This paper presents optimal tests for parameter instability in the generalized method of moments (GMM) framework. The new tests include tests that are optimal for both one-sided and two-sided alternatives. One of the optimal tests for two-sided alternatives is the GMM generalization of the test presented in Andrews and Ploberger (1994) for the likelihood framework. The new tests include a class of optimal tests that direct the test's power to specific locations in the sample. One of these optimal tests has the attractive feature of a normal distribution under the null hypothesis. Copyright 1996 by The Econometric Society.
Linear models with error components are widely used to analyse panel data. Some applications of these models require knowledge of the probability densities of the error components. Existing methods handle this requirement by assuming that the densities belong to known parametric families of distributions (typically the normal distribution). This paper shows how to carry out nonparametric estimation of the densities of the error components, thereby avoiding the assumption that the densities belong to known parametric families. The nonparametric estimators are applied to an earnings model using data from the Current Population Survey. The model's transitory error component is not normally distributed. Use of the nonparametric density estimators yields estimates of the probability that individuals with low earnings will become high earners in the future that are much lower than the estimates obtained under the assumption of normally distributed error components.
developed and under general conditions an increase in the disregard is shown to increase both the part-time and overall re-employment hazards. Data from the Current Population Survey's Displaced Worker Supplements are used to test these predictions. Estimates from a competing risks model with correlated risks and time-varying coefficients shows that increasing the disregard significantly increases the conditional probability of part-time re-employment during the first three months of joblessness.
A class of tests for first, second, and third order stochastic dominance, together with modifications to the Pearson goodness of fit test are proposed for the nonparametric comparison of income distributions. They are implemented and compared with tests for generalised Lorenz dominance (which is the indirect test of second order stochastic dominance currently employed in income distribution studies) utilizing Canadian family income data. Copyright 1996 by The Econometric Society.
This paper uses the Panel Study of Income Dynamics to test whether risk-sharing is complete between or within American families. The tests accommodate wide variety in the configuration and availability of family data. The test results reject inter- as well as intra-family full risk-sharing even assuming that leisure is endogenous or that leisure and consumption are nonseparable. Copyright 1996 by The Econometric Society.
Consider the estimation of unemployment duration when the statistician samples individuals from the pool of unemployed persons and later interviews them and asks how long they had been unmployed. This incurs the problem of left-censoring; ignoring left-censoring overestimates the mean duration since longer spells tend to be observed more frequently than shorter ones. Lancaster (1979) gives a simple and convenient solution to the problem by introducing a conditional maximum likelihood estimator (MLE), i.e. analysis conditional on duration at the time of sampling. Here we give answers to the question whether or not such an approach is optimal in the sense that a semiparametric efficiency bound is achieved.
This paper studies the effects of unions on the structure of wages using an estimation technique that accounts for misclassification errors in reported union status and potential correlations between union status and unobserved productivity. The model is estimated separately for five skill groups using a panel data set formed from the U.S. Current Population Survey. The results suggest that unions raise wages more for workers with lower levels of observed skills. Union workers are positively selected from the population of workers with lower levels of observed skill and negatively selected from the population with higher observed skills. Copyright 1996 by The Econometric Society.
This paper presents a semiparametric procedure to analyze the effects of institutional and labor market factors on recent changes in the U.S. distribution of wages. The effects of these factors are estimated by applying kernel density methods to appropriately weighted samples. The procedure provides a visually clear representation of where in the density of wages these various factors exert the greatest impact. Using data from the Current Population Survey, we find, as in previous research, that de-unionization and supply and demand shocks were important factors in explaining the rise in wage inequality from 1979 to 1988. We find also compelling visual and quantitative evidence that the decline in the real value of the minimum wage explains a substantial proportion of this increase in wage inequality, particularly for women. We conclude that labor market institutions are as important as supply and demand considerations in explaining changes in the U.S. distribution of wages from 1979 to 1988.
By using nonparametric kernel estimation method and a central limit theorem for degenerate U-statistics of order higher than two, the authors develop several consistent model specification tests in the context of a nonparametric regression model. These include tests for omitted variables, tests for a partially linear model, and tests for a semiparametric single index model. The asymptotic normality of the test statistics are established under the respective null hypotheses and consistent estimators of the asymptotic variances are provided. Copyright 1996 by The Econometric Society.
This paper constructs a space of states of the world representing the exhaustive uncertainty facing each player in a strategic situation. The innovation is that preferences are restricted primarily by 'regularity' conditions and need not conform with subjective expected utility theory. The construction employs a hierarchy of preferences, rather than of beliefs as in the standard Bayesian model. Applications include the provision of foundations for a Harsanyi-style game of incomplete information and a rich framework for the axiomatization of solution concepts for complete information normal form games. Copyright 1996 by The Econometric Society.