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Political Polarization and the Size of Government

Published online by Cambridge University Press:  27 August 2010

ERIK LINDQVIST*
Affiliation:
Stockholm School of Economics and Research Institute of Industrial Economics
ROBERT ÖSTLING*
Affiliation:
Stockholm University
*
Erik Lindqvist is Assistant Professor, Stockholm School of Economics, P.O. Box 6501, SE-113 83 Stockholm, Sweden and Research Associate, Research Institute of Industrial Economics, P.O. Box 55665, SE-102 15 Stockholm, Sweden (erik.lindqvist@hhs.se).
Robert Östling is Assistant Professor, Institute for International Economic Studies, Stockholm University, SE-106 91 Stockholm, Sweden (robert.ostling@iies.su.se).
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Abstract

In this article, we study the relationship between political polarization and public spending using the dispersion of self-reported political preferences as our measure of polarization. Political polarization is strongly associated with smaller government in democratic countries, but there is no relationship between polarization and the size of government in undemocratic countries. The results are robust to a large set of control variables, including gross domestic product per capita and income inequality.

Type
Research Article
Copyright
Copyright © American Political Science Association 2010

Countries differ widely in the extent to which they rely on the government to allocate resources, goods, and services. For example, government consumption in the year 2000 amounted to 34.3% of total consumption in Sweden as compared to 17.6% in the United States (Gwartney and Lawson Reference Gwartney and Lawson2008). Such large differences in government size are hard to reconcile with the standard political economy model of redistribution (Meltzer and Richard Reference Meltzer and Richard1981), where the size of government is determined by the economic interest of the median voter.Footnote 1 However, more recent research in economics and political science has suggested that the size of government is also determined by the dispersion or polarization of political preferences.

For example, polarization can affect political decision making within governments and legislatures. Veto player theory (Tsebelis Reference Tsebelis2002) predicts fewer changes in the budget in countries where the government consists of several parties and the ideological distance between parties is large. Alesina, Baqir, and Easterly (Reference Alesina, Baqir and Easterly1999) show that disagreement about the appropriate use of public spending leads to lower spending if the size of the budget is decided before its composition. Following Alesina and Tabellini (Reference Alesina and Tabellini1990) and Persson and Svensson (Reference Persson and Svensson1989), there are several articles that study the incentives of incumbent governments to limit future governments’ ability to tax and spend. Depending on the specific assumptions, this type of explanation can rationalize both negative (e.g., Svensson Reference Svensson1998) and positive (e.g., Azzimonti n.d.) relationships between polarization and size of government. Furthermore, polarization could lead to conflicts of interest among the poor that affect their ability to form coalitions for increased redistribution (Fernández and Levy Reference Fernández and Levy2008). Polarization might also be more directly related to preferences for redistribution. Similarity of attitudes and opinions has been shown to be positively related to altruism (e.g., Byrne Reference Byrne1961; Newcomb Reference Newcomb1961) and, therefore, potentially also to higher support for redistribution.

So far, empirical work on political polarization and economic outcomes has used indirect measures of political preferences based on income, ethnicity, or religion.Footnote 2 However, if political views do not follow straight from economic self-interest or group identification, polarization in terms of income, ethnicity, or religious beliefs may not fully capture the true level of political polarization.Footnote 3 In this article, we instead derive measures of political polarization based on voters’ self-reported political preferences. We then test whether these measures can explain differences in the size of government across countries.Footnote 4 Although it is unclear from a theoretical perspective whether the net effect of polarization on the size of government is positive or negative, our measures of political polarization based on survey data are strongly negatively related to the level of public spending.

Do these relationships reflect a causal effect of polarization on government size? An alternative explanation is that political polarization is instead affected by the size of government. As a simple test of the direction of causality, we divide the sample according to the level of democratic development. The idea is that voters must have a say in the political process for polarization in the electorate to affect spending decisions. Political polarization may be affected by government policies, but it is not obvious why this should depend on the level of democratic development. We find that the relationship between polarization and size of government is substantially stronger in democratic countries, supporting the view that polarization affects public spending rather than the other way around.

Figure 1 shows the relationship between one of our polarization measures (the standard deviation of responses to a question about government vs. individual responsibility) and government consumption as a fraction of total consumption for countries that are classified as “weak” or “strong” democracies, respectively. The correlation between polarization and size of government is clearly much stronger for strong democracies. Moreover, Figure 1 shows that the relationship is not driven by extreme values in a few countries.

FIGURE 1. General Government Consumption and Polarization (Standard Deviation of Government Responsibility Question) in Weak (left) and Strong (right) Democracies

The pattern in Figure 1 is suggestive, but it does not allow us to conclude that political polarization causes smaller government. There are three specific problems associated with testing the effect of polarization on the size of government that we address. First, our measure of political polarization may be correlated with some other factor that in turn affects size of government. For example, polarization is higher in countries that either are poor, are ethnically fragmented, or have a low level of trust. We show that our measure of political polarization remains a robust predictor of size of government when controlling for these factors, as well as a wide range of other variables.

Second, standard political economy models of redistribution (e.g., Meltzer and Richard Reference Meltzer and Richard1981) predict that political polarization is increasing in income inequality. If government spending affects income inequality, for example, by improving labor market opportunities for the poor, then this would give rise to an endogeneity problem (i.e., that political polarization is itself a function of the size of government). However, our results are robust to controlling for income inequality and using polarization measures that adjust for the distribution of income within countries.

Third, our measure of polarization may reflect uncertainty as to how to answer survey questions rather than genuine disagreement over economic policy. For example, it is conceivable that certain types of public spending (e.g., schooling) reduce the uncertainty respondents feel about how to respond to survey questions, thereby creating a spurious link between government size and political polarization. Our main test for this possibility is to calculate a measure of “ideological coherence”—the extent to which answers to questions of economic policy follow a certain pattern—and then use this measure as a control variable. We also perform additional robustness checks related to our use of survey data, but none of these tests change our results appreciably.

Having established that there exists a strong, robust correlation—and perhaps also a causal relationship—between political polarization and public spending, we devote the last section of the article to the question of why this relationship exists. Surprisingly, we do not find that countries with high levels of polarization among the electorate have more fragmented legislatures or governments in terms of the number and relative size of political parties. We do, however, find that the average level of polarization among the supporters of different political parties is higher in polarized countries. For example, the U.S. Congress is much more concentrated than the Swedish seven-party parliament in terms of the number of political parties, but the level of polarization is larger among the supporters of both the Democratic Party and Republican Party than within the entire Swedish electorate.

As a further test of why polarization is related to government size, we calculate the level of polarization among respondents who support a party in government and among supporters of opposition parties. Although there are several reasons to expect polarization among government supporters to affect size of government, it is not clear that polarization among supporters of the opposition should have a direct effect on size of government. We indeed find that polarization among government supporters is a stronger predictor of size of government than polarization among opposition supporters. We also find that the relationship between political polarization in the electorate and size of government is substantially stronger in democracies with fragmented governments or legislatures. This result is consistent with veto player theory (Tsebelis Reference Tsebelis2002); spending proposals are more likely to be vetoed when there are several parties that disagree about the proper course of action.

Our results should be interpreted with some caution. The association between political polarization and size of government is robust, but much work remains before we can establish whether this correlation reflects a causal effect of polarization on public spending and, if so, which is the main mechanism behind this relationship.

Before proceeding to the empirical analysis, we describe our measures of polarization and the outcome and control variables. Data sources and definitions of variables are provided in Appendix A. All empirical results not provided in the text are available online in a Supplementary Appendix, which is available at http://www.journals.cambridge.org/psr2010005.

DATA

Political Polarization

We base our measures of polarization on responses to multiple-choice questions from the World Values Surveys (WVS) (European Values Study Group and World Values Association 2006). We focus on the 2000 wave for most countries, but data from the 1995 wave are used for some countries so as to increase the sample size. The WVS is based on face-to-face interviews with about 1,000 respondents in 83 different countries, but 9 of these are not included in our analysis.Footnote 5 The included countries and the year when the survey was carried out are listed in Table A1 of Appendix A.

We consider four questions that, broadly speaking, measure various economic aspects of left and right on a 1-to-10 scale.Footnote 6 Table 1 displays the wording of each question. Two things are worth noting about the way the questions are formulated. First, the questions capture preferences for the size of government rather than the focus of public spending (with the question about competition as a possible exception). Second, all but the competition question ask whether the government should be larger or smaller than the status quo in each country. We return to these issues in what follows.

TABLE 1. Economic Policy Questions

The wording of the questions has been slightly abbreviated.

To compare the level of polarization across countries in a systematic way, we use the standard deviation as our main measure of polarization. The standard deviation is perhaps the most common measure of dispersion and has the advantage of being simple and transparent. A property of the standard deviation is that it does not depend on whether answers are clustered in distinct groups. In this sense, it is a measure of “dispersion” as much as “polarization.” To see why this may be important, consider the histogram of responses for the government responsibility (GOV) question in Brazil and Sweden shown in Figure 2. Clearly, by any sensible interpretation of “polarization,” Brazil is more polarized than Sweden with respect to respondents’ views about the proper size for government. Note that in the case of Brazil there are two distinct groups at each end point (the respondents who state “1” and “10,” respectively), whereas responses are spread out more evenly for Sweden. Esteban and Ray (Reference Esteban and Ray1994) developed a polarization measure that takes this into account. We therefore also calculate the level of polarization using Esteban and Ray's measure and a simple measure of bipolarization: the minimum of the proportion of respondents that answer “1” or “10.” These measures are highly correlated with the standard deviation (see Appendix B for a more detailed discussion of the different polarization measures).

FIGURE 2. Histogram of Responses to GOV Question in Brazil and Sweden

The economic policy questions are posed in different languages and contexts. Moreover, the fact that three of the questions relate to the current size of government is potentially problematic. For example, fewer people might prefer an increase in the size of government if the current size of government is large. Consequently, not only mean responses, but also polarization of preferences may depend on the size of government (e.g., larger size of government might generate agreement that government size should be reduced). The set of questions listed in Table 1 is therefore not ideal; it would have been better to use questions about the preferred absolute size of government rather than preferred changes from the status quo. However, as long as there is no censoring of responses and concentration of responses do not directly depend on the current size of government, the standard deviation is unaffected by whether questions refer to preferred changes from the status quo or preferences for the absolute size of government.Footnote 7 Table 2 also shows that the standard deviations calculated from the different economic policy questions are strongly correlated at the country level. The lowest correlation is 0.66 and the highest 0.86. The mean values are correlated to a much lower extent; the correlation ranges from −0.14 to 0.41. This suggests that it is much less of a problem that questions are country specific when focusing on the dispersion of responses rather than mean values.

