Chapter 6 Search, Matching, and Unemployment . Introduction This chapter applies dynamic programming to a choice between only two actions, to accept or reject a take-it-or-leave-it job offer. An unemployed worker faces a probability distribution of wage offers or job characteristics | Chapter 6 Search Matching and Unemployment . Introduction This chapter applies dynamic programming to a choice between only two actions to accept or reject a take-it-or-leave-it job offer. An unemployed worker faces a probability distribution of wage offers or job characteristics from which a limited number of offers are drawn each period. Given his perception of the probability distribution of offers the worker must devise a strategy for deciding when to accept an offer. The theory of search is a tool for studying unemployment. Search theory puts unemployed workers in a setting where they sometimes choose to reject available offers and to remain unemployed now because they prefer to wait for better offers later. We use the theory to study how workers respond to variations in the rate of unemployment compensation the perceived riskiness of wage distributions the quality of information about jobs and the frequency with which the wage distribution can be sampled. This chapter provides an introduction to the techniques used in the search literature and a sampling of search models. The chapter studies ideas introduced in two important papers by McCall 1970 and Jovanovic 1979a . These papers differ in the search technologies with which they confront an unemployed We also study a related model of occupational choice by Neal 1999 . 1 Stigler s 1961 important early paper studied a search technology different from both McCall s and Jovanovic s. In Stigler s model an unemployed worker has to choose in advance a number n of offers to draw from which he takes the highest wage offer. Stigler s formulation of the search problem was not sequential. - 137 - 138 Search Matching and Unemployment . Preliminaries This section describes elementary properties of probabilty distributions that are used extensively in search theory. . Nonnegative random variables We begin with some characteristics of nonnegative random variables that possess first moments. Consider a .
