Job Search Theory - Springer

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Job Search Theory Alessandra Faggian

Contents 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 The Standard Job Search Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Basic Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 The Matching Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Job Search and Migration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter summarizes the main developments in job search theory ever since its inception in the 1970s. After describing the assumptions and formulation of the basic model, the chapter moves onto analyzing how the original framework has been extended by removing some of the initial limitations. A separate section is then devoted to the matching function theory which represents one of the main developments of job search theory in more recent years and whose importance has been recognized by the award of the 2010 Nobel Prize in economics. The last section attempts to reconcile job search and migration theory by introducing the role of space and describing the main contributions on these topics by regional economists.

A. Faggian AED Economics, Ohio State University, Columbus, OH, USA e-mail: [email protected] M.M. Fischer, P. Nijkamp (eds.), Handbook of Regional Science, DOI 10.1007/978-3-642-23430-9_8, # Springer-Verlag Berlin Heidelberg 2014

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4.1

A. Faggian

Introduction

With two thirds of national incomes coming, on average, from labor, it is not surprising that labor economists have devoted so much effort in modeling job search decisions. Although the share of labor income in more developed countries has decreased in recent years, labor still represents the main means of support of most households. Hence, choosing the “right” job is one of the most important lifetime decisions individuals have to make. Job search theory became popular in the 1970s as an alternative to the “standard” neoclassical labor supply theory. The neoclassical framework, based on the assumption of perfect information, did not allow for unemployment where individuals actively sought work but were unable to find it. Individual agents only had two options, either being employed or being inactive (i.e., not part of the labor force). However, evidence showed that unemployment and its duration were not negligible. This led a group of scholars to formulate an alternative theory able to account for unemployment, which became known as “job search theory.” The main premise of job search models is that looking for a job is a dynamic sequential process and that individuals have to decide when to stop this process under conditions of uncertainty and imperfect information. Frictional unemployment is a natural outcome of this process. Ever since the 1970s, job search theory has been refined and extended in several directions and countless contributions have been published on the topic. While most of these contributions are interesting and provide new insights into the labor search process, the development of a “matching function” stands out as being possibly the most fundamental development in job search theory since its inception. The importance of this latest development was recognized by awarding the 2010 Nobel Prize to Peter Diamond, Dale Mortensen, and Christopher Pissarides, whose work formed the basis of such development. This chapter tries to survey the key features of the job search theory while facing some constraints. Firstly, the literature on job search theory is so vast that only the milestones can be presented. Secondly, job search models involve a high degree of mathematical sophistication, which goes beyond the scope of this chapter. In presenting the models, the mathematical formulation is streamlined to a minimum while preserving the main insights of each model. The economic meaning and intuition behind the mathematical formulation is also provided. The organization of the chapter is chronological going from the initial contributions in the 1970s to the more recent contributions (also known as the DiamondMortensen-Pissarides model) for which the 2010 Nobel Prize was awarded. The last section before the conclusions will introduce the role of migration into job search theory and will present some contributions developed specifically in the regional economics field.

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4.2

The Standard Job Search Model

4.2.1

Basic Formulation

Although the origin of job search theory is normally attributed to the two seminal articles by McCall (1970) and Mortensen (1970), two papers by Stigler (1961, 1962) questioned the perfect information assumption of the neoclassical theory and laid some of the foundations of what was then developed in the 1970s. Both in Stigler’s model and in the basic job search model, the individual has more than one earning opportunities available and has to select the “best” one. However, the “strategy” to select the best job is different. In Stigler’s model, the main decision an individual has to make is how many jobs to sample before deciding which one is the “best.” Sampling an extra job has an associated “search” marginal cost c over a given time period, and the decision variable is the sample size n representing the number of firms a job seeker will consider in their search. The neoclassical assumption of perfect information is a special case where the cost c equals zero. In job search models, the decision process is sequential. There is no “optimal” sample size because the jobs are randomly sampled one at a time and the individual stops when an acceptable job becomes available. Hence, the number of jobs sampled depends on their sequence and the sample size itself is a random variable (Mortensen 1986). The basic job search model is simply an “optimal stopping rule” problem which can be described as follows. Each job seeker receives n wage offers – w1, w2, . . ., wn – per period of length h spent searching for a job. The best offer in each period is equal to w ¼ max fw1 ; w2 ; . . . ; wn g

(4.1)

Wages associated with future job offers are distributed according to a probability distribution f(w). The job seeker’s aim is to maximize net benefits (future stream of income minus search costs). In its simplest form, the job search model is based on the following assumptions: (i) Time is continuous; t denotes the time periods, each of length h. (ii) Although wages associated with future job offers are unknown to the seeker, the probability distribution f(w) is known and it is constant over time. (iii) The search cost per unit of time is c. (iv) Once the seeker accepts a job offer, this leads to permanent employment at a fixed per-period wage, w. (v) The discount rate is r. (vi) Individuals have infinite lifetimes. (vii) The seeker receives one job offer per period. (viii) If the job is rejected, it cannot be recalled. (ix) The seeker is unemployed. Based on these assumptions, the basic model can be formalized as follows.

