Citation

    FidrmucIan2003Economic Reform, Democracy and Growth during Post-communist TransitionEuropean Journal of Political EconomyVol. 19No. 3 September pp. 583-604.

    • Crossref
    • Search Google Scholar
    • Export Citation

    GiavazziFrancesco; and GuidoTabellini2005Economic and Political LiberalizationsJournal of Monetary EconomicsVol. 52 pp. 12971330.

    • Crossref
    • Search Google Scholar
    • Export Citation

    Grosjean and Senik(forthcoming) “Democracy, Market Liberalization and Political PreferencesReview of Economics and Statistics.

    HaggardStephan1990Pathways from Periphery. The Politics of growth in the Newly Industrializing Countries (Ithaca: Cornell University Press).

    • Export Citation

    HuntingtonSamuel P.1968Political Order in Changing Societies (New Haven: Yale University Press).

    • Export Citation

    International Monetary Fund2004World Economic Outlook: Fostering Structural ReformsApril2004 (Washington).

    • Export Citation

    International Monetary Fund2008Structural Reforms and Economic Performance in Advanced and Developing CountriesIMF Occasional Paperforthcoming (Washington).

    • Search Google Scholar
    • Export Citation

    LoraEduardo1998What makes reforms likely? Timing and Sequencing of Structural Reforms in Latin AmericaIADB Working Paper No. W-424.

    • Search Google Scholar
    • Export Citation

    KoopmansT. C.1951An Analysis of Production as an Efficient Combination of Activities” in Activity Analysis of Production and Allocationed. by T. C.Koopmans(New York: Wiley).

    • Search Google Scholar
    • Export Citation

    MilnerH.V. and B.Mukherjee2009Democratization and Economic GlobalizationAnnual Review of Political Science pp. 163-181.

    • Crossref
    • Search Google Scholar
    • Export Citation

    MilnerH.V. and KubotaK.2005Why Move to Free Trade? Democracy and Trade Policy in Developing CountriesInternational OrganizationVol. 59 pp. 107-143.

    • Crossref
    • Search Google Scholar
    • Export Citation

    MulliganC. B.R.Gil and X.Sala-i-Martin2004Do Democracies Have Different Public Policies than Non-democracies?Journal of Economic Perspectives (March).

    • Crossref
    • Search Google Scholar
    • Export Citation

    OlperAlessandroJanFalkowski and JohanSwinnen2009Political Reforms and Public Policies: Evidence from Agricultural ProtectionLICOS Discussion Paper No. 251/2009.

    • Search Google Scholar
    • Export Citation

    McGuireMartin C. and MancurOlson1996The Economics of Autocracy and Majority Rule: The Invisible Hand and the Use of ForceJournal of Economic LiteratureVol. 34 pp. 7296.

    • Search Google Scholar
    • Export Citation

    PerssonT. and GuidoTabellini2002Political Economics: Explaining Economic PolicyMIT Press.

    • Export Citation

    PerssonT. and GuidoTabellini2009Democratic Capital: The Nexus of Political and Economic ChangeAmerican Economic Journal: Macroeconomics1 pp. 88-126.

    • Search Google Scholar
    • Export Citation

    Polity IV. Political regime characteristics and transitions, 1800–2002 [Data Project]. College Park: University of Maryland2002 _http://www.cidcm.umd.edu/inscr/polity/_.

    • Export Citation

    PrzeworskiA. and LimongiF.1993Political Regimes and Economic GrowthJournal of Economic PerspectivesVol. 7 pp. 5170.

    PrzeworskiA. and LimongiF.2000Democracy and Development: Political Regimes and Well-Being in the World, 1950–1990 (Cambridge (UK)Cambridge University Press).

    • Export Citation

    QuinnDennis P.1997The Correlates of Change in International Financial RegulationAmerican Political Science ReviewVol. 91 pp. 5351.

    QuinnDennis P.2000Democracy and International Financial LiberalizationmimeoGeorgetown University.

    QuinnDennis P. and A. MariaToyodaforthcomingDoes Capital Account Liberalization Lead to Economic Growth?Review of Financial Studies.

    • Search Google Scholar
    • Export Citation

    RajanRaghuram and LuigiZingales2003The Great Reversals: The Politics of Financial Development in the Twentieth CenturyJournal of Financial EconomicsVol. 69 pp. 550.

    • Crossref
    • Search Google Scholar
    • Export Citation

    ReinhartC. and K.RogoffThis Time is Different: a Panoramic View of Eight Centuries of Financial CrisesNBER Working Paper No. 13882.

