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Shades of red and blue: government ideology and sustainable development

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Abstract

We study the effect of government ideology on sustainable development, measured as investment in genuine wealth, in a dynamic panel of 79 countries between 1981 and 2013. We find robust and statistically significant evidence that genuine investment grows faster under right-wing governments than under left-wing or center governments. In contrast, we find no indication of opportunistic cycles.

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Notes

  1. Natural capital refers to physical stocks of renewable and non-renewable resources and to the physical receptor systems that can assimilate pollution (e.g., the seas and the atmosphere).

  2. This, of course, not the only definition of sustainable development. In fact, many different definitions have been proposed in the literature (see, e.g., Lawn 2003). The advantage of the World Commission’s definition over alternatives is that it is firmly based on welfare economics considerations.

  3. One consequence of the intertemporal emphasis is that tradeoffs are allowed, in the sense that social welfare may be lower at some future date than it is today so long as the discounted present value is not declining. See Arrow et al. (2004, p. 150) for further discussion of the implications of this definition.

  4. Formally, let xij be a particular indicator of “development” i in country j. Then the preformance gap for that indicator for that country is \(I_{ij} = \frac{{\left\{ {max_{j} x_{ij} - x_{ij} } \right\}}}{{\left\{ {max_{j} x_{ij} - min_{j} x_{ij} } \right\}}}\); the HDI for country j is \(1 - \frac{1}{M}\sum\nolimits_{i} {I_{ij} } ,\) where M is the number of indicators (see Fleurbaey (2009) for a discussion of human development index and other measures of social welfare).

  5. Persistence is a strong assumption as institutions do change. It can be justified by the so-called “critical junctions” theory of institutional development. According to that theory, institutional reform happens at critical junctions in history. Once the new institutions are in place, they persist for a long time—until the next critical junction. (See Acemoglu et al. 2001 for an example of this line of reasoning.) That view is, however, challenged by modernization theory, according to which democratic institutions emerge gradually as a consequence of economic development (see, e.g., Gundlach and Paldam 2009; Guerriero 2016, who shows legal institutions also evolve gradually in response to socio-economic factors). In the statistical analysis, we do attempt to capture institutional changes, but for the logic of the theoretical analysis to go through, it is a convenient simplification to consider institutions as fixed and ideology as the aspect that fluctuates.

  6. See also Dasgupta (2001, chapter 9) and Hamilton and Clemens (1999).

  7. See also Reed (2006), Imbeau et al. (2001) and Frederiksson et al. (2013). Moreover, Folke (2014) shows that small political parties with a focus on specific issues such as the environment or immigration can influence policy on those margins. For a good survey of the relevance of government ideology, see Potrafke (2017).

  8. The theoretical foundation for the opportunistic political business cycle was laid by Nordhaus (1975) and integrated into rational expectations models by Rogoff and Sibert (1988) and Rogoff (1990) and applied in Aidt and Mooney (2014). The literature recently has been surveyed by Dubois (2016). Empirical studies suggest that favorable economic conditions in the lead-up to an election do benefit the incumbent government (Hibbs 2006).

  9. Specifically, we use the Legislative and Executive Indices of Electoral Competitiveness from the Database of Political Institutions (DPI) to define the sample. It scores countries on a 1–7 scale with higher values meaning more competitive elections. We excluded countries with values lower than 6, meaning that we include countries (during periods) in which they had competitive elections and when multiple parties did win seats. A score of 6 indicates that the largest party received more than 75% of the seats, while a score of 7 indicates that it won less than that (in some robustness checks, we restrict the sample to those countries with a score of 7). The countries in our sample are listed in the note to Table 2. It includes countries from Europe, the Americas, Africa, Oceania, the Middle East and Asia.

  10. For details on how it is computed, see Arrow el al. (2003). The WDI use the term “adjusted net savings” to describe what we refer as “genuine investment”.

  11. It has two parts. The first is designed to capture the cost of global warming. An estimate of the social cost of carbon dioxide emissions is subtracted from national savings, with the assumption that the average social cost of a ton of carbon is US$30. The second part is designed to capture the impact of local environmental degradation. The World Bank makes a financial deduction for an estimate of the health damages caused by urban air pollution (particulate emissions) from gross savings.

  12. The rents are calculated as the market price of the resource minus average extraction cost for the two non-renewable resources (energy and mineral depletion). For renewable forest resources, the rent is estimated as the market price per unit of harvest in excess of the natural regeneration rate.

  13. In the baseline, we follow Arrow et al. (2004) and the ratios we use are 0.2 for industrialized countries and 0.15 for developing and oil-rich countries. We have investigated if the results are sensitive to this choice and Table A2 in the supplementary material shows that the results are not sensitive to variations within the range of plus/minus 25.

  14. For the subset of OECD countries and for individual countries (such as the United States and Canada), more refined classifications of party ideology exist (see Bjørnskov 2005, 2008; Bjørnskov and Potrafke 2012, 2013; Lamérisa et al. 2018).