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W(w) is an unspecified functional relationship representing the future stream of income associated with a per-period wage equal to w. The present value of the lifetime wealth, at time t, is Vt ¼ ch þ erh WðwÞ

(4.2a)

if the individual accepts the job offer at time t or Vt ¼ ch þ erh EðVtþ1 Þ

(4.2b)

if the individual rejects the job offer at time t and continues the search at time t+1. The best strategy is one which maximizes Vt or, in other words, Vt ¼ ch þ erh Efmax½WðwÞ; Vtþ1 g

(4.3)

where E{.} denotes the expectation operator. Remember that, by assumption, the cost of search, c, is constant over time, the wage distribution is constant over time, and the individual has an infinite lifetime. We know that Vt ¼ Vtþ1 ¼ V

(4.4)

And so it follows that V ¼ ch þ erh EfmaxðWðwÞ; Vg ¼ ch þ erh EfmaxðWðwÞ  V; 0g

(4.5)

In the continuous time version of the model with infinite time horizon, this formula simplifies to n w o rV ¼ c þ E max  V; 0 r

(4.6)

An individual would accept the job offer if w/r > V and reject it if w/ r 0 and @Hab =@Vb > 0: The model is quite innovative because it considers regional level variables (at UK Government Office Regions level, which is comparable to the European NUTS1 level) rather than individual characteristics, but the motivation for the need of such a model is rather weak. Jackman and Savouri (1992), indeed, begin by stressing that their model represents an alternative to the traditional human capital migration model (Sjaastad 1962), which fails to explain the direction of interregional flows in a recession. According to the human capital migration theory,

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migration can be seen as an investment in the human agent, which has costs and renders returns. A person will decide to migrate when the net present value of a migration investment is positive. Let us suppose that a potential migrant wants to move from region a to region b. He/she will migrate only if the net present value (NPV) of his expected returns in region b (destination) is greater than that in region a (origin) minus the cost associated with relocation (Cab), i.e., NPVb > NPVa – Cab. Jackman and Savouri argue that, since regional differences are highest in a recession, the human capital model forecasts that more people would move from poorer to richer regions, but the evidence shows that actual migration flows tend to “rise in times of prosperity and fall in a recession” (p. 1433) when they are most needed to restore balance to the system. The hiring function approach provides an explanation to these perverse migration flows by assuming that the number of engagements falls in a recession. Although the authors are correct in pointing out that the human capital migration model, as such, is inadequate to explain the actual patterns of migration flows observed during recession, the human capital framework can easily be adapted to fit these facts. The human capital approach is neoclassical in essence so the decision to migrate depends exclusively on the comparison of future net benefits associated with the decision to move (Sjaastad 1962). The probability of finding a job is set equal to one and is unaffected by macroeconomic conditions. The addition of a probability function depending on the status of the economy could solve the inadequateness of the human capital migration model to explain lower migration flows in a recession without the need of a completely new alternative model. Especially in the case where the person is actually employed in the region of origin (enjoying a certain future income stream even though it may be low), there is less incentive to move because the probability of finding a job elsewhere is lower. The reasons for the negative relationship between increased regional gaps in recession and lower probability of finding a job by migrating includes the Jackman and Savouri (1992) argument that employers react to crisis by reducing recruitment and therefore jobs become more difficult to find. As a result, the role of information costs also needs to be considered. Information costs increase when jobs become more sparsely distributed throughout the territory. Moreover, since people perceive that there is a crisis, their reservation wages normally go down. Jobs with lower wages may be more easily available locally and this in turn reduces the chances of having to make a migratory move. Properly defining the function for probability could then reconcile the job search and human capital theories of migration. Despite the fact that the human capital and job search theories are often regarded as competing, they reach similar conclusions regarding migration. First of all, they both predict that individuals with higher human capital are more likely to migrate. In the case of the human capital theory, this is due to the fact that individuals have to be compensated for their investment in education, and in the case of job search, they need to be compensated for their higher reservation wage. However, one difference needs to be emphasized. In the human capital theory, the migration propensity of each single individual increases with education, while in the traditional job search

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theory, on average, higher-human-capital individuals are more mobile than lowerhuman-capital individuals, but this does not necessarily hold true for every single individual. Indeed, whether or not an individual migrates is related to the location of the first acceptable job (i.e., the job that meets the reservation wage). Jobs are randomly distributed over space and the process is sequential (one offer at a time), so it may be that some individuals are lucky enough to find an acceptable offer close to their current location. However, higher-reservation-wage jobs are expected to be more sparsely distributed in space so that, on average, higher-human-capital (and therefore higher-reservation-wage) individuals have to move further.

4.5

Conclusions

The aim of this chapter was to present the main ideas behind job search theory and its importance in the field of economics. Job search theory, though microeconomic in nature, contributed to explain macroeconomic phenomena such as frictional unemployment, which could not be explained by the traditional neoclassical theory. Since its inception, there have been many extensions to the model. For example, on the theoretical front, the heterogeneity of individuals has been emphasized, while other contributions focused on “family” job search, in which the decision regarding a job is not taken by an individual but rather by the whole household. On the empirical side, the availability of better data – both individual and aggregate – provided the basis to test some of the propositions of the models. In recent years, many empirical contributions employed experimental methods to better understand individual behavior in the labor market. While this chapter only scratched the surface of job search theory, it hopefully provided the basic notions for further study. Acknowledgments I acknowledge the support of research grant ECO2010-16006 by the Spanish Ministry of Science.

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