Gay and lesbian partnership: Evidence from California

Much recent research on sexual minorities has used couples-based samples, which--by construction--provide no information on nonpartnered individuals. We present the first systematic empirical analysis of partnership and cohabitation among self-identified gay men and lesbians using two independent, large, population-wwbased data sources from California. These data indicate that 37%-46% of gay men and 51%-62% of lesbians aged 18-59 are in cohabiting partnerships (compared with 62% of heterosexual individuals in coresidential unions at comparable ages). Unlike previous research, we find that white and highly educated gay men and lesbians are more likely to be partnered, and we confirm that same-sex cohabiting partners in our data have demographic characteristics that are similar to California same-sex couples from Census 2000. We also present the first detailed analysis of officially registered domestic partnerships in California. We find that almost half of partnered lesbians are officially registered with the local or state government, while less than a quarter of partnered gay men are officially registered. We conclude with implications of our findings for couples-based research on gay men and lesbians, as well as recommendations for survey data collection.     

TWO-PIECE VON NEUMANN-MORGENSTERN UTILITY FUNCTIONS*

Thirty empirically assessed utility functions on changes in wealth or return on investment were examined for general features and susceptability to fits by linear, power, and exponential functions. Separate fits were made to below-target data and above-target data. The usual “target” was the no-change point. The majority of below-target functions were risk seeking; the majority of above-target functions were risk averse; and the most common composite shape was convex-concave, or risk seeking in losses and risk averse in gains. The least common composite was concave-concave. Below-target utility was generally steeper than above-target utility with a median below-to-above slope ratio of about 4.8. The power and exponential fits were substantially better than the linear fits. Power functions gave the best fits in the majority of convex below-target and concave above-target cases, and exponential functions gave the best fits in the majority of concave below-target and convex above-target cases. Several implications of these results for decision making under risk are mentioned.     

USING DUMMY VARIABLES TO CHECK FOR ROUNDING ERROR IN COMPUTERIZED REGRESSION PROGRAMS*

After a brief review of the role of dummy variables in regression analysis and the current state-of-the art in rounding/truncation error detection in computerized least squares programs, this paper presents a theorem that can be used to detect this type of error whenever an analyst is running a regression program that has one (or more) dummy variables as independent variables.