Political Polarization and Economic Growth 

Political Polarization and Economic Growth | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Political Polarization and Economic Growth Youngho Kang, Byung-Yeon Kim, Dongwon Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4244901/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the effect of political polarization, measured by the dispersion of self-reported political ideologies, on economic growth. Using a panel of 75 countries from 1990 to 2019, we find that political polarization has a negative effect on economic growth through its effect on private investment, human capital investment, and total factor productivity. We reveal that state capacity—the government’s ability to achieve intended policy goals—mitigates the adverse effect of polarization. JEL Classifications: D72, O47. economic growth political polarization investment total factor productivity state capacity Figures Figure 1 Figure 2 Figure 3 1. Introduction Political polarization is central to understanding contemporary politics and society. Hence, many studies have explored the conceptualization and measurement of political polarization, whereas others have characterized its nature and origins (Abramowitz and Saunders 2008 ; Fiorina and Abrams 2008 ; Hetherington 2009 , 2011 ; Druckman et al. 2013 ; Iyengar et al. 2012 , 2019 ; Iyengar and Westwood 2014; Poole and Rosenthal 1984 ). Related research has also examined the effect of political polarization on the quality of democracy (Graham and Svolik 2020 ; McCoy and Somer 2019 ; Orhan 2022 ). For instance, political polarization can result in a backsliding of democracy because it divides citizens into opposing blocs: one group always supports the policies of the party with which it is affiliated but blindly opposes those of the opposing party without properly considering its substance. 1 In sharply divided societies, voters may place partisan interests (or policy preferences) above democratic principles (Graham and Svolik 2020 ). Political polarization has also attracted the attention of economists. They found that political polarization increases economic policy uncertainty as well as the volatility of economic variables (Azzimonti and Talbert 2014 ), reduces the size of government (Lindqvist and Östling 2010), and affects institutional quality (Keefer and Knack 2002 ; Melki and Pickering 2020 ). The prior research shows that democratic countries have experienced different trajectories of political polarization (Draca and Schwarz 2021 ; Boxell et al. 2022 ). However, only a few studies have examined the effect of political polarization on economic growth (Azzimonti 2011 , 2018). Azzimonti ( 2011 ) uses a theoretical model to show that, by increasing barriers to private investment, political polarization decreases economic growth. Furthermore, Azzimonti (2018) develops a partisan conflict index based on newspaper articles and finds a negative correlation between this index and aggregate investment in the United States (US hereafter). Nevertheless, these works do not empirically explore whether political polarization affects economic growth. 2 This paper makes three contributions. First, we provide the first empirical evidence of the effect of political polarization on economic growth. According to partisan theory, left- and right-wing politicians adopt economic policies that reflect the preferences of their constituents (Potrakfe 2017 ). For instance, left-wing governments tend to promote expansionary policies, while right-wing governments are more active in privatization and market deregulation (Alesina 1987 ; Hibbs 1977 ; Bjørnskov 2005 ; Castro and Martins 2018; Potrakfe 2017 ). When parties with widely different ideologies alternate in power, political turnover generates economic policy uncertainty, which, in turn, raises variability about the returns on investment (Azzimonti and Talbert 2014 ). Therefore, ideological polarization is likely to influence real economic outcomes. However, previous empirical studies have mainly focused on the effect of the mean value of ideology, rather than the distribution of ideology—that is, political polarization (e.g., Bjørnskov 2005 ). Second, we fill a gap in the literature by examining the transmission mechanisms through which political polarization influences economic growth. One channel suggested by Azzimonti ( 2011 , 2018) is private (corporate) investment. Nevertheless, other determinants of economic growth, such as investment in human capital and total factor productivity (TFP), have not been considered systematically, although the literature on economic growth suggests that the majority of variation in real gross domestic product (GDP) per capita across countries can be explained by these factors (Solow 1956 ; Lucas 1988 ; Easterly and Levine 2001 ). Third, we investigate the impact of state capacity, defined as the government’s ability to achieve its intended policy goals, on the relationship between political polarization and economic growth. Given that state capacity may reduce economic policy uncertainty, one might argue that countries with greater state capacity can moderate the negative effect of polarization on growth more effectively. Yet, this hypothesis has not been empirically explored. Using the World Values Survey (WVS) and European Values Survey (EVS), we create a panel dataset of 75 countries for six non-overlapping five-year periods from 1990 to 2019 (1990–1994, 1995–1999, 2000–2004, etc.). As our measure of political polarization, we use the dispersion of self-reported political ideology, as well as the dispersion of responses to economic policy questions, ranging from 1 (left) to 10 (right). 3 The main dependent variable is the log of real GDP per capita. To examine the transmission mechanisms, we employ four alternative dependent variables: per capita private investment, per capita government investment, a human capital index, and TFP. To measure state capacity, we use government effectiveness, regulation quality, and the rule of law obtained from the World Governance Indicators (WGI). To address the potential endogeneity problem in estimating the causal effect of polarization on economic growth, our empirical strategy employs the system generalized method of moments (GMM) estimator and instrumental variables (IV) approach. In the IV approach, our instruments include the leader’s extraordinary personal characteristics, such as trustworthiness, that can bridge deep political divides. For instance, after being elected president of South Africa in 1994, Nelson Mandela united a severely divided country partly through his personal traits of respect and inclusion (International Foundation for Electoral Systems 2003). The “person of the leader” variable is newly available from the Varieties of Democracy (V-Dem) dataset. Moreover, we use an alternative instrument based on the person of the leader but uncorrelated with populism, in order to address the concern that the “person of the leader” may be a populist, which can affect growth in the long run (Funke et al. 2023 ). 4 We find that political polarization has a robust, negative effect on per capita real GDP. In terms of the magnitude of the effect, an increase in a polarization measure of one standard deviation, based on self-reported political ideology, would be associated with a decrease in per capita real GDP of 3.2%. Our results are robust to alternative measures of political polarization based on economic issues of the left and right: equality, government ownership, government responsibility, and competition. Our results are also robust to alternative methods of constructing polarization measures, such as the measure developed by Esteban and Ray ( 1994 ), and to the inclusion of economic polarization, measured by the dispersion of self-reported income scale, and ethnic fractionalization. We show that polarization negatively affects private investment, human capital investment, and TFP. In other words, these three variables provide a transmission mechanism that links political polarization to economic growth. Finally, we find that in countries with high state capacity (measured by government effectiveness, regulatory quality, and rule of law), polarization has a smaller effect on per capita real GDP. The remainder of this paper is organized as follows. Section 2 explains the influence of political polarization on economic growth. Section 3 describes the data, and Section 4 explains the empirical strategy and reports the main empirical results. Section 5 presents results from the robustness checks. Section 6 discusses the transmission mechanisms linking political polarization to GDP. Section 7 examines the extent to which state capacity moderates the detrimental effect of polarization on growth. Section 8 concludes. 2. Links between political polarization and growth The key drivers of per capita economic growth are physical capital accumulation, human capital accumulation, and technological development. The literature on political polarization discusses its effect on physical capital accumulation more extensively than the other two. For example, Azzimonti ( 2011 , 2018) found that polarization depresses private investment. This finding is in line with the argument that intense political disagreement about fiscal policy (e.g., the size and composition of government) discourages private investment by increasing fiscal policy uncertainty such as larger swings in spending and revenue (Azzimonti and Talbert 2014 ; Azzimonti 2018). 5 In general, higher political polarization induces greater economic policy uncertainty, which, in turn, generates variability about the returns on private investment and affects real economic outcomes (Azzimonti and Talbert 2014 ; Baker et al. 2020; Frye 2002 ). 6 Using the partisan conflict index based on lawmakers’ disagreements about policy, Azzimonti (2018) showed that, in the US, partisan discord is negatively associated with investment at the firm level. 7 Political polarization is also likely to lower the expected return on investments by reducing the quality of policy reforms that may prevent negative shocks to the economy (Alesina and Drazen 1991 ; Azzimonti 2018; Kim and Pirtilla, 2006 ; Frye 2002 ). For instance, governments in polarized and unstable societies have fewer incentives to implement legal reforms to protect property rights, thus reducing investment (Svensson 1998 ). 8 There is also debate over whether political polarization increases the size of government. Polarization may increase the utility loss from losing office—that is, from seeing the opposition party’s platform implemented (Alt and Lassen 2006 ; Azzimonti 2011 ). 9 Hence, the incumbent has a stronger incentive to overspend and be reelected. Because overspending is financed by distortionary taxes, greater government spending reduces investment (Azzimonti 2011 ). In contrast, some studies have found that political polarization negatively affects the size of government (Lindqvist and Östling 2010; Bellani and Scervini 2020 ). In particular, Lindqvist and Östling (2010) measured polarization by the dispersion of self-reported political preferences and showed that political polarization is associated with smaller government in democracies. In line with this finding, Bellani and Scervini ( 2020 ) used a panel of 23 European countries to show that heterogeneity in preferences for redistribution reduces redistributive expenditure. 10 Less attention has been paid to the effect of political polarization on human capital accumulation, one of the key drivers of per capita income growth. Like investment in physical capital, investment in human capital depends on the expected returns on the investment (Aisen and Veiga 2013 ). Political polarization is likely to reduce the expected returns from investing in human capital because it increases uncertainty about future policy and thus returns on education. This may even induce economic agents with high levels of human capital to migrate to other countries (Gyimah-Brempong and Camacho 1998 ). Finally, related research found that polarized societies tend to have lower productivity because polarization increases transaction costs by increasing the social distance between individuals in the economy and elevating social conflict (Gradstein and Justman 2002 ; Alesina et al. 1999; Easterly and Levine 1997; Layman and Carsey 2002 ; Esteban and Schneider 2008 ). Similarly, diversity in cultural values (e.g., trust and norms) negatively affects regional economic development (Beugelsdijk et al. 2019 ). In this way, political polarization may influence productivity because political preferences are related to social preferences. 3. Data Our measure of political polarization is based on respondents’ self-reported political ideologies, ranging from 1 (left) to 10 (right), obtained from the WVS and the EVS. These two surveys, conducted independently, are designed to be compatible and comparable across countries and waves, and thus they are presented as an integrated dataset. Although the coverage varies depending on the wave, the integrated dataset covers a wide range of countries across waves. 11 To illustrate the evolution of political polarization over time, Panels (a)-(d) of Fig. 1 present the distributions of political ideology in Wave 2 (approximately 1990) and Wave 7 (approximately 2017) for France, Mexico, South Korea, and the US, respectively. The figure shows that, for each country, the distribution has evolved differently across waves. For instance, between Waves 2 and 7, Mexico and the US experienced a large increase in the share of respondents with two extreme values in the political spectrum. In particular, consistent with the existing evidence, the increase in the US polarization is driven by a disappearing center (Draca and Schwarz 2021 ). In South Korea, the mean distribution of the political spectrum shifted to the left between the two waves, whereas in France, it shifted to the right. [Figure 1 Here] To measure polarization, we use the standard deviation of self-reported political ideologies, ranging from 1 (left) to 10 (right) by country and wave (Lindqvist and Östling 2010; Azzimonti and Talbert 2014 ; Grechyna 2016 ). The standard deviation is the most common measure of the dispersion of a set of values because of its simplicity and transparency. However, one limitation of using the standard deviation is that it fails to consider whether responses are clustered into different groups (Lindqvist and Östling 2010). Following the previous literature, we use two alternative measures: (1) Esteban and Ray’s ( 1994 ) measure of polarization, which takes into account the degree of clustering (rather than dispersion) and (2) the proportion of respondents who reply either 1 or 10. As alternative measures of political polarization, we use responses to multiple-choice questions that measure various left and right economic issues (Lindqvist and Östling 2010). Specifically, we use the question: “How would you place your views on this scale [from 1 to 10]?” for the following four statements. 