Stochastic Problems in the Simulation of Labor Supply

Modern work in labor supply attempts to account for nonlinear budget sets created by government tax and transfer programs. Progressive taxation leads to nonlinear convex budget sets while the earned income credit, social security contributions, AFDC, and the proposed NIT plans all lead to nonlinear, nonconvex budget sets. Where nonlinear budget sets occur, the expected value of the random variable, labor supply, can no longer be calculated by simply 'plugging in' the estimated coefficients. Properties of the stochastic terms which arise from the residual or from a stochastic preference structure need to be accounted for. This paper considers both analytical approaches and Monte Carlo approaches to the problem. We attempt to find accurate and low cost computational techniques which would permit extensive use of simulation methodology. Large samples are typically included in such simulations which makes computational techniques an important consideration. But these large samples may also lead to simplifications in computational techniques because of the averaging process used in calculation of simulation results. This paper investigates the tradeoffs available between computational accuracy and cost in simulation exercises over large samples.

Choice Under Uncertainty: A Model of Applications for the Social Security Disability Insurance Program

Not all people with health problems are disabled. Some individuals with severe physical or mental impairments, such as blindness or limb amputation, continue to hold jobs and generally function satisfactorily.They constitute, however, a group of potentially disabled individuals who might apply and qualify for Disability Insurance or other disability-related benefits if they were to lose their jobs or to decide that employment offered an inadequate financial or non-pecuniary reward. Thus, disability, or a health-related inability to work, is more than a medical problem but involves motivational and attitudinal factors. We specify a model of the application process, which we model as choice under uncertainty about approval of an application for Disability Insurance. We specify the possible outcomes to the choice process of an individual in which the probability of acceptance for Disability Insurance is a key consideration. We then estimate a joint model of labor supply and application to the Disability Insurance program based on the 1972 survey. We then compare our results to the observed time series applications process since 1976. Lastly, we estimate the sensitivity of the application process to the probability of acceptance and the level of benefits.

Technical Problems in Social Experimentation: Cost versus Ease of Analysis

The goal of the paper is to set forth general guidelines that we believe would enhance the usefulness of future social experiments and to suggest ways of correcting for inherent limitations of them. Although the major motivation for an experiment is to overcome the inherent limitations of structural econometric models, in many instances the experimental designs have subverted this motivation. The primary advantages of randomized controlled experiments were often lost. The major complication for the analysis of the experiments was induced by an endogenous sample selection and treatment assignment procedure that selected the experimental participants and assigned them to controlversus treatment groups partly on the basis of the variable whose response the experiments were intended to measure. We propose that to overcome these difficulties, the goal of an experimental design should be as nearly as possible to allow analysis based on a simple analysis of variance model. Although complexities attendant to endogenous stratification can be avoided, there are inherent limitations of the experiments that cannot. Two major ones are self-determination of participation and self-selection out, through attrition.But these problems, we believe, can be corrected for with relative ease if endogenous stratification is eliminated. Finally, we propose that as a guiding principle, the experiments should have as a first priority the precise estimation of a single or a small number of treatment effects.