    • Search Google Scholar
    • Export Citation

    RodrikDani1999Democracies Pay Higher WagesQuarterly Journal of EconomicsVol. 114No. 3 pp. 70738.

    Sala-i-MartinX.2006The World Distribution of Income, Falling Poverty and … Convergence, PeriodQuarterly Journal of EconomicsVol. 121No. 2 pp. 351-97.

    • Crossref
    • Search Google Scholar
    • Export Citation

    SchwarzGerhard1992Democracy and Market-Oriented Reform: A Love-Hate Relationship?Economic Education Bulletin32.

    SeifordL. M. and R.M.Thrall1990Recent Developments in DEA: The Mathematical Programming Approach to Frontier AnalysisJournal of EconometricsVol. 46 pp. 7-38.

    • Crossref
    • Search Google Scholar
    • Export Citation

    WacziargRomain and Karen HornWelch2008Trade Liberalization and Growth: New EvidenceWorld Bank Economic ReviewVol. 22No. 2 pp. 187-231.

    • Crossref
    • Search Google Scholar
    • Export Citation
Appendix Tables
Table 1.Summary Statistics
VariableObsMeanStd. Dev.MinMax
Change in reform index20,1230.010.08-11
Lagged democracy20,1230.590.3701
Lagged reform_index20,1230.400.3701
Lagged crisis (inflation>40)5,2520.100.3001
Lagged real devaluation5,2520.010.17-1.001.30
Lagged public expenditure as a percent of GDP5,25215.065.182.9834.39
Lagged bureaucratic quality5,2522.541.1404
Lagged tertiary enrollment5,2520.270.220.000.97
Lagged reforms in geographical neighbor5,2520.020.03-0.210.22
Lagged dummy for left5,2520.330.4701
Lagged dummy for presidential5,2520.550.5001
Lagged democracy in political neighbors18,9701.255.12-910
Lagged crisis (growth<0)5,2340.260.4401
Terms of trade shocks5,252-0.010.14-0.700.47
Lagged crisis (debt)4,6790.010.1201
Lagged crisis (bank)4,6790.050.2201
Political reform (Giavazzi and Tabellini, 2005)21,9190.280.4501
Lagged reform in trade neighbors5,2520.010.03-0.210.39
Change in reform index (principal component)1,4180.020.04-0.180.31
Lagged reform index (principal component)1,4180.500.2501.00
The summary statistics correspond to samples used in Tables 4, 5, 8a and 8b.
The summary statistics correspond to samples used in Tables 4, 5, 8a and 8b.
Table 2A.Country Codes in Figure 2
CodeCountryCodeCountryCodeCountry
AFGAfghanistanGHAGhanaNLDNetherlands
AGOAngolaGINGuineaNORNorway
ALBAlbaniaGMBGambiaNPLNepal
AREUAEGNBGuinea-BissauNZLNew Zealand
ARGArgentinaGNQEquat GuineaOMNOman
ARMArmeniaGRCGreecePAKPakistan
AUSAustraliaGTMGuatemalaPANPanama
AUTAustriaGUYGuyanaPHLPhilippines
AZEAzerbaijanHNDHondurasPNGPapua New G.
BDIBurundiHRVCroatiaPOLPoland
BELBelgiumHTIHaitiPRTPortugal
BENBeninHUNHungaryPRYParaguay
BFABurkina FasoIDNIndonesiaQATQatar
BGDBangladeshINDIndiaROMRomania
BGRBulgariaIRLIrelandRUSRussia
BHRBahrainIRNIranRWARwanda
BLRBelarusIRQIraqSAUSaudi Arabia
BOLBoliviaISRIsraelSDNSudan
BRABrazilITAItalySENSenegal
BTNBhutanJAMJamaicaSGPSingapore
BWABotswanaJORJordanSLBSolomon Is
CAFCARJPNJapanSLESierra Leone
CANCanadaKAZKazakhstanSLVEl Salvador
CHESwitzerlandKENKenyaSOMSomalia
CHLChileKGZKyrgyz RepSVKSlovak Rep
CHNChinaKHMCambodiaSVNSlovenia
CIVCote D’IvoireKORKoreaSWESweden
CMRCameroonKWTKuwaitSYRSyria
