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There exists a useful framework for jointly implementing Durbin-Wu-Hausman exogeneity and Sargan-Hansen overidenti cation tests, as a single arti cial regression. This note sets out the framework for linear models and discusses its extension to non-linear models. It also provides an empirical example and some Monte Carlo results.

We investigate the consequences of discreteness in the assignment variable in regression-discontinuity designs for cases where the outcome variable is itself discrete. We find that constructing confidence intervals that have the correct level of coverage in these cases is sensitive to the assumed distribution of unobserved heterogeneity. Since local linear estimators are improperly centered, a smaller variance for unobserved heterogeneity in discrete outcomes actually requires larger confidence intervals, since standard confidence intervals become narrower around a biased estimator, leading to a higher-than-nominal false positive rate. We provide a method for mapping structural assumptions regarding the distribution and variance of unobserved heterogeneity to the construction of "honest" confidence intervals that have the correct level of coverage. An application to retirement behavior reveals that the spike in retirement at age 62 in the United States can be reconciled with a wider range of values for the variance of unobserved heterogeneity (due to reservation wages or offers) than the spike at age 65.

This paper provides a comprehensive econometric framework for the empirical analysis of buyer power. It encompasses the two main features of pricing schemes in business-to-business relationships: nonlinear price schedules and bargaining over rents. Disentangling them is critical to the empirical identification of buyer power. Testable predictions from the theoretical analysis are delineated, and a pragmatic empirical methodology is presented. It is readily implementable on the basis of transaction data, routinely collected by antitrust authorities. The empirical framework is illustrated using data from the UK brick industry. The paper emphasizes the importance of controlling for endogeneity of volumes and for heterogeneity across buyers and sellers.

This paper considers structural nonparametric random utility models for continuous choice variables. It provides suffcient conditions on random preferences to yield reduced- form systems of nonparametric stochastic demand functions that allow global invertibility between demands and random utility components. Invertibility is essential for global identification of structural consumer demand models, for the existence of well-specified probability models of choice and for the nonparametric analysis of revealed stochastic preference.

This paper considers parametric estimation problems with independent, identically,non-regularly distributed data. It focuses on rate-effciency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality criterion,largely unexplored in parametric estimation.Under mild conditions, the Hellinger metric,defined on the space of parametric probability measures, is shown to be an essentially universally applicable tool to determine maximal possible convergence rates. These rates are shown to be attainable in general classes of parametric estimation problems.