12 Equality: from 1 = “Income should be made more equal” to 10 = “We need larger income differences as incentives.” Government ownership: from 1 = “Government ownership of business should be increased” to 10 = “Private ownership of business should be increased.” Government responsibility: from 1 = “The government should take more responsibility to ensure that everyone is provided for” to 10 = “People should take more responsibility for providing for themselves.” Competition: from 1 = “Competition is harmful. It brings out the worst in people” to 10 = “Competition is good. It stimulates people to work hard and develop new ideas.” The main dependent variable is the log of per capita GDP in constant 2015 dollars obtained from the World Development Indicators (WDI). To investigate the transmission mechanism that links political polarization to growth, we employ four alternative dependent variables: real per capita private investment and real per capita general government investment from the International Monetary Fund, and a human capital index and TFP from the Penn World Tables 10.0. 13 To measure state capacity, which moderates the effect of polarization on growth, we use government effectiveness, regulation quality, and the rule of law from the WGI. The control variables are gross fixed capital formation (a proxy variable for the savings rate), trade openness (the sum of exports and imports divided by GDP), population growth, inflation, and urbanization, all taken from the WDI. In addition, we include the proportion of respondents with more than a low-level tertiary education from the WVS and the EVS. 14 Our sample includes an unbalanced panel of 75 countries for six non-overlapping five-year periods from 1990 to 2019 (1990–1994, 1995–1999, 2000–2004, etc.). All control variables except for low-level tertiary education are averaged over each five-year period. Appendix Table A1 lists the 75 countries included in the final sample. Appendix Table A2 presents summary statistics for the main variables used. 4. Empirical strategy and results 4.1 Empirical specification and main results To test the effects of political polarization on economic growth, we consider a standard dynamic panel specification (Islam 1995 ; Acemoglu et al. 2019 ): $$\text{ln}{y}_{i,t}={\beta }_{1}\text{ln}{y}_{i,t-1}+{\beta }_{2}{POL}_{i,t-1}+{\beta }_{3}{Mean}_{i,t-1}+{\Phi }{X}_{it}+{\alpha }_{i}+{\theta }_{t}+{u}_{i,t}$$ 1 where \(\text{ln}{y}_{i,t}\) is the log of real GDP per capita for country \(i\) and time \(t\) (which indexes five-year periods). \({POL}_{i,t-1}\) measures political ideology polarization, and \({Mean}_{i,t-1}\) is the mean value of the responses. \({X}_{i,t}\) is a vector of the standard control variables in the growth regression, as described in Section 3 . \({\alpha }_{i}\) is a country fixed effect that absorbs the impact of any time-invariant country characteristics such as geography; \({\theta }_{t}\) denotes a set of period fixed effects to capture technological progress at the frontier, as well as any cyclical trends in the global economy; and \({u}_{i,t}\) is the error term. We estimate Eq. ( 1 ) using both the fixed-effects estimator and the system-GMM estimator. Among these, we prefer the system GMM estimator developed by Blundell and Bond ( 1998 ) for two reasons: 15 First, the presence of country fixed effects and the lagged dependent variable causes potential bias in the ordinary least squares (OLS) estimator (Nickell 1981 ). This bias in our sample is unlikely to be small because the average length of the time-series in our panel is approximately 3.3 five-year periods. The GMM estimator controls for country unobserved heterogeneity as well as the bias from the lagged dependent variable. Second, the GMM estimator addresses the potential endogeneity problem in estimating the causal effect of polarization on GDP. For instance, voters might blame politics for poor economic performance, regardless of the party in power, which may weaken the ruling coalition and push voters to become more ideologically extreme (Mian et al. 2014 ; Funke et al. 2016 ). Then, political polarization would be the consequence, not the cause, of changes in economic performance (Dalgaard and Olsson 2013 ; Grechyna 2016 ). Another possibility is that time-varying unobservable variables may affect both political polarization and GDP. We use Windmeijer’s ( 2005 ) correction for small sample bias in standard errors because the standard error estimates from a two-step estimation tend to be biased downward. For specification checks, we provide two tests of the system GMM estimator: a test for serial correlation in the first-differenced errors (null hypothesis: there is no second-order serial correlation in the first-difference residuals) and Hansen’s J test for overidentifying restrictions (null hypothesis: instruments are uncorrelated with the residuals). 16 [Table 1 Here] Table 1 The effect of political polarization on real GDP per capita: main results Fixed effects GMM IV 1 2 3 4 5 1st stage 6 2nd stage Lagged ln per capita GDP 0.402*** (0.076) 0.409*** (0.077) 0.919*** (0.022) 0.924*** (0.023) -0.315*** (0.117) 0.294*** (0.093) Mean 0.017 (0.021) -0.002 (0.030) 0.012 (0.056) 0.026 (0.027) POL -0.072* (0.039) -0.072* (0.039) -0.077** (0.036) -0.090** (0.039) \(\widehat{\text{P}\text{O}\text{L}}\) -0.445*** (0.140) IV(Charisma) -0.084*** (0.028) IV(Egal.) -0.623*** (0.218) POP growth -0.035 (0.028) -0.035 (0.028) -0.041** (0.018) -0.047*** (0.016) 0.123** (0.060) 0.045 (0.044) GFCF 0.007** (0.003) 0.007** (0.003) 0.0001 (0.004) 0.0004 (0.003) 0.004 (0.006) 0.007** (0.003) Trade 0.002*** (0.0008) 0.002*** (0.0008) 0.00078** (0.00032) 0.0008* (0.0004) 0.001 (0.001) 0.003*** (0.001) Tertiary 0.101* (0.058) 0.100* (0.058) 0.015 (0.071) -0.002 (0.067) 0.136 (0.093) 0.113** (0.056) INF -0.0002 (0.0002) -0.0002 (0.0002) -0.0008 (0.0006) -0.001 (0.001) 0.005 (0.011) -0.018 (0.013) Urban -0.005 (0.006) -0.005 (0.006) -0.001 (0.001) -0.002 (0.002) 0.004 (0.012) -0.002 (0.008) Wave dummy Yes Yes Yes Yes Yes Yes AR(1) / AR(2) 0.017/0.102 0.008/0.102 Hansen test 0.752 0.969 Kleibergen-Paap F-statistics [p-value] 11.41 [0.000] Hansen’s J test [p-value] 2.623 [0.105] R-squared 0.835 0.836 Observations 257 257 257 257 254 No. countries 75 75 75 75 74 Notes. The dependent variable is real GDP per capita (in natural logs). POL is the level of political polarization based on the self-reported political ideologies. MEAN is the average level of political ideology. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Columns 1 through 4 of Table 1 presents the fixed effects estimates (Columns 1 and 2) and the GMM estimates for real GDP per capita (Columns 3 and 4). 17 Columns 1 and 3 include polarization and a set of control variables, and Columns 2 and 4 add the mean value of the political spectrum because polarization might be correlated with the mean value of the responses (Lindqvist and Östling 2010). All four columns show that political polarization, measured by the standard deviation of the political spectrum, ranging from 1 (left) to 10 (right), is negatively associated with per capita real income. In Columns 1 through 4, political polarization (POL) has a negative and statistically significant effect on real GDP per capita. Based on Column 4, our preferred specification, evaluated at the mean, a one standard deviation shock to POL is associated with a 3.2% decline in real GDP per capita. 4.2 IV estimations We further address the endogeneity problem using an instrumental variables (IV) approach. We use two external instruments for political polarization: (1) the person of the leader (personal characteristics, such as charm and trustworthiness) and (2) the egalitarian component index (a measure of equal protection of rights and freedoms and equal access to power across all social groups), both obtained from the V-Dem dataset. 18 In more detail, in V-Dem, person of the leader is measured by the question “To what extent is the chief executive portrayed as being endowed with extraordinary personal characteristics and/or leadership skills (e.g., as father or mother of the nation, exceptionally heroic, moral, pious, or wise, or any other extraordinary attribute valued by the society)?” The egalitarian component index is measured by the question: “To what extent is the egalitarian principle achieved?” The egalitarian principle of democracy is achieved when (1) the rights and freedoms of individuals are protected equally across all social groups, (2) resources are distributed equally across all social groups, and (3) access to power is equally distributed by gender, socioeconomic class and social group. In order to be valid, IV in our study has to satisfy two criteria: it should affect political polarization and not directly affect economic growth. The person of the leader, our first instrument, can influence political polarization yet is not directly related to future economic performance. For instance, consider a charismatic leader who can unite different groups of people by bridging deep political divides and reducing mistrust among political opponents. One strand of political science literature emphasizes that a political leader’s personal traits, such as trustworthiness, are major determinants of political trust or public confidence in the political process (e.g., Citrin 1974 ; Citrin and Green 1986 ; Greenstein 2000 ). 19 For example, after being elected president of South Africa in 1994, Nelson Mandela united a severely divided country in part through his personal characteristics of respect and inclusion (of all parties, including those no longer in power; International Foundation for Electoral Systems 2003). Appendix Figure A1 shows that the distribution of political ideology in South Africa became less polarized in Wave 3 (survey year 1996) after Nelson Mandela took office, relative to the distribution in Wave 2 (survey year 1990). Note, however, that leaders with extraordinary personal characteristics are not necessarily related with higher economic growth. Additionally, there is little consensus about whether the emergence of extraordinary leaders is a direct consequence of economic circumstances. The egalitarian principle of democracy, our second instrument, reduces political polarization by protecting the rights and freedoms of individuals equally and ensuring equal access to power across groups with different ideologies (Dahl 1971 ). For instance, equal protection of rights and freedoms across all groups can help minimize feelings of resentment and disenfranchisements among some groups, which is a source of polarization (Dahl 1971 ; Sigman and Lindberg 2018). In addition, equal distribution of power diversifies political leadership, which leads to less polarizing policies. However, the egalitarian principle does not appear to be directly relevant to GDP growth because it more relevant to the equal protection of rights and equal access to power than to the efficient allocation of resources. By separating the variations in polarization that are driven by the personality of the leader and the egalitarian principle of democracy, our IV strategy mitigates the potential for idiosyncratic changes in a country’s political institutions that are endogenous to GDP growth to bias our results (for a similar argument, see Acemoglu et al. 2019 ). [Table 2 Here] Table 2 Robustness check using alternative political polarization measures, system GMM 1 2 3 4 Lagged ln per capita GDP 0.889*** (0.025) 0.908*** (0.025) 0.895*** (0.023) 0.920*** (0.031) Mean_ownership -0.016 (0.025) POL_ownership -0.088** (0.034) Mean_responsible 0.043** (0.020) POL_responsible -0.090** (0.044) Mean_compete 0.035 (0.035) POL_compete -0.095* (0.050) Mean_equality 0.022** (0.011) POL_equality 0.002 (0.031) Wave dummy Yes Yes Yes Yes AR(1)/AR(2) 0.017/0.128 0.007/0.134 0.015/0.221 0.017/0.102 Hansen test 0.721 0.952 0.833 0.888 Observations 247 244 256 253 No. countries 75 75 75 75 Notes. The dependent variable is real GDP per capita (in natural logs). Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education, inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Columns 5 and 6 of Table 1 present the results of estimating a two-stage least squares (2SLS) regression, employing the “person of the leader” and “egalitarian component index” from the V-Dem dataset as IVs. In Column 5, the first-stage regression results display that the estimated coefficients for “person of the leader” and “egalitarian component index” are negative and statistically significant. The first-stage F-statistic is 11.41, indicating that the instruments are relevant (Staiger and Stock 1997). In Column 6, the second-stage results show that the effect of POL on real GDP per capita is negative and significant. As expected, the IV estimate is larger in magnitude than the GMM estimate. Hansen’s J-test for over-identifying restrictions does not reject the null hypothesis of instrument validity. 5. Robustness checks To test the robustness of our main results, we consider a number of variations of the original model. Table 2 presents the results using alternative measures of political polarization. Following Lindqvist and Östling (2010), we employ polarization measures based on the responses to specific questions on economic policies from the WVS and the EVS on (1) government ownership, (2) government responsibility, (3) competition, and (4) equality. In Table 2 , each column refers to the effect of the polarization measure based on the responses to each of the four economic policy questions. In Columns 1 through 3, political polarization has a negative and statistically significant effect on real GDP per capita. In Column 4, the effect of the polarization measure based on equality is statistically insignificant. [Table 2 Here] For a further robustness check, we employ (1) Esteban and Ray’s ( 1994 ) polarization measure, which considers clusters of responses and (2) a bipolarization measure, which is the share of respondents who answer either 1 or 10 (see Lindqvist and Östling 2010). Both measures are highly correlated with the standard deviation. 20 According to the results presented in Columns 1 and 2 of Table 3 , both alternative measures of polarization have a robust and negative effect on per capita real GDP. Table 3 Various robustness checks 1 All 2 All 3 Excl. developed countries 4 Incl. economic polarization 5 Incl. ethnic fractionalization 6 2SLS using alternative IV Esteban and Ray -0.186** (0.075) Bipolarization -0.454*** (0.159) POL -0.074** (0.037) -0.076** (0.035) -0.102** (0.045) -0.296** (0.140) POL_ECON -0.002 (0.024) Ethnic_Frac -0.056 (0.119) Wave dummy Yes Yes Yes Yes Yes Yes AR(1) / AR(2) 0.008/0.115 0.009/0.113 0.007/0.108 0.026/0.140 0.008/0.119 Kleibergen-Paap F-statistics [p-value] 8.31 [0.001] Hansen test 0.912 0.943 0.890 0.943 0.781 0.108 Observations 257 257 187 252 237 195 No. countries 75 75 53 75 67 53 Notes. The dependent variable is real per capita GDP (in natural logs). Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education, inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Another concern is that the relationship between political polarization and growth might be limited to developed counties. Because developed countries tend to be established (higher-quality) democracies, an increase in ideological polarization is more likely to lead to more frequent change in ruling parties in a group of developed countries, resulting in larger swings in economic policies. In Column 3 of Table 3 , we show the results from excluding 22 developed countries from the sample. 21 The main results do not change qualitatively. One can argue that political polarization affects growth not independently but through economic inequality, as they are significantly correlated. In other words, the effect of political polarization might capture the effect of economic polarization if the two types of polarization are correlated with each other (McCarty et al. 2006 ). Indeed, some studies have found that income inequality negatively influences economic growth (e.g., Alesina and Rodrik Perotti 1996 ), but others maintained that the relationship between economic inequality and growth is either inconclusive or insignificant (e.g., Barro 2000 ; Benos and Karagiannis 2018 ). To address this issue, we add economic inequality, POL_ECON, measured by the standard deviation of self-reported income on a scale from 1 (poor) to 10 (rich). 22 The results in Column 4 of Table 3 show that the coefficient of POL_ECON is small and insignificant whereas the coefficient of political polarization remains negative and significant. We also test whether political polarization affects growth through social polarization by controlling for ethnic fractionalization, a proxy for social polarization. We employ an annual ethnic fractionalization index from the Drazanova ( 2020 ) dataset. 23 The results in Column 5 of Table 3 display that the effect of ethnic fractionalization is negative but statistically insignificant while the effect of political polarization remains negative and significant. Lastly, we deal with a potential concern with our IV estimates that one of our instruments for political polarization, the person of the leader, may be correlated with populism which might cause a decline in GDP per capita in the medium and long run (Funke et al. 2023 ). In this case, the person of the leader may be an invalid instrument as it directly affects economic growth. To address this concern, we first regress the person of the leader on the number of left-wing and right-wing populist incumbent governments during the past five years. We then use the residual as the instrument for polarization along with the egalitarian component index. In Column 6 of Table 3 , the 2SLS results show that the effect of POL on per capita real GDP is still negative and significant. [Table 3 Here] 6. Transmission mechanisms Given our findings that political polarization undermines long-run growth, we subsequently examine the transmission mechanism that links political polarization to per capita real GDP. Table 4 presents the GMM estimates for the four alternative dependent variables: real per capita private investment (Column 1), real per capita government investment (Column 2), human capital investment per worker proxied by the human capital index (Column 3), and TFP (Column 4). The results indicate that POL has negative and significant effects on private investment, human capital investment, and TFP. In contrast, POL has a statistically insignificant effect on real government investment. Consistent with the discussions in Section 2 , these results indicate that political polarization influences economic development mainly by depressing private investment and productivity (Azzimonti and Talbert 2014 ; Azzimonti 2018). 24 Table 4 Transmission mechanisms 1 2 3 4 Dep. Var. ln PINV ln GINV ln HCAP ln TFP Lagged ln PINV 0.756*** (0.086) Lagged ln GINV 0.649*** (0.110) Lagged ln HCAP 0.927*** (0.029) Lagged ln TFP 0.658*** (0.093) Mean 0.046 (0.082) -0.065 (0.146) 0.012 (0.010) 0.010 (0.019) POL -0.189** (0.090) -0.045 (0.211) -0.019* (0.010) -0.070*** (0.026) Wave dummy Yes Yes Yes Yes AR(1) / AR(2) 0.032/0.115 0.024/0.224 0.017/0.254 0.032/0.398 Hansen test 0.917 0.785 0.710 0.961 Observations 250 250 227 227 No. countries 73 73 65 65 Notes. Among the dependent variables, PINV is real per capita private investment, GINV is real per capita general government investment, HCAP is human capital investment per worker, and TFP is total factor productivity. POL is the level of political polarization based on self-reported political ideologies. MEAN is the average level of political ideology. Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education (except in Column 3), inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. [Table 4 Here] We also calculate the relative contribution of each transmission component to the effect of political polarization on economic growth. Appendix A3 and Appendix Table A3 explain how we calculated the relative contribution of each transmission component. Figure 2 shows that two large contributors to the effects of polarization on growth are TFP (which accounts for 43.8%) and private investment (which accounts for 37.3%). [Figure 2 Here] 7. The effect of political polarization conditional on state capacity State capacity may moderate the detrimental effect of polarization on growth because economic policy uncertainty is lower when the government can effectively implement appropriate policies and thus make credible commitments to investors (Acemoglu et al. 2010 ; Hendrix 2010 ; North 1981 ). Hence, the effect of political polarization on economic growth might depend on state capacity. State capacity is defined as the government’s ability to achieve its intended policy goals (Dincecco 2017 ; Dincecco and Katz 2014 ; O’Reilly and Murphy 2022 ). To measure it, we follow the literature and employ three indicators: government effectiveness, regulatory quality, and rule of law (Pritchett 2022 ; O’Reilly and Murphy 2022 ). Government effectiveness refers to the quality of policy implementation and the credibility of the government’s commitment to these policies (Kaufmann et al. 2010 ). Regulatory quality captures the government’s ability to implement sound policies that promote economic development (Kaufmann et al. 2010 ). Lastly, the rule of law captures the extent to which people have confidence in the quality of contract enforcement, property rights, and the courts. All three indicators are obtained from the Worldwide Governance Indicators ( www.govindicators.org ). We add both a state capacity measure and its interaction term with polarization to Eq. ( 1 ) and present the results in Table 5 . It shows the effect of polarization on per capita real GDP conditional on each measure of state capacity: government effectiveness, regulatory quality, and the rule of law. In all columns, the interaction terms are positive and significant, indicating that countries with high state capacity (i.e., effective government, high-quality regulation, and strong rule of law) tend to experience less effects of polarization on real GDP per capita than would be the case otherwise. Table 5 The effect of political polarization conditional on state capacity 1 2 3 Lagged ln per capita GDP 0.911*** (0.037) 0.884*** (0.030) 0.920*** (0.044) Mean 0.001 (0.034) -0.015 (0.037) -0.021 (0.040) POL -0.072** (0.033) -0.099** (0.038) -0.059* (0.032) POL * GEE 0.056* (0.033) POL * RQE 0.066** (0.033) POL * RLE 0.078* (0.043) GEE -0.101 (0.073) RQE -0.099 (0.063) RLE -0.170 (0.108) Wave dummy Yes Yes Yes AR(1)/AR(2) 0.001/0.181 0.001/0.184 0.002/0.226 Hansen test 0.943 0.905 0.875 Observations 234 234 234 No. countries 75 75 75 Notes. The dependent variable is real GDP per capita (in natural logs). Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education, inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1 [Table 5 Here] Panels (a)-(c) of Fig. 3 illustrate variations in the effect of polarization on GDP with the degree of government effectiveness, rule of law, and regulatory quality, respectively. The figures show the 90% confidence interval for the relationship between polarization and per capita GDP, conditional on the level of state capacity measures. At low levels of state capacity, the point estimate is negative and significant at the 10% level as the confidence intervals are below the zero line (Brambor et al. 2006 ). The effect of polarization turns statistically insignificant at higher levels of state capacity. For instance, a one-standard-deviation increase in polarization would reduce real GDP per capita by about 5% in Zimbabwe (whose average government effectiveness score is -1.29). However, the polarization effect is statistically insignificant for the US (whose average government effectiveness score is 1.54). In other words, the effectiveness of the US government has been able to prevent large political polarization from undermining economic growth. These findings indicate that political polarization is more likely to hamper growth in countries with low state capacity, as measured by an ineffective government, low-quality regulation, and weak rule of law. [Figure 3 Here] 8. Conclusions Political polarization is regarded as a key phenomenon in contemporary democracies. A vast body of literature suggests that this is a serious underlying problem that affects various aspects of democratic systems. Previous research has found that political polarization decreases the quality of political parties and the government. Although political polarization has recently attracted much attention from economists, few papers address its economic effects. This study raises three questions: Does political polarization reduce economic growth? If so, what are the channels through which polarization results in lower growth rates? Does state capacity mitigate the adverse effect of polarization on the economy? Using polarization measures based on self-reported ideologies from the WVS and EVS, we found a robust negative correlation between political polarization and economic growth. The magnitude of this effect is considerable. This result remains robust to different estimation methods (GMM and IV) and various measures of political polarization. The effect of political polarization on growth is sizable. Based on the system GMM estimates, an increase of one standard deviation in the polarization measure is associated with a 3.2% decrease in per capita GDP. We also reveal a transmission mechanism that translates polarization into lower economic growth. The results suggest that polarization reduces growth not only through physical investment but through human capital investment and productivity. Moreover, we find that strong state capacity, such as effective government, high-quality regulation, and strong rule of law, prevents polarization from dampening growth. These findings indicate that the combination of political polarization and weak state capacity poses an important threat to economic growth. Declarations Author Contribution Kang ,Kim, and Lee wrote and reviewed the main manuscript. Kang and Lee ran regressions and reported the empirical results, and Kim reviewed the results and made comments. All authors participated in the revision of the first draft. Data Availability The World Values Survey (WVS) and European Values Survey (EVS) can be accessed https://www.worldvaluessurvey.org/wvs.jsp and https://europeanvaluesstudy.eu/, respectively. References Abramowitz, A.I. and K.L. Saunders, 2008. Is polarization a myth? 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Structure and Change in Economic History . New York: Norton. O’Reilly, C. and R.H. Murphy, 2022. An index measuring state capacity. 1789-2018. Economica 89, 713-745. Orhan, Y.E., 2022. The relationship between affective polarization and democratic backsliding: Comparative evidence. Democratization 29(4), 714-735. Pierce, D.R. and R.R. Lau. 2019. Polarization and correct voting in U.S. presidential elections. Electoral Studies 60, 102048. Perotti, R. 1996. Growth, income distribution, and democracy: What the data say. Journal of Economic Growth 1, 149-187. Poole, K.T., and H. Rosenthal, 1984. The Polarization of American politics. Journal of Politics 46(4), 1061-1079. Potrakfe, N., 2017. Partisan politics: The empirical evidence from OECD panel studies. Journal of Comparative Economics 45, 712-750. Pritchett, L., 2022. National development delivers: And how! And how? Economic modelling 107, 105717. Roodman, D., 2009. How to do xtabond2: an introduction to difference and system GMM in Stata. The Stata Journal 9(1), 86-136. Roodman, D., 2009. A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics 71(1), 135-158. Sigman, R. and S.I. Lindberg, 2019. Democracy for all: conceptualizing and measuring egalitarian democracy. Political Science Research and Methods 7(3), 595-612. Solow, R.M., 1956. A contribution to the theory of economic growth. Quarterly Journal of Economics 70(1), 65-94. Svensson, J., 1998. Investment, property rights and political instability: theory and evidence. European Economic Review 42, 1317-1341. Windmeijer, F., 2005. A finite sample correction for the variance of the linear two-step GMM estimator. Journal of Econometrics 126(1), 25-25. Footnotes There are some works emphasizing the positive aspects of political polarization. For example, political polarization at the elite level may facilitate more consistent political attitudes by providing voters with clear ideological differences between major parties (Levendusky 2010 ; Hetherington 2011 ; Pierce and Lau 2019 ) In addition, the related literature examines the effect of political instability (e.g., measured by political violence and cabinet changes) on economic growth (Aisen and Veiga 2013 ; Alesina et al. 1996 ; Alesina and Perotti 1996 ; Barro 1991 ; Jong-A-Pin 2009 ). However, political polarization and political instability (a multidimensional concept) are two different concepts. The question asks: “In political matters, people talk of the left and the right. How would you place your views on this scale, generally speaking?” Respondents are instructed to choose a number between 1 and 10, where 1 is labeled “Left” and 10 is labeled “Right”. Populism is a political style focused on the struggle between the people and the elite (Funke et al. 2023 ). The concept may overlap with other leader characteristics such as charisma. Investment decisions are delayed to the extent that investment requires fixed upfront costs and is irreversible (Azzimonti 2018). Political turnover in polarized societies generates uncertainty in economic policies because parties with widely different ideologies alternate in power (Azzimonti and Talbert 2014 ). Woo (2003, 2005) similarly showed that social polarization measured by income inequality causes larger fiscal deficits and more volatile fiscal outcomes, and thus lower economic growth. Additionally, political polarization may undermine democracy because even voters who value democracy may trade off democratic principles for partisan interests to elect politicians whom they