This paper examined factors influencing clothing expenditures by households in the United States. In particular, the impact of various household characteristics on clothing expenditures was investigated using data from the 1972–73 Bureau of Labor Statistics Consumer Ex penditure Survey. The results indicated that income plays a major role in concert with demographic characteristics in determining household expenditures on clothing and services. Expenditures were positively related to income and education and negatively related to age of household head. Households headed by blacks with wives in the labor force spent more on clothing than other households. Location also proved to be a significant variable with urban households spending more on clothing expenditures than rural households. The results should provide information concerning the demand for clothing under different economic and demographic conditions.

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This paper employs a hazard model to analyse the impact of education and two types of prison employment programmes on recidivism over a ten-year period for 4515 prisoners released from Ohio prisons in 1992. Estimations with a Weibull mixture model and propensity score approach provide two means for investigating self-selection bias. Selection bias is detected for participation in the most common prison job programme but has little effect on estimated marginal savings impacts of prison industry and education programmes. Estimates of the cost savings from postponing return to prison due to programme participation are provided. The potential for cost savings through decreasing or delaying return to prison is an important finding given the substantial and increasing cost of incarceration. Copyright (c) The London School of Economics and Political Science 2008.

Physical chemistry is commonly viewed as formidable by chemistry faculty and students alike. It is the gateway course to advanced chemistry courses in ACS-certified degree programs. Hypotheses concerning success in physical chemistry based on previous chemistry, physics, and mathematics courses are tested using bivariate correlation analysis, multiple regression on the full set of variables, and multiple regression with a subset of variables deleted. Data on chemistry, physics, and mathematics grades and the number of times these courses were repeated were collected for physical chemistry students at Valdosta State University for the period 1976–1999. The most important subsets of variables were chemistry and mathematics. The most important individual predictors of success in the first course in physical chemistry are grade in second course in organic chemistry and grade in physics. The number of times courses were repeated is important but less significant.