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Cushioning the Fall: Scandals, Economic Conditions, and Executive Approval

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An Erratum to this article was published on 01 April 2014

Abstract

Why do some presidents emerge from a scandal unscathed while for others it may lead to a crisis of legitimacy? This question is crucial to understanding the conditions under which elected leaders are held accountable. This study proposes a theory of conditional accountability by which the public most consistently punishes presidents for scandals when the economy is weak. Under strong economic conditions, scandals do not tarnish presidents’ public standing. To test the theory, we use a new dataset that includes measures of scandals, presidential approval, and the economy for 84 presidential administrations in 18 Latin American countries. Consistent with our expectations, scandals only appear to damage presidential approval when inflation and unemployment are high.

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Notes

  1. In addition, differences in question wording, sample design, and survey frequency limit the comparability of approval data across countries (Pérez-Liñán 2007, p 116). We discuss this issue below.

  2. Dates vary by country; see Table 1 in the Supporting Information (SI).

  3. The raw data series that are the basis for presidential approval come from a variety of sources. Most have been generously provided by private survey firms in each Latin American country.

  4. It is unclear what grade, or grades, indicate “approval” of the president. Further, we have no way of verifying whether respondents base their grades on country-specific scales or norms for “passing” and “failing.” Thus, parsing the scale to calculate a survey marginal of presidential approval from a grading scale is arbitrary and likely invalid.

  5. To ensure our findings are not unduly influenced by countries with shorter series we estimated the models using only the eight countries with the longest series, at least 63 quarters, and the results are substantively identical to those presented below (see SI, Tables 4, 5).

  6. Table 1 in the online supplemental materials displays summary statistics for approval across the sample.

  7. Adopting Palmer and Whitten’s (1999) strategy, the quarterly indicator of unemployment was calculated on the basis of the following formula: ρ = [ρ(t − 1) × (4 − σ(t))/4] + [ρ(t) × (σ(t)/4)], whereas “ρ” is the annual economic indicator, “σ” the quarter of interest, and “t” the year of reference. For example, to compute a value for the first quarter of 1996, we would multiply the 1996 annual indicator by 1/4 and add it to the 1995 annual indicator multiplied by 3/4. We followed the same process for GDP and calculated growth as the percent change in quarterized GDP.

  8. Results using the ECM specification of the model are identical to the ADL, indicating the model does not suffer from co-integrated data. Similarly, augmented Dickey-Fuller panel tests of the approval and the key economic variables show the data to be stationary.

  9. Using the (Arellano and Bond 1991) test for autocorrelation in panel data for the models in Table 2, we reject the null hypothesis of remaining autocorrelation in the error terms (P = 0.302).

  10. Both of these effects are direct and additive. When the signs on the two short-run effects are in opposite directions it often indicates that the variable’s effect, whatever it is, is short lived. The influence of Xt can be attenuated when Xt−1 has an opposite effect; however, when both coefficients carry the same sign the variable’s effect is likely long lasting. While lags greater than one period can be incorporated into the ADL framework, we find no evidence that additional lag lengths contribute to model fit.

  11. Without controls for inflation and unemployment, more proximate economic indicators, growth has direct but not conditional effects on scandals (see SI, Tables 2 , 3, column V).

  12. Scandal has a significant and positive coefficient in some of the interactive models because at no time are the interactive terms zero. To assess how scandals affect approval, the effect of the interaction terms with unemployment, inflation, and growth must be taken into account (see Fig. 2).

  13. Controlling for press freedom and whether the president’s party controls the legislature (high clarity of responsibility) does not change the result. For reasons of over-fitting, parsimony, and clarity of presentation we report these models in the SI, Tables 2 , 3.

  14. We also tested whether the conditioning effect of the economy is dependent on trade openness, Polity score, press freedom, or unified government (using 3-way interactions). We find no evidence for such relationships and because of issues of multicollinearity and data limitations we exclude them from the analysis.

  15. Using the natural log of inflation in the full sample model does not substantively change the results from those presented. We use the untransformed data for easier interpretation of effects.

  16. In all interaction graphs the other variables are set at their sample means: 9.6 % unemployment, 9.1 % inflation, and .38 % quarterly growth (without Brazil, 9.6, 7.12, and .39 %, respectively).

  17. The estimate from the fixed-effects model is also close to the observed value: a drop of 14.6 percentage points.

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Acknowledgments

The authors acknowledge a great deal of support for this study. For feedback regarding its scope and approach we thank Jonathan Hartlyn, Gregg Johnson, Aníbal Pérez-Liñán, David Samuels, Matthew Singer, James Stimson and participants in the Comparative Politics Working Group at UNC. Data were graciously provided by Sergio Berenzstein, Taylor Boas, Ernesto Calvo, Julio Carrión, Francois Gélineau, Kirk Hawkins, Gregg Johnson, Beatriz Magaloni, Andrés Mejía Acosta, Jana Morgan, Observatorio Electoral of Universidad Diego Portales, Aníbal Pérez-Liñán, Matthew Singer, and Leslie Schwindt-Bayer. We are grateful for research assistance from Aries Arugay, Tyra Bouhamdan, Sarah Shair-Rosenfield, Alissandra Stoyan, Inés Valdez, and Harry Young. Financial support came in part from UNC’s University Research Council Grant #3-10059.

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Authors and Affiliations

  1. Political Science Department, Georgia State University, Atlanta, GA, USA

    Ryan E. Carlin

  2. Political Science Department, University of Mississippi, University, MS, USA

    Gregory J. Love

  3. Political Science Department, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Cecilia Martínez-Gallardo

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  1. Ryan E. Carlin
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Correspondence to Gregory J. Love.

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Carlin, R.E., Love, G.J. & Martínez-Gallardo, C. Cushioning the Fall: Scandals, Economic Conditions, and Executive Approval. Polit Behav 37, 109–130 (2015). https://doi.org/10.1007/s11109-014-9267-3

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