TABLE 2. Pairwise Correlations of Standard Deviations

What characterizes countries with high or low degrees of political polarization? Table 3 lists the 10 countries with the highest and lowest standard deviations for the question about government responsibility (GOV). Perhaps surprisingly, Pakistan is the country with the lowest level of political polarization. This is not a peculiarity of this particular question. As shown in Table A1 in Appendix A, Pakistan also has a very low standard deviation for the other economic policy questions. However, Pakistan is among the countries with the lowest response rates. In the case of the government responsibility question, 37% of the respondents in Pakistan said that they did not know or gave no answer at all.Footnote 8 The other countries on the list are less surprising, with the Scandinavian countries among the 10 most cohesive and 5 Latin American countries among the most polarized.Footnote 9 Another indication that our measure of polarization captures something essential is that political polarization is relatively stable over time. The correlation between our polarization measures and polarization calculated from the previous wave of the WVS varies between 0.72 and 0.81 for the four questions.Footnote 10

TABLE 3. Countries with Lowest and Highest Levels of Political Polarization

Outcome and Control Variables

We focus on one broad measure of government size: general government consumption as a fraction of total consumption (GOVCONS). This measure has been compiled by Gwartney and Lawson (Reference Gwartney and Lawson2008), based on data from the World Bank and the International Monetary Fund. To reduce measurement error, we consider the average of the years 2003 to 2005. This measure captures the extent to which governments rely on political rather than private choice to allocate resources, but it could also reflect whether governments have the fiscal and legal capacity to collect tax revenue. As we see in the empirical analysis, our results for democratic countries are robust when controlling for gross domestic product (GDP) per capita, indicating that our results are unlikely to be driven by differences in tax-collecting capacity. We also report the main results using a measure of redistribution, transfers, and subsidies as a fraction of GDP (GOVTRANSSUB), which is obtained from the same source as the consumption measure. Naturally, this measure says nothing about the beneficiaries of redistribution. A high share of transfers and subsidies in the economy does not necessarily imply that the government redistributes resources from one group to another (e.g., from the rich to the poor). Keeping this caveat in mind, we nevertheless interpret this as a noisy measure of the level of redistribution.

We use the same basic set of control variables as Persson and Tabellini (Reference Persson and Tabellini2003, sect. 3.2.1) in their government size regressions. We divide the Persson and Tabellini controls into two categories: one set of control variables that are likely to be exogenous with respect to both polarization and government size, and one set that may be endogenous. The exogenous controls are geographic dummy variables and colonial origin. The regional dummies are Africa (AFRICA), South and East Asia (ASIAE), and Latin and South America and the Caribbean (LAAM). The colonial variables indicate British (COL_UKA), Spanish (COL_ESPA), or other colonial origin (COL_OTHA) weighted by years of independence. The variables that may be endogenous are logarithm of GDP per capita in 2000 (LYP), openness to trade in 2000 (TRADE), proportion of population between 15 and 64 (PROP1564) in 2000, proportion of population above 65 in 2000 (PROP65), a dummy variable indicating whether the country has a federal political structure (FEDERAL), and an indicator variable for Organisation for Economic Cooperation and Development (OECD) membership before 1993 with Turkey excluded (OECD). We include a number of additional control variables as robustness checks, but these are described further in connection with the results. The definitions and sources of all variables are listed in Table A2 in Appendix A.

ESTIMATION

In this section, we discuss our empirical strategy for investigating the relationship between polarization and size of government. Let yi denote a measure of government size in country i. To test whether political polarization is related to size of government, we run the regression

(1)

where Polarizationi is a measure of polarization in country i and Xi is a vector of control variables measured at the country level. Because polarization may be correlated with the mean value of responses, we control for the mean in all regressions. Higher levels of political polarization are associated with smaller government in case β < 0. There are three main issues associated with the estimation of β. (There are also some other issues related to income inequality and survey data that we address toward the end of the Results section.)

First, Polarizationi may be correlated with other variables that affect the size of government. We use three different specifications of the vector of control variables Xi to test for this possibility. In the “basic” specification, we only include the mean response as a control variable. In the “short” specification, we include the geographic and colonial controls from Persson and Tabellini (Reference Persson and Tabellini2003). In the “long” specification, we also include the potentially endogenous set of control variables (i.e., GDP per capita, openness to trade, federal political structure, OECD membership, and the two demographic variables). Note that by including endogenous variables in the regression, we control for mechanisms through which political polarization may affect size of government.Footnote 11 Comparing the estimate of β in the basic, short, and long specifications gives an indication of the robustness of the relationship between polarization and government size. We also perform further robustness tests by controlling for geographic, demographic, cultural, and political factors.

Second, political polarization may itself be affected by the size of government. Our main way of dealing with this problem is to divide the sample according to the level of democratic development. The idea is that government policy is more likely to be affected by polarization in democratic countries. Although political polarization may, in turn, be affected by government policies, it is not obvious why this should depend on the level of democratic development. A simple test of whether polarization causes smaller government is therefore to see whether the relationship between polarization and size of government is stronger in more democratic countries. We use the Polity IV democracy index (Marshall and Jaggers Reference Marshall and Jaggers2007) and classify the 30 countries with a democracy score (DEMOC) of 9 to 10 as “strong” democracies and the 39 countries with a score of 0 to 8 as “weak” democracies. We choose this particular cutoff in order to get roughly half of the countries in each group. The democracy index is not available for 5 countries, but we classify 3 of these countries as strong democracies, giving us a sample of 33 strong democracies in total.Footnote 12 As a robustness test, we divide the sample according to more inclusive criteria for “strong” democracies.

Third, the specification of regression (1) is problematic from both conceptual and statistical points of view for countries where respondents agree that the government should be kept at a minimum (or maximum). From a conceptual perspective, it is not possible for polarization to vary between countries where all citizens favor minimal government because polarization is then always zero. From a statistical point of view, it is difficult to disentangle the effect of polarization from the effect of changing the mean when responses are close to the end points of the scale.Footnote 13 Fortunately, there is no country in our data with a mean value of responses close to the end points of the scale or where the actual size of government is negligible.Footnote 14 For example, there are only two countries with a mean response below 4 and no country with a mean response above 8 for the GOV question.Footnote 15 We have done robustness checks where we remove the countries with the two highest or two lowest mean values from the data, but because the results remain essentially unchanged, we do not discuss them further.Footnote 16 Another indication that extreme mean values are not a serious problem is that the correlations between mean and standard deviation are low for the economic policy questions. The exception is the question regarding private ownership of business (PRIVATE), where the correlation is 0.44.Footnote 17

RESULTS

We first report the results from our three main specifications of control variables for different levels of democratic development. We then perform robustness tests with respect to additional control variables, income inequality, and issues related to our use of survey data. In the following section, we discuss theoretical mechanisms suggested by previous literature. In the main text of the article, we focus on general government consumption (GOVCONS) as the measure of government size, which is the government size variable available for most countries (74 countries), but we also report the main result for transfers and subsidies (GOVTRANSSUB). Some results that we refer to in the text are not reported in the article, but these are available in the Supplementary Appendix.

The results from regression (1) for the three different specifications (basic, short, and long) tested on the three samples (all countries, weak and strong democracies) are shown in Table 4. Political polarization has a negative and statistically significant relationship with government consumption in the specifications with controls for the mean response and exogenous set of control variables, but the size of the coefficients and significance levels are reduced in the specification with the endogenous set of control variables. However, the results depend entirely on the level of democratic development. When the sample is restricted to strong democracies, the estimated effect of polarization on government consumption is statistically significant and robust to the different sets of control variables, whereas it is close to zero and statistically insignificant for the weak democracies.Footnote 18 The strength of the association between polarization and public spending is substantial in strong democracies. For example, an increase in our polarization measure with respect to the GOV question by one standard deviation predicts a decrease in government consumption as a share of total consumption by 4.0 percentage points. The corresponding estimate varies between 2.0 and 6.1 percentage points for the other questions.

TABLE 4. Political Polarization and Government Consumption

Note: This table reports coefficients and heteroscedasticity robust standard errors for the standard deviation of each question for the three specifications discussed in the text.

*p = .10; **p = .05, ***p = .01.

As expected, the results for strong democracies get somewhat weaker, but are generally still statistically significant—when we use more inclusive definitions of strong democracies. The same also holds if we use the classification of democracies from the Polity IV project, which is based on the Polity score (POLITY). According to this classification, 51 countries are defined as democracies. However, because there are so few countries in the nondemocracy category, it is difficult to make an inference about heterogeneous effects based on this classification.

An alternative explanation for the stronger relationship between polarization and size of government in strong democracies is that polarization is measured with more error in weak democracies, thus exacerbating attenuation bias. To adjust for measurement error, we instrument polarization in weak democracies with polarization from the most recent prior wave of the WVS. The estimates from these regressions are imprecise due to the limited number of observations, but the size of the point estimates does not indicate that the results for weak democracies are due to problems of measurement.Footnote 19

We interpret the stronger effect of polarization in democracies as suggestive evidence that there is a causal effect of polarization on the size of government. However, the possibility that polarization is affected by size of government cannot be ruled out. In particular, a larger size of government may induce respondents to agree that government should not expand, thereby generating a correlation between government size and polarization (see the discussion in the Data section). Because democratic countries on average have larger public sectors, this mechanism could potentially account for the stronger correlation between polarization and size of government in democracies. Although we cannot completely rule out this alternative explanation, there are two reasons why we find it less plausible. First, the results are similar for the question about attitudes toward competition (COMP), which is stated in absolute terms. Second, government size is not systematically related to a desire for smaller government (in terms of the mean responses). For example, people tend to favor a higher level of redistribution (as measured by the EQUALITY question) the larger is the size of government. This does not fit well with the idea that the low level of polarization in countries with large public sectors is caused by a general agreement that the size of government ought to be reduced.