COGCongoLAOLaoTCDChad
COLColombiaLBRLiberiaTGOTogo
COMComorosLBYLibyaTHAThailand
CRICosta RicaLKASri LankaTJKTajikistan
CUBCubaLSOLesothoTKMTurkmenistan
CYPCyprusLTULithuaniaTTOTrinidad Tob
CZECzech RepLVALatviaTUNTunisia
DEUGermanyMARMoroccoTURTurkey
DJIDjiboutiMDAMoldovaTWNTaiwan
DNKDenmarkMDGMadagascarTZATanzania
DOMDominican RepMEXMexicoUGAUganda
DZAAlgeriaMKDMacedoniaUKRUkraine
ECUEcuadorMLIMaliURYUruguay
EGYEgyptMMRMyanmarUSAUS
ERIEritreaMNGMongoliaUZBUzbekistan
ESPSpainMOZMozambiqueVENVenezuela
ESTEstoniaMRTMauritaniaVNMViet Nam
ETHEthiopiaMUSMauritiusYEMYemen
FINFinlandMWIMalawiZAFSouth Africa
FJIFijiMYSMalaysiaZARZaire
FRAFranceNAMNamibiaZMBZambia
GABGabonNERNigerZWEZimbabwe
GBRUKNGANigeria
GEOGeorgiaNICNicaragua
Table A3.Country Groups in Figure 2
FinanceCapital
CountryCodeGroupCountryCodeGroupCountryCodeGroup
Burkina FasoBFA1BelarusBLR1BoliviaBOL14
Kyrgyz RepKGZ1ChinaCHN1IndiaIND14
IndonesiaIDN2Viet NamVNM1ThailandTHA14
TurkeyTUR2EgyptEGY2ChileCHL15
ColombiaCOL3MoroccoMAR2JamaicaJAM15
ParaguayPRY3CameroonCMR3PolandPOL15
UkraineUKR3KazakhstanKAZ3TaiwanTWN15
MadagascarMDG4Burkina FasoBFA4South AfricaZAF15
El SalvadorSLV4TunisiaTUN4AustraliaAUS16
BulgariaBGR5JordanJOR5AustriaAUT16
Dominican RepDOM5KenyaKEN5BelgiumBEL16
NicaraguaNIC5SingaporeSGP5CanadaCAN16
SenegalSEN5GhanaGHA6SwitzerlandCHE16
KoreaKOR6TanzaniaTZA6Czech RepCZE16
RomaniaROM6AlbaniaALB7GermanyDEU16
ArgentinaARG7GeorgiaGEO7DenmarkDNK16
PhilippinesPHL7MozambiqueMOZ8SpainESP16
IndiaIND8NepalNPL8FinlandFIN16
JamaicaJAM8BangladeshBGD9UKGBR16
BoliviaBOL9EcuadorECU9GreeceGRC16
ChileCHL9RussiaRUS9HungaryHUN16
AustriaAUT10UkraineUKR9IrelandIRL16
Czech RepCZE10IndonesiaIDN10IsraelISR16
FinlandFIN10MadagascarMDG10ItalyITA16
GreeceGRC10ColombiaCOL11JapanJPN16
LithuaniaLTU10ParaguayPRY11LithuaniaLTU16
PortugalPRT10El SalvadorSLV11NetherlandsNLD16
NorwayNOR11TurkeyTUR11NorwayNOR16
IsraelISR11VenezuelaVEN11New ZealandNZL16
JapanJPN11ArgentinaARG12PortugalPRT16
GermanyDEU12BrazilBRA12SwedenSWE16
HungaryHUN12GuatemalaGTM12UruguayURY16
ItalyITA12PhilippinesPHL12USUSA16
BelgiumBEL13SenegalSEN12
SwitzerlandCHE13BulgariaBGR13
DenmarkDNK13KoreaKOR13
NetherlandsNLD13LatviaLVA13
New ZealandNZL13MexicoMEX13
SwedenSWE13NicaraguaNIC13
AustraliaAUS14
CanadaCAN14
SpainESP14
UKGBR14
IrelandIRL14
USUSA14
ProductAgri
CountryCodeGroupCountryCodeGroupCountryCodeGroup
OmanOMN1TurkmenistanTKM1IndiaIND15
TurkmenistanTKM1UzbekistanUZB1South AfricaZAF15
AzerbaijanAZE2BelarusBLR2ChileCHL16
ChinaCHN2ChinaCHN2FranceFRA16
LaoLAO2EgyptEGY3JamaicaJAM16
Viet NamVNM2PakistanPAK3PolandPOL16
KenyaKEN3CameroonCMR4ThailandTHA16
ChadTCD3UgandaUGA4BoliviaBOL17
TogoTGO3Burkina FasoBFA5Slovak RepSVK17
Solomon IsSLB4TunisiaTUN5AustraliaAUS18
Sierra LeoneSLE4KenyaKEN6CanadaCAN18
BeninBEN5ChadTCD6Czech RepCZE19
GuyanaGUY5TogoTGO6JapanJPN19
MozambiqueMOZ5Cote D’IvoireCIV7Trinidad TobTTO19
BangladeshBGD6NigeriaNGA7BelgiumBEL20
NamibiaNAM6GeorgiaGEO8GermanyDEU20
HondurasHND7Sri LankaLKA8DenmarkDNK20
MadagascarMDG7BeninBEN9SpainESP20
TurkeyTUR7GuyanaGUY9FinlandFIN20
MexicoMEX8MaliMLI9UKGBR20
PhilippinesPHL8BangladeshBGD10GreeceGRC20
