Economists tend to see discrimination as based on actions of individuals, who in turn are interacting in markets and society. However, sociologists do not feel the same compulsion as economists to build their theories on purposeful decision-making by individuals: "Sociologists generally understand racial discrimination as differential treatment on the basis of race that may or may not result from prejudice or animus and may or may not be intentional in nature." The Spring 2020 issue of the Journal of Economic Perspectives illustrates the difference with a two-paper symposium on "Perspectives on Racial Discrimination: "Sociological Perspectives on Racial Discrimination," by Mario L. "Race Discrimination: An Economic Perspective," by Kevin Lang and Ariella Kahn-Lang SpitzerAs most
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- "Sociological Perspectives on Racial Discrimination," by Mario L.
- "Race Discrimination: An Economic Perspective," by Kevin Lang and Ariella Kahn-Lang Spitzer
Because a higher proportion of blacks have criminal records than whites do, one might expect that preventing employers from inquiring about criminal records, at least at an early stage, would increase black employment. However, if firms cannot ask for information about criminal records, they may rely on correlates of criminal history, including being a young black man. This concern is even greater if employers tend to exaggerate the prevalence of criminal histories among black men, thus leading to inaccurate statistical discrimination. Agan and Starr (2018) investigate “ban the box” legislation in which companies are forbidden from asking job applicants about criminal background. Before such rules took effect, employers interviewed similar proportions of black and white male job applicants without 84 Journal of Economic Perspectives criminal records. Prohibiting firms from requesting this information reduced callbacks of black men relative to otherwise similar whites. Consistent with this, Doleac and Hansen (2016) find that banning the box reduced the employment of low-skill young black men by 3.4 percentage points and low-skill young Hispanic men by 2.3 percentage points. Similarly, occupational licensing increases the share of minority workers in an occupation despite their lower pass rates on such exams (Law and Marks 2009). Prohibiting the use of credit reports in hiring reduced black employment rather than increasing it (Bartik and Nelson 2019). Taken together, these studies provide strong evidence that statistical discrimination plays an important role in hiring.As sociologists, Small and Pager have no direct issue with this kind of work in economics: as they point out, some sociologists work in a similar vein. But their essay emphasizes that discriminatory outcomes can emerge from reasonable-sounding institutional choices and from history.
It is not surprising that a national study of 327 establishments that downsized between 1971 and 2002 found that downsizing reduced the diversity of the firm’s managers—female and minority managers tended to be laid off first. But what is perhaps more surprising is that those companies whose layoffs were based formally on tenure or position saw a greater decline in the diversity of their managers; net of establishment characteristics such as size, personnel structures, unionization, programs targeting minorities for management, and many others; and of industry characteristics such as racial composition of industry and state labor force, proportion of government contractors, and others (Kalev 2014). In contrast, those companies whose layoffs were based formally on individual performance evaluations did not see greater declines in managerial diversity (Kalev 2014).
However, the Home Owners Loan Corporation and Federal Housing Administration were also responsible for the spread of redlining. As part of its evaluation of whom to help, the HOLC created a formalized appraisal system, which included the characteristics of the neighborhood in which the property was located. Neighborhoods were graded from A to D, and those with the bottom two grades or rankings were deemed too risky for investment. Color-coded maps helped assess neighborhoods easily, and the riskiest (grade D) neighborhoods were marked in red. These assessments openly examined a neighborhood’s racial characteristics, as “% Negro” was one of the variables standard HOLC forms required field assessors to record (for example, Aaronson, Hartley, and Mazumder 2019, 53; Norris and Baek 2016, 43). Redlined neighborhoods invariably had a high proportion of AfricanAmericans. Similarly, an absence of African-Americans dramatically helped scores. For example, a 1940 appraisal of neighborhoods in St. Louis by the Home Owners Loan Corporation gave its highest rating, A, to Ladue, an area at the time largely undeveloped, described as “occupied by ‘capitalists and other wealthy families’” and as a place that was “not the home of ‘a single foreigner or Negro’” (Jackson 1980, 425). In fact, among the primary considerations for designating a neighborhood’s stability were, explicitly, its “protection from adverse influences,” “infiltration of inharmonious racial or nationality groups,” and presence of an “undesirable population” (as quoted in Hillier 2003, 403; Hillier 2005, 217).
The results are consistent with the HOLC boundaries having a causal impact on both racial segregation and lower outcomes for predominantly black neighborhoods. As the authors write, “areas graded ‘D’ become more heavily African-American than nearby C-rated areas over the 20th century, [a].segregation gap [that] rises steadily from 1930 until about 1970 or 1980 before declining thereafter” (p. 3). They find a similar pattern when comparing C and B neighborhoods, even though “there were virtually no black residents in either C or B neighborhoods prior to the maps” (p. 3). Furthermore, the authors find “an economically important negative effect on homeownership, house values, rents, and vacancy rates with analogous time patterns to share AfricanAmerican, suggesting economically significant housing disinvestment in the wake of restricted credit access” (pp. 2–3).