CONVERGENCE: AN EXPERIMENTAL STUDY OF TEACHING AND LEARNING IN REPEATED GAMES

Nash equilibrium can be interpreted as a steady state where players hold correct beliefs about the other players’ behavior and act rationally. We experimentally examine the process that leads to this steady state. Our results indicate that some players emerge as teachers—those subjects who, by their actions, try to influence the beliefs of their opponent and lead the way to a more favorable outcome—and that the presence of teachers appears to facilitate convergence to Nash equilibrium. In addition to our experiments, we examine games, with different properties, from other experiments and show that teaching plays an important role in these games. We also report results from treatments in which teaching is made more difficult. In these treatments, convergence rates go down and any convergence that does occur is delayed.     

Mixed results in a transitional planning program for alternative school students

Disciplinary alternative schools have a reputation as gateways to the juvenile and criminal justice systems. The authors conducted an evaluation of an intervention (Strategies for Success) designed to divert seventh-, eighth-, and ninth-grade alternative school students from this gateway. They used propensity score matching and a multivariate random effects model to estimate program impacts and found that the program not only increased attendance rates, at least in the short term, but also increased the likelihood of reassignment to alternative schools. The discussion focuses on possible reasons and solutions for high rates of return to alternative school and for the erosion of program effects.     

MARKET STRUCTURE,OPPONENT BEHAVIOR,AND INFORMATION IN A MARKET GAME

An experimental duopoly game was used to test the effects of market structure, opponent behavior, and information about opponent behavior in the game. Rational behavior would be responsive only to market structure. Problem-solving behavior would be responsive to all three factors. Results showed that decision behavior was responsive to all three factors in interaction as well as reponsive to interactive effects of time.     

Subsampling Intervals in Autoregressive Models with Linear Time Trend

A new method is proposed for constructing confidence intervals in autoregressive models with linear time trend. Interest focuses on the sum of the autoregressive coefficients because this parameter provides a useful scalar measure of the long‐run persistence properties of an economic time series. Since the type of the limiting distribution of the corresponding OLS estimator, as well as the rate of its convergence, depend in a discontinuous fashion upon whether the true parameter is less than one or equal to one (that is, trend‐stationary case or unit root case), the construction of confidence intervals is notoriously difficult. The crux of our method is to recompute the OLS estimator on smaller blocks of the observed data, according to the general subsampling idea of Politis and Romano (1994a), although some extensions of the standard theory are needed. The method is more general than previous approaches in that it works for arbitrary parameter values, but also because it allows the innovations to be a martingale difference sequence rather than i.i.d. Some simulation studies examine the finite sample performance.