Polarization is also associated with smaller governments when regression (1) is estimated using government transfers and subsidies as the dependent variable instead of government consumption. For strong democracies, political polarization is associated with lower levels of redistribution, whereas there is no relationship between polarization and redistribution in weak democracies. Political polarization is not statistically significant in the short specification for strong democracies, but statistically significant in three out of four cases in the long regression. The reason is that GDP per capita is not controlled for in the short specification. Conditional on the set of exogenous control variables (i.e., the variables in the short specification), richer countries have lower levels of redistribution. As poorer countries are also more polarized on average, not controlling for GDP per capita leads to an omitted variable bias toward zero in the short specification.

The relationship between polarization and size of government changes very little when we replace the standard deviation with the alternative polarization measures discussed in the Data section.Footnote 20

As the effect of polarization on government consumption is only present in strong democracies, we focus on this subsample for the remainder of the article. To provide a more complete description of our results, Table 5 shows the estimated coefficients for all control variables when the sample is restricted to strong democracies.Footnote 21 We now turn to robustness checks with respect to additional control variables, income inequality, and survey data.

TABLE 5. Political Polarization and Government Consumption (Strong Democracies)

Note: This table reports coefficients and heteroscedasticity robust standard errors for the standard deviation of each question for the three specifications discussed in the text.

*p = .10; **p = .05, ***p = .01.

Robustness: Additional Control Variables

Table 6 reports the results when we add additional controls to the long specification. The first set of controls is geographic factors: percent of mountainous terrain (MOUNTAIN), the logarithm of country areaFootnote 22 (AREA), and absolute distance to the equator (LATITUDE). The second set of controls includes additional demographic factors: the logarithm of total population (LOGPOP) and population density (POPDENS). We also include the average level of trust (TRUST), as well as measures of ethnic (ETHFRAC), religious (RELFRAC), and linguistic (LINGFRAC) fractionalization. Finally, we control for a number of political variables that have been found to explain the size of government in previous studies (e.g., Persson and Tabellini Reference Persson and Tabellini2003): whether the country has a presidential regime (PRES) and whether the legislature is elected under a majoritarian rule (MAJ). Note that we restrict the sample to strong democracies and that the degrees of freedom are small in these regressions, implying that standard errors become large. Overall, the relationship between polarization and size of government remains robust when additional control variables are included in the regression. It is also worth noting that none of the additional control variables are consistently statistically significant.

TABLE 6. Political Polarization and Government Consumption: Additional Control Variables (Strong Democracies)

Notes: All regressions include control variables from the long specification. This table reports coefficients and heteroscedasticity robust standard errors for the standard deviation of each question for the three specifications discussed in the text.

*p = .10; **p = .05, ***p = .01.

Robustness: Income Inequality

One concern with the estimates reported previously is that polarization of political preferences could be a direct consequence of income inequality, which in turn might be affected by the size of government.Footnote 23 For example, spending on public schooling for the poor is likely to reduce pretax income inequality. One way to control for this is to include a measure of income inequality in regression (1). As seen in Table 6, including the Gini coefficient (a measure of income inequality) in the long specification does not change the coefficients by much, with the competition (COMP) question as the exception. Note, however, that the Gini coefficient is strongly correlated with political polarization, implying that including the Gini index as a control exacerbates attenuation bias.Footnote 24

Another way to control for income inequality is to create an “income-adjusted” measure of political polarization. For each country and question, we run a regression of the respondents’ answers on the respondents’ income.Footnote 25 We then calculate new polarization measures for each country based on the residuals from these regressions. This gives us polarization measures based on political opinions orthogonal to personal income. The income-adjusted polarization measures are highly correlated with the nonadjusted polarization measures; all correlation coefficients are above 0.99. Not surprisingly, rerunning the regressions of government performance using the income-adjusted standard deviations yields very similar results. The reason for the small differences between the income-adjusted and ordinary polarization measures is the low explanatory power of stated income for political preferences. A potential explanation for this result is that income is measured with error in the WVS.Footnote 26

Robustness: Survey Data

A key problem in using survey data is that questions may not only capture differences in political preferences. In particular, the dimension of political conflict measured by our economic policy questions could be more salient in some countries than in others. If people do not perceive a question as capturing a relevant dimension of politics, then it seems plausible that they give it less thought, or that they are more uncertain about their preferences.Footnote 27 We perform two different tests to check whether political polarization is due to respondents’ uncertainty about their actual preferences.

First, we include the country response rate as a control variable in regression (1). The idea is that in countries where many people are uncertain about their preferences, more people will also state that they “don't know” what they think or not answer the question at all. As shown in Table 7, the estimated effect of polarization is practically unchanged when the response rate (PROPRESP) to each question is included as a control variable in the long specification.

TABLE 7. Political Polarization and Government Consumption: Survey Data Issues (Strong Democracies)

Notes: All regressions include control variables from long specification. This table reports coefficients and heteroscedasticity robust standard errors for the standard deviation of each question for the three specifications discussed in the text.

*p = .10; **p = .05, ***p = .01.

Second, we calculate the country-level correlations between individuals’ responses to the economic policy questions. For each question, we then calculate the country average of the absolute value of the correlations with the other questions. This measure (COHERENCE) captures countries’ “ideological coherence”—the extent to which responses to the questions follow a certain pattern—and we expect it to be lower the more uncertain people are about their political preferences.Footnote 28 Political polarization is negatively correlated with ideological coherence in both weak and strong democracies.Footnote 29 That is, the more polarized opinions are in a country, the lower is the correlation between responses to different questions. Moreover, ideological coherence is positively correlated with public spending.Footnote 30 However, as shown in Table 7, our results for polarization are robust to controlling for ideological coherence.Footnote 31 Ideological coherence has a positive sign in three out of four regressions, but the coefficients are never statistically significant.

The result that ideological coherence is higher in countries with a low level of polarization is reassuring in another sense. Because respondents may interpret questions in the political context of their own country, a potential concern is that political polarization is a consequence of partisan policies. For example, suppose that the government in a certain country redistributes income from group X to group Y. If people in this country think of “redistribution” as redistribution from X to Y, then measured preferences for redistribution may be polarized, even if the preferences are homogenous regarding some other redistribution scheme (say, from the rich to the poor). However, as shown previously, the estimated effect of polarization on government consumption is similar for all four questions, implying that partisan policies must shape opinions on these questions in order to invalidate our argument. The fact that the responses to the economic policy questions are more strongly correlated at the individual level in countries where polarization is low therefore indicates that divisive policies are not a main cause of the measured level of polarization.Footnote 32

A related concern is that people might be uncertain about the trustworthiness of politicians. Such uncertainty could give rise to an unwillingness to funnel resources to the public sector and, in case people have different beliefs about how trustworthy politicians are, polarization in stated preferences for the size of the public sector. To test this possibility, we include the average response to the WVS question regarding the confidence in parliament (CONFIDENCE) as an additional control variable in regression (1). We also use the level of corruption (CORRUPTION) within the political system as a proxy for the trustworthiness of politicians. As shown in Table 7, the results change very little from either of these tests.

A final concern with the use of survey data is that people might not want to deviate too much from the opinions of others. A respondent who wants to minimize the maximum deviation from other respondents will answer 5 or 6 provided that he or she does not know the responses of others. If so, responses would be centered around 5.5 in countries where people are concerned about conforming to others. Hence, we include the absolute deviation from 5.5 (CONSENSUS) as a control variable in regression (1) to serve as a rough control for “false consensus.” There is an additional reason to include CONSENSUS as a control variable. Mean values need not perfectly reflect the true mean of preferences if responses are centered at either end of the scale (e.g., 1 or 10 on a 1-to-10 scale). For example, consider two countries with normally distributed underlying distributions of preferences with the same mean. If the mean is above 5.5, the country with the highest standard deviation of the underlying distribution will have a lower observable mean because a larger share of respondents has their answers censored at 10. Hence, the measured standard deviation might be informative about the true mean of preferences, even if we control for the measured mean. Including the absolute deviation from 5.5 as an additional control variable is a rough way of controlling for this confounding factor. As it turns out, our results remain almost exactly the same when CONSENSUS is included as a control variable in the main specifications. Another indication that censoring is quantitatively unimportant is that there is no systematic relationship between the mean values (in terms of left or right) and government size in the basic specification of regression (1) reported in Table 5.

WHY IS POLARIZATION RELATED TO THE SIZE OF GOVERNMENT?

So far, we have shown that polarization in the electorate is strongly correlated with size of government in democratic countries. We also presented some tentative evidence that the relationship is causal. In the remainder of the article, we try to answer the question as to why polarization among voters is related to the level of public spending. Most of the theoretical mechanisms mentioned at the beginning of this article imply that polarization in the electorate translates into polarization in the legislature or government. We therefore first investigate the overall question of whether polarization in the electorate is related to polarization in the legislature/government and then proceed to discuss specific theories. There are also theoretical reasons for why polarization in the electorate could have a direct effect on public spending. We discuss these theories toward the end of the section.

Polarization in the Legislature and Government

A previous empirical literature measured polarization or fractionalization in the legislature and government based on the size and number of political parties. For example, Bawn and Rosenbluth (Reference Bawn and Rosenbluth2006) and Perotti and Kontopoulos (Reference Perotti and Kontopoulos2002) showed that a larger number of parties in government is associated with higher levels of public spending. In a similar spirit, we use the data about parties in the legislature and in government, as well as a classification of the ideology of parties from the Database of Political Institutions (Beck et al., Reference Beck, Clarke, Groff, Keefer and Walsh2001). We focus on five different measures: an index of government fractionalization (HERFGOV), an index of fractionalization in the legislature (HERFLEG), the number of political parties in government (NGOV), the number of political parties in the legislature (NLEG), and an index of the political polarization of parties in the legislature (LEGPOL). The first two measures are Herfindahl indexes calculated as the sum of the squared seat shares of all parties in the government/legislature and is thus higher the more concentrated is the government or legislature to a few large parties.Footnote 33 The number of parties in the legislature (NLEG) and government (NGOV) are simply the raw sums of the number of parties. The index of political polarization of parties in the legislature (LEGPOL) is based on an assessment of the ideology of each political party. The polarization index measures the maximum political distance between the ideology of the executive's political party (Left, Center, or Right) and the ideologies of the three largest government parties and the largest opposition party.

