{"id":7434,"date":"2018-10-08T08:27:36","date_gmt":"2018-10-08T07:27:36","guid":{"rendered":"http:\/\/emilkirkegaard.dk\/en\/?p=7434"},"modified":"2018-10-09T11:38:17","modified_gmt":"2018-10-09T10:38:17","slug":"tests-of-colorism-in-pelotas-brazil-sample-for-income-wealth-and-education-outcomes","status":"publish","type":"post","link":"https:\/\/emilkirkegaard.dk\/en\/2018\/10\/tests-of-colorism-in-pelotas-brazil-sample-for-income-wealth-and-education-outcomes\/","title":{"rendered":"Tests of colorism in Pelotas (Brazil) sample for income, wealth and education outcomes"},"content":{"rendered":"

In 2016, a Brazilian PHD student with access to the Brazilian Pelotas dataset<\/a> was kind enough to run a few regressions for us. We apparently forgot to make the results public, but do so now so others can see. I have also previously analyzed<\/a> some of this data which was later published in an obscure place (thanks to Random Critical Analysis<\/a> for finding it). Unfortunately, the IQ variable was not among the published variables and the ancestry data was binned which distorts results<\/a>, but still colorism could be rejected for that dataset.<\/p>\n

Anyway, back to the Pelotas results from the pure dataset. The first table gives summary statistics for the genomically measured ancestry variables.<\/p>\n

Table 1.<\/b><\/span> Mean and standard deviation of European, African and Amerindian genomic ancestry (N=3030).*<\/span><\/p>\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n
Genomic ancestry<\/b><\/span><\/td>\nMean (%)<\/b><\/span><\/td>\nStandard deviation (%)<\/b><\/span><\/td>\n<\/tr>\n<\/tbody>\n
European<\/span><\/td>\n77.3<\/td>\n20.2<\/td>\n<\/tr>\n
African<\/span><\/td>\n15.5<\/td>\n19.2<\/td>\n<\/tr>\n
Amerindian<\/span><\/td>\n7.2<\/td>\n4.6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

*Refers to individuals with data for at least one socioeconomic outcome.<\/span><\/p>\n

 <\/p>\n

The second table shows the correlations between ancestry and the social status measures. These were included in our 2017 meta-analysis<\/a>.<\/p>\n

Table 2.<\/b><\/span> Pearson correlation coefficients of European, African and Amerindian genomic ancestry with socioeconomic outcomes measured at 30-31 years of age.<\/span><\/p>\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n
Genomic ancestry<\/b><\/span><\/td>\nHousehold asset index (N=2845)<\/b><\/span><\/td>\nIncome (Brazilian reais) (N=3030)<\/b><\/span><\/td>\nSchooling in complete years (N=3005)<\/b><\/span><\/td>\n<\/tr>\n<\/tbody>\n
European<\/span><\/td>\n0.27<\/span><\/span><\/td>\n0.15<\/span><\/span><\/td>\n0.22<\/span><\/span><\/td>\n<\/tr>\n
African<\/span><\/td>\n-0.24<\/span><\/span><\/td>\n-0.14<\/span><\/span><\/td>\n-0.19<\/span><\/span><\/td>\n<\/tr>\n
Amerindian<\/span><\/td>\n-0.17<\/span><\/span><\/td>\n-0.12<\/span><\/span><\/td>\n-0.17<\/span><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\n

The sample sizes for the dataset. Note the tiny samples for Asian meaning that these should be ignored. They should also be ignored because the ancestry estimation did not include a proper East Asian ancestry, these are probably Japanese descent people<\/a>.<\/p>\n

Table 3.<\/b><\/span> Number of individuals in each skin color with valid data for each socioeconomic outcome.<\/span><\/p>\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Skin color<\/b><\/span><\/td>\nPredictors<\/b><\/span><\/td>\nHousehold asset index<\/b><\/span><\/td>\nIncome (Brazilian reais)<\/b><\/span><\/td>\nSchooling in complete years<\/b><\/span><\/td>\n<\/tr>\n<\/tbody>\n
Interviewer-rated<\/span><\/td>\nWhite<\/span><\/td>\n2258<\/td>\n2386<\/td>\n2368<\/td>\n<\/tr>\n
<\/td>\nBrown or Mulatto<\/span><\/td>\n185<\/td>\n203<\/td>\n202<\/td>\n<\/tr>\n
<\/td>\nBlack<\/span><\/td>\n390<\/td>\n418<\/td>\n412<\/td>\n<\/tr>\n
<\/td>\nAsian (\u201cyellow\u201d)<\/span><\/td>\n11<\/td>\n11<\/td>\n11<\/td>\n<\/tr>\n
<\/td>\nNative American<\/span><\/td>\n10<\/td>\n12<\/td>\n12<\/td>\n<\/tr>\n<\/tbody>\n
Self-reported<\/span><\/td>\nWhite<\/span><\/td>\n2138<\/td>\n2261<\/td>\n2244<\/td>\n<\/tr>\n
<\/td>\nBrown or Mulatto<\/span><\/td>\n161<\/td>\n171<\/td>\n170<\/td>\n<\/tr>\n
<\/td>\nBlack<\/span><\/td>\n462<\/td>\n496<\/td>\n489<\/td>\n<\/tr>\n
<\/td>\nAsian (\u201cyellow\u201d)<\/span><\/td>\n50<\/td>\n54<\/td>\n54<\/td>\n<\/tr>\n
<\/td>\nNative American<\/span><\/td>\n43<\/td>\n48<\/td>\n48<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\n

