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Regime Responsiveness to Basic Needs: a Dimensional Approach

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Abstract

Despite a considerable amount of research over the last three decades, an unequivocal conclusion regarding democracy’s impact on social outcomes has not been reached. This paper attempts to enhance understanding of the impact of political regimes on social outcomes by applying a dimensional approach. Unlike previous studies, which have focused on the overall effect of democracy, this paper separates the dimension of elite competition from the dimension of popular participation and tests their relative effects on the satisfaction of basic needs. Cross-national statistical tests demonstrate that effective participation has a positive effect on need satisfaction, whereas excessive competition has a negative impact. Theoretical explanations of these different impacts are provided. It is argued that the best way to understand the relationship between democracy and social outcomes is to realize that democracy’s overall effect might conceal the existence of opposing effects of its component parts. This finding suggests more nuanced ways of reforming political systems that bypass the possible trade-off between democratization and social development.

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Notes

  1. The data define the sample size. For example, one indicator of basic needs attainment—the multidimensional poverty index (MPI)—covers only developing countries, which reduces the sample size in the models where MPI appears as the dependent variable. A similar case is the Bertelsmann Management Index, which is not available for developing countries. Variation with the data sources and sample sizes represents a check for robustness of the results. The common practice of including both developed and developing nations, in turn, allows maximizing variation in the variables of interest and captures both the successes and failures in basic needs attainment around the world.

  2. See Appendix for links to all data sources used in this research.

  3. See “Introduction” in Vanhanen’s dataset manuscript for more details on coding procedures. Available at: https://www.prio.org/Data/Governance/Vanhanens-index-of-democracy/Polyarchy-Dataset-Manuscript/.

  4. Vanhanen himself estimates that in extreme cases this bias may be about 10–15 percentage points. See more detailed coding procedures available from https://www.prio.org/Data/Governance/Vanhanens-index-of-democracy/Polyarchy-Dataset-Manuscript/.

  5. Vanhanen (2002, 262) explains: “those who would like to challenge any of the assumptions of aggregation may classify governmental systems differently…. This dataset is not inextricably linked to my [Vanhanen’s] interpretations, but can provide data for many alternative formulations.”

  6. For a more detailed analysis of these two objective indicators and the problems with other subjective indexes of state institutional capacity, see Popov, Vladimir: “Developing New Measurement of State Institutional Capacity,” PONARS Eurasia Policy Memo No. 158, May 2011, available at: http://http-server.carleton.ca/~vpopov/documents/Institutional%20capacity%20measurement-PONARS-May%202011.pdf.

  7. The Hausman test, which checks whether the unique errors are correlated with the regressors, has been applied, and the results show that country-fixed effects are necessary as the null hypothesis (that the random effects are preferred) was rejected with high level of significance. To see if time-fixed effects are necessary a test that checks if the dummies for all years are jointly equal to zero (the null hypothesis) was applied. This null was also rejected with high level of significance which shows that time-fixed effects is the preferred model.

  8. Theories do not tell us what the correct lag should be. The 2-year lag seems reasonable, but each model was also tested with lags ranging from 0 to 6 years. Varying the lag of variables had little effect on the magnitude and significance of the correlations between competition, participation, and basic needs.

  9. It is particularly the case with HDI, because GDP is a part of it. To deal with this, all models were also re-tested with GDP excluded from the control variables. The VIF in this case drops below 2.

  10. A more detailed analysis of the concept of regime responsiveness to “basic needs” versus “wants” has been developed in Korolev, A. (2015) Needs/Wants Dichotomy and Regime Responsiveness, Critical Review: A Journal of Politics and Society, 27(1): 23–48.

  11. It is recognized that the crude indicator of voter turnout may not fully grasp the whole complexity of the phenomenon of public participation. However, it is logical to assume that political regimes where public votes actively are also likely to be participatory in other ways. Conversely, if voter turnout is low, which means the public does not use the easily available instrument of participation, other forms of peaceful and legal participation may also be unlikely.

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Authors and Affiliations

  1. Centre on Asia and Globalisation, Lee Kuan Yew School of Public Policy, National University of Singapore, 469C Bukit Timah Road, Singapore, 259772, Singapore

    Alexander Korolev

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Correspondence to Alexander Korolev.

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Korolev, A. Regime Responsiveness to Basic Needs: a Dimensional Approach. St Comp Int Dev 51, 434–455 (2016). https://doi.org/10.1007/s12116-015-9209-z

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