Sheila D. Ards

Racial disproportionality in reported and substained child abuse and nelgect: an examination of systematic bias

Using data from Minnesota fo 2000, we show that measures of discrimination in maltreatment substantiation are inflated by a failure to disaggegate counties with large minority populations from those with small minority populations. Racial disparities in substantiaion rates, conditional upon reports to child protective service workers, are not huge. Nonetheless, measures of discrimination -- once one accounts for characteristics of victims, offenders, reporters, counties and types of maltreatment--are non-trivial. For African Americans they are higher in the state as a whole than in the counties that have the largest share of minority children. Although the discrimination measures do not vanish when disaggregaed analysis is performed, our findings suggest that caution should be displayed when reporting disproportionality statistics that include data from widely dispersed geographical areas.

The Effects of Sample Selection Bias on Racial Differences in Child Abuse Reporting

OBJECTIVE The aim was to examine whether design features of Wave 1, 1980 National Incidence Study (NIS) data resulted in sample selection bias when certain victims of maltreatment were excluded. METHOD Logistic regression models for the probability of child abuse reports to the child protective services (CPS) were estimated using maximum likelihood methods for Black (n = 511) and White (n = 2499) child abuse cases. The models were estimated with and without correction for selection bias using a two-step procedure proposed by Heckman. RESULTS Substantial differences were found in the characteristics of Black and White victims by source of report and by type of maltreatment. Also found were sizeable differences within each racial group between sampled agencies and nonsampled agencies. Sample selection bias affected the estimation of both White and Black child abuse reporting rates. In the Black sample, however, the effect of sample selection bias was to reduce the statistical significance of the impacts of reporting agency and physical and sexual abuse on report rates. In the White sample, most significant factors in the basic model remained statistically significant with correction for selection bias. CONCLUSIONS Selection bias was found to be caused by the exclusion of family, friends, and neighbors in the NIS sample design. Such exclusion has the effect of altering the interpretation of the determinants of child abuse reporting among Blacks, but not among Whites. Thus, conclusions about racial differences in child maltreatment must be reached cautiously, given the NIS study design.

Decomposing Black-White Differences in Child Maltreatment

This article examines conflicting visions of the racial composition of the maltreated populations. The National Child Abuse and Neglect Data System (NCANDS) data shows Blacks are overrepresented among reported and substantiated abuse and neglect cases, while the National Incidence Study of Child Abuse and Neglect (NIS) shows no apparent overrepresentation of children of color. To understand the conflicting evidence, the authors produce from NIS approximate measures of maltreatment rates in NCANDS. Maltreatment rates is broken down into allegation, report and substantiation components. Without disaggregating the data by welfare status, all or most of the racial gap in official maltreatment is found to arise from racial differences in allegations. Disaggregation changes the results. Among welfare cases, on average, half of the Black-White gap in maltreatment is due to racial differences in substantiation. Among nonwelfare cases, about half of the racial gap in official maltreatment is due to racial differences in allegations.

The Color of Money: Bad Credit, Wealth, and Race

This article examines the myth of bad credit in the Black community. Historically, Blacks have had higher savings rates and lower use of credit than Whites. Discrimination in lending led to an aversion to credit. Later, Blacks believed their credit to be bad, even among many better qualified Black loan applicants. The authors find that there is no statistically significant difference in the average level of “bad credit” among Blacks and Whites who have been turned down for loans or who have not applied for loans, as seen in national data sets measuring wealth and expenditures. Contrary to conventional wisdom, no statistically significant difference exists in bad credit rates between Black and White households at the lowest and highest wealth levels. The authors contend that the observed differences in the bad credit rates between Blacks and Whites in the middle wealth range are attributable to different treatment of Blacks and Whites in credit markets.

Bad Credit and Intergroup Differences in Loan Denial Rates

Research has found wide disparities in loan denial rates among different racial/ethnic groups. Two competing explanations for these gaps arise. One argument is that these disparities result from underlying racial disparities in credit worthiness. A competing view is that the disparities arise from a pattern of racial discrimination among mortgage lenders. This paper adopts a stratification economics approach to evaluate these competing claims. Using Freddie Mac’s Consumer Credit Survey dataset, we test the hypothesis that measures of discrimination disappear when one accounts for racial differences in credit scores. A novel contribution of the paper, built upon the premise that inter-group inequalities sustain themselves through self-fulfilling mechanisms, is to test the hypothesis that loan denials explain misperceptions of credit worthiness. We demonstrate that one cause of the appearance of poor credit risk among black applicants is that blacks with good credit risk underestimate their credit worthiness and apply for loans in lower numbers. Our findings suggest that even nondiscriminatory lending behavior has the unintended effect of screening out low-risk blacks and thereby yields higher denial rates among blacks. This in turn confirms prior beliefs about the poor credit of average black applicants. Much, but not all, of the racial disparity in loan outcomes can be explained by racial differences in credit scores and the resulting racial disparity in loan outcomes explains much of the racial difference in false perceptions about bad credit. Thus, a possible self-fulfilling mechanism remains within the credit market that perpetuates views about black bad credit.

The role of housing vouchers in baltimore city, Maryland

In Baltimore City, the relative well-being of black and white families using Section 8 housing vouchers versus Section 8 housing certificates is compared. Logistic regression is used to examine whether the social and economic characteristics of a regional planning district play a significantly different role in the likelihood that a district will have voucher or certificate recipients. A second analysis examines the average monthly rent paid by blacks and whites for housing in the certificate and voucher programs. The results suggest that whites receive greater economic benefits in the voucher program than in the certificate program while blacks do not.

If it shall seem just and proper: The effect of race and morals on alimony and child support appeals in the District of Columbia, 1950-1980

This article tests the hypothesis that judicial arbitrariness dominated alimony or child support appeals in the pre-no-fault era by analyzing data on all alimony and child support appeals in the District of Columbia from 1950 through 1980. Censored regression analysis is used to isolate the impacts of race and morals grounds for divorce on changes in alimony and child support awards from trial to appeal. The results show large race effects but small morals effects. Judicial discretion—measured by unexplained gaps in awards—dominated relevant eco nomic factors in determining changes in alimony and child support awards during the pre-no-fault era.