The Electoral Dynamics of Human Development

Abstract

This paper analyses the impact of elections, partisan and political support effects on the dynamics of human development in a panel of 82 countries over the period 1980–2013. A Generalised Method of Moments(GMM) estimator is employed and the results point out to the presence of an electoral cycle in the growth rate of human development. Majority governments also influence it, but no evidence is found regarding partisan effects. The electoral cycles have proved to be stronger in non-OECD countries, in countries with less frequent elections, with lower levels of income and human development, in presidential and non-plurality systems and in proportional representation regimes.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Bloom and Freeman (1987), Bloom and Williamson (1998) and Bloom, Canning, and Sevilla (2003) also show that the drop in the economic dependency ratio has an impact on how human development evolves over time.

2. Rational versions of opportunistic models tend to reduce the ability of policy-maker’s to induce the political cycle. Empirical studies suggest that favourable economic conditions do benefit governments (Hibbs, 2006). However, opportunistic behaviour appears to gather more support in developing countries (see, for instance, Shi & Svensson, 2002a, b, 2006; Brender & Drazen, 2008; Vergne, 2009).

3. Veiga and Veiga (2007), Drazen and Eslava (2010), Aidt, Veiga, and Veiga (2011) and Sakurai and Menezes-Filho (2011) also found political opportunism at aggregated and disaggregated levels of public expenditures but restricted to the municipal level of government.

4. In general, empirical evidence points out that partisan behaviour seems to be more recurrent in developed countries (see Alesina, Cohen, & Roubini, 1992, 1997).

5. Studies that take a look at disaggregated public expenditures found none or weak support for partisan effects in welfare related areas. See, for instance Enkelman and Leibrecht (2013) and Castro and Martins (2016).

6. The countries used in this study are listed in Table A1 in the Appendix.

7. For details on how the HDI is computed, see the Technical Notes of the Human Development Report at http://hdr.undp.org/en/data. As the data for HDI and its three components (life expectancy, education and income indices) are only available for periods of five years between 1980 and 2000, the missing data were obtained by linear interpolation for each of the three components (more recent data are provided annually); then the HDI was computed as the cubic root of the product of those three components for the entire time period (1980–2013). A direct linear interpolation of HDI was also considered, as well as cubic and natural cubic spline interpolations, in some robustness checks. To circumvent any remaining issues with interpolation, we also report estimations for shorter and more recent time periods, where fewer years are interpolated or where there is no interpolation at all: 1990–2013; 2000–2013; 2005–2013. However, independently of the kind of interpolation and time period used, the results and conclusions of this study remain unchanged.

8. An increase in the economic, financial or political rating risk index means an improvement in the respective rating risk, that is, that the economic, financial or political environment has improved.

9. We prefer to control for the impact of the economy using this indicator instead of GDP or income per capita or other related variable. As one of the components of the HDI is precisely an income index, using those variables as regressors would certainly be highly correlated with HDI.

10. The 12 components are: government stability, socioeconomic conditions, investment profile, internal conflict, external conflict, corruption, military in politics, religious tensions, law and order, ethnic tensions, democratic accountability, and bureaucracy quality. For details, see ICRG at http://www.prsgroup.com.

11. Judson and Owen (1999) notice that even for T = 30 the bias can be as much as 20 per cent of the true value of the coefficient of interest.

12. For this difference in GMM estimator to be consistent, it must be ensured that there is no autocorrelation in the errors and no correlation between individuals in the residuals. The passage of time is considered in the specification to overcome this problem.

13. Even though the magnitude of this effect seems small, we should note that, on average, the HDI grows very slowly over time. Hence, we cannot expect higher magnitudes for the estimated coefficients.

14. The differences-GMM estimator requirements are fulfilled as the Hansen tests does not reject the validity of the instruments and there is autocorrelation in the first order but not of second order.

15. We follow Andrew Gelman (2008) to standardise our variables. The author proposes dividing each numeric variable by two times its standard deviation, so that the generic comparison is with inputs equal to the mean ±1 standard deviation. The resulting coefficients are then directly comparable for untransformed binary predictors.

16. In the LSDVC regressions, we employ the Arellano and Bond (1991) estimator as the initial estimator, collapsing the instruments as suggested by Roodman (2009a, b). Following Bloom, Canning, Mansfield, and Moore (2007), we undertake 50 repetitions of the procedure to bootstrap the estimated standard errors. Nevertheless, results do not qualitatively change with different repetitions (25, 100 or even 200).

17. It is equal to 1 in the election year.

18. Aidt (2011) provides evidence of a negative impact of corruption on sustainable development.

19. GovSize is the ‘fi_sog’ index in the Economic Freedom of the World published by the Fraser Institute. Despite those effects not being relevant in our sample, Martins and Veiga (2014) have found a significant impact of government size on human development in a larger panel of 156 countries and using a convergence specification with five-year time spans. Our sample only includes countries with established democracies.

20. We also tried to test for government turnover effects using a dummy that accounts only for those elections in which there are changes in the ideology of the government, but, in this case, no significant impact was found on human development. Additionally, we tested for the presence of interaction effects between Elect_yr and GovLeft, GovMaj and EcoRating, but the respective coefficients were also always statistically insignificant. These results are not reported here to save space, but they are available upon request.

21. Another option could be to consider differences in the constitutional duration of terms in each country. However, we would face the problem that, in general, they are not very different (usually set at four years).

22. For the countries in each sample see Table A1 in the Appendix. As the number of countries is low when we split the sample, an LSDVC was also used. The results – not reported here to save space – have proved to be very similar.

23. The results for the additional covariates are not reported to save space, but they are available upon request.

24. High-income countries are those that, according to the World Bank in 2014, have a GNI per capita of $12,736 or more. The high-HDI group are considered those that, according to the United Nations Development Program, have an HDI higher than 0.800.

25. The HIC, LIC, HHDIC and LHDIC variables in the specifications (multiplied by Elect_yr) are dummies that take the value of 1 if a country belongs to that group (the differences between the respective coefficients are given by Diff_IC and Diff_HDI). An LSDVC estimator was also used for each sub-sample, but the results did not change. They are not shown here to save space, but they are available upon request.

26. Persson and Tabellini (2002) and Gassner et al. (2006) show that electoral cycles differ across political systems.

27. Presid takes the value of 1 in presidential systems, that is when the head of government is also head of state and leads an executive branch separated from the legislative branch, and 0 otherwise (NonPresid). Plural takes the value of 1 in plurality systems, that is when legislators are elected using a ‘winner-take-all’ rule, and 0 otherwise (NonPlural). PR takes the value of 1 in proportional representation regimes, that is in those regimes in which candidates are elected based on the per cent of votes received by their party, and 0 otherwise (NonPR).

Additional information

Funding

This work was supported by the Fundação para a Ciência e a Tecnologia (Portugal) [SFRH/BSAB/113588/2015].