  15. For further information on how the party classification is constructed, see the DPI codebook (Keefer 2012).

  16. Although the two-step estimator is asymptotically more efficient than the one-step estimator and relaxes the assumption of homoscedasticity, the efficiency gains are not that important even in the case of heteroscedastic errors. That result is supported by Judson and Owen (1999). They show empirically that the one-step estimator outperforms the two-step estimator, especially when the number of time periods is relatively large (T = 30), which is the case in this study. Arellano and Bover (1995) and Blundel and Bond (1998) suggest another GMM estimator with additional moment conditions. If the conditions are valid, efficiency will increase. The system GMM estimator combines the moment conditions of the model in first differences with those of the model in levels. However, if the orthogonality conditions for the first-differenced equation are valid, but those for the level equation are not, then the system GMM estimator may not be better than first-differences GMM estimator. That can happen, for example, if the regressors used in the orthogonality conditions for the levels equation are correlated with the individual effects. Moreover, simulations suggest that the system GMM estimator is not necessarily superior to the standard GMM estimator in cases for which the autoregressive parameter is below 0.8 and the time-series observations are relatively large (Blundell and Bond 1998; Moshirian and Wu 2012). That is what we observe in our data. So, to sum up, the estimator that is most suitable for our empirical analysis is the one-step first-differences GMM estimator.

  17. Table A6 in the supplementary material reports the results from a system-GMM estimator. The results are similar to those shown in Table 3.

  18. That conjecture is substantiated by the fact that the correlation between the Fraser Institute’s Economic Freedom Index and the right-wing government indicator is positive (0.11) and significant at the 1% level. Moreover, the correlation between the right-wing government indicator and the regulation sub-component of the Freedom House index (capturing credit, labor and business regulations) is negative (− 0.14) and also significant at the 1% level.

  19. In additional experiments, reported in Table A1 in the supplementary material, we investigate the existence of cycles in elections that result in a change in the political orientation of the government, if differences are observed in pre- and post-election years, or if it matters how long the interval between elections is. Apart from a weak positive effect of elections that result in a change in government ideology, we find no evidence of an election cycle.

  20. Specifically, we consider the democratization index proposed by Acemoglu et al. (2018) and the machine learning-based index proposed by Gründler and Krieger (2016) as alternatives to the Polity IV index and find similar results [available upon request]. We also have investigated the effect of controlling for specific (as opposed to general) features of the political system including controls for the type of political regime (presidential versus parliamentarian; plurality versus non-plurality), for the election system (majority versus proportional rules) and for various indicators of the quality of institutions from the International Country Risk Guide. Those results are reported in Tables A3 and A4 in the supplementary material. Very occasionally one of the institutional controls is significant, but in no case does it have more than a small effect on the size and significance of the estimated effect of right-wing government ideology.

  21. We have investigated if the effect of right-wing government ideology on sustainable development is conditional on the general quality of political institutions, on the regime type or on the election rule. We cannot find any evidence that it is contigent on the general quality of political institutions (results available upon request). Tables A3 and A4 in the supplementary material report that the effect is larger in plurality regimes and in countries with proportional election rules.

  22. While in the group of OECD countries the growth rate of genuine wealth per capita is, on average, 0.13% points higher when a right-wing party is in office, in the non-OECD countries it is 0.24% points higher, ceteris paribus.

  23. Besides dividing the sample between the OECD and non-OECD countries, we also investigated alternative sample splits. Those results, reported in Tables A3, A4 and A5 in the supplementary material, show that right-wing parties affect investment in genuine wealth in presidential, plurality and proportional representation regimes and are observed in both high- and low-income countries/democracies.

  24. Furthermore, the positive relationship between right-wing governments and genuine investment is robust to changes in the proxies for the economy’s capital stocks, shadow prices (see Table A2 in the supplementary material), exclusion of some countries (with more populist reputations), and to the use of the Blundell-Bond system GMM estimator (see Tables A6 in the supplementary material).

  25. We use the Stata procedure PSACALC (Oster, 2017) to calculate the numbers.

  26. See, for example, the seminal papers by Mueller (1970) and Veiga and Veiga (2004).

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Acknowledgements

The authors acknowledge the helpful comments and suggestions from the participants at the 23rd International Academic Conference of the International Institute of Social and Economic Sciences, Venice International University, Venice, Italy, 27–30 April 2016; the participants at the 10th Annual Meeting of the Portuguese Economic Journal, University of Coimbra, Portugal, 1–3 July 2016; and the participants at the 2017 annual Meeting of the European Public Choice Society, Central European University, Budapest, Hungary, 19–22 April. Vitor Castro also wishes to thank the financial support provided by the Portuguese Foundation for Science and Technology under the research grant SFRH/BSAB/113588/2015 (partially funded by COMPTE, QREN and FEDER).

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Authors and Affiliations

  1. Faculty of Economics and Jesus College, University of Cambridge, Cambridge, CB3 9DD, UK

    Toke S. Aidt

  2. School of Business and Economics, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK

    Vitor Castro

  3. Economic Policies Research Unit (NIPE), University of Minho, Campus of Gualtar, 4710-057, Braga, Portugal

    Vitor Castro

  4. Faculty of Economics, University of Coimbra, Av. Dias da Silva 165, 3004-512, Coimbra, Portugal

    Rodrigo Martins

  5. Centre for Business and Economic Research (CeBER), Av. Dias da Silva 165, 3004-512, Coimbra, Portugal

    Rodrigo Martins

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  1. Toke S. Aidt
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Aidt, T.S., Castro, V. & Martins, R. Shades of red and blue: government ideology and sustainable development. Public Choice 175, 303–323 (2018). https://doi.org/10.1007/s11127-018-0536-2

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