FranceFRA9MozambiqueMOZ10HungaryHUN20
South AfricaZAF9NamibiaNAM10IrelandIRL20
LithuaniaLTU10NepalNPL10LithuaniaLTU20
Trinidad TobTTO10ColombiaCOL11NorwayNOR20
UruguayURY10VenezuelaVEN11PortugalPRT20
Czech RepCZE11HondurasHND12SwedenSWE20
HungaryHUN11MoldovaMDA12SwitzerlandCHE21
JapanJPN11MalawiMWI12ItalyITA21
AustraliaAUS12UkraineUKR12MongoliaMNG21
BelgiumBEL12IndonesiaIDN13NetherlandsNLD21
CanadaCAN12MadagascarMDG13New ZealandNZL21
IrelandIRL12ArgentinaARG14UruguayURY21
New ZealandNZL12BulgariaBGR14USUSA21
PortugalPRT12BrazilBRA14
USUSA12GuatemalaGTM14
DenmarkDNK13MexicoMEX14
FinlandFIN13PhilippinesPHL14
ItalyITA13
NorwayNOR13
SwedenSWE13
SpainESP14
UKGBR14
NetherlandsNLD14
LaborFiscal
CountryCodeGroupCountryCodeGroupCountryCodeGroup
MozambiqueMOZ1Viet NamVNM1South AfricZAF14
BangladeshBGD1MyanmarMMR1BotswanaBWA14
CroatiaHRV2BelarusBLR2BoliviaBOL14
RussiaRUS2AzerbaijanAZE2ThailandTHA15
IndonesiaIDN3AlgeriaDZA3PolandPOL15
MalawiMWI3Burkina FaBFA3IsraelISR16
LatviaLVA4ChadTCD4MauritiusMUS16
KoreaKOR4TogoTGO4BelgiumBEL17
South AfricaZAF5IranIRN5Czech RepCZE17
ChileCHL5MalaysiaMYS5AustriaAUT18
ItalyITA6NamibiaNAM6PortugalPRT18
DenmarkDNK6BeninBEN6LithuaniaLTU18
IrelandIRL7CroatiaHRV7DenmarkDNK18
UKGBR7MoldovaMDA7IrelandIRL19
NorwayNOR8ColombiaCOL8HungaryHUN19
CyprusCYP8UkraineUKR8ItalyITA19
USUSA8El SalvadoSLV8USUSA19
RussiaRUS9NetherlandNLD19
TurkeyTUR9GermanyDEU20
VenezuelaVEN10New ZealaNZL20
ParaguayPRY10SpainESP20
MadagascaMDG10CanadaCAN20
MalawiMWI11GreeceGRC21
IndonesiaIDN11JapanJPN21
MexicoMEX12SwedenSWE21
GuatemalaGTM12AustraliaAUS21
ArgentinaARG12CyprusCYP21
RomaniaROM12UKGBR22
PhilippinesPHL12Costa RicaCRI22
IndiaIND13NorwayNOR22
ChileCHL13UruguayURY23
FranceFRA13FinlandFIN23
TradeCurrent
CountryCodeGroupCountryCodeGroupCountryCodeGroup
ChinaCHN1Dominican RepDOM14IndonesiaIDN1
Viet NamVNM1PhilippinesPHL14TurkeyTUR1
CongoCOG2LatviaLVA15GuatemalaGTM2
MauritaniaMRT2NicaraguaNIC15PhilippinesPHL2
GabonGAB3BoliviaBOL16FranceFRA3
CameroonCMR3ChileCHL16JamaicaJAM3
UgandaUGA4JamaicaJAM16AustraliaAUS4
KazakhstanKAZ4TaiwanTWN16Costa RicaCRI4
JordanJOR5PanamaPAN16JapanJPN4
KenyaKEN5South AfricaZAF17AustriaAUT5
TogoTGO5Slovak RepSVK17IsraelISR5
TanzaniaTZA6HungaryHUN18BelgiumBEL6
CambodiaKHM6SloveniaSVN18CanadaCAN6
Cote D’IvoireCIV7Trinidad TobTTO18GermanyDEU6
NigerNER7UruguayURY18DenmarkDNK6
GeorgiaGEO8CyprusCYP19SpainESP6
Sri LankaLKA8Costa RicaCRI19FinlandFIN6
MacedoniaMKD9AustriaAUT19UKGBR6
NepalNPL9Czech RepCZE19GreeceGRC6
BeninBEN9IsraelISR19ItalyITA6
MozambiqueMOZ9AustraliaAUS20NetherlandsNLD6
EcuadorECU10BelgiumBEL20NorwayNOR6
MaliMLI10GermanyDEU20New ZealandNZL6
GuyanaGUY10DenmarkDNK20PortugalPRT6
MalawiMWI11SpainESP20SwedenSWE6
TurkeyTUR11FinlandFIN20UruguayURY6
VenezuelaVEN11UKGBR20USUSA6
CroatiaHRV11GreeceGRC20Hong KongHKG6
ColombiaCOL11IrelandIRL20PeruPER6
RussiaRUS11ItalyITA20
ParaguayPRY11NetherlandsNLD20
MoldovaMDA12PortugalPRT20
IndonesiaIDN12SwedenSWE20
HondurasHND12CanadaCAN20
El SalvadorSLV12USUSA20
BrazilBRA13New ZealandNZL20
BulgariaBGR13LithuaniaLTU20
RomaniaROM13JapanJPN20
KoreaKOR13NorwayNOR20
ArgentinaARG13
*

