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2011
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AI-generated Abstract
The paper examines the imbalance between job vacancies and unemployed individuals post the 2007-09 recession. It emphasizes how search frictions and geographic constraints contributed to persistent unemployment despite available job openings. The authors highlight industry-specific job losses and gains, illustrating that while new positions emerge in rapidly growing sectors, they often require different skill sets, hindering effective job matching for displaced workers.
Review, 2013
I n the years following the Great Recession, high unemployment rates persisted across the United States despite the steady increase in job openings. 1 This unexplained dynamic has led many to believe that the U.S. labor market's slow and jobless recovery could be explained as a mismatch phenomenon. 2 For instance, supporters of the sectoral mismatch hypothesis have pointed to changes in the employment and vacancy breakdown by sector. From December 2007 to February 2011, more than 50 percent of job losses occurred in the manufacturing and construction sectors, while over 90 percent of new positions opened in other sectors, suggesting that sectoral mismatch may have increased. Proponents of geographic mismatch-characterized by job vacancies in places different from those where people are looking for work-believe that the slow labor market recovery is rooted in the real estate bust and the subsequent extreme declines in housing prices, which may have reduced the mobility of homeowners. For example, Ferreira, Gyourko, and Joseph (2010) Labor mismatch, also known as structural imbalance, can be defined as a poor match between the characteristics of unemployed workers and those required for vacant jobs. In the wake of the jobless recovery from the Great Recession, economists have sought to explain the coexistence of a high unemployment rate and increasing job openings as a mismatch phenomenon. This article reviews five studies that have contributed to the development of mismatch indexes and computes the corresponding indexes over the period May 2005-May 2012 using job vacancy data from the Conference Board Help Wanted OnLine® (HWOL) Data Series. For most of the indexes, mismatch increased during the Great Recession, although the indexes exhibit a range of behaviors. According to an index developed in Jackman and Roper (1987), mismatch can account for at most 2.72 percentage points of the 5.30-percentage-point increase in the unemployment rate from the beginning of the recession to the unemployment rate peak. (JEL E24, J01, J23, J63, J64)
1999
Abstract This paper examines employer-jobseeker mismatch and the extent to which the time needed to fill vacancies is affected by characteristics and practices of employers in two different travel to work areas. Unemployment due to mismatch has been explained in economic literature as a function of factors such as changes in market structure, information asymmetry caused by inefficient job matching processes such as employment agencies, and lack of workforce flexibility in terms of geographic mobility, wages and skills.
2014
This paper explores rich longitudinal data to gain a better understanding of the importance of spatial mismatch in lower-paid workers' job search. The data infrastructure at our disposal allows us to investigate the impact on a variety of job search-related outcomes of localized and individual-specific job accessibility measures using identification strategies that mitigate the impact of residential self-selection. Our results suggest that better access to jobs causes a statistically significant, but modest decrease in the duration of joblessness among lowerpaid displaced workers, while an abundance of competing searchers for those jobs increases duration modestly. Search durations for older workers, Hispanic workers, and those displaced from manufacturing jobs are especially sensitive to job accessibility.
The main emphasis of this article is focused on the growing problem of structural unemployment in selected group of transition countries. Namely, if a certain region has a greater degree of unemployment rate than the frictional one, and if another region shows greater number of available vacancies than in conditions of frictional unemployment, it is referred to as structural disequilibrium or mismatch. Such unemployment is called structural unemployment. The estimates clearly show that the mismatch explains only a portion of unemployment and could be considered as a factor of increased unemployment. The empirical study refers to measuring the structural unemployment caused by regional mismatch in selected transition countries by known theoretical methods of mismatch indicators. The empirical findings of the crosscountry data sets suggest that the values for the particular mismatch indicators differ in a great extent. Therefore, it is very hard to estimate the real size of structural unemployment. The measured values for all mismatch indicators cannot give a uniform conclusion, but they show corresponding trend.
Journal of the European Economic Association
We investigate unemployment due to mismatch in the United States over the past three and a half decades. We propose an accounting framework that allows us to estimate the contribution of each of the frictions that generated labor market mismatch. Barriers to job mobility account for the largest part of mismatch unemployment, with a smaller role for barriers to worker mobility. We find little contribution of wage-setting frictions to mismatch.
Review of Economic Dynamics, 2013
Unemployment during and after the Great Recession has been persistently high. One concern is that the housing bust reduced geographical mobility and prevented workers from moving for jobs. We characterize flows out of unemployment that are related to geographical mobility to construct an upper bound on the effect of mobility on unemployment between 2007 and 2012. The effect of geographical mobility is always small: Using pre-recession mobility rates, decreased mobility can account for only an 11 basis points increase in the unemployment rate over the period. Using dynamics of renter geographical mobility in this period to calculate homeowner counterfactual mobility, delivers similar results. Using the highest mobility rate observed in the data, reduced mobility accounts for only a 33 basis points increase in the unemployment rate.
2013
Here Ut−1 is the set of unemployed at time t− 1; UH,t−1 is the set of unemployed homeowners at time t− 1; UR,t−1 is the set of unemployed renters at time t−1; MJt−1 is the set of people who move for jobs between time t−1 and t (people whose labor market outcomes improve as a result of moving); MJt−1 is the complement of the set MJt−1 and includes all non-movers and people who move but their moves were not job related; Other Net in f lowt−1 refers to all separations between employer and worker which lead to a transition of the worker from employment to unemployment between t− 1 and t, and to net inflows to unemployment from out of the labor force; and Et is the set of employed people at time t. Using shares and reorganizing, equation (A.1) becomes
2015
We investigate unemployment due to mismatch in the US over the past three decades. We propose an accounting framework that allows us to estimate the overall amount of mismatch unemployment, as well as the contribution of each of the frictions that caused the mismatch. Mismatch is quantitatively important for unemployment and the cyclical behavior of mismatch unemployment is very similar to that of the overall unemployment rate. Geographic mismatch is driven primarily by wage frictions. Mismatch across industries is driven by wage frictions as well as barriers to job mobility. We find virtually no role for worker mobility frictions.
Urban Studies, 2019
The literature on spatial mismatch often focuses on a mismatch within cities or local labour markets. This paper looks at the spatial mismatch between local labour markets. Using US data, we study the evolution of inter-regional mismatch between 1980 and 2010 and how this evolution varies across skill levels. Since we expect the spatial structure of supply and demand in the labour market to play a central role at this geographical level, we develop an extension of the spatial mismatch index, as the standard version does not take this spatial structure into account. Our results indicate that spatial mismatch has been increasing over the past decades, an increase that is largely attributable to spatial structure effects. The inter-regional spatial mismatch mainly affects low-skilled jobs and workers: our findings suggest that the degree of the spatial mismatch for low-skilled, relative to high-skilled workers, increased from a ratio of two in 1980 to almost four in 2010.
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