Perhaps surprisingly, these five measures of polarization in legislature/government are not systematically related to our polarization measures based on the stated opinions of survey respondents. The Herfindahl index for the legislature (HERFLEG) is positively related to polarization in the electorate (i.e., the party structure is more concentrated in polarized countries), but the correlation is only significant for the government responsibility question (GOV). In contrast, the number of parties in the legislature is positively correlated with polarization based on three of the four questions, but the relationship is only significant for the question about private versus government ownership (PRIVATE). The measures based on the number of parties in the government (HERFGOV and NGOV) are positively related with polarization for some questions and negatively for others, but none of the correlations are statistically significant. The polarization index based on party ideologies (LEGPOL) is negatively related to polarization for all four questions, but none of the correlations are statistically significant.

These findings suggest that polarization in the electorate does not affect public spending through a direct effect on the level of polarization in the legislature or government. However, the number of political parties is a crude measure of polarization because it does not say anything about the political positions of different parties. LEGPOL is based on a classification of party ideology, but this classification is coarse (Left, Center, Right) and primarily based on the names of political parties. Moreover, the formation of political parties depends on many other factors than voters’ political preferences. Examples include electoral rules (e.g., Duverger Reference Duverger1954; Riker Reference Riker1982), sociological factors (e.g., Lipset and Rokkan Reference Lipset and Rokkan1967), and the ability of social and political groups to overcome collective action problems inherent in party formation (Olson Reference Olson1965).

As an alternative way to measure polarization in the government and legislature, we use information about party sympathies in the WVS to derive measures of the political opinions among the supporters of different parties.Footnote 34 Polarization among supporters of political parties can be informative about polarization in the legislature/government both because the opinions of the party elite are related to the opinions of the party's supporters and because the party elite may act based on the preferences of their voters (irrespective of their own preferences).

We first calculate the standard deviation of responses for supporters of different political parties in the legislature in each country. Interestingly, the average level of political polarization among the supporters of parties in the legislature is closely correlated with our measures of polarization in the whole electorate.Footnote 35 For example, the level of polarization among Republican Party supporters in the United States in terms of our economic policy questions is higher than the level of polarization in the entire Swedish electorate. However, polarization of political parties (as measured by the Herfindahl index) is substantially lower in the U.S. Congress than in the Swedish seven-party parliament. This suggests that whether polarization in the electorate leads to a polarized party structure depends, among other things, on whether parties are formed based on differences in opinion regarding economic policy or according to views along other dimensions of political cleavage.Footnote 36

We also calculate the level of polarization among respondents who support a party in government, as well as polarization among supporters of parties in opposition. This gives us two polarization measures for each country, one for the government and one for the opposition. If polarization in the electorate is related to government size through polarization in the government or legislature, polarization among supporters of the government should arguably have a stronger effect than polarization among supporters of the opposition. Table 8 shows that polarization among the supporters of the government is a more robust predictor of government consumption than polarization among the supporters of the opposition. The estimated effect of polarization among opposition supporters is close to zero or even positive when we include both polarization measures in the same regression.Footnote 37

TABLE 8. Political Polarization and Government Size: Test of Theoretical Mechanisms (Strong Democracies)

Notes: All regressions include control variables from the long specification. The table reports coefficients and heteroscedasticity robust standard errors for the standard deviation of each question for the three specifications discussed in the text.

*p = .10; **p = .05, ***p = .01.

Taken together, these results indicate that polarization among voters does not affect the level of spending by influencing the number and relative sizes of political parties. We do find, however, that polarization among supporters of the government is more strongly associated with public spending than polarization among opposition supporters. With these results in mind, we now continue to discuss a number of specific theoretical mechanisms that can potentially explain how polarization affects spending.

Veto Players. According to Tsebelis’ (Reference Tsebelis2002) veto player theory, political decisions are more likely to be vetoed by political parties if there are many parties in government and if the ideological distance between parties is large. This suggests that polarization leads to fewer changes in government spending, but the theory is ambiguous with respect to the level of government spending.

As we showed previously, political polarization in the electorate is not related to measures of polarization in the government or legislature based on the number of political parties. However, as pointed out by, for example, Tsebelis (Reference Tsebelis1999), the importance of veto players depends both on the number of veto players and on the ideological distance between them. This suggests that we should expect an interaction effect between political polarization and the number of veto players. To test for this, we include an interaction term between polarization and HERFGOV and HERLEG in regression (1). As we show in Table 8, the relationship between polarization and size of government is stronger for countries with fragmented governments and legislatures. The interaction effects are not statistically significant for all four questions, but this is partly due to few degrees of freedom in the long specification.Footnote 38 In addition, we interact polarization with the number of parties in the legislature and government (NLEG and NGOV). Political polarization is more strongly related to government size in countries with many parties in government and the legislature, but the difference is generally not statistically significant.Footnote 39

Although the interaction effects are imprecisely estimated due to few observations, the results suggest that political polarization in the electorate is a stronger predictor of public spending in countries with fragmented legislatures and governments.

Strategic Incumbents. Following the seminal work by and Alesina and Tabellini (Reference Alesina and Tabellini1990) and Persson and Svensson (Reference Persson and Svensson1989), there is a large literature that focuses on the dynamic strategic incentives of incumbent governments. One of the main ideas in this literature is that incumbents who are uncertain whether they will be reelected have an incentive to behave strategically by implementing policies that restrict the choice set of future governments. The more the preferences of the incumbent government depart from the preferences of potential future governments, the more the incumbent will try to restrict future governments’ room to maneuver. For example, Persson and Svensson consider a model in which political parties differ in their preferred size of government and show that incumbents will act strategically by incurring debt in order to affect the cost of public spending in future periods. As pointed out by Persson and Svensson, another state variable that incumbents might use to influence future governments is a “public capital stock” that may be required for the production of public goods. This implies that polarization of preferences over the size of government may be systematically related to the actual size of government. The net effect of polarization on size of government may be either positive or negative, depending on whether it is easier to build up or destroy the stock of public capital. Azzimonti (n.d.), Glazer (Reference Glazer1989), and Svensson (Reference Svensson1998) develop models along similar lines, although size of government is increasing in polarization in Azzimonti (n.d.) and Glazer (Reference Glazer1989), whereas it is decreasing in Svensson (Reference Svensson1998).

The dynamic political economy models rely on electoral uncertainty: polarization only matters in countries where reelection probabilities are sufficiently low. To test for this, we include an interaction term between polarization and the government's share of the total number of seats in the legislature (GOVSEATS). The idea is that the reelection probability is increasing in the government's vote share. As shown in Table 8, the interaction term is negative, indicating that the effect of polarization on size of government is larger when the government's reelection probability is high.Footnote 40 Svensson (Reference Svensson1998) models a more specific mechanism; incumbents restrict future governments’ opportunity to raise funds by implementing an inefficient legal system. Although polarization is the ultimate cause of small government in his model, an inefficient legal system is the proximate cause. We test this aspect of Svensson's model by including a measure of property rights (PRIGHTS) into regression (1). As reported in Table 8, the estimated effect of polarization is not particularly sensitive to controlling for property rights, thus not supporting this particular model of strategic incumbent behavior either.

Two-stage Voting on the Budget. Alesina, Baqir, and Easterly (Reference Alesina, Baqir and Easterly1999) develop a model of two-stage voting where the size of the budget is decided before its composition. Agents first vote on the amount to spend on a public good, and then they vote on the type of public good to provide. As voters in the first stage anticipate the outcome of the second stage, support for spending on the public good is decreasing in the dispersion of preferences over its type. This mechanism relies on a two-stage budget process and is therefore most plausible as a model of voting in legislatures that vote on the budget in two stages.

The main prediction of the model is that disagreement about how to spend public resources leads to preferences for lower levels of spending. Unfortunately, there are no questions in the WVS that directly capture preferences over the type of spending. Although our economic policy questions may partly reflect preferences for the focus of spending (e.g., spending on social relief programs instead of military equipment), they arguably capture preferences for the overall size of government better.Footnote 41 To distinguish between these two types of preferences, we therefore use a principal factor analysis. The underlying idea is that the responses to the four questions depend both on a factor common to all questions and one idiosyncratic term for each question. We interpret the common factor as reflecting a general preference for increasing or decreasing the size of government, whereas the idiosyncratic terms reflect preferences for a specific type of government intervention. This interpretation is supported by the factor loadings. The common factor has a positive impact on the private ownership (PRIVATE), government responsibility (GOV), and competition (COMP) questions, but a negative loading for the income inequality question (EQUALITY), which has a “reversed” scale. We calculate new polarization measures based on the common factor and the residuals for each question from the factor analysis. As it turns out, the new polarization measure based on the common factor is strongly positively correlated with each polarization measure based on the idiosyncratic factors. Both types of polarization measures are negatively related to government consumption, indicating that polarization over both size of government and composition of public goods matters for size of government.Footnote 42 The polarization measures based on the question residuals appear to be somewhat more robust as predictors of public spending when both types of measures are added jointly to regression (1), which gives some support for this particular mechanism. However, due to the high correlation between these measures and the limited number of degrees of freedom, we are reluctant to put much emphasis on this result.Footnote 43 In addition, we have not taken into account that not all countries use a two-stage voting process and that our measures of polarization are based on the preferences of voters, not on those of members of the legislature (which would be more suitable for testing this mechanism).

Coalition Formation. Fernández and Levy (Reference Fernández and Levy2008) develop a model that explicitly shows how polarization in the electorate may affect the formation of political parties and redistribution. In their model, parties are endogenous and preference diversity among the poor affects their ability to extract resources from the rich. As taste diversity increases from a low level, redistribution becomes increasingly tilted toward special interest groups and general redistribution to the poor goes down. However, at a certain threshold, all special interest coalitions break down and general redistribution to the poor increases. Fernández and Levy's model thus predicts a U-shaped relationship between preference heterogeneity and general redistribution.

