scholarly journals Measuring the True Impact of Job Loss on Future Earnings

2017 ◽  
pp. 1-4
Author(s):  
Pawel M. Krolikowski
Keyword(s):  
Job Loss ◽  
Job Displacement ◽  
Future Earnings ◽  
Earnings Losses

The effect of job displacement on future earnings losses has often been calculated by comparing the earnings of individuals who suffer a displacement at some point in their career with the earnings of those who never lose a job. I show this approach leads to an overstatement of the earnings losses following displacement and discuss an alternative that can ascertain the true effects of displacement in some instances.

The Long-Term Costs of Job Displacement for Young Adult Workers

ILR Review ◽  
2003 ◽  
Vol 56 (4) ◽  
pp. 682-698 ◽  
Author(s):  
Lori G. Kletzer ◽  
Robert W. Fairlie
Keyword(s):  
Young Adults ◽  
Older Workers ◽  
Job Loss ◽  
Job Displacement ◽  
Young Workers ◽  
Earnings Growth ◽  
Earnings Losses ◽  
Expected Earnings ◽  
Annual Earnings

Using NLSY data, the authors estimate the long-term costs of job displacement for young adults. Earnings and wage losses were large for the first three years following displacement. Compared to earnings losses found by other studies for more mature workers, however, earnings losses for these young adults were short-lived, with differences between observed and expected earnings narrowing considerably five years after job loss. At that point, the shortfall in annual earnings (relative to what would have been expected absent job loss) was 9% for men and 12.5% for women, and the shortfall in hourly wages was 21.2% for men. Young workers also apparently differ from more established workers in the composition of total earnings losses: for older workers, total losses largely represent actual, immediate earnings losses, whereas for young workers the loss of opportunities for rapid earnings growth is more important.

scholarly journals Job Loss, Credit, and Crime in Colombia

2021 ◽  
Vol 3 (1) ◽  
pp. 97-114
Author(s):  
Gaurav Khanna ◽  
Carlos Medina ◽  
Anant Nyshadham ◽  
Christian Posso ◽  
Jorge Tamayo
Keyword(s):  
Job Loss ◽  
Policy Reform ◽  
Economic Incentives ◽  
Job Displacement ◽  
Access To Credit ◽  
Mass Layoffs ◽  
Earnings Losses ◽  
Banking Policy ◽  
Younger Men ◽  
Participation Decisions

We investigate the effects of job displacement, as a result of mass layoffs, on criminal arrests using a matched employer-employee crime dataset from Medellín, Colombia. Job displacement leads to immediate and persistent earnings losses and higher probability of arrest for both the displaced worker and family members. Leveraging a banking policy reform, we find that greater access to credit attenuates the criminal response to job loss. Impacts on arrests are pronounced for property crimes and among younger men for whom opportunities in criminal enterprises are prevalent. Taken together, our results are consistent with economic incentives contributing to criminal participation decisions after job losses. (JEL G21, G51, J63, K42, O16, O17)

scholarly journals Job Displacement

1998 ◽  
Vol 12 (1) ◽  
pp. 115-136 ◽  
Author(s):  
Lori G Kletzer
Keyword(s):  
Job Loss ◽  
Training Programs ◽  
White Collar ◽  
Job Displacement ◽  
The Past ◽  
Earnings Losses ◽  
Specific Human Capital ◽  
College Educated ◽  
And Training

The past decade and a half has seen tremendous research growth in the area of job displacement. This paper discusses the state of knowledge on the issues and questions of job loss. The 1984-96 Displaced Worker