Knowledge that Transforms

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.

We present and analyze a model of noncooperative bargaining among n participants, applied to situations describable as games in coalitional form. This leads to a unified solution theory for such games that has as special cases the Shapley value in the transferable utility (TU) case, the Nash bargaining solution in the pure bargaining case, and the recently introduced Maschler-Owen consistent value in the general nontransferable utility (NTU) case. Moreover, we show that any variation (in a certain class) of our bargaining procedure which generates the Shapley value in the TU setup must yield the consistent value in the general NTU setup.

[We propose a nonparametric estimation procedure for continuous-time stochastic models. Because prices of derivative securities depend crucially on the form of the instantaneous volatility of the underlying process, we leave the volatility function unrestricted and estimate it nonparametrically. Only discrete data are used but the estimation procedure still does not rely on replacing the continuous-time model by some discrete approximation. Instead the drift and volatility functions are forced to match the densities of the process. We estimate the stochastic differential equation followed by the short-term interest rate and compute nonparametric prices for bonds and bond options.]

This paper examines how, in the presence of individual risk, economic efficiency can be achieved without an unrealistically large number of contingent claims. Market uncertainty is specified in such a way that general types of individual risk and collective risk are properly accounted for and so that, specifically, market clearing is always satisfied ex post as well as ex ante. We show that consistency of beliefs and optimality of allocation can be guaranteed with an appropriate array of pure Arrow securities to spread collective risk and mutual insurance policies to pool individual risk. When there is individual risk common to like groups of individuals, pooling risk by means of mutual insurance permits substantial economizing on market transactions, as compared to those required if dealing instead with the full complement of pure Arrow securities. We show that if there are N households (consisting of H types), each facing the possibility of being in S individual states together with T collective states, then ensuring Pareto optimality requires only H(S-1)T independent mutual insurance policies plus T pure Arrow securities. Our results also help to clarify the question of which missing markets may affect allocational efficiency.

Egalement paru dans : INRA-ESR Toulouse Série D ; 92-04D et 94-04D

A random price adjustment model is developed for an exchange economy which is decentralized in that the trades permitted to an agent and the resulting price changes depend only on the commodity vector currently held by that agent, and not on the whole economy. We obtain asymptotic results as the number of agents goes to infinity, subject to stability assumptions on the price paths. With probability arbitrarily close to one the price path in our model will approximate the price path of the corresponding tatonnement process on a rapid time scale, and will then remain close to a limit price. Moreover, the economy will approach a competitive equilibrium, and the process will be feasible in the sense that the market maker's inventory is approximately constant over time. Copyright 1996 by The Econometric Society.

This paper develops an asymptotic theory of Bayesian inference for time series. A limiting representation of the Bayesian data density is obtained and shown to be of the same general exponential form for a wide class of likelihoods and prior distributions. Continuous time and discrete time cases are studied. In discrete time, an embedding theorem is given which shows how to embed the exponential density in a continuous time process. From the embedding we obtain a large sample approximation to the model of the data that corresponds to the exponential density. This has the form of discrete observations drawn from a nonlinear stochastic differential equation driven by Brownian motion. No assumptions concerning stationarity or rates of convergence are required in the asymptotics. Some implications for statistical testing are explored and we suggest tests that are based on likelihood ratios (or Bayes factors) of the exponential densities for discriminating between models.