The views expressed in this paper are those of the author(s) and do not necessarily represent those of the IMF or its board of directors. Alessandro Prati provided invaluable comments and suggestions. We are grateful to Daron Acemoglu, Paola Conconi, Francesco Giavazzi, Dennis Quinn, Guido Tabellini and the seminar participants at the 2007 IMF seminar on structural reforms, the 2008 Annual Meetings of the American Economic Association in Atlanta, the 2008 North-Eastern Universities Development Conference in Boston, the 2008 IMF seminar on structural reforms, and the 2010 annual meeting of the Society for Economic Dynamics for helpful comments.

1

Along these lines, Haggard (1990) argues “… Institutions can overcome collective-action dilemmas by restraining the self-interested behavior of groups through sanctions: collective action problems can be resolved by command.”

2

We will use the term “sector” in the rest of the paper to denote the broad area in which the reforms take place.

3

See below for data description.

5

Not, however, that the results are not directly comparable because Giavazzi and Tabellini (2005) consider only trade reforms.

6

Banerji and Ghanem (1997), and Milner and Kubota (2005) also look at trade reforms. The former presents cross-country evidence to show that authoritarian regimes are associated with higher protectionism (measured by an index of protectionism from Dollar (1992)), while the latter show that regime changes towards democracy are associated with greater liberalization (measured by tariff rates and Sachs Warner indices). Banerji and Ghanem (1997) also find evidence that more authoritarian regimes are associated with greater wage distortions, as measured by the ratio of manufacturing wage rate to the nonmanufacturing value added per worker.

7

Micro-reforms are defined as reforms that lower the administrative costs of starting or running a business. The World Bank’s Doing Business Database dataset covers only the last 5 years so a long-term analysis is not possible.

8

Their measure of trade liberalization is imports plus exports as a fraction of GDP; the authors also check the robustness of their results using the dichotomous measure of Wacziarg and Welch (2004). Capital controls are measured combining information from the International Monetary Fund’s Annual Report on Exchange Arrangements and Exchange Restrictions together with historical data taken from Eichengreen and Bordo (2003).

9

Mulligan, Gill and Sala-i-Martin (2004) do not look specifically at reforms, but analyze the effect of democracy on public spending and taxes. They do not find any significant relationship between democracy and total government consumption, education or social spending; but find that democracies are associated with flatter income taxes (or less income redistribution).

10

This paper does not consider the issue of sequencing among different types of reforms. For an analysis of sequencing see IMF (2008), showing that trade reforms tend to precede financial and capital account reforms.

