Separate Crop Accounts for the Western Grain Stabilization Program

Payouts from the Western Grain Stabilization Program are determined on the basis of prairie-wide net cash flow from grains. Of particular importance is what happens to the returns to wheat – the predominant crop. Thus while wheat producers in aggregate can be expected to benefit from the current program, producers of nonwheat crops may not. This paper examines the economics of separate crop accounts as a way of providing greater sensitivity to such producers. It is concluded that the gains are not large enough to warrant such a program change. Les paiements versés en vertu du Programme de stabilisation des grains de ?Ouest sont déterminés à partir des fonds autogénérés par la production céréalière à ?échelle des Prairies. Or, il est particulièrement important de savoir ce qu'il advient des revenus provenant de la production du blé, la culture prédominante dans cette région. Ainsi, même si on peut s'attendre que dans ?ensemble, les producteurs de blé tirent avantage du programme actuel, tel n'est peut-être pas le cas pour les producteurs ?autres céréales. Dans le présent article, nous examinons les aspects économiques ?un traitement séparé du blé et des autres céréales en guise de moyen pour mieux tenir compte des besoins de ces producteurs. Nous concluons que les avantages ainsi obtenus ne sont pas suffisamment importants pour justifier un tel changement du programme.     

The effect of potential emigration on the optimal linear income tax

This paper amends a standard model of optimal linear income taxation to allow individuals to escape taxation by migrating. The income tax is used only to redistribute income in this model. It is found that, if individuals with low and high ability levels are prevented from migrating, then the optimal marginal tax and poll subsidy increase. But preventing migration at ability levels in some intermediate interval lowers the optimal marginal tax.     

Why Do Women Wait? Matching, Wage Inequality, and the Incentives for Fertility Delay

This paper explores the interaction between wage inequality and the marriage and fertility decisions of young women. We develop an equilibrium search model of marriage, divorce, and investment in children that allows for differential timing of fertility. We show how patterns of fertility timing in U.S. data can be explained by the incentives for fertility delay implied by marriage and labor markets. We find that these incentives help explain both the cross-sectional relationship between women's wages and fertility timing and the changes over the past 40 years in married women's fertility timing and labor supply. Journal of Economic Literature Classification Numbers: J12, J13.     

Inter-industry technology flows in the US food-processing industries

The study examines the origins of technology important to improving productivity in the food-processing industries. Technology flows were measured both by patents in patent classes closely identified with six food industries, and by a sample of significant food-processing innovations. These data are consistent with the hypothesis that interindustry technology flows are the most significant determinant of productivity improvements in the food industries. These findings solve the enigma that the food-processing industries have enjoyed rapid improvements in productivity despite making very modest investments in research and development.     

Why should firms manufacture retailer brands?

For firms manufacturing convenience goods there are three branding policies available, a proprietory brand policy, a retailer brand policy and a mixed brand policy. A firm's choice depends on differences in demand and promotion costs between the proprietory and retailer brand markets. This can be analysed using a simple elaboration of the standard 3rd degree price discrimination model. But if the two markets are not independent over the long-term there may be other consequences of following the optimization rules of the model. If retailers develop consumers' preference for their own shops and their own brands, the demand advantage enjoyed by manufacturers' brands may be reduced further. The more willing are manufacturers to supply retailer brands, the more retailers win undermine the demand for manufacturers' proprietory brands.     

OR vice: Forecasting and classification techniques for narcotics interdiction

Counternarcotics interdiction efforts have traditionally relied on historically determined sorting criteria or “best guess” to find and classify suspected smuggling traffic. We present a more quantitative approach which incorporates customized database applications, graphics software and statistical modeling techniques to develop forecasting and classification models. Preliminary results show that statistical methodology can improve interdiction rates and reduce forecast error. The idea of predictive modeling is thus gaining support in the counterdrug community. The problem is divided into sea, air and land forecasting, only part of which will be addressed here. The maritime problem is solved using multiple regression in lieu of multivariate time series. This model predicts illegal boat counts by behavior and geographic region. We developed support software to present the forecasts and to automate the process of performing periodic model updates. During the period, the model was in use at. Coast Guard Headquarters. Because of deterrence provided by improved intervention, the vessel seizure rate declined from 1 every 36 hours to 1 every 6 months. Due in part to the success of the sea model, the maritime movement of marijuana has ceased to be a major threat. The air problem is more complex, and required us to locally design data collection and display software. Intelligence analysts are using a customized relational database application with a map overlay to perform visual pattern recognition of smuggling routes. We are solving the modeling portion of the air problem using multiple regression for regional forecasts of traffic density, and discriminant analysis to develop tactical models that classify “good guys” and “bad guys”. The air models are still under development, but we discuss some modeling considerations and preliminary results. The land problem is even more difficult, and data collection is still in progress.