This paper provides a general framework for proving the "square root of" T-consistency and asymptotic normality of a wide variety of semiparametric estimators. The class of estimators considered consists of estimators that can be defined as the solution to a minimization problem based on a criterion function that may depend on a preliminary infinite dimensional nuisance parameter estimator. The method of proof exploits results concerning the stochastic equicontinuity of stochastic processes. The results are applied to the problem of semiparametric weighted least squares estimation of partially parametric regression models. Primitive conditions are given for "square root of" T-consistency and asymptotic normality of this estimator. Copyright 1994 by The Econometric Society.

This paper establishes a correspondence in large samples between classical hypothesis tests and Bayesian posterior odds tests for models without trends. More specifically, tests of point null hypotheses and one- or two-sided alternatives are considered (where nuisance parameters may be present under both hypotheses). It is shown that, for certain priors, the Bayesian posterior odds test is equivalent in large samples to classical Wald, Lagrange multiplier, and likelihood ratio tests for some significance level and vice versa. The priors considered under the alternative hypothesis are taken to shrink to the null hypothesis at rate n[superscript -1/2] as the sample size n increases. Copyright 1994 by The Econometric Society.

Reviews the book `Updating Standard Cost Systems,' by Carole B. Cheatham and Leo R. Cheatham.

This paper derives asymptotically optimal tests for testing problems in which a nuisance parameter exists under the alternative hypothesis but not under the null. For example, the results apply to tests of structural change with unknown changepoint. The testing problem considered is nonstandard and the classical asymptotic optimality results for the Lagrange multiplier, Wald, and likelihood ratio do not apply. A weighted average power criterion is used here to generate optimal tests. This criterion is similar to that used by A. Wald (1943) to obtain the classical asymptotic optimality properties of Wald tests in 'regular' testing problems. Copyright 1994 by The Econometric Society.

Preface What Is a Growth Stock? A Hypothesis Regarding the Market's Pricing of Growth Stocks Market Expectations and Responses to New Information Using Fundamental Analysis to Segregate Mispriced Growth Stocks Competitive Analysis Implementing the Strategy Market Anomalies of Importance to Trading Diversification, Risk and Market Efficiency Some Concluding Thoughts Notes Bibliography Index