support (Svolik 2019). The utility loss increases with the distance between the platforms of the incumbent and the opponent (Alt and Lassen 2006 ). The heterogeneity in preferences for redistribution is measured by the share of individuals who take extreme positions on the Likert scale, i.e., the share of individuals who respond “strongly agree” or “strongly disagree” to the statement “The government should take measures to reduce differences in income levels.” The number of countries in the dataset is 24 in Wave 1 (1981–1983), 43 in Wave 2 (1990–1992), 55 in Wave 3 (1995–1998), 71 in Wave 4 (2000–2004), 82 in Wave 5 (2005–2008), 60 in Wave 6 (2010–2014), and 81 in Wave 7 (2017–2022). In all, the integrated dataset, from 1981 to 2017, covers 115 countries, including more than 645,000 interviews. We recode all the questions so that a higher number indicates the right. The human capital index is based on the average years of schooling and an assumed rate of return to education. The data are available for a larger sample of countries than the secondary enrolment rate in the WDI. The system GMM is derived from the estimation of a system of two simultaneous equations, one in levels (with lagged first differences as instruments) and the other in first differences (with lagged levels as instruments) (Blundell and Bond 1997). To address the problem of too many instruments, we limit the instruments for the lagged dependent variable to the second lag. We also limit the instruments for some explanatory variables to the second to fourth lags in most specifications, and collapse instruments for others (Roodman 2009 ). In Columns 1 and 2, robust standard errors are clustered by country to account for country-level serial correlation. V-Dem, which refers to Varieties of Democracy, attempts to conceptualize and measure democracy in a multidimensional way ( https://v-dem.net ). In the robustness check section, we address the potential concern that the person of the leader may be correlated with populism, a political style focused on the struggle between the people and the elite, which might directly cause a decline in GDP per capita in the medium and long run (Funke et al. 2023 ). The correlation between POL and Esteban and Ray’s measure is 0.92, and the correlation between POL and Bipolarization is 0.89. The countries include Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Luxembourg, the Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom, and the United States. We do not use the Gini coefficient because some countries do not report it during the sample period. Drazanova ( 2020 ) dataset covers 162 countries for the 1945–2013 period. We use the index value of 2013 as the value of 2015. According to the IV estimates for transmission mechanisms, POL has negative and significant effects on private and human capital investments, while the effects of POL on government investment and TFP are statistically insignificant. These results are available upon request from the authors. Additional Declarations No competing interests reported. Supplementary Files Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4244901","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291772258,"identity":"8fa21f52-741a-4415-b006-5285f677245d","order_by":0,"name":"Youngho Kang","email":"","orcid":"","institution":"Soongsil University","correspondingAuthor":false,"prefix":"","firstName":"Youngho","middleName":"","lastName":"Kang","suffix":""},{"id":291772259,"identity":"2d4ad7f0-984a-4af2-8c17-7b2b7291aa8e","order_by":1,"name":"Byung-Yeon Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACCWYGNgaGChj3ANFazpCkhQGohbGNFC2S7dxpj3nn1eUZHGB++IHhzD3CWqSZebcb8247XGxwgM1YguFGMWEtcsy826R5tx1I3HCAwYyB4UMCsVrm1AG1sH8jTos0WEsDM1ALD9CWG0RokWzm3W4459jhxJmHeYolEs4QoUXi/NltD97U1CX2HW/f+OHDMSK0gAATD4hkBmIiNTAwMP4gVuUoGAWjYBSMTAAAkKU3FygCS9oAAAAASUVORK5CYII=","orcid":"","institution":"Seoul National University","correspondingAuthor":true,"prefix":"","firstName":"Byung-Yeon","middleName":"","lastName":"Kim","suffix":""},{"id":291772260,"identity":"710be912-a06d-46df-aaf1-edebdd6fe2f0","order_by":2,"name":"Dongwon Lee","email":"","orcid":"","institution":"Sungkyunkwan University","correspondingAuthor":false,"prefix":"","firstName":"Dongwon","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2024-04-10 03:49:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4244901/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4244901/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54822824,"identity":"ddf03618-7356-4cbd-bf51-83a7b7fa49a3","added_by":"auto","created_at":"2024-04-17 09:08:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86994,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions of political ideology, wave 2 and wave 7\u003c/p\u003e\n\u003cp\u003eNote: Each panel shows the distribution of political ideology, ranging from 1 (left) to 10 (right), in Wave 2 (approximately 1990) and Wave 7 (approximately 2017).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4244901/v1/6fef7e951615b72e96807bda.png"},{"id":54822826,"identity":"dc89cdda-aec9-4ef5-b7c1-5ca2b4e8042d","added_by":"auto","created_at":"2024-04-17 09:08:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34014,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative contribution of each transmission mechanism to the effect of polarization on economic growth\u003c/p\u003e\n\u003cp\u003eNote: See Appendix A3 for the detailed discussion on how we calculate the relative contribution of each transmission component.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4244901/v1/762135c6d033b562268daed0.png"},{"id":54822825,"identity":"22e53def-deb7-4333-b96a-78e792cfac82","added_by":"auto","created_at":"2024-04-17 09:08:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":108375,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of political polarization on per capita GDP with state capacity measures\u003c/p\u003e\n\u003cp\u003eNote: Each panel shows the relationship between polarization and per capita GDP, conditional on the level of state capacity measure.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4244901/v1/70159af06d61bab0ab5cb5ed.png"},{"id":58222855,"identity":"7eaf1a8b-340c-486d-aab0-be4f8fcd27d7","added_by":"auto","created_at":"2024-06-12 17:08:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1063529,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4244901/v1/1d2098f0-aefe-4a1c-acb2-710dbd57bc58.pdf"},{"id":54822828,"identity":"c80c4e28-a552-45ab-91d2-dcbeb4772374","added_by":"auto","created_at":"2024-04-17 09:08:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":47551,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-4244901/v1/a797c35c3d83a4a1155b9a63.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Political Polarization and Economic Growth ","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePolitical polarization is central to understanding contemporary politics and society. Hence, many studies have explored the conceptualization and measurement of political polarization, whereas others have characterized its nature and origins (Abramowitz and Saunders \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Fiorina and Abrams \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hetherington \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Druckman et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Iyengar et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Iyengar and Westwood 2014; Poole and Rosenthal \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). Related research has also examined the effect of political polarization on the quality of democracy (Graham and Svolik \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; McCoy and Somer \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Orhan \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For instance, political polarization can result in a backsliding of democracy because it divides citizens into opposing blocs: one group always supports the policies of the party with which it is affiliated but blindly opposes those of the opposing party without properly considering its substance.\u003csup\u003e1\u003c/sup\u003e In sharply divided societies, voters may place partisan interests (or policy preferences) above democratic principles (Graham and Svolik \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePolitical polarization has also attracted the attention of economists. They found that political polarization increases economic policy uncertainty as well as the volatility of economic variables (Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), reduces the size of government (Lindqvist and \u0026Ouml;stling 2010), and affects institutional quality (Keefer and Knack \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Melki and Pickering \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The prior research shows that democratic countries have experienced different trajectories of political polarization (Draca and Schwarz \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Boxell et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, only a few studies have examined the effect of political polarization on economic growth (Azzimonti \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, 2018). Azzimonti (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) uses a theoretical model to show that, by increasing barriers to private investment, political polarization decreases economic growth. Furthermore, Azzimonti (2018) develops a partisan conflict index based on newspaper articles and finds a negative correlation between this index and aggregate investment in the United States (US hereafter). Nevertheless, these works do not empirically explore whether political polarization affects economic growth.\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis paper makes three contributions. First, we provide the first empirical evidence of the effect of political polarization on economic growth. According to partisan theory, left- and right-wing politicians adopt economic policies that reflect the preferences of their constituents (Potrakfe \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For instance, left-wing governments tend to promote expansionary policies, while right-wing governments are more active in privatization and market deregulation (Alesina \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Hibbs \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1977\u003c/span\u003e; Bj\u0026oslash;rnskov \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Castro and Martins 2018; Potrakfe \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). When parties with widely different ideologies alternate in power, political turnover generates economic policy uncertainty, which, in turn, raises variability about the returns on investment (Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Therefore, ideological polarization is likely to influence real economic outcomes. However, previous empirical studies have mainly focused on the effect of the mean value of ideology, rather than the distribution of ideology\u0026mdash;that is, political polarization (e.g., Bj\u0026oslash;rnskov \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSecond, we fill a gap in the literature by examining the transmission mechanisms through which political polarization influences economic growth. One channel suggested by Azzimonti (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, 2018) is private (corporate) investment. Nevertheless, other determinants of economic growth, such as investment in human capital and total factor productivity (TFP), have not been considered systematically, although the literature on economic growth suggests that the majority of variation in real gross domestic product (GDP) per capita across countries can be explained by these factors (Solow \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e1956\u003c/span\u003e; Lucas \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Easterly and Levine \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThird, we investigate the impact of state capacity, defined as the government\u0026rsquo;s ability to achieve its intended policy goals, on the relationship between political polarization and economic growth. Given that state capacity may reduce economic policy uncertainty, one might argue that countries with greater state capacity can moderate the negative effect of polarization on growth more effectively. Yet, this hypothesis has not been empirically explored.\u003c/p\u003e \u003cp\u003eUsing the World Values Survey (WVS) and European Values Survey (EVS), we create a panel dataset of 75 countries for six non-overlapping five-year periods from 1990 to 2019 (1990\u0026ndash;1994, 1995\u0026ndash;1999, 2000\u0026ndash;2004, etc.). As our measure of political polarization, we use the dispersion of self-reported political ideology, as well as the dispersion of responses to economic policy questions, ranging from 1 (left) to 10 (right).\u003csup\u003e3\u003c/sup\u003e The main dependent variable is the log of real GDP per capita. To examine the transmission mechanisms, we employ four alternative dependent variables: per capita private investment, per capita government investment, a human capital index, and TFP. To measure state capacity, we use government effectiveness, regulation quality, and the rule of law obtained from the World Governance Indicators (WGI).\u003c/p\u003e \u003cp\u003eTo address the potential endogeneity problem in estimating the causal effect of polarization on economic growth, our empirical strategy employs the system generalized method of moments (GMM) estimator and instrumental variables (IV) approach. In the IV approach, our instruments include the leader\u0026rsquo;s extraordinary personal characteristics, such as trustworthiness, that can bridge deep political divides. For instance, after being elected president of South Africa in 1994, Nelson Mandela united a severely divided country partly through his personal traits of respect and inclusion (International Foundation for Electoral Systems 2003). The \u0026ldquo;person of the leader\u0026rdquo; variable is newly available from the Varieties of Democracy (V-Dem) dataset. Moreover, we use an alternative instrument based on the person of the leader but uncorrelated with populism, in order to address the concern that the \u0026ldquo;person of the leader\u0026rdquo; may be a populist, which can affect growth in the long run (Funke et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWe find that political polarization has a robust, negative effect on per capita real GDP. In terms of the magnitude of the effect, an increase in a polarization measure of one standard deviation, based on self-reported political ideology, would be associated with a decrease in per capita real GDP of 3.2%. Our results are robust to alternative measures of political polarization based on economic issues of the left and right: equality, government ownership, government responsibility, and competition. Our results are also robust to alternative methods of constructing polarization measures, such as the measure developed by Esteban and Ray (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), and to the inclusion of economic polarization, measured by the dispersion of self-reported income scale, and ethnic fractionalization.