A distinguishing feature of this model is that the level of redistribution is determined by polarization among the poor. As a rough test of this model, we therefore calculate two measures of polarization for each country, one based on respondents who reported a below-median or median income and another for respondents with an income above the median. As is shown in Table 8, the results remain qualitatively similar irrespective of which measure is used, thus not supporting the mechanism suggested by Fernández and Levy (Reference Fernández and Levy2008).

Voter Preferences and Turnout

We now turn to a discussion of some theoretical mechanisms that can explain how polarization among voters can affect spending without necessarily implying polarization in the legislature or government.

In Meltzer and Richard's (Reference Meltzer and Richard1981) canonical model of redistribution, the size of government is determined by the income of the median voter. Two minor modifications of the model, however, directly imply that dispersion of voter preferences may be related to the size of government. We discuss each case in turn.

Voter Turnout. The first modification of Meltzer and Richard's (Reference Meltzer and Richard1981) model is to relax the implicit assumption that all citizens vote in elections. Empirical research indicates that the income of the median voter tends to be above the median income in the population (Bassett, Burkett, and Putterman Reference Bassett, Burkett and Putterman1999). If people with a preference for a larger government are less likely to vote, then the median voter will prefer a smaller government than the median opinion in the population. Moreover, the difference between the median voter and the median in the population will often be larger the higher is the variance of the distribution of preferences. To see this, note that there are typically fewer voters in-between two points close to the median (e.g., two different tax rates) the more dispersed are political preferences. Footnote 44

If voter turnout is the mechanism by which polarization affects size of government, then it would imply two other phenomena. First, we should expect the median respondent in polarized countries to desire an increase in spending (because the decisive voter prefers a lower level of spending than the median opinion in the population). Second, the effect of polarization should depend on the level of voter turnout.

Because the questions do not clearly distinguish preferences over the size of the budget from preferences about the type of spending, we use a principal factor analysis. We follow the same procedure as in the test of Alesina, Baqir, and Easterly's (Reference Alesina, Baqir and Easterly1999) model, but exclude the competition question (COMP) from the analysis because that question does not refer to the status quo. Hence, the common factor reflects the preferred change from the status quo size of government. The correlation between the median and standard deviation of the common factor for strong democracies is positive (0.27), indicating that the median voter in polarized countries indeed desires an increase in public spending, although the correlation is modest and not statistically significant. Yet, if polarization affects government size through the nonrepresentativeness of the decisive voter, then we should also expect the estimated effect of polarization in the common factor to be sensitive to the inclusion of the median as a control variable. This is not the case, which casts doubt on the importance of the voter turnout mechanism. Furthermore, we find no evidence in favor of the voter turnout mechanism when we include an interaction term between polarization and voter turnout in parliamentary elections (TURNOUT) in regression (1) (Table 8).

Altruism. The second modification of Meltzer and Richard's (Reference Meltzer and Richard1981) model is that voters may not be completely selfish. Previous research has shown that attitudinal similarity is a strong predictor of altruism, attraction, and friendship (e.g., Batson et al. Reference Batson, Duncan, Ackerman, Buckley and Birch1981; Byrne Reference Byrne1961, Reference Byrne1971; Chen and Kenrick Reference Chen and Kenrick2002; Feren, Carroll, and Olian Reference Feren, Carroll and Olian1988; McGrath Reference McGrath1984; Newcomb Reference Newcomb1961; Suedfeld, Bochner, and Wnek Reference Suedfeld, Bochner and Wnek1972), suggesting that political polarization may be related to voter altruism.Footnote 45 Depending on the exact shape of the income distribution, a general decrease in altruism could in theory lead to either more or less redistribution. In practice, however, the median voter typically does not gain from redistribution. This implies that lower levels of altruism reduce redistribution and provision of public goods (Bassett, Burkett, and Putterman Reference Bassett, Burkett and Putterman1999).

In contrast to the other theoretical mechanisms, an effect of polarization on size of government via altruism could arise due to polarization about any type of attitude question that respondents consider salient. As a test of this mechanism, we therefore compare the results for polarization in economic policy with the results for polarization using other types of questions. We use five questions that have been deemed particularly important to explain cultural differences in value orientation across time and cultures (Inglehart and Baker Reference Inglehart and Baker2000).Footnote 46 The five questions are questions about the importance of god (GOD), strength of national pride (PRIDE), respect for authorities (AUTHORITY), and two questions about whether abortion (ABORT) and homosexuality (HOMO) are justifiable. Naturally, the validity of this test hinges on the assumption that attitudinal similarity in terms of economic-political values is not more important for altruism than attitudinal similarity in other domains.

The estimated effects of polarization (in economic policy) remain largely unchanged when the standard deviations and means of the five questions about value orientation are included in the long specification. Polarization in terms of respect for authorities and attitudes toward homosexuality is associated with larger government, whereas polarization in the other three questions is negatively related to size of government, but the coefficients are most often not statistically significant. It is noteworthy that polarization in all five questions is negatively correlated with polarization in three of the four economic policy questions. For example, recall that Sweden was one of the most cohesive countries with respect to the government responsibility question, whereas Brazil was one of the most polarized. The opposite holds for the question about respect for authorities: Sweden is among the 10 most polarized and Brazil among the 20 most cohesive.

Taken together, these results do not lend much support to the idea that polarization affects public spending through voter altruism. The results also suggest that polarization is not one dimensional, but highly domain specific.

Theoretical Mechanisms: Summary of Results

The main result from our tests of theoretical mechanisms is that polarization is more strongly related to the size of government in countries with fragmented party structures. This is in line with veto player theory; spending proposals are more likely to be vetoed when there are several parties that disagree about the proper course of action. We also found some support for the idea that disagreement about the direction of spending matters more than disagreement about the level of spending (as predicted by Alesina, Baqir, and Easterly Reference Alesina, Baqir and Easterly1999). Although we found no support for theories that rely on strategic behavior of incumbent governments, coalition formation, voter turnout, or voter altruism, our tests of these theories are quite weak, mainly due to few observations and data limitations. More theoretical and empirical research on the link between polarization and size of government is needed before definitive conclusions can be drawn.

CONCLUSION

The relationship between political polarization and size of government has been the subject of much theoretical work in economics and political science. In this article, we conduct the first empirical test of this relationship that uses a measure of political polarization based on self-reported political preferences. From a theoretical perspective, polarization could lead to either larger or smaller governments. We show that our measures of political polarization are strongly negatively correlated with the level of public spending. This relationship is robust to a large set of control variables and holds for several different polarization measures. We also find the correlation between polarization and government size to be significantly stronger among democratic countries, which supports (although it does not prove) a causal interpretation. One particular concern with this interpretation, however, is that three out of our four measures of polarization are based on respondents’ preferred changes from the current size of government, which implies that measured polarization may depend on government size. This is an alternative explanation for our findings that we could not completely rule out.

We made some progress in uncovering why polarization is related to government spending, although further research is needed to draw a firm conclusion. One noteworthy finding is that polarization in the electorate is unrelated to the fragmentation of the government and legislature in terms of the number of political parties. We did, however, find that the effect of political polarization was stronger in countries with fragmented governments, suggesting that polarization in terms of opinions and party structure interact in a way consistent with veto player theory.

The main priority for future research is to better identify the underlying causal mechanism. For this purpose, it would be interesting to examine whether political polarization can explain variation in public spending within countries. A definite test of the causal mechanism does, however, require some kind of exogenous variation in political polarization that does not have an independent effect on the size of government. Unfortunately, it is difficult—if at all possible—to come up with an instrument that affects political polarization, but does not have an independent effect on government size.

Another area for future research is to analyze the determinants of political polarization, a topic that is beyond the scope of this article. Previous research presents several interesting ways to study this question. For example, media probably plays a role in shaping political preferences. Bernhardt, Krasa, and Polborn (Reference Bernhardt, Krasa and Polborn2008) developed a model that predicts that profit-maximizing media firms may have an incentive to supply biased news to partisan audiences, and DellaVigna and Kaplan (Reference DellaVigna and Kaplan2007) and Gerber, Karlan, and Bergan (Reference Gerber, Karlan and Bergan2006) empirically showed that biased media actually affects voting behavior. Political polarization could also be due to a divergence in beliefs about the effects of different policies rather than by a conflict of interest or partisanship. Dixit and Weibull (Reference Dixit and Weibull2007) and Acemoglu, Chernozhukov, and Yildiz (Reference Acemoglu, Chernozhukov and Yildiz2007) theoretically studied how such polarized beliefs could arise.

APPENDIX A: DATA

Data on Party-level/Government/Opposition Polarization

To calculate polarization for political parties and for supporters of the government and opposition, we use the question in the World Values Survey (WVS) that asks respondents about which party the respondent would vote for if national elections were held tomorrow (WVS code: e179). The political parties in the WVS were then matched with data on the number of seats in the legislature and whether the party was in government or opposition. All respondents that supported parties that were not represented in the legislature were excluded from the data. The resulting data was then used to calculate the standard deviation of responses for each political party in each country and for government/opposition supporters in each country.

The data about political parties (number of seats and government/opposition) is based on election results from the most recent election prior to the start of the survey in each country. The main data source Beck et al. (Reference Beck, Clarke, Groff, Keefer and Walsh2001), but we have also relied on other data sources (details are available on request).

TABLE A1. List of Countries, Survey Year, and Political Polarization

Note: Asterisks (*) indicate strong democracies.

TABLE A2. Dependent and Control Variables

Note: GDP, gross domestic product; OECD, Organisation for Economic Development; WVS, World Values Survey.

APPENDIX B: ALTERNATIVE POLARIZATION MEASURES

As discussed in the Data section, there are several ways to measure polarization. In this appendix, we discuss alternative polarization measures, in particular, the polarization measure suggested by Esteban and Ray (Reference Esteban and Ray1994).

Two of the theoretical papers about the relationship between polarization and size of government discussed in this article suggest specific measures of polarization. Alesina, Baqir, and Easterly (Reference Alesina, Baqir and Easterly1999) construct a model where the provision of public goods is decreasing in the median deviation from the median preference for the composition of public goods. This is a crude measure given that there are only a few discrete responses to the questions in the WVS. A close substitute to the median distance to the median is the average absolute deviation from the average. This measure is practically indistinguishable from the standard deviation in our data; the correlation is 0.992 for the government responsibility question. The model by Fernández and Levy (Reference Fernández and Levy2008) calls for a polarization measure based on the probability that two randomly matched individuals in the population hold the same opinion. However, this measure does not resonate well with multiple-choice questions because it treats “4” and “5” on a 1-to-10 scale as two groups, as distinct as “1” and “10”.

