No abstract

A two-period model is developed in which a risk-averse farmer uses off-farm labor to smooth consumption, leading to greater use of fertilizer. Fertilizer demand is shown to increase with the depth of the off-farm labor market. Controlling for exogenous weather risk, farmers use more fertilizer the lower the unemployment rate and the higher the share of nonagricultural work in total off-farm labor. The results suggest that off-farm labor markets and own-farm production may be complementary in risky production environments, so that policies which promote the depth of the off-farm labor market in low-income areas may also bolster farm productivity. Copyright 2003, Oxford University Press.

International research has suggested that rapist criminal histories can be predicted from certain offence behaviours. Ninety-six solved stranger rape cases were examined to determine if there was consistency in a New Zealand sample. Rapist behaviours during the offence were compared with criminal convictions prior to the rape. The primary statistical technique used was likelihood ratio stepwise binary logistic regression. Predictive utility of the results was limited, due to significant correlation coefficients between the criminal history variables. Nevertheless, the current study reflected the general findings of similar descriptive international research. These outcomes were: the majority of stranger rapists had prior criminal convictions, and the majority of those convictions were for property offences not sexual offending. Furthermore, ethnic minorities were over-represented among the offenders, and the majority of stranger rapists started committing their first known rapes in their midto late 20s. Finally, methodological difficulties were encountered during this study. This highlights the need to refine existing statistical approaches to predictive offender-based research.

JEL Classification Codes: C1, C2, C4, C5Key words: Agricultural supply response, Bayesian estimation, MELO estimation Abstract: Estimates of the response of agricultural supply to movements in expected price display curiously large variation across crops, regions and time periods. We argue that this anomaly may be traced, at least in part, to the statistical properties of the commonly-used econometric estimator, which has infinite moments of all orders and may have a bimodal distribution. We propose an alternative minimum-expected-loss estimator, establish its improved sampling properties, and argue for its usefulness in the empirical analysis of agricultural supply response.Acknowledgements: We thank the Co-Editor and referees for constructive suggestions, but we alone should be blamed for remaining inadequacies. Parts of this work were completed at the University of Chicago, whose hospitality is gratefully acknowledged. Particular thanks go to Arnold Zellner, who provided exceptionally useful input. Participants at meetings of the Econometric Society and the American Agricultural Economics Association provided helpful comments, as did Ed Leamer, Doug McManus and Marc Nerlove on a long-ago draft. Asad Zaman brought the problem treated in this paper to our attention. We are grateful for support from the National Science Foundation, the Sloan Foundation, the International Food Policy Research Institute, and the University of Pennsylvania Research Foundation.See for example Braulke (1982), Gardner (1993), Just (1993, and Tomek and Myers 1 (1993).A related paper, of which we became aware after completing ours, is Bewley and Fiebig 2 (1990). As will become clear shortly, however, the two papers are very different. Ours, in particular, focuses entirely on the agricultural supply question and treats it in depth.