Medicaid reform: programming solutions to the equity problem

This paper demonstrates the application of a mathematical programming model to a longstanding policy issue in the Medicaid reform debate: the redistribution of program funds necessary to achieve equity in eligibility and benefit coverage across states. The model is used to estimate the potential degree of equity achievable in the current Medicaid system given various budgetary and political constraints. Two model simulations, based on a 1979 data set for aged recipients of Supplementary Security Income, are presented. The results indicate that half or more of the interstate differences in spending for this population group are due to actuarial and efficiency factors rather than deviations from equity potential. The implications of eliminating the remaining differences are discussed.     

Campaign advertising and political ambiguity

This paper develops a model to explain candidates' strategic decisions to provide or withhold information about policy positions in the course of an election campaign. The analysis treats this problem as a game of imperfect information. Attention is focused on modeling voter suspicion of candidates whose positions are ambiguous. Specific numerical examples illustrate that candidate decisions about providing information via informative advertising depend upon candidate policy preferences, campaign fund endowments, partisan reputations, and incumbency status. The model also provides theoretical underpinnings for empirical findings regarding the effects of campaign advertising.     

Choosing appropriate techniques for socio-political forecasting

After defining scientific forecasting, the crucial role of assumptions in such forecasts is explicated. This is followed by a discussion of the representations upon which forecasting systems are based. Six variables are then introduced to capture differences in socio-political forecasting circumstances: level of detail, accuracy, agreement on problem representation, robustness-brittleness, number of variables and interdependencies, and disturbance. A categorization of forecasting approaches - expert based, Bayesian, extremal statistical, and rule based - is offered. These forecasting approaches are then cross-referenced with the forecasting circumstances to produce recommendations for choosing an appropriate forecasting technique in a given policy circumstance. Most examples in the article are drawn from the realm of foreign policy and international politics, and the cross-referencing section concentrates on foreign energy policy examples.