In Young (1993, 1998) agents are recurrently matched to play a finite game and almost always play a myopic best reply to a frequency distribution based on a sample from the recent history of play. He proves that in a generic class of finite n-player games, as the mutation rate tends to zero,...

This paper considers the large sample behavior of the maximum likelihood estimator of random effects models with serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. Consistent estimation and asymptotic normality as N and/or T grows large is established...

This paper is concerned with maximum likelihood based inference in random effects models with serial correlation. Allowing for individual effects we introduce serial correlation of general form in the time effects as well as the idiosyncratic errors. A straightforward maximum likelihood...

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained in the general...

The value of preventing a fatality or (saving) a statistical life is an important question in health economics as well as environmental economics. This paper reviews and adds new insights to several of the issues discussed in the literature. For example, how do we define the value of a...

In this paper I define an evolutionary stability criterion for learning rules. Using Monte Carlo simulations, I then apply this criterion to a class of learning rules that can be represented by Camerer and Ho's (1999) model of learning. This class contains perturbed versions of reinforcement and...

In this paper, I analyze stochastic adaptation in finite n-player games played by heterogeneous populations of myopic best repliers, better repliers and imitators. In each period, one individual from each of n populations, one for each player role, is drawn to play and chooses a pure strategy...