How does political instability affect economic growth?

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Abstract

The purpose of this paper is to empirically determine the effects of political instability on economic growth. By using the system-GMM estimator for linear dynamic panel data models on a sample covering up to 169 countries, and 5-year periods from 1960 to 2004, we find that higher degrees of political instability are associated with lower growth rates of GDP per capita. Regarding the channels of transmission, we find that political instability adversely affects growth by lowering the rates of productivity growth and, to a smaller degree, physical and human capital accumulation. Finally, economic freedom and ethnic homogeneity are beneficial to growth, while democracy may have a small negative effect.

Highlights

► We empirically analyze the effects of political instability on economic growth. ► We perform system-GMM estimations on a panel of 169 countries (1960 to 2004). ► Political instability is found to lead to lower growth rates of GDP per capita. ► The channels of transmission are analyzed through a growth accounting exercise. ► Pol. instability lowers the growth rates of TFP and of physical and human capital.

Introduction

Political instability is regarded by economists as a serious malaise harmful to economic performance. Political instability is likely to shorten policymakers' horizons leading to sub-optimal macroeconomic policies. It may also lead to a more frequent switch of policies, creating volatility and thus, negatively affecting macroeconomic performance. Considering its damaging repercussions on economic performance the extent at which political instability is pervasive across countries and time is quite surprising. Measuring political instability by Cabinet changes, that is, the number of times in a year in which a new premier is named and/or 50% or more of the cabinet posts are occupied by new ministers, figures speak for themselves. In Africa, for instance, there was on average a cabinet change once every two years in the period 2000–2003. Though extremely high, this number is a major improvement relative to previous years when there were, on average, two Cabinet changes every three years. While Africa is the most politically unstable region of the world, it is by no means alone; as similar trends are observed in other regions (see Fig. 1).

The widespread phenomenon of political (and policy) instability in several countries across time and its negative effects on their economic performance has arisen the interest of several economists. As such, the profession has produced an ample literature documenting the negative effects of political instability on a wide range of macroeconomic variables including, among others, GDP growth, private investment, taxation, public expenditures and investment, debt and inflation. Brunetti (1997) comprehensively surveys and summarizes the main political variables affecting economic growth, concluding that, among several variables, measures of policy volatility and subjective perception of politics are most successful in cross-country growth regressions, while democracy is the least successful.1 Alesina et al. (1996) use data on 113 countries from 1950 to 1982 to show that GDP growth is significantly lower in countries and time periods with a high propensity of government collapse. Chen and Feng (1996) show that regime instability, political polarization and government repression all have a negative impact on economic growth. In a more recent paper, Jong-a-Pin (2009) uses a factor analysis to examine the effect of 25 political instability indicators and their effect on economic growth. The main finding is that higher degrees of instability of the political regime lead to lower economic growth.2 As regards to private investment, Alesina and Perotti (1996) show that socio-political instability generates an uncertain politico-economic environment, raising risks and reducing investment.3 Political instability leads to higher shares of government spending in GDP (Devereux and Wen, 1998) and political uncertainty in OECD countries tends to reduce public investment (Darby et al., 2004). Political instability also leads to greater reliance on seigniorage revenues and to higher inflation as shown in Aisen and Veiga, 2006, Aisen and Veiga, 2008. Quite interestingly, the mechanisms at work to explain inflation in their papers resemble those affecting economic growth; namely that political instability shortens the horizons of governments, disrupting long term economic policies conducive to a better economic performance.

This paper revisits the relationship between political instability and GDP growth. This is because we believe that, so far, the profession has been unable to tackle some fundamental questions behind the negative relationship between political instability and GDP growth. What are the main transmission channels from political instability to economic growth? How quantitatively important are the effects of political instability on the main drivers of growth, namely, total factor productivity and physical and human capital accumulation? This paper addresses these important questions providing estimates from panel data regressions by using system-GMM4 on a dataset of up to 169 countries for the period from 1960 to 2004. Our results are strikingly conclusive: in line with the results previously documented, political instability reduces GDP growth rates significantly. An additional cabinet change per year (a new premier is named and/or 50% of cabinet posts are occupied by new ministers) reduces the annual real GDP per capita growth rate by 2.39 percentage points. This reduction is mainly due to the negative effects of political instability on total factor productivity growth, which account for more than half of the effects on GDP growth. Political instability also affects growth through physical and human capital accumulation, with the former having a slightly larger effect than the latter. These results go a long way to clearly understand why political instability is harmful to economic growth. It suggests that countries need to address political instability, dealing with its root causes and attempting to mitigate its effects on the quality and sustainability of economic policies engendering economic growth.

The paper continues as follows: Section 2 describes the dataset and presents the empirical methodology, Section 3 discusses the empirical results, and Section 4 concludes the paper.

Section snippets

Data and the empirical model

Annual data on economic, political and institutional variables, from 1960 to 2004 were gathered for 209 countries, but missing values for several variables reduce the number of countries in the estimations to at most 169, which cover all regions of the world. The sources of economic data were the Penn World Table Version 6.2 — PWT (Heston et al., 2006), the World Bank's World Development Indicators (WDI) and Global Development Network Growth Database (GDN), and the International Monetary Fund's

Empirical results

The empirical analysis is divided into two parts. First, we test the hypothesis that political instability has negative effects on economic growth, by estimating regressions for GDP per capita growth. As described above, the effects of institutional variables will also be analyzed. Then, the second part of the empirical analysis studies the channels of transmission. Concretely, we test the hypothesis that political instability adversely affects output growth by reducing the rates of

Conclusions

This paper analyzes the effects of political instability on growth. In line with the literature, we find that political instability significantly reduces economic growth, both statistically and economically. But, we go beyond the current state of the literature by quantitatively determining the importance of the transmission channels of political instability to economic growth. To the best of our knowledge, there has been no attempt so far to systematically estimate the effect of political

Acknowledgments

The authors wish to thank John H. McDermott, Pierre-Guillaume Méon, the conference participants at the 2010 Meeting of the European Public Choice Society and at the 4th Conference of the Portuguese Economic Journal, the seminar participants at the Free University of Brussels (ULB) and at the University of Minho, and two anonymous referees for very useful comments. Francisco Veiga is also thankful for the financial support provided by ERDF funds through COMPETE and the Portuguese Foundation for

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    The views expressed in this paper are those of the authors and do not necessarily represent those of the International Monetary Fund.

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