\u003c/p\u003e \u003cp\u003eWe show that polarization negatively affects private investment, human capital investment, and TFP. In other words, these three variables provide a transmission mechanism that links political polarization to economic growth. Finally, we find that in countries with high state capacity (measured by government effectiveness, regulatory quality, and rule of law), polarization has a smaller effect on per capita real GDP.\u003c/p\u003e \u003cp\u003eThe remainder of this paper is organized as follows. Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e explains the influence of political polarization on economic growth. Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e describes the data, and Section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e4\u003c/span\u003e explains the empirical strategy and reports the main empirical results. Section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents results from the robustness checks. Section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e6\u003c/span\u003e discusses the transmission mechanisms linking political polarization to GDP. Section \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003e7\u003c/span\u003e examines the extent to which state capacity moderates the detrimental effect of polarization on growth. Section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e8\u003c/span\u003e concludes.\u003c/p\u003e"},{"header":"2. Links between political polarization and growth","content":"\u003cp\u003eThe key drivers of per capita economic growth are physical capital accumulation, human capital accumulation, and technological development. The literature on political polarization discusses its effect on physical capital accumulation more extensively than the other two. For example, Azzimonti (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, 2018) found that polarization depresses private investment. This finding is in line with the argument that intense political disagreement about fiscal policy (e.g., the size and composition of government) discourages private investment by increasing fiscal policy uncertainty such as larger swings in spending and revenue (Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Azzimonti 2018).\u003csup\u003e5\u003c/sup\u003e In general, higher political polarization induces greater economic policy uncertainty, which, in turn, generates variability about the returns on private investment and affects real economic outcomes (Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Baker et al. 2020; Frye \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003csup\u003e6\u003c/sup\u003e Using the partisan conflict index based on lawmakers\u0026rsquo; disagreements about policy, Azzimonti (2018) showed that, in the US, partisan discord is negatively associated with investment at the firm level.\u003csup\u003e7\u003c/sup\u003e Political polarization is also likely to lower the expected return on investments by reducing the quality of policy reforms that may prevent negative shocks to the economy (Alesina and Drazen \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Azzimonti 2018; Kim and Pirtilla, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Frye \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). For instance, governments in polarized and unstable societies have fewer incentives to implement legal reforms to protect property rights, thus reducing investment (Svensson \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThere is also debate over whether political polarization increases the size of government. Polarization may increase the utility loss from losing office\u0026mdash;that is, from seeing the opposition party\u0026rsquo;s platform implemented (Alt and Lassen \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Azzimonti \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003csup\u003e9\u003c/sup\u003e Hence, the incumbent has a stronger incentive to overspend and be reelected. Because overspending is financed by distortionary taxes, greater government spending reduces investment (Azzimonti \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In contrast, some studies have found that political polarization negatively affects the size of government (Lindqvist and \u0026Ouml;stling 2010; Bellani and Scervini \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In particular, Lindqvist and \u0026Ouml;stling (2010) measured polarization by the dispersion of self-reported political preferences and showed that political polarization is associated with smaller government in democracies. In line with this finding, Bellani and Scervini (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) used a panel of 23 European countries to show that heterogeneity in preferences for redistribution reduces redistributive expenditure.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLess attention has been paid to the effect of political polarization on human capital accumulation, one of the key drivers of per capita income growth. Like investment in physical capital, investment in human capital depends on the expected returns on the investment (Aisen and Veiga \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Political polarization is likely to reduce the expected returns from investing in human capital because it increases uncertainty about future policy and thus returns on education. This may even induce economic agents with high levels of human capital to migrate to other countries (Gyimah-Brempong and Camacho \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, related research found that polarized societies tend to have lower productivity because polarization increases transaction costs by increasing the social distance between individuals in the economy and elevating social conflict (Gradstein and Justman \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Alesina et al. 1999; Easterly and Levine 1997; Layman and Carsey \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Esteban and Schneider \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Similarly, diversity in cultural values (e.g., trust and norms) negatively affects regional economic development (Beugelsdijk et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In this way, political polarization may influence productivity because political preferences are related to social preferences.\u003c/p\u003e"},{"header":"3. Data","content":"\u003cp\u003eOur measure of political polarization is based on respondents\u0026rsquo; self-reported political ideologies, ranging from 1 (left) to 10 (right), obtained from the WVS and the EVS. These two surveys, conducted independently, are designed to be compatible and comparable across countries and waves, and thus they are presented as an integrated dataset. Although the coverage varies depending on the wave, the integrated dataset covers a wide range of countries across waves.\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo illustrate the evolution of political polarization over time, Panels (a)-(d) of Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e present the distributions of political ideology in Wave 2 (approximately 1990) and Wave 7 (approximately 2017) for France, Mexico, South Korea, and the US, respectively. The figure shows that, for each country, the distribution has evolved differently across waves. For instance, between Waves 2 and 7, Mexico and the US experienced a large increase in the share of respondents with two extreme values in the political spectrum. In particular, consistent with the existing evidence, the increase in the US polarization is driven by a disappearing center (Draca and Schwarz \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In South Korea, the mean distribution of the political spectrum shifted to the left between the two waves, whereas in France, it shifted to the right.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003eTo measure polarization, we use the standard deviation of self-reported political ideologies, ranging from 1 (left) to 10 (right) by country and wave (Lindqvist and \u0026Ouml;stling 2010; Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Grechyna \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The standard deviation is the most common measure of the dispersion of a set of values because of its simplicity and transparency. However, one limitation of using the standard deviation is that it fails to consider whether responses are clustered into different groups (Lindqvist and \u0026Ouml;stling 2010). Following the previous literature, we use two alternative measures: (1) Esteban and Ray\u0026rsquo;s (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) measure of polarization, which takes into account the degree of clustering (rather than dispersion) and (2) the proportion of respondents who reply either 1 or 10.\u003c/p\u003e \u003cp\u003eAs alternative measures of political polarization, we use responses to multiple-choice questions that measure various left and right economic issues (Lindqvist and \u0026Ouml;stling 2010). Specifically, we use the question: \u0026ldquo;How would you place your views on this scale [from 1 to 10]?\u0026rdquo; for the following four statements.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEquality: from 1 = \u0026ldquo;Income should be made more equal\u0026rdquo; to 10 = \u0026ldquo;We need larger income differences as incentives.\u0026rdquo;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGovernment ownership: from 1 = \u0026ldquo;Government ownership of business should be increased\u0026rdquo; to 10 = \u0026ldquo;Private ownership of business should be increased.\u0026rdquo;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGovernment responsibility: from 1 = \u0026ldquo;The government should take more responsibility to ensure that everyone is provided for\u0026rdquo; to 10 = \u0026ldquo;People should take more responsibility for providing for themselves.\u0026rdquo;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCompetition: from 1 = \u0026ldquo;Competition is harmful. It brings out the worst in people\u0026rdquo; to 10 = \u0026ldquo;Competition is good. It stimulates people to work hard and develop new ideas.\u0026rdquo;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe main dependent variable is the log of per capita GDP in constant 2015 dollars obtained from the World Development Indicators (WDI). To investigate the transmission mechanism that links political polarization to growth, we employ four alternative dependent variables: real per capita private investment and real per capita general government investment from the International Monetary Fund, and a human capital index and TFP from the Penn World Tables\u0026nbsp;10.0.\u003csup\u003e13\u003c/sup\u003e To measure state capacity, which moderates the effect of polarization on growth, we use government effectiveness, regulation quality, and the rule of law from the WGI.\u003c/p\u003e \u003cp\u003eThe control variables are gross fixed capital formation (a proxy variable for the savings rate), trade openness (the sum of exports and imports divided by GDP), population growth, inflation, and urbanization, all taken from the WDI. In addition, we include the proportion of respondents with more than a low-level tertiary education from the WVS and the EVS.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur sample includes an unbalanced panel of 75 countries for six non-overlapping five-year periods from 1990 to 2019 (1990\u0026ndash;1994, 1995\u0026ndash;1999, 2000\u0026ndash;2004, etc.). All control variables except for low-level tertiary education are averaged over each five-year period. \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e Table A1 lists the 75 countries included in the final sample. \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e Table A2 presents summary statistics for the main variables used.\u003c/p\u003e"},{"header":"4. Empirical strategy and results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Empirical specification and main results\u003c/h2\u003e \u003cp\u003eTo test the effects of political polarization on economic growth, we consider a standard dynamic panel specification (Islam \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Acemoglu et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\text{ln}{y}_{i,t}={\\beta }_{1}\\text{ln}{y}_{i,t-1}+{\\beta }_{2}{POL}_{i,t-1}+{\\beta }_{3}{Mean}_{i,t-1}+{\\Phi }{X}_{it}+{\\alpha }_{i}+{\\theta }_{t}+{u}_{i,t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{ln}{y}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is the log of real GDP per capita for country \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(i\\)\u003c/span\u003e\u003c/span\u003e and time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(t\\)\u003c/span\u003e\u003c/span\u003e (which indexes five-year periods). \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({POL}_{i,t-1}\\)\u003c/span\u003e\u003c/span\u003e measures political ideology polarization, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Mean}_{i,t-1}\\)\u003c/span\u003e\u003c/span\u003e is the mean value of the responses. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is a vector of the standard control variables in the growth regression, as described in Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\alpha }_{i}\\)\u003c/span\u003e\u003c/span\u003e is a country fixed effect that absorbs the impact of any time-invariant country characteristics such as geography; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\theta }_{t}\\)\u003c/span\u003e\u003c/span\u003e denotes a set of period fixed effects to capture technological progress at the frontier, as well as any cyclical trends in the global economy; and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is the error term.\u003c/p\u003e \u003cp\u003eWe estimate Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) using both the fixed-effects estimator and the system-GMM estimator. Among these, we prefer the system GMM estimator developed by Blundell and Bond (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) for two reasons:\u003csup\u003e15\u003c/sup\u003e First, the presence of country fixed effects and the lagged dependent variable causes potential bias in the ordinary least squares (OLS) estimator (Nickell \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). This bias in our sample is unlikely to be small because the average length of the time-series in our panel is approximately 3.3 five-year periods. The GMM estimator controls for country unobserved heterogeneity as well as the bias from the lagged dependent variable.