Comments on Garcia and Stout 2020 "Responding to Racial Resentment: How Racial Resentment Influences Legislative Behavior"

Political Research Quarterly published Garcia and Stout 2020 "Responding to Racial Resentment: How Racial Resentment Influences Legislative Behavior". The article abstract indicates (emphasis added):

Through an automated content analysis of more than fifty four thousand press releases from almost four hundred U.S. House members in the 114th Congress (2015–2017), we show that Republicans from districts with high levels of racial resentment are more likely to issue press releases that attack President Barack Obama. In contrast, we find no evidence of racial resentment being positively associated with another prominent Democratic white elected official, Hillary Clinton. Our results suggest that one reason Congress may remain racially conservative even as representatives' cycle out of office may be attributed to the electoral process.

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Racial resentment conflates racial attitudes and political ideology, apparently even when controlling for factors such as partisanship and political ideology, so comparing how district racial resentment predicts the percentage of press releases attacking Barack Obama to how district racial resentment predicts the percentage of press releases attacking Hillary Clinton is a useful way to assess whether any association of racial resentment is due to the racial component of district racial resentment. But that comparison should involve a statistical test of whether the coefficient for district racial resentment in the Obama models differs from the coefficient for district racial resentment in the Clinton models. And my analyses indicate that, for results reported in the article, these coefficients don't differ at p<0.20.

My analyses indicated that the p-value is p=0.23 for a test of whether the coefficient on district racial resentment in an Obama model differs from the coefficient on district racial resentment in a Clinton model, using only a predictor of weighted district racial resentment and limiting the sample to Republican representatives. The p-value is about p=0.33 for a test comparing the key interaction coefficients in Models C and D in Garcia and Stout 2020 Table 1 (see the plot below).

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The Garcia and Stout 2020 abstract's claim that "…we find no evidence of racial resentment being positively associated with another prominent Democratic white elected official, Hillary Clinton" (p. 812) is contradicted in the main text of Garcia and Stout 2020:

Pearson's R for the relationship between the unweighted (.16) and the weighted (.14) district's racial resentment score and Republicans issuing of negative-Clinton press releases are statistically significant at .05.

I think that the "no evidence" claim refers to the lack of statistical significance for the Clinton models in Table 1 when adding statistical control, but the coefficient/standard error ratio is about 1.3 for the key coefficient for Clinton in Table 1 Model D, so that's some evidence. Adding "cluster(robust)" to the regression specification increases this t-statistic to 1.78, which is not no evidence. And then removing the control for candidate margin of victory gets the p-value under p=0.05.

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For the outcome variable codings of the percentage of press releases attacking Obama and the percentage of press releases attacking Clinton, 53% and 76% of the observations are zero, respectively. The outcome is a percentage, so I re-estimated the models using fractional logistic regression. As indicated in the output, the p-value for the interaction coefficient did not fall under p=0.15 in the Clinton models mentioned above or in the Obama models mentioned above.

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The key Table 1 coefficient is an interaction term that involves district racial resentment and the political party of the representative, but the abstract claims are limited to Republican representatives. I estimated the Table 1 models limited to Republican representatives: the p-value for racial resentment did not fall under p=0.80 for the Obama models. The p-value for racial resentment did not fall under p=0.40 for the Obama models limited to non-Republican representatives.

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So, in the fractional regression models discussed above, the key Table 1 interaction coefficient did not have a p-value under p=0.15; in the linear regression models discussed above with statistical control, district racial resentment did not predict at p<0.80 among Republican representatives the percentage of press releases attacking Obama; and in the linear regression models discussed above, the association of district racial resentment and the percentage of press releases attacking Obama did not differ at p<0.20 from the association of district racial resentment and the percentage of press releases attacking Clinton.

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NOTES

1. Thanks to Jennifer R. Garcia for sending me data for the article.

2. Results reported in the post are for the weighted models, but the Stata output contains results for unweighted models, in which the inferences or a lack of inferences are the same or similar.

3. Stata code. Stata output. R code for the plot.

4. For what it's worth, Republican members of Congress from districts with relatively low levels of racial resentment were more likely to issue press releases that attacked Obama than to issue press releases that attacked Clinton, measuring low district racial resentment as the bottom 10% of GOP districts by racial resentment; the same pattern held for Republican members of Congress from districts with relatively high levels of racial resentment, measured as the top 10% of GOP districts by racial resentment. Stata code for this analysis. Stata output for this analysis.