Finally, the regressions of interest. Note the effect sizes and directions here, not just the p values. <\/strong>Skin color as rated by either interviewers or subjects themselves (models 1-2) had non-random relations to outcomes, but in the wrong directions! Controlling for ancestry, darker skin generally was related to better<\/em> outcomes, not worse. Thus, at least for this sample, colorism seems disproved as one would expect. Brazil has various affirmative action policies<\/a> and these should result in the positive associations one sees because such policies are based on visual racial cues, not genomic ancestry.<\/p>\n

Table 4.<\/b><\/span> Standardized linear regression coefficients (standard errors) of socioeconomic outcomes at 30-31 years of age according to European genomic ancestry and skin color.<\/span><\/p>\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Skin color<\/b><\/span><\/td>\nPredictors<\/b><\/span><\/td>\nHousehold asset index<\/b><\/span><\/td>\nIncome (Brazilian reais)<\/b><\/span><\/td>\nSchooling in complete years<\/b><\/span><\/td>\n<\/tr>\n<\/tbody>\n
Model 1<\/span><\/td>\nEuropean ancestry<\/b><\/span><\/td>\nP=3.8\u00d710-48<\/sup><\/td>\nP=3.8\u00d710-18<\/sup><\/td>\nP=2.4\u00d710-38<\/sup><\/td>\n<\/tr>\n
<\/td>\n<\/td>\n0.299 (0.036)<\/td>\n0.187 (0.035)<\/td>\n0.311 (0.034)<\/td>\n<\/tr>\n
Interviewer-rated<\/span><\/td>\nSkin color<\/b><\/span><\/td>\n<\/a>P=0.045<\/td>\nP=0.384<\/td>\nP=3.8\u00d710-5<\/sup><\/td>\n<\/tr>\n
<\/td>\nWhite<\/span><\/td>\n0 (Ref.)<\/td>\n0 (Ref.)<\/td>\n0 (Ref.)<\/td>\n<\/tr>\n
<\/td>\nBrown or Mulatto<\/span><\/td>\n0.139 (0.088)<\/td>\n-0.010 (0.086)<\/td>\n0.052 (0.085)<\/td>\n<\/tr>\n
<\/td>\nBlack<\/span><\/td>\n0.076 (0.100)<\/td>\n0.113 (0.098)<\/td>\n0.277 (0.097)<\/td>\n<\/tr>\n
<\/td>\nAsian (\u201cyellow\u201d)<\/span><\/td>\n-0.583 (0.291)<\/td>\n-0.359 (0.299)<\/td>\n-0.795 (0.293)<\/td>\n<\/tr>\n
<\/td>\nNative American<\/span><\/td>\n-0.511 (0.306)<\/td>\n-0.205 (0.286)<\/td>\n-0.770 (0.281)<\/td>\n<\/tr>\n<\/tbody>\n
Model 2<\/td>\nEuropean ancestry<\/b><\/span><\/td>\nP=3.5\u00d710-48<\/sup><\/td>\nP=3.7\u00d710-18<\/sup><\/td>\nP=2.2\u00d710-38<\/sup><\/td>\n<\/tr>\n
<\/td>\n<\/td>\n0.286 (0.034)<\/td>\n0.177 (0.033)<\/td>\n0.287 (0.033)<\/td>\n<\/tr>\n
Self-reported<\/span><\/td>\nSkin color<\/b><\/span><\/td>\nP=0.017<\/td>\nP=0.169<\/td>\nP=1.5\u00d710-5<\/sup><\/td>\n<\/tr>\n
<\/td>\nWhite<\/span><\/td>\n0 (Ref.)<\/td>\n0 (Ref.)<\/td>\n0 (Ref.)<\/td>\n<\/tr>\n
<\/td>\nBrown or Mulatto<\/span><\/td>\n-0.114 (0.088)<\/td>\n-0.053 (0.088)<\/td>\n-0.151 (0.086)<\/td>\n<\/tr>\n
<\/td>\nBlack<\/span><\/td>\n0.077 (0.090)<\/td>\n0.083 (0.089)<\/td>\n0.213 (0.088)<\/td>\n<\/tr>\n
<\/td>\nAsian (\u201cyellow\u201d)<\/span><\/td>\n-0.362 (0.140)<\/td>\n-0.221 (0.139)<\/td>\n-0.396 (0.136)<\/td>\n<\/tr>\n
<\/td>\nNative American<\/span><\/td>\n-0.103 (0.149)<\/td>\n0.162 (0.145)<\/td>\n-0.140 (0.142)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

In 2016, a Brazilian PHD student with access to the Brazilian Pelotas dataset was kind enough to run a few regressions for us. We apparently forgot to make the results public, but do so now so others can see. I have also previously analyzed some of this data which was later published in an obscure […]<\/p>\n","protected":false},"author":17,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2463,2591,1921],"tags":[2343],"class_list":["post-7434","post","type-post","status-publish","format-standard","hentry","category-genomics","category-intelligence-iq-cognitive-ability","category-sociology","tag-colorism","entry"],"_links":{"self":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts\/7434","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/users\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/comments?post=7434"}],"version-history":[{"count":4,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts\/7434\/revisions"}],"predecessor-version":[{"id":7438,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/posts\/7434\/revisions\/7438"}],"wp:attachment":[{"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/media?parent=7434"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/categories?post=7434"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/emilkirkegaard.dk\/en\/wp-json\/wp\/v2\/tags?post=7434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}