Noneconomic Variables Sample Clauses

Noneconomic Variables. ‌ In addition, I match on a few other non-economic variables. The human rights literature has developed a list of “the usual suspects” for use as control variables, which I will match on in this study. Namely, as laid out in Hill and ▇▇▇▇▇ (2014), these are: level of democracy (Polity IV), civil war (UCDP/PRIO), and alliance status with the US/EU (voting record in the United Nations General Assembly) (▇▇▇▇▇▇, Strezhnev and ▇▇▇▇▇▇ ▇▇▇▇, ▇▇▇▇▇▇, Strezhnev and ▇▇▇▇▇▇ 2009). I will use these variables as well in this analysis. Of particular interest is degree to which states vote with the United States in the UN General Assembly. Given the US’ and Europe’s disproportionate sway in determining the lending behavior of the IMF, it may be the case that being in an alliance with one of these bodies may make loan terms more favorable, allow the state to repress its citizens more and avoid shaming, or shorten the window between crisis onset and implementation of an agreement. Other factors, such as youth bulges (Urdal 2006), may also be important for matching and explaining levels of repression, but due to data missingness these were not included in this study.4 Of potential concern regarding these variables is the fact that they are only available at the annual level. In order to conform the data to the country-month setup used in the rest of the analysis, I impute the values for a given month by using the value for the year. Thus, if a country received a score of “4” on the Polity IV (democracy) scale for 2010, then I give that country a “4” for all the months of 2010. This is not a perfect method, but I do so to try to take into account other variables that may affect human rights, repression, and protest outcomes. Figure 2, below, is a balance test for the dataset used to test the backlash hypotheses. It shows the differences in means between these variables before and after propensity score matching. Summary statistics for each subgroup are available in the appendix (where C = Control, T = Treatment group). In order for matching to be an improvement on a simpler model, we want to have the absolute mean differences as close to zero as possible, meaning that the difference between the two samples regarding these relevant covariates is negligible5 After matching, I then examine two different time periods, depending on the hypothesis. For H1 (protest and repression as a result of being under a program), I look at the frequency of protest and repression for those cou...
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