Book contents
- Frontmatter
- Contents
- Preface and Acknowledgments
- Introduction
- PART 1 URBAN SEARCH-MATCHING
- PART 2 URBAN EFFICIENCY WAGES
- PART 3 URBAN GHETTOS AND THE LABOR MARKET
- General Conclusion
- A Basic Urban Economics
- B Poisson Process and Derivation of Bellman Equations
- C The Harris-Todaro Model
- Bibliography
- Author Index
- Subject Index
PART 1 - URBAN SEARCH-MATCHING
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface and Acknowledgments
- Introduction
- PART 1 URBAN SEARCH-MATCHING
- PART 2 URBAN EFFICIENCY WAGES
- PART 3 URBAN GHETTOS AND THE LABOR MARKET
- General Conclusion
- A Basic Urban Economics
- B Poisson Process and Derivation of Bellman Equations
- C The Harris-Todaro Model
- Bibliography
- Author Index
- Subject Index
Summary
Introduction of Part 1
There is a vast amount of literature on search and matching theory that emphasizes the importance of flows in the labor markets (Mortensen and Pissarides, 1999; Pissarides, 2000). These models, now widely used in labor economics and macroeconomics, have greatly enriched research on unemployment as an equilibrium phenomenon, labor market dynamics, and cyclical adjustment. The starting point of the analysis is to recognize that labor markets are characterized by search frictions. This means that it takes time for workers to find a job and for firms to fill up a vacancy so that unemployed workers and vacant jobs can coexist in equilibrium, a feature not possible in a standard Walrasian world (i.e., a frictionless world where workers and firms can move costlessly and instantaneously between working and not working). Because of these search frictions, the contacts between workers and firms depend on the market variables and the arrival rate of contacts for workers increases with the number of unemployed searchers, while the arrival rate of contacts for firms increases with the number of vacant firms. A constant-return to scale function is a convenient way of capturing these properties, which is referred to as the “matching function” (Pissarides, 1979). Indeed, the matching function relates job creation to the number of unemployed, the number of job vacancies, and the intensities with which workers search and firms recruit. It successfully captures the key implications of frictions that prevent an instantaneous encounter of trading partners.
However, the spatial dimension is absent in all these models, even if it has been recognized for a long time that distance interacts with the diffusion of information.
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- Urban Labor Economics , pp. 7 - 9Publisher: Cambridge University PressPrint publication year: 2009