Esteban and Ray's (Reference Esteban and Ray1994) measure of polarization includes a parameter α that, loosely speaking, measures the extent of sensitivity to polarization rather than dispersion. To satisfy their axioms, α must be between zero and approximately 1.6. We calculate Esteban and Ray's measure for α equal to 0.5, 1.0, and 1.5. As pointed out in Section 4 of Esteban and Ray's article, their measure is not designed for cases in which individuals in one category also identify with people in the neighboring category. For example, if 25% of respondents answer “1”, 25% answer “2”, and the rest answer “10”, then this is considered less polarized than an equal split between “2” and “10”. However, if people who answer “1” or “2” have similar opinions, then it can be argued that the first example is more polarized because preferences in this group are closer to the end point of the scale. For this reason, we also consider a simple measure of bipolarization: the minimum of the proportion of respondents that answer “1” or “10”. Note that both the standard deviation and Esteban and Ray's polarization measure treat the ordinal scale of responses to multiple-choice questions as an interval scale. Mouw and Sobel (Reference Mouw and Sobel2001) demonstrate that it is possible to measure dispersion without this assumption, but their measure is difficult to interpret in our context. Our bipolarization measure, however, is only based on the ordinal properties of responses.

In the case of Sweden and Brazil (see the Data section), Brazil is more polarized irrespective of which measure is used. The standard deviation is 3.44 in Brazil and 2.22 in Sweden, whereas the measure of bipolarization is 0.23 in Brazil and 0.02 in Sweden. Brazil ranks higher than Sweden based on Esteban and Ray's (Reference Esteban and Ray1994) measure of polarization for all three levels of α, but the relative difference between the two countries falls substantially the higher is α.

Table B1 shows the correlation between the standard deviation and the other polarization measures for all countries in our data based on the question about government responsibility. Esteban and Ray's (Reference Esteban and Ray1994) measure of polarization is strongly correlated with the standard deviation, but the higher is α, the lower the correlation. This suggests that we could test whether it is polarization or dispersion that matters for public spending simply by comparing our results for the standard deviation with those for Esteban and Ray's measure with high α. However, as noted previously, Esteban and Ray's polarization measure is not ideal for measuring polarization of responses to survey questions. In addition, the distribution of polarization scores becomes more skewed the higher is α. To see this, Figure B1 displays histograms of Esteban and Ray's measure for the three different values of α. For example, when α is equal to 1.5, half of the countries are lumped together in a very narrow range. This makes reliable inference difficult. Moreover, our measure of bipolarization is strongly correlated with the standard deviation. This implies that it is difficult to distinguish empirically between “dispersion” and “polarization.”

TABLE B1. Correlations with Polarization Measures (GOV)

FIGURE B1. Histogram of Esteban and Ray's (Reference Esteban and Ray1994) Polarization Measure for the Government Responsibility Question (GOV) for α = 0.5 (left), α = 1.0 (center), and α = 1.5 (right)

Footnotes

Note: Asterisks (*) indicate strong democracies.

Note: GDP, gross domestic product; OECD, Organisation for Economic Development; WVS, World Values Survey.

1 Previous literature has considered many other potential determinants of the size of government. Electoral rules (e.g., Iversen and Soskice Reference Iversen and Soskice2006; Persson and Tabellini Reference Persson and Tabellini2003), social insurance (Moene and Wallerstein Reference Moene and Wallerstein2001), country size (Alesina and Wacziarg Reference Alesina and Wacziarg1998), and openness to international trade (Rodrik Reference Rodrik1998) are just a few examples.

2 For example, ethnic diversity is associated with smaller size and lower quality of government (e.g., Alesina, Baqir, and Easterly Reference Alesina, Baqir and Easterly1999; Alesina, Glaeser, and Sacerdote Reference Alesina, Glaeser and Sacerdote2001; Alesina and Zhuravskaya Reference Alesina and Zhuravskaya2008; Luttmer Reference Luttmer2001; Vigdor Reference Vigdor2004). Another line of research has focused on the polarization of political parties and various economic outcomes (e.g., Alt and Dreyer Lassen Reference Alt and Dreyer Lassen2006; Cukierman, Edwards, and Tabellini Reference Cukierman, Edwards and Tabellini1992; Frye Reference Frye2002; Svensson Reference Svensson1998).

3 See Shayo (Reference Shayo2009) for a model of how group identification may affect political preferences.

4 To the best of our knowledge, we are the first to test the effect of polarization on the size of government using direct measures of political preferences. We are not the first, however, to study the dispersion of responses to multiple-choice questions at the country level. DiMaggio, Evans, and Bryson (Reference DiMaggio, Evans and Bryson1996) use survey data to study changes in dispersion and polarization of attitudes over time. Au (Reference Au1999) and Au and Cheung (Reference Au and Cheung2004) study how variation in job characteristics affects certain social outcomes, such as job satisfaction. There is also a literature within social psychology on the determinants of value consensus (e.g., Shalom and Sagie Reference Shalom and Sagie2000). See also Gerber and Lewis (Reference Gerber and Lewis2004), who calculated a measure of heterogeneity in voter preferences from voting records and showed that legislators were more constrained by the preferences of the median voter in homogeneous districts.

5 We excluded three countries (Northern Ireland, Puerto Rico, Taiwan) because they were not included as separate entities in the other data sources, and four other countries (Serbia and Montenegro, Iraq, Belarus, Saudi Arabia) because government size data were unavailable. In addition, we excluded two countries (Israel and India) because fewer response alternatives were used in these countries.

6 There are other questions in the WVS that might also be relevant, but these four questions satisfy a number of criteria (more than two response alternatives, sufficiently many observations, and not too high correlation between the mean and standard deviation) that we used in a previous version of this article. We considered using an index combining all economic policy questions instead of reporting the results for the four questions separately. However, we abstained from doing so primarily because there would be fewer observations for this index than for any single question. Moreover, the results for an index would be less straightforward to interpret, and it is unclear how to control for the mean value. Comparing the results for four related questions is also a sensible first robustness check.

7 A simple numerical example illustrates the point. Consider two countries (denoted 1 and 2) with two types of voters (denoted A and B) of equal share of the population. In both countries, type A's ideal size of government is “2”, whereas type B's ideal size is “8”. If voters are asked about their ideal size of government, the mean value will thus be 5 and the standard deviation 3 in both countries. Now suppose that the actual size of government is “4” in country 1 and “5” in country 2 and that voters are asked how they want the size of government to change. In country 1, A prefers a change of −2, whereas B prefers a change of +4. In country 2, A prefers a change of −3, whereas B prefers a change of +3. In this case, the mean values will be +1 in country 1 and 0 in country 2, but the standard deviation will still be 3 in both countries. Note that this argument presumes that the scale of the responses is interpreted similarly irrespectively of whether questions ask about relative or absolute size.

8 The report from the person responsible for collecting WVS data in Pakistan does not reveal anything particular except that certain regions of the country could not be included in the survey for political and security reasons (e.g., close to the Afghan border). The data from Pakistan may thus not be fully representative.

9 It should be kept in mind, however, that we cannot readily compare polarization across continents because we only have data from 74 countries. In addition, there seems to be a tendency that larger and more developed countries are more likely to be included in the WVS.

10 We use the most recent prior wave (1990 or 1995) that is available for each country to calculate the intertemporal correlations. There is also a 1980 wave of the WVS, but none of the four economic policy questions were used in that first wave. Another indication that political polarization is relatively stable over time is that the level of political polarization in East and West Germany in 1990, the year of the reunification, is remarkably similar. Ranking all countries by polarization in 1990, the rank of East and West Germany is 13 and 16 for EQUALITY, 12 and 4 for PRIVATE, 29 and 11 for GOV, and 14 and 9 for COMP.

11 For example, Gradstein and Justman (Reference Gradstein and Justman2002) argue that polarization has a negative effect on national income (which, in turn, may affect government size) because it increases transaction costs. Interestingly, the correlations between GDP per capita (LYP) and the polarization measures are strongly negative: −0.28 (SD_EQUALITY), −0.66 (SD_PRIVATE), −0.50 (SD_GOV), and −0.40 (SD_COMP).

12 The countries for which data are missing are Bosnia and Herzegovina, Iceland, Luxembourg, Malta, and Peru. However, Iceland, Luxembourg, and Malta receive the highest possible score on the political and civil rights indices in 2000 published by Freedom House (2005) and, therefore, it seems uncontroversial to classify them as strong democracies. The democracy index is not available for Peru in 2000 because the country was “in transition” with a very low score on the democracy index prior to 2000 and a high score thereafter. Bosnia and Herzegovina was reported “in transition” for the years around 2000.

13 As an extreme example, consider a country where all respondents answer “1” to a question on a 1-to-10 scale, implying a mean value of 1 and a standard deviation of 0. Now, because “1” is the lowest possible answer, any change in the structure of responses would change both the mean and the standard deviation, implying that the mean and the standard deviation would be highly correlated.

14 Among the strong democracies, the share of GDP that goes to government consumption is lowest in Hungary (13.3%).

15 The distribution of mean values looks similar for the other economic policy questions, except for COMP, where the average mean value is 3.64 (3.86 for strong democracies).

16 The results from this robustness check are available in the Supplementary Appendix.

17 The correlations between mean value and standard deviation for the other polarization measures are: EQUALITY, −0.17; GOV, 0.13; and COMP, 0.27.

18 The difference between “weak” and “strong” democracies is statistically significant, except for the EQUALITY question in the “long” specification, when we include an interaction effect between democratic development and polarization in regression (1).

19 Another indication that the results for weak democracies are unlikely to be driven by measurement error is that restricting the sample of weak democracies to countries with higher response rates, higher levels of literacy, or a high correlation between individual question responses does not give systematically different estimates.