\u003c/p\u003e \u003cp\u003eSecond, the GMM estimator addresses the potential endogeneity problem in estimating the causal effect of polarization on GDP. For instance, voters might blame politics for poor economic performance, regardless of the party in power, which may weaken the ruling coalition and push voters to become more ideologically extreme (Mian et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Funke et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Then, political polarization would be the consequence, not the cause, of changes in economic performance (Dalgaard and Olsson \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Grechyna \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Another possibility is that time-varying unobservable variables may affect both political polarization and GDP.\u003c/p\u003e \u003cp\u003eWe use Windmeijer\u0026rsquo;s (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) correction for small sample bias in standard errors because the standard error estimates from a two-step estimation tend to be biased downward. For specification checks, we provide two tests of the system GMM estimator: a test for serial correlation in the first-differenced errors (null hypothesis: there is no second-order serial correlation in the first-difference residuals) and Hansen\u0026rsquo;s J test for overidentifying restrictions (null hypothesis: instruments are uncorrelated with the residuals).\u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of political polarization on real GDP per capita: main results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFixed effects\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eGMM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e1st stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e2nd stage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln per capita GDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.402***\u003c/p\u003e \u003cp\u003e(0.076)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.409***\u003c/p\u003e \u003cp\u003e(0.077)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.919***\u003c/p\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.924***\u003c/p\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.315***\u003c/p\u003e \u003cp\u003e(0.117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.294***\u003c/p\u003e \u003cp\u003e(0.093)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003cp\u003e(0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003cp\u003e(0.056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003cp\u003e(0.027)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.072*\u003c/p\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.072*\u003c/p\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.077**\u003c/p\u003e \u003cp\u003e(0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.090**\u003c/p\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\widehat{\\text{P}\\text{O}\\text{L}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.445***\u003c/p\u003e \u003cp\u003e(0.140)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV(Charisma)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.084***\u003c/p\u003e \u003cp\u003e(0.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV(Egal.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.623***\u003c/p\u003e \u003cp\u003e(0.218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOP growth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003cp\u003e(0.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003cp\u003e(0.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.041**\u003c/p\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.047***\u003c/p\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.123**\u003c/p\u003e \u003cp\u003e(0.060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003cp\u003e(0.044)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFCF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.007**\u003c/p\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007**\u003c/p\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007**\u003c/p\u003e \u003cp\u003e(0.003)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002***\u003c/p\u003e \u003cp\u003e(0.0008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002***\u003c/p\u003e \u003cp\u003e(0.0008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00078**\u003c/p\u003e \u003cp\u003e(0.00032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0008*\u003c/p\u003e \u003cp\u003e(0.0004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.101*\u003c/p\u003e \u003cp\u003e(0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.100*\u003c/p\u003e \u003cp\u003e(0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003cp\u003e(0.071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003cp\u003e(0.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003cp\u003e(0.093)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.113**\u003c/p\u003e \u003cp\u003e(0.056)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0002\u003c/p\u003e \u003cp\u003e(0.0002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0002\u003c/p\u003e \u003cp\u003e(0.0002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0008\u003c/p\u003e \u003cp\u003e(0.0006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003cp\u003e(0.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003cp\u003e(0.013)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003cp\u003e(0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003cp\u003e(0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e(0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003cp\u003e(0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWave dummy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR(1) / AR(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.017/0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008/0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHansen test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKleibergen-Paap\u003c/p\u003e \u003cp\u003eF-statistics [p-value]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.41\u003c/p\u003e \u003cp\u003e[0.000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHansen\u0026rsquo;s J test [p-value]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.623\u003c/p\u003e \u003cp\u003e[0.105]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. countries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNotes. The dependent variable is real GDP per capita (in natural logs). POL is the level of political polarization based on the self-reported political ideologies. MEAN is the average level of political ideology. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eColumns 1 through 4 of Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the fixed effects estimates (Columns 1 and 2) and the GMM estimates for real GDP per capita (Columns 3 and 4).\u003csup\u003e17\u003c/sup\u003e Columns 1 and 3 include polarization and a set of control variables, and Columns 2 and 4 add the mean value of the political spectrum because polarization might be correlated with the mean value of the responses (Lindqvist and \u0026Ouml;stling 2010). All four columns show that political polarization, measured by the standard deviation of the political spectrum, ranging from 1 (left) to 10 (right), is negatively associated with per capita real income. In Columns 1 through 4, political polarization (POL) has a negative and statistically significant effect on real GDP per capita. Based on Column 4, our preferred specification, evaluated at the mean, a one standard deviation shock to POL is associated with a 3.2% decline in real GDP per capita.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e4.2 IV estimations\u003c/h2\u003e \u003cp\u003eWe further address the endogeneity problem using an instrumental variables (IV) approach. We use two external instruments for political polarization: (1) the person of the leader (personal characteristics, such as charm and trustworthiness) and (2) the egalitarian component index (a measure of equal protection of rights and freedoms and equal access to power across all social groups), both obtained from the V-Dem dataset.\u003csup\u003e18\u003c/sup\u003e In more detail, in V-Dem, person of the leader is measured by the question \u0026ldquo;To what extent is the chief executive portrayed as being endowed with extraordinary personal characteristics and/or leadership skills (e.g., as father or mother of the nation, exceptionally heroic, moral, pious, or wise, or any other extraordinary attribute valued by the society)?\u0026rdquo; The egalitarian component index is measured by the question: \u0026ldquo;To what extent is the egalitarian principle achieved?\u0026rdquo; The egalitarian principle of democracy is achieved when (1) the rights and freedoms of individuals are protected equally across all social groups, (2) resources are distributed equally across all social groups, and (3) access to power is equally distributed by gender, socioeconomic class and social group.\u003c/p\u003e \u003cp\u003eIn order to be valid, IV in our study has to satisfy two criteria: it should affect political polarization and not directly affect economic growth. The \u003cem\u003eperson\u003c/em\u003e of the leader, our first instrument, can influence political polarization yet is not directly related to future economic performance. For instance, consider a charismatic leader who can unite different groups of people by bridging deep political divides and reducing mistrust among political opponents. One strand of political science literature emphasizes that a political leader\u0026rsquo;s personal traits, such as trustworthiness, are major determinants of political trust or public confidence in the political process (e.g., Citrin \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; Citrin and Green \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Greenstein \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003csup\u003e19\u003c/sup\u003e For example, after being elected president of South Africa in 1994, Nelson Mandela united a severely divided country in part through his personal characteristics of respect and inclusion (of all parties, including those no longer in power; International Foundation for Electoral Systems 2003). \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e Figure A1 shows that the distribution of political ideology in South Africa became less polarized in Wave 3 (survey year 1996) after Nelson Mandela took office, relative to the distribution in Wave 2 (survey year 1990). Note, however, that leaders with extraordinary personal characteristics are not necessarily related with higher economic growth. Additionally, there is little consensus about whether the emergence of extraordinary leaders is a direct consequence of economic circumstances.\u003c/p\u003e \u003cp\u003eThe egalitarian principle of democracy, our second instrument, reduces political polarization by protecting the rights and freedoms of individuals equally and ensuring equal access to power across groups with different ideologies (Dahl \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). For instance, equal protection of rights and freedoms across all groups can help minimize feelings of resentment and disenfranchisements among some groups, which is a source of polarization (Dahl \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Sigman and Lindberg 2018). In addition, equal distribution of power diversifies political leadership, which leads to less polarizing policies. However, the egalitarian principle does not appear to be directly relevant to GDP growth because it more relevant to the equal protection of rights and equal access to power than to the efficient allocation of resources.\u003c/p\u003e \u003cp\u003eBy separating the variations in polarization that are driven by the personality of the leader and the egalitarian principle of democracy, our IV strategy mitigates the potential for idiosyncratic changes in a country\u0026rsquo;s political institutions that are endogenous to GDP growth to bias our results (for a similar argument, see Acemoglu et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRobustness check using alternative political polarization measures, system GMM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln per capita GDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.889***\u003c/p\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.908***\u003c/p\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.895***\u003c/p\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.920***\u003c/p\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean_ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL_ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.088**\u003c/p\u003e \u003cp\u003e(0.034)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean_responsible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.043**\u003c/p\u003e \u003cp\u003e(0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL_responsible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.090**\u003c/p\u003e \u003cp\u003e(0.044)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean_compete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL_compete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.095*\u003c/p\u003e \u003cp\u003e(0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean_equality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022**\u003c/p\u003e \u003cp\u003e(0.011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL_equality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003cp\u003e(0.031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWave dummy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR(1)/AR(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.017/0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007/0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015/0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017/0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHansen test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. countries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes. The dependent variable is real GDP per capita (in natural logs). Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education, inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eColumns 5 and 6 of Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e present the results of estimating a two-stage least squares (2SLS) regression, employing the \u0026ldquo;person of the leader\u0026rdquo; and \u0026ldquo;egalitarian component index\u0026rdquo; from the V-Dem dataset as IVs. In Column 5, the first-stage regression results display that the estimated coefficients for \u0026ldquo;person of the leader\u0026rdquo; and \u0026ldquo;egalitarian component index\u0026rdquo; are negative and statistically significant. The first-stage F-statistic is 11.41, indicating that the instruments are relevant (Staiger and Stock 1997). In Column 6, the second-stage results show that the effect of POL on real GDP per capita is negative and significant. As expected, the IV estimate is larger in magnitude than the GMM estimate. Hansen\u0026rsquo;s J-test for over-identifying restrictions does not reject the null hypothesis of instrument validity.