Seth G. Sanders

Demographics of the Gay and Lesbian Population in the United States: Evidence from Available Systematic Data Sources

This work provides an overview of standard social science data sources that now allow some systematic study of the gay and lesbian population in the United States. For each data source, we consider how sexual orientation can be defined, and we note the potential sample sizes. We give special attention to the important problem of measurement error, especially the extent to which individuals recorded as gay and lesbian are indeed recorded correctly. Our concern is that because gays and lesbians constitute a relatively small fraction of the population, modest measurement problems could lead to serious errors in inference. In examining gays and lesbians in multiple data sets we also achieve a second objective: We provide a set of statistics about this population that is relevant to several current policy debates.

Teenage Childbearing and its Life Cycle Consequences: Exploiting a Natural Experiment

We exploit a “natural experiment” associated with human reproduction to identify the causal effect of teen childbearing on the socioeconomic attainment of teen mothers. We exploit the fact that some women who become pregnant experience a miscarriage and do not have a live birth. Using miscarriages an instrumental variable, we estimate the effect of teen mothers not delaying their childbearing on their subsequent attainment. We find that many of the negative consequences of teenage childbearing are much smaller than those found in previous studies. For most outcomes, the adverse consequences of early childbearing are short-lived. Finally, for annual hours of work and earnings, we find that a teen mother would have lower levels of each at older ages if they had delayed their childbearing.

The impact of economic conditions on participation in disability programs: Evidence from the coal boom and bust

We examine the impact of the coal boom of the 1970s and the coal bust of the 1980s on disability program participation. These shocks provide clear evidence that as the value of labor-market participation increases, disability program participation falls. For the Disability Insurance program, the elasticity of payments with respect to local earnings is between -0.3 and -0.4 and for Supplemental Security Income the elasticity is between -0.4 and -0.7. Consistent with a model where qualifying for disability programs is costly, the relationship between economic conditions and program participation is much stronger for permanent than for transitory economic shocks.

The Earnings Effects of Sexual Orientation

This investigation of the effect of sexual orientation on earnings employs General Social Survey data from 1989–96. Depending largely on the definition of sexual orientation used, earnings are estimated as having been between 14% and 16% lower for gay men than for heterosexual men, and between 20% and 34% higher for lesbian women than for heterosexual women. This evidence, the authors suggest, is consistent with either of two complementary constructions: Gary Beckers argument that male/female earnings differentials are rooted in specialization within households and in optimal human capital accumulation decisions individuals make when they are young; and Claudia Goldins observations about marriage-based gender discrimination, according to which the paternalistic “protection” of wives and mothers from the world of work has tended to overlook lesbians.

A simulation estimator for dynamic models of discrete choice

This paper analyses a new estimator for the structural parameters of dynamic models of discrete choice. Based on an inversion theorem due to Hotz and Miller (1993), which establishes the existence of a one-to-one mapping between the conditional valuation functions for the dynamic problem and their associated conditional choice probabilities, we exploit simulation techniques to estimate models which do not possess terminal states. In this way our Conditional Choice Simulation (CCS) estimator complements the Conditional Choice Probability (CCP) estimator of Hotz and Miller (1993). Drawing on work in empirical process theory by Pakes and Pollard (1989), we establish its large sample properties, and then conduct a Monte Carlo study of Rusts (1987) model of bus engine replacement to compare its small sample properties with those of Maximum Likelihood (ML).

Bounding Causal Effects Using Data from a Contaminated Natural Experiment: Analysing the Effects of Teenage Childbearing

In this paper, we consider what can be learned about causal effects when one uses a contaminated instrumental variable. In particular, we consider what inferences can be made about the causal effect of teenage childbearing on a teen mothers subsequent outcomes when we use the natural experiment of miscarriages to form an instrumental variable for teen births. Miscarriages might not meet all of the conditions required for an instrumental variable to identify such causal effects for all of the observations in our sample. However, it is an appropriate instrumental variable for some women, namely those pregnant women who experience a random miscarriage. Although information from typical data sources does not allow one to identify these women, we show that one can adapt results from Horowitz and Manski (1995) on identification with data from contaminated samples to construct informative bounds on the causal effect of teenage childbearing. We use these bounds to re-examine the effects of early chilbearing on the teen mothers subsequent educational and labour market attainment as considered in Hotz, McElroy and Sanders (1995a, 1995b). Consistent with their study, these bounds indicate that women who have births as teens have higher labour market earnings and hours worked compared to what they would have attained if their childbearing had been delayed.

The Decision to Work by Married Immigrant Women

Using 1980 Census data, the authors analyze the labor force participation of married immigrant Asian women by country of origin, compared with that of married immigrant women from Europe and Canada. The results suggest the existence of a family investment strategy: evidence from both across groups and within groups indicates that a womans decision to work is affected by whether she has a husband who invests in skills specific to the U.S. labor market, and also by the extent of that investment. Such a family response may help offset the low earnings of immigrant men who initially lack skills for which there is a demand in the American labor market.

Gender Wage Disparities among the Highly Educated.

We examine gender wage disparities for four groups of college-educated women—black, Hispanic, Asian, and non-Hispanic white—using the National Survey of College Graduates. Raw log wage gaps, relative to non-Hispanic white male counterparts, generally exceed –0.30. Estimated gaps decline to between –0.08 and –0.19 in nonparametric analyses that (1) restrict attention to individuals who speak English at home and (2) match individuals on age, highest degree, and major. Among women with work experience comparable to men’s, these estimated gaps are smaller yet—between –0.004 and –0.13. Importantly, we find that inferences from familiar regression-based decompositions can be quite misleading.

Why do minority men earn less? A study of wage differentials among the highly educated

We estimate wage gaps using nonparametric matching methods and detailed measures of field of study for university graduates. We find a modest portion of the wage gap is the consequence of measurement error in the Census education measure. For Hispanic and Asian men, the remaining gap is attributable to premarket factorsprimarily differences in formal education and English language proficiency. For black men, only about one-quarter of the wage gap is explained by these same factors. For a subsample of black men born outside the South to parents with some college education, these factors do account for the entire wage gap.

Measurement of Higher Education in the Census and Current Population Survey

We examine measurement error in the reporting of higher education in the 1990 Decennial Census and the post-1991 Current Population Survey (CPS). We document that measurement error in the reporting of higher education is prevalent in Census data. Further, these errors violate models of classical measurement error in important ways. The level of education is consistently reported as higher than it is (errors are not mean 0), errors in the reporting of education are correlated with covariates that appear in earnings regressions, and errors in the reporting of education appear correlated with the error term in a model of earnings determination. Thus, neither well-known results on classical measurement error nor recent models of nonclassical measurement error are likely valid when using Census and CPS data. We find some evidence that the measurement error is lower in the CPS than in the Census, presumably because first interviews are generally conducted in person.