20 The results based on Esteban and Ray's (Reference Esteban and Ray1994) measure of polarization are, however, weaker for certain parameter values. As discussed in Appendix B, Esteban and Ray's measure of polarization includes a parameter that measures the extent of sensitivity to polarization rather than dispersion. The results are weaker for high values of this parameter, which suggests that it is dispersion rather than polarization (i.e., concentration of responses to particular groups) that matters for size of government. We are reluctant to put much emphasis on this result due to the skewness of the country-level distribution of polarization for high values of the parameter (Figure B1). Note that the coefficient estimates (reported in the Supplementary Appendix) are not directly comparable across polarization measures. The reason is that each measure has a different scale (we have not undertaken any normalization with respect to the different measures).

21 Note that the regressions reported in Table 5 are identical to the regressions for strong democracies in Table 4.

22 Alesina and Wacziarg (Reference Alesina and Wacziarg1998) show that smaller countries have a larger share of public consumption of GDP.

23 Recall that in political economy models such as Meltzer and Richard's (Reference Meltzer and Richard1981) model, voters’ preferences for redistribution merely reflect their relative position in the distribution of income. Political preferences regarding redistribution will consequently be more dispersed the higher is pretax income inequality.

24 Another problem is that the Gini index is based on consumption data for developing countries. To the extent that government consumption is correlated with redistribution from rich to poor, higher government consumption is therefore likely to reduce the Gini index for developing countries (because it is based on after-tax income). This would imply that Gini index is endogenous with respect to government consumption, thereby spuriously reducing the estimated effect of political polarization.

25 Income in the WVS is measured on a 1-to-10 scale that is specific to each country. We include each income category as a dummy variable in the regressions.

26 Current income may not be a very good proxy for permanent income. Therefore, we have also tested to add educational attainment (on a 1-to-3 scale) as a regressor in the first stage when computing the income-adjusted polarization measures. This “income-and-education–adjusted” measure of polarization is also highly correlated with our standard measure, with all correlation coefficients larger than 0.98.

27 It is not clear whether uncertainty about preferences would lead to an upward or downward bias of the measured level of political polarization. For example, a uniform randomization on a 1-to-10 scale implies a standard deviation of 2.63, far from the theoretical maximum of 4.5 (when half of the respondents answers 1 and the other half 10). Alternatively, uncertain respondents may cluster around certain focal values (e.g., “5”), which would give a very low measured level of polarization. If uncertain respondents instead randomize between extreme values (i.e., “1” and “10”), then the measured level of polarization would be very high. It is uncertain a priori which case better represents the behavior of respondents.

28 Our measure of “ideological coherence” is related to a literature in public opinion research on “ideological constraint.” Linzer (Reference Linzer2008, chap. 3) discusses this literature and proposes new measures.

29 The correlation coefficients for the four questions vary between −0.19 and −0.38 in weak democracies and between −0.31 and −0.44 in strong democracies.

30 The correlation coefficients are between 0.39 and 0.53 for strong democracies.

31 Note that the size of the coefficients for ideological coherence and polarization cannot be directly compared because the scaling of the variables is different.

32 Another form of endogeneity occurs if large governments invest more in policies that foster homogeneity. However, we have not found any evidence to support this view. For example, there is no indication in our data that political polarization is lower in countries with censorship and lack of a free press. The partial correlations between our measures of polarization and reporters without borders’ index of press freedom (PFREEDOM) range from 0.16 and 0.40, where a higher score indicates less freedom.

33 The inverse of the Herfindahl index is often referred to as the effective number of legislative/government parties (e.g., Bawn and Rosenbluth Reference Bawn and Rosenbluth2006).

34 See Appendix A for a more detailed description of these data.

35 This is true for all four economic policy questions, for unweighted averages across parties, and for averages weighted by the number of seats in the legislature for each party. All correlations between polarization in the electorate and the unweighted averages are above 0.84, and the correlations with the weighted averages are 0.92 or higher.

36 In principle, the electorate could select perfectly between parties based on their political opinions along some dimension so that all supporters of the same party hold highly similar political view on that dimension or, alternatively, each party could harbor the same level of political polarization as society as a whole. The type of economic policy questions we consider, although important, only capture one relevant dimension of politics.

37 We also calculate polarization among respondents that support parties in the legislature, but this measure is too highly correlated with polarization among government parties for us to be able to make any meaningful inference (the correlation is above 0.92 for all four questions).

38 In the basic specification without other control variables than the mean, the interaction effects with HERFGOV and HERFLEG are significant in three out of four regressions.

39 The results from these regressions are not reported in Table 8, but they are available in the Supplementary Appendix. The estimate for the interaction term with NLEG is sensitive to which controls are included. The estimated effect is positive for some questions in the basic and short specifications.

40 This finding is somewhat sensitive to which controls are included in the regression. In the basic specification (without other control variables than the mean), the interaction effect is insignificant for all questions, and the sign of the interaction effect is positive for two questions (but negative for the other two questions).

41 Ideally, we would like to compute an aggregate measure of each voter's satisfaction with the focus on current spending using questions about many different areas of spending, such as schools, the armed forces, and poverty relief.

42 Because data on all four questions are only available for 22 strong democracies, there are few degrees of freedom in the long specification, leading to large standard errors.

43 Another complication in interpreting these results is that it is not clear from a theoretical perspective that the relevant variation in the polarization measures should be orthogonal.

44 This holds if, for example, voter preferences follow a normal or a uniform distribution. More generally, it holds whenever an increase in dispersion shifts probability mass from the center to the tails. See Landsberger and Meilijson (Reference Landsberger and Meilijson1990) for one characterization of such changes in the context of risk measurement.

45 The relationship between attitudinal similarity and altruism can be rationalized in terms of evolutionary psychology; see Hamilton (Reference Hamilton1964); Olson, Vernon, and Jang (Reference Olson, Vernon and Jang2001); Park and Schaller (Reference Park and Schaller2005); and Tesser (Reference Tesser1993).

46 Inglehart and Baker (Reference Inglehart and Baker2000) list 10 different questions, but we exclude 5 of these because they concern behavior, are based on an index of other questions, or only allow dichotomous responses. We also exclude questions about personal happiness because they do not refer to a preference or a belief.