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Robustness checks","content":"\u003cp\u003eTo test the robustness of our main results, we consider a number of variations of the original model. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the results using alternative measures of political polarization. Following Lindqvist and \u0026Ouml;stling (2010), we employ polarization measures based on the responses to specific questions on economic policies from the WVS and the EVS on (1) government ownership, (2) government responsibility, (3) competition, and (4) equality. In Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, each column refers to the effect of the polarization measure based on the responses to each of the four economic policy questions. In Columns 1 through 3, political polarization has a negative and statistically significant effect on real GDP per capita. In Column 4, the effect of the polarization measure based on equality is statistically insignificant.\u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003eFor a further robustness check, we employ (1) Esteban and Ray\u0026rsquo;s (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) polarization measure, which considers clusters of responses and (2) a bipolarization measure, which is the share of respondents who answer either 1 or 10 (see Lindqvist and \u0026Ouml;stling 2010). Both measures are highly correlated with the standard deviation.\u003csup\u003e20\u003c/sup\u003e According to the results presented in Columns 1 and 2 of Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, both alternative measures of polarization have a robust and negative effect on per capita real GDP.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVarious robustness checks\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003eExcl. developed countries\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003eIncl. economic polarization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003eIncl. ethnic fractionalization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003e2SLS using alternative IV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsteban and Ray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.186**\u003c/p\u003e \u003cp\u003e(0.075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBipolarization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.454***\u003c/p\u003e \u003cp\u003e(0.159)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.074**\u003c/p\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.076**\u003c/p\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.102**\u003c/p\u003e \u003cp\u003e(0.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.296**\u003c/p\u003e \u003cp\u003e(0.140)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL_ECON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003cp\u003e(0.024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnic_Frac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003cp\u003e(0.119)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWave dummy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR(1) / AR(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.008/0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.009/0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007/0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.026/0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008/0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKleibergen-Paap\u003c/p\u003e \u003cp\u003eF-statistics [p-value]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.31\u003c/p\u003e \u003cp\u003e[0.001]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHansen test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. countries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNotes. The dependent variable is real per capita GDP (in natural logs). Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education, inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnother concern is that the relationship between political polarization and growth might be limited to developed counties. Because developed countries tend to be established (higher-quality) democracies, an increase in ideological polarization is more likely to lead to more frequent change in ruling parties in a group of developed countries, resulting in larger swings in economic policies. In Column 3 of Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, we show the results from excluding 22 developed countries from the sample.\u003csup\u003e21\u003c/sup\u003e The main results do not change qualitatively.\u003c/p\u003e \u003cp\u003eOne can argue that political polarization affects growth not independently but through economic inequality, as they are significantly correlated. In other words, the effect of political polarization might capture the effect of economic polarization if the two types of polarization are correlated with each other (McCarty et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Indeed, some studies have found that income inequality negatively influences economic growth (e.g., Alesina and Rodrik Perotti \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), but others maintained that the relationship between economic inequality and growth is either inconclusive or insignificant (e.g., Barro \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Benos and Karagiannis \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). To address this issue, we add economic inequality, POL_ECON, measured by the standard deviation of self-reported income on a scale from 1 (poor) to 10 (rich).\u003csup\u003e22\u003c/sup\u003e The results in Column 4 of Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e show that the coefficient of POL_ECON is small and insignificant whereas the coefficient of political polarization remains negative and significant.\u003c/p\u003e \u003cp\u003eWe also test whether political polarization affects growth through social polarization by controlling for ethnic fractionalization, a proxy for social polarization. We employ an annual ethnic fractionalization index from the Drazanova (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) dataset.\u003csup\u003e23\u003c/sup\u003e The results in Column 5 of Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e display that the effect of ethnic fractionalization is negative but statistically insignificant while the effect of political polarization remains negative and significant.\u003c/p\u003e \u003cp\u003eLastly, we deal with a potential concern with our IV estimates that one of our instruments for political polarization, the person of the leader, may be correlated with populism which might cause a decline in GDP per capita in the medium and long run (Funke et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this case, the person of the leader may be an invalid instrument as it directly affects economic growth. To address this concern, we first regress the person of the leader on the number of left-wing and right-wing populist incumbent governments during the past five years. We then use the residual as the instrument for polarization along with the egalitarian component index. In Column 6 of Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the 2SLS results show that the effect of POL on per capita real GDP is still negative and significant.\u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Here]\u003c/p\u003e"},{"header":"6. Transmission mechanisms","content":"\u003cp\u003eGiven our findings that political polarization undermines long-run growth, we subsequently examine the transmission mechanism that links political polarization to per capita real GDP. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the GMM estimates for the four alternative dependent variables: real per capita private investment (Column 1), real per capita government investment (Column 2), human capital investment per worker proxied by the human capital index (Column 3), and TFP (Column 4). The results indicate that POL has negative and significant effects on private investment, human capital investment, and TFP. In contrast, POL has a statistically insignificant effect on real government investment. Consistent with the discussions in Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, these results indicate that political polarization influences economic development mainly by depressing private investment and productivity (Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Azzimonti 2018).\u003csup\u003e24\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTransmission mechanisms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDep. Var.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eln PINV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eln GINV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eln HCAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eln TFP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln PINV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.756***\u003c/p\u003e \u003cp\u003e(0.086)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln GINV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.649***\u003c/p\u003e \u003cp\u003e(0.110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln HCAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.927***\u003c/p\u003e \u003cp\u003e(0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln TFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658***\u003c/p\u003e \u003cp\u003e(0.093)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003cp\u003e(0.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.065\u003c/p\u003e \u003cp\u003e(0.146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003cp\u003e(0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.189**\u003c/p\u003e \u003cp\u003e(0.090)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003cp\u003e(0.211)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.019*\u003c/p\u003e \u003cp\u003e(0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.070***\u003c/p\u003e \u003cp\u003e(0.026)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWave dummy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR(1) / AR(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.032/0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024/0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.017/0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.032/0.398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHansen test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. countries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes. Among the dependent variables, PINV is real per capita private investment, GINV is real per capita general government investment, HCAP is human capital investment per worker, and TFP is total factor productivity. POL is the level of political polarization based on self-reported political ideologies. MEAN is the average level of political ideology. Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education (except in Column 3), inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003eWe also calculate the relative contribution of each transmission component to the effect of political polarization on economic growth. \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e A3 and \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e Table A3 explain how we calculated the relative contribution of each transmission component. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that two large contributors to the effects of polarization on growth are TFP (which accounts for 43.8%) and private investment (which accounts for 37.3%).\u003c/p\u003e \u003cp\u003e[Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Here]\u003c/p\u003e"},{"header":"7. The effect of political polarization conditional on state capacity","content":"\u003cp\u003eState capacity may moderate the detrimental effect of polarization on growth because economic policy uncertainty is lower when the government can effectively implement appropriate policies and thus make credible commitments to investors (Acemoglu et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hendrix \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; North \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Hence, the effect of political polarization on economic growth might depend on state capacity.\u003c/p\u003e \u003cp\u003eState capacity is defined as the government\u0026rsquo;s ability to achieve its intended policy goals (Dincecco \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Dincecco and Katz \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; O\u0026rsquo;Reilly and Murphy \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). To measure it, we follow the literature and employ three indicators: government effectiveness, regulatory quality, and rule of law (Pritchett \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; O\u0026rsquo;Reilly and Murphy \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Government effectiveness refers to the quality of policy implementation and the credibility of the government\u0026rsquo;s commitment to these policies (Kaufmann et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Regulatory quality captures the government\u0026rsquo;s ability to implement sound policies that promote economic development (Kaufmann et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Lastly, the rule of law captures the extent to which people have confidence in the quality of contract enforcement, property rights, and the courts. All three indicators are obtained from the Worldwide Governance Indicators (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"https://v-dem.net\" target=\"_blank\"\u003ewww.govindicators.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.govindicators.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe add both a state capacity measure and its interaction term with polarization to Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and present the results in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. It shows the effect of polarization on per capita real GDP conditional on each measure of state capacity: government effectiveness, regulatory quality, and the rule of law. In all columns, the interaction terms are positive and significant, indicating that countries with high state capacity (i.e., effective government, high-quality regulation, and strong rule of law) tend to experience less effects of polarization on real GDP per capita than would be the case otherwise.