11

We also check our results using the Freedom House Index and the index proposed by Przeworski, Alvarez, Cheibub, and Limongi (1993). For an exhaustive discussion of these indices, see Przeworski, Alvarez, Cheibub, and Limongi (2000) or Acemoglu and Robinson (2006). Note that the trend toward more democratic regimes has not been linear. Significant retrenchment of democracy has not only been observed in isolated countries but also in several regions of the world. The examples include the general decrease in democracy in Asia in the 1950s and 1960s, the marked decline in Latin America in 1960s and 1970s, and the prolonged stasis in Africa since the 1960s (Acemoglu and Robinson, 2006).

12

The data on banking and debt crises come from Reinhart and Rogoff (2008).

13

For instance, some important reforms happened together with large devaluation and in the context of IMF-supported programs.

14

The measure of bureaucratic quality from ICRG is scored between 0-6. High scores indicate “autonomy from political pressure” and “strength and expertise to govern without drastic changes in policy or interruptions in government services”; also existence of an “established mechanism for recruiting and training.”

15

The source for geographic distance is http://www.cepii.fr/anglaisgraph/bdd/distances.htm and for bilateral trade flows, the IMF’s Direction of Trade Statistics.

16

Alesina and Roubini (1992) argue that right-wing governments are normally considered more inclined to market-oriented reforms; Persson and Tabellini (2002) finds that a presidential system facilitates reforms as they are more able to overcome the resistance of small interest groups.

17

We also included in the regressions additional political variables such as number of executive constraints, the presence of legislative or executive elections, the number of years left in the current term for the executive and the presence of an absolute majority in the legislature by the party of the executive. The results are robust to the inclusion of these additional political variables.

18

Note, however, that the reform variables do not have a unit root being bounded between zero and one.

19

The Durbin-Watson statistics is 1.94 indicating that there is little evidence of serial correlation in the error terms.

20

Note that specifications (2)–(4) reduce slightly the estimation sample because one observation per country is used to calculate the correlation coefficient of the error terms.

21

We include alternative measures of crisis in Table 7b.

22

For each column in Table 4, we also estimate the basic specification (Table 3, column 4) on the restricted sample with fewer observations (not shown) to analyze the effect of adding controls on a consistent sample. The results shown in Table 4 do not appear to be driven by sample selection. We also include additional controls viz. dummies for WTO, EU, and OECD accessions (=1 in years following the accession); and for the existence of an IMF program. Democracy continues to have a positive and statistical effect on reforms, after controlling for these. Accession to EU and OECD; and the existence of an IMF program are significant in explaining reforms; however, they are not significant when included with all the controls in column (6) of Table 4 (results are available upon request).

23

The controls are described in the data section. Note also that the different control variables reduce substantially the sample size.

24

The idea underlying this instrument is based on Persson and Tabellini (2009), who use democracy in neighboring countries as a proxy for democratic capital. In addition, building on this concept, we also tried different measures of distance, including geographical distance between countries and commercial distance defined as the (inverse of) trading flows between countries. While these measures are highly correlated, they confirm the result of political distance reported here.

25

For each specification with controls in Table 7a, we also estimated the basic specification (Table 3, column 4) without any controls on the restricted sample (not shown). We do this to analyze the effect of adding controls on a consistent sample. The results in Table 7a are not driven by sample selection.

26

Results are reported in column 8.

27

Note, however, that we assume a country specific long run level of reforms by putting country fixed effects.

28

This is consistent with a positive correlation between (lagged) democracy and the lagged reform index, and a negative relationship between reform and the lagged reform index.

29

Note that unlike Equation (1), the specification in Equation (2) has the drawback that the steady state level of the index is undefined; hence the long-run effect of democracy on the reform index cannot be estimated. In effect, we are assuming that a certain level of democracy is associated only with a rate of growth of the reform index. Column (9) in Table 7b repeats only the final specification in Table 3 without the lagged reform index. The estimated coefficient on lagged democracy is identical when we replicate columns (1)-(3) in Table 3 without the lagged reform index (results available upon request).

30

We also explore whether democracy affects the probability of reversal in reforms (defined as a decrease in the level of index) and do not find any evidence for this hypothesis.

31

For robustness, we also estimate Equation (3) with longer lags; but do not evidence for any feedback effects (results available on request).

32

Since income is considered an important determinant of democratization, we also test robustness to including per capita income in the regressions (results available upon request). Including the lagged level of the index, rather than the change as in Table 9a, also does not alter the findings in Table 9a.

33

The variable is then normalized between 0 and 1 to make the results comparable to the remaining part of the paper.

Other Resources Citing This Publication