References

REFERENCES

Acemoglu, D., Chernozhukov, V., and Yildiz, M.. 2007. “Learning and Disagreement in an Uncertain World.” Massachusetts Institute of Technology. Unpublished manuscript.Google Scholar
Adserà, A., Boix, C., and Payne, M.. 2003. “Are You Being Served? Political Accountability and Quality of Government.” Journal of Law, Economics, and Organization 19 (2): 445–90.Google Scholar
Alesina, A., Baqir, R., and Easterly, W.. 1999. “Public Goods and Ethnic Divisions.” Quarterly Journal of Economics 115 (4): 1167–99.Google Scholar
Alesina, A., Devleeschauwer, A., Easterly, W., Kurlat, S., and Wacziarg, R.. 2003. “Fractionalization.” Journal of Economic Growth 8 (2): 155–94.Google Scholar
Alesina, A., Glaeser, E., and Sacerdote, B.. 2001. “Why Doesn't the United States Have a European-style Welfare State?Brookings Paper on Economics Activity 2001 (2): 187254.Google Scholar
Alesina, A., and Tabellini, G.. 1990. “A Positive Theory of Fiscal Deficits and Government Debt.” Review of Economic Studies 57 (3): 403–14.Google Scholar
Alesina, A., and Wacziarg, R.. 1998. “Openness, Country Size and Government.” Journal of Public Economics 69 (3): 305–21.Google Scholar
Alesina, A., and Zhuravskaya, E.. 2008. “Segregation and the Quality of Government of Countries.” National Bureau of Economic Research (NBER) Working Paper 14316.Google Scholar
Alt, J.E., and Dreyer Lassen, D.. 2006. “Transparency, Political Polarization, and Political Budget Cycles in OECD Countries.” American Journal of Political Science 50 (3): 530–50.Google Scholar
Au, K. 1999. “Intra-Cultural Variation: Evidence and Implications for International Business.” Journal of International Business Studies 30 (4): 799812.Google Scholar
Au, K., and Cheung, M.. 2004. “Intra-cultural Variation and Job Autonomy in 42 Countries.” Organization Studies 25 (8): 1339–62.Google Scholar
Azzimonti, M. n.d. “Barriers to Investment in Polarized Societies.” American Economic Review. Forthcoming.Google Scholar
Bassett, W., Burkett, J., and Putterman, L.. 1999. “Income Distribution, Government Transfers, and the Problem of Unequal Influence.” European Journal of Political Economy 15 (2): 207–28.Google Scholar
Batson, C.D., Duncan, B.D., Ackerman, P., Buckley, T., and Birch, K.. 1981. “Is Empathic Emotion a Source of Altruistic Motivation?Journal of Personality and Social Psychology 40 (2): 290302.Google Scholar
Bawn, K., and Rosenbluth, F.. 2006. “Short versus Long Coalitions: Electoral Accountability and the Size of the Public Sector.” American Journal of Political Science 50 (2): 251–65.Google Scholar
Beck, T., Clarke, G., Groff, A., Keefer, P., and Walsh, P.. 2001. “New Tools in Comparative Political Economy: The Database of Political Institutions.” World Bank Economic Review 15 (1): 165–76. http://go.worldbank.org/2EAGGLRZ40 (accessed July 11, 2010).Google Scholar
Bernhardt, D., Krasa, S., and Polborn, M.. 2008. “Political Polarization and the Electoral Effects of Media BiasJournal of Public Economics 92 (5/6): 10921104.Google Scholar
Byrne, D. 1961. “Interpersonal Attraction and Attitude Similarity.” Journal of Abnormal Social Psychology 62: 713–15.Google Scholar
Byrne, D. 1971. The Attraction Paradigm. New York: Free Press.Google Scholar
Chen, F., and Kenrick, D.. 2002. “Repulsion or Attraction? Group Membership and Assumed Attitude Similarity.” Journal of Personality and Social Psychology 83 (1): 111–25.Google Scholar
Cukierman, A., Edwards, S., and Tabellini, G.. 1992. “Seignorage and Political Instability.” American Economic Review 82 (3): 537–55.Google Scholar
DellaVigna, S., and Kaplan, E.. 2007. “The Fox News Effect: Media Bias and Voting.” Quarterly Journal of Economics 122 (3): 11871234.Google Scholar
DiMaggio, P., Evans, J., and Bryson, B.. 1996. “Have Americans’ Social Attitudes Become More Polarized?American Journal of Sociology 102 (3): 690755.Google Scholar
Dixit, A., and Weibull, J.. 2007. “Political Polarization.” Proceedings of the National Academy of Sciences 104: 7351–56.Google Scholar
Duverger, M. 1954. Political Parties: Their Organization and Activity in the Modern State. New York: Wiley.Google Scholar
Esteban, J-M., and Ray, D.. 1994. “On the Measurement of Polarization.” Econometrica 62 (4): 819–51.Google Scholar
European Values Study Group and World Values Association. 2006. European and World Values Surveys Four-wave Integrated Data File 1981−2004. Version 20060423. http://www.wvsevsdb.com/wvs/WVSData.jsp (accessed July 17, 2010).Google Scholar
Fearon, J., and Laitin, D.. 2003. “Ethnicity, Insurgency, and Civil War.” American Political Science Review 97 (1): 7590.Google Scholar
Feren, D., Carroll, S., and Olian, J.. 1988. “Effects of Managerial Performance and Attitudinal Similarity on Interpersonal Attraction.” Basic and Applied Social Psychology 9 (1): 3344.Google Scholar
Fernández, R., and Levy, G.. 2008. “Diversity and Redistribution.” Journal of Public Economics 92 (5/6): 925–43.Google Scholar
Freedom House. 2005. Freedom in the World Country Rankings 1973–2005. Washington, DC: Freedom House.Google Scholar
Frye, T. 2002. “The Perils of Polarization: Economic Performance in the Postcommunist World.” World Politics 54 (3): 308–37.Google Scholar
Gerber, A., Karlan, D.S., and Bergan, D.. 2006. “Does the Media Matter? A Field Experiment Measuring the Effect of Newspapers on Voting Behavior and Political Opinions.” Yale Economic Applications and Policy Discussion Paper 12.Google Scholar
Gerber, E., and Lewis, J.. 2004. “Beyond the Median: Voter Preferences, District Heterogeneity, and Representation.” Journal of Political Economy 112 (6): 1364–83.Google Scholar
Glazer, A. 1989. “Politics and the Choice of Durability.” American Economic Review 79 (5): 1207–13.Google Scholar
Gradstein, M., and Justman, M.. 2002. “Education, Social Cohesion, and Economic Growth.” American Economic Review 92 (4): 11921204.Google Scholar
Gwartney, J., and Lawson, R.. 2008. Economic Freedom of the World: 2008 Annual Report. Vancouver, Canada: Fraser Institute. http://www.freetheworld.com/release_2008.html (accessed July 17, 2010).Google Scholar
Hamilton, W.D. 1964. “The Genetic Evolution of Social Behaviour.” Journal of Theoretical Biology 7: 152.Google Scholar
Inglehart, R., and Baker, W.E.. 2000. “Modernization, Cultural Change, and the Persistence of Traditional Values.” American Sociological Review 65: 1951.Google Scholar
Iversen, T., and Soskice, D.. 2006. “Electoral Systems and the Politics of Coalitions: Why Some Democracies Redistribute More Than Others.” American Political Science Review 100 (2): 165–81.Google Scholar
Keefer, P., and Stasavage, D.. 2003. “The Limits of Delegation: Veto Players, Central Bank Independence and the Credibility of Monetary Policy.” American Political Science Review 97 (3): 407–23.Google Scholar
La Porta, R., Lopez de Silanes, F., Shleifer, A., and Vishny, R.. 1999. “The Quality of Government.” Journal of Law, Economics, and Organization 15 (1): 222–79.Google Scholar
Landsberger, M., and Meilijson, I.. 1990. “A Tale of Two Tails: An Alternative Characterization of Comparative Risk.” Journal of Risk and Uncertainty 3 (1): 6582.Google Scholar
Lindqvist, E. 2007. Essays on Privatization, Identity and Political Polarization. Ph.D. diss. Stockholm School of Economics.Google Scholar
Linzer, D.A. 2008. The Structure of Mass Ideology and Its Consequences for Democratic Governance. Ph.D. diss. University of California, Los Angeles.Google Scholar
Lipset, S.M., and Rokkan, S. (eds). 1967. Party Systems and Voter Alignments: Cross-national Perspectives. New York: Free Press.Google Scholar
Luttmer, E.F.P. 2001. “Group Loyalty and the Taste for Redistribution.” Journal of Political Economy 109 (3): 500–28.Google Scholar
Marshall, M.G., and Jaggers, K.. 2007. Political Regime Characteristics and Transitions 1800−2007. Polity IV Project. University of Maryland. http://www.systemicpeace.org/inscr/inscr.htm (accessed May 14, 2010).Google Scholar
McGrath, J.E. 1984. Groups: Interaction and Process. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Meltzer, A.H., and Richard, S.F.. 1981. “A Rational Theory of the Size of Government.” Journal of Political Economy 89 (5): 914–27.Google Scholar
Moene, K.O., and Wallerstein, M.. 2001. “Inequality, Social Insurance, and Redistribution.” American Political Science Review 95 (4): 859–74.Google Scholar
Mouw, T. and Sobel, M.E.. 2001. “Culture Wars and Opinion Polarization: The Case of Abortion.” American Journal of Sociology 106 (4): 913–43.Google Scholar
Newcomb, T.M. 1961. The Acquaintance Process. New York: Holt, Rinehart & Winston.Google Scholar
Olson, J.M., Vernon, P.A., and Jang, K.L.. 2001. “The Heritability of Attitudes: A Study of Twins.” Journal of Personality and Social Psychology 80 (6): 845–60.Google Scholar
Olson, M. 1965. The Logic of Collective Action. Cambridge, MA: Harvard University Press.Google Scholar
Östling, R. 2008. Bounded Rationality and Endogenous Preferences. Ph.D. diss. Stockholm School of Economics.Google Scholar
Park, J., and Schaller, M.. 2005. “Does Attitude Similarity Serve as a Heuristic Cue for Kinship? Evidence of an Implicit Cognitive Association.” Evolution and Human Behavior 26: 158–70.Google Scholar
Perotti, R., and Kontopoulos, Y.. 2002. “Fragmented Fiscal Policy.” Journal of Public Economics 86 (2): 191222.Google Scholar
Persson, T., and Svensson, L.E.O.. 1989. “Why a Stubborn Conservative Would Run a Deficit: Policy with Time-inconsistent Preferences.” Quarterly Journal of Economics 104 (2): 325–45.Google Scholar
Persson, T., and Tabellini, G.. 2003. The Economic Effects of Constitutions. Cambridge, MA: MIT Press.Google Scholar
Riker, W.H. 1982. “The Two-party System and Duverger's Law: An Essay on the History of Political Science.” American Political Science Review 76 (4): 753–66.Google Scholar
Rodrik, D. 1998. “Why Do More Open Economies Have Bigger Governments?Journal of Political Economy 106 (5): 9971032.Google Scholar
Shalom, S., and Sagie, G.. 2000. “Value Consensus and Importance.” Journal of Cross-cultural Psychology 31 (4): 465–97.Google Scholar
Shayo, M. 2009. “A Model of Social Identity with an Application to Political Economy: Nation, Class, and Redistribution.” American Political Science Review 103 (2): 147–74.Google Scholar
Suedfeld, P., Bochner, S., and Wnek, D.. 1972. “Helper-Sufferer Similarity and a Specific Request for Help: Bystander Intervention during a Peace Demonstration.” Journal of Applied Social Psychology 2 (1): 1723.Google Scholar
Svensson, J. 1998. “Investment, Property Rights and Political Instability: Theory and Evidence.” European Economic Review 42 (7): 1317–41.Google Scholar
Teorell, J., Holmberg, S., and Rothstein, B.. 2008, May. The Quality of Government Dataset. Version 1.5. Quality of Government Institute, University of Gothenburg. http://www.qog.pol.gu.se (accessed May 18, 2010).Google Scholar
Tesser, A. 1993. “The Importance of Heritability in Psychological Research: The Case of Attitudes.” Psychological Review 100 (1): 129–42.Google Scholar
Tsebelis, G. 1999. “Veto Players and Law Production in Parliamentary Democracies: An Empirical Analysis.” American Political Science Review 93 (3): 591608.Google Scholar
Tsebelis, G. 2002. Veto Players: How Political Institutions Work. Princeton, NJ: Princeton University Press.Google Scholar
Vigdor, J.L. 2004. “Community Composition and Collective Action: Analyzing Initial Mail Response to the 2000 Census.” Review of Economics and Statistics 86 (1): 303–12.Google Scholar
World Bank. 2009. World Development Indicators 2009. Washington, DC: World Bank.Google Scholar
Figure 0

FIGURE 1. General Government Consumption and Polarization (Standard Deviation of Government Responsibility Question) in Weak (left) and Strong (right) Democracies

Figure 1

TABLE 1. Economic Policy Questions

Figure 2

FIGURE 2. Histogram of Responses to GOV Question in Brazil and Sweden

Figure 3

TABLE 2. Pairwise Correlations of Standard Deviations

Figure 4

TABLE 3. Countries with Lowest and Highest Levels of Political Polarization

Figure 5

TABLE 4. Political Polarization and Government Consumption

Figure 6

TABLE 5. Political Polarization and Government Consumption (Strong Democracies)

Figure 7

TABLE 6. Political Polarization and Government Consumption: Additional Control Variables (Strong Democracies)

Figure 8

TABLE 7. Political Polarization and Government Consumption: Survey Data Issues (Strong Democracies)

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TABLE 8. Political Polarization and Government Size: Test of Theoretical Mechanisms (Strong Democracies)

Figure 10

TABLE A1. List of Countries, Survey Year, and Political Polarization

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TABLE A2. Dependent and Control Variables

Figure 12

TABLE B1. Correlations with Polarization Measures (GOV)

Figure 13

FIGURE B1. Histogram of Esteban and Ray's (1994) Polarization Measure for the Government Responsibility Question (GOV) for α = 0.5 (left), α = 1.0 (center), and α = 1.5 (right)

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