Learning to Become Rational: The Case of Self-Referential Autoregressive and Non-Stationary Models (Lecture Notes in Economics and Mathematical Systems, 439)

1. 1 Rational Expectations and Learning to Become Rational A characteristic feature of dynamic economic models is that, if future states of the economy are uncertain, the expectations of agents mat­ ter. Producers have to decide today which amount of a good they will produce not knowing what demand will be tomorrow. Consumers have to decide what they spend for consumption today not knowing what prices will prevail tomorrow. Adopting the neo-classical point of view that economic agents are 'rational' in the sense that they behave in their own best interest given their expectations about future states of the ecomomy it is usually assumed that agents are Bayesian deci­ sion makers. But, as LUCAS points out, there remains an element of indeterminacy: Unfortunately, the general hypothesis that economic agents are Bayesian decision makers has, in many applications, lit­ tle empirical content: without some way of infering what an agent's subjective view of the future is, this hypothesis is of no help in understanding his behavior. Even psychotic behavior can be (and today, is) understood as "rational", given a sufficiently abnormal view of relevant probabili­ ties. To practice economics, we need some way (short of psychoanalysis, one hopes) of understanding which decision problem agents are solving. (LucAs (1977, p. 15)) 2 CHAPTER 1. INTRODUCTION 1. 1. This book is a study on the asymptotic behaviour of boundedly rational learning procedures in self-referential models. It reports important results of current research on this topic. These results, e.g., global convergence results for autoregressive and for non-stationary models, considerably extend the boundedly rational learning approach Front Matter....Pages N1-vii Introduction....Pages 1-27 Univariate AR(1) Models....Pages 29-74 Univariate ARX Models....Pages 75-112 Univariate Non-Stationary Models....Pages 113-141 Multivariate ARX Models....Pages 143-159 Multivariate Non-Stationary Models....Pages 161-168 Back Matter....Pages 169-205 This is a study on the asymptotic behaviour of boundedly rational learning procedures in self-referential models. It reports important results of current research on this topic, results which extend the boundedly rational learning appraoch. Markus Zenner. Includes Bibliographical References (p. [189]-197).