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of political polarization conditional on state capacity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLagged ln per capita GDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.911***\u003c/p\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.884***\u003c/p\u003e \u003cp\u003e(0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.920***\u003c/p\u003e \u003cp\u003e(0.044)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003cp\u003e(0.034)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.072**\u003c/p\u003e \u003cp\u003e(0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.099**\u003c/p\u003e \u003cp\u003e(0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.059*\u003c/p\u003e \u003cp\u003e(0.032)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL * GEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.056*\u003c/p\u003e \u003cp\u003e(0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL * RQE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.066**\u003c/p\u003e \u003cp\u003e(0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOL * RLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.078*\u003c/p\u003e \u003cp\u003e(0.043)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.101\u003c/p\u003e \u003cp\u003e(0.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRQE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.099\u003c/p\u003e \u003cp\u003e(0.063)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.170\u003c/p\u003e \u003cp\u003e(0.108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWave dummy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAR(1)/AR(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001/0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001/0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002/0.226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHansen test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. countries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes. The dependent variable is real GDP per capita (in natural logs). Other control variables (not reported) include population growth, gross fixed capital formation (GFCF), trade openness, tertiary education, inflation, and urbanization. All columns include country fixed effects and wave dummies. Robust standard errors are reported in parentheses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e Here]\u003c/p\u003e \u003cp\u003ePanels (a)-(c) of Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate variations in the effect of polarization on GDP with the degree of government effectiveness, rule of law, and regulatory quality, respectively. The figures show the 90% confidence interval for the relationship between polarization and per capita GDP, conditional on the level of state capacity measures. At low levels of state capacity, the point estimate is negative and significant at the 10% level as the confidence intervals are below the zero line (Brambor et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The effect of polarization turns statistically insignificant at higher levels of state capacity. For instance, a one-standard-deviation increase in polarization would reduce real GDP per capita by about 5% in Zimbabwe (whose average government effectiveness score is -1.29). However, the polarization effect is statistically insignificant for the US (whose average government effectiveness score is 1.54). In other words, the effectiveness of the US government has been able to prevent large political polarization from undermining economic growth.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese findings indicate that political polarization is more likely to hamper growth in countries with low state capacity, as measured by an ineffective government, low-quality regulation, and weak rule of law.\u003c/p\u003e \u003cp\u003e[Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Here]\u003c/p\u003e"},{"header":"8. Conclusions","content":"\u003cp\u003ePolitical polarization is regarded as a key phenomenon in contemporary democracies. A vast body of literature suggests that this is a serious underlying problem that affects various aspects of democratic systems. Previous research has found that political polarization decreases the quality of political parties and the government. Although political polarization has recently attracted much attention from economists, few papers address its economic effects.\u003c/p\u003e \u003cp\u003eThis study raises three questions: Does political polarization reduce economic growth? If so, what are the channels through which polarization results in lower growth rates? Does state capacity mitigate the adverse effect of polarization on the economy?\u003c/p\u003e \u003cp\u003eUsing polarization measures based on self-reported ideologies from the WVS and EVS, we found a robust negative correlation between political polarization and economic growth. The magnitude of this effect is considerable. This result remains robust to different estimation methods (GMM and IV) and various measures of political polarization. The effect of political polarization on growth is sizable. Based on the system GMM estimates, an increase of one standard deviation in the polarization measure is associated with a 3.2% decrease in per capita GDP. We also reveal a transmission mechanism that translates polarization into lower economic growth. The results suggest that polarization reduces growth not only through physical investment but through human capital investment and productivity. Moreover, we find that strong state capacity, such as effective government, high-quality regulation, and strong rule of law, prevents polarization from dampening growth. These findings indicate that the combination of political polarization and weak state capacity poses an important threat to economic growth.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKang ,Kim, and Lee wrote and reviewed the main manuscript. Kang and Lee ran regressions and reported the empirical results, and Kim reviewed the results and made comments. All authors participated in the revision of the first draft.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe World Values Survey (WVS) and European Values Survey (EVS) can be accessed https://www.worldvaluessurvey.org/wvs.jsp and https://europeanvaluesstudy.eu/, respectively.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbramowitz, A.I. and K.L. Saunders, 2008. Is polarization a myth? \u003cem\u003eJournal of Politics\u003c/em\u003e 70(2), 542-555.\u003c/li\u003e\n\u003cli\u003eAcemoglu, D., S. Johnson, and J.A. Robinson, 2010. The colonial origins of comparative development: An empirical investigation. \u003cem\u003eAmerican Economic Review\u003c/em\u003e 91(5), 1369-1401. \u003c/li\u003e\n\u003cli\u003eAcemoglu, D., S. Naidu, P. Restrepo, and J.A. Robinson, 2019. Democracy does cause growth. \u003cem\u003eJournal of Political Economy\u003c/em\u003e 127(1), 47-100.\u003c/li\u003e\n\u003cli\u003eAisen, A. and F.J. 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A finite sample correction for the variance of the linear two-step GMM estimator. \u003cem\u003eJournal of Econometrics\u003c/em\u003e 126(1), 25-25.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e There are some works emphasizing the positive aspects of political polarization. For example, political polarization at the elite level may facilitate more consistent political attitudes by providing voters with clear ideological differences between major parties (Levendusky \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hetherington \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Pierce and Lau \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In addition, the related literature examines the effect of political instability (e.g., measured by political violence and cabinet changes) on economic growth (Aisen and Veiga \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Alesina et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Alesina and Perotti \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Barro \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Jong-A-Pin \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, political polarization and political instability (a multidimensional concept) are two different concepts.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The question asks: \u0026ldquo;In political matters, people talk of the left and the right. How would you place your views on this scale, generally speaking?\u0026rdquo; Respondents are instructed to choose a number between 1 and 10, where 1 is labeled \u0026ldquo;Left\u0026rdquo; and 10 is labeled \u0026ldquo;Right\u0026rdquo;.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Populism is a political style focused on the struggle between the people and the elite (Funke et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The concept may overlap with other leader characteristics such as charisma.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Investment decisions are delayed to the extent that investment requires fixed upfront costs and is irreversible (Azzimonti 2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Political turnover in polarized societies generates uncertainty in economic policies because parties with widely different ideologies alternate in power (Azzimonti and Talbert \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Woo (2003, 2005) similarly showed that social polarization measured by income inequality causes larger fiscal deficits and more volatile fiscal outcomes, and thus lower economic growth.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Additionally, political polarization may undermine democracy because even voters who value democracy may trade off democratic principles for partisan interests to elect politicians whom they support (Svolik 2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The utility loss increases with the distance between the platforms of the incumbent and the opponent (Alt and Lassen \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The heterogeneity in preferences for redistribution is measured by the share of individuals who take extreme positions on the Likert scale, i.e., the share of individuals who respond \u0026ldquo;strongly agree\u0026rdquo; or \u0026ldquo;strongly disagree\u0026rdquo; to the statement \u0026ldquo;The government should take measures to reduce differences in income levels.\u0026rdquo;\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The number of countries in the dataset is 24 in Wave 1 (1981\u0026ndash;1983), 43 in Wave 2 (1990\u0026ndash;1992), 55 in Wave 3 (1995\u0026ndash;1998), 71 in Wave 4 (2000\u0026ndash;2004), 82 in Wave 5 (2005\u0026ndash;2008), 60 in Wave 6 (2010\u0026ndash;2014), and 81 in Wave 7 (2017\u0026ndash;2022). In all, the integrated dataset, from 1981 to 2017, covers 115 countries, including more than 645,000 interviews.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e We recode all the questions so that a higher number indicates the right.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The human capital index is based on the average years of schooling and an assumed rate of return to education.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The data are available for a larger sample of countries than the secondary enrolment rate in the WDI.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The system GMM is derived from the estimation of a system of two simultaneous equations, one in levels (with lagged first differences as instruments) and the other in first differences (with lagged levels as instruments) (Blundell and Bond 1997).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e To address the problem of too many instruments, we limit the instruments for the lagged dependent variable to the second lag. We also limit the instruments for some explanatory variables to the second to fourth lags in most specifications, and collapse instruments for others (Roodman \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In Columns 1 and 2, robust standard errors are clustered by country to account for country-level serial correlation.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e V-Dem, which refers to Varieties of Democracy, attempts to conceptualize and measure democracy in a multidimensional way (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://v-dem.net\u003c/span\u003e\u003cspan address=\"https://v-dem.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In the robustness check section, we address the potential concern that the person of the leader may be correlated with populism, a political style focused on the struggle between the people and the elite, which might directly cause a decline in GDP per capita in the medium and long run (Funke et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The correlation between POL and Esteban and Ray\u0026rsquo;s measure is 0.92, and the correlation between POL and Bipolarization is 0.89.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The countries include Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Luxembourg, the Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom, and the United States.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e We do not use the Gini coefficient because some countries do not report it during the sample period.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Drazanova (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) dataset covers 162 countries for the 1945\u0026ndash;2013 period. We use the index value of 2013 as the value of 2015.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e According to the IV estimates for transmission mechanisms, POL has negative and significant effects on private and human capital investments, while the effects of POL on government investment and TFP are statistically insignificant. These results are available upon request from the authors.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"economic growth, political polarization, investment, total factor productivity, state capacity","lastPublishedDoi":"10.21203/rs.3.rs-4244901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4244901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the effect of political polarization, measured by the dispersion of self-reported political ideologies, on economic growth. Using a panel of 75 countries from 1990 to 2019, we find that political polarization has a negative effect on economic growth through its effect on private investment, human capital investment, and total factor productivity. We reveal that state capacity—the government’s ability to achieve intended policy goals—mitigates the adverse effect of polarization.\u003c/p\u003e\n\u003cp\u003eJEL Classifications: D72, O47.\u003c/p\u003e","manuscriptTitle":"Political Polarization and Economic Growth ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-17 09:08:19","doi":"10.21203/rs.3.rs-4244901/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"965bbae3-a403-4e67-8f44-a2f44cbb7b58","owner":[],"postedDate":"April 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-12T17:00:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-17 09:08:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4244901","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4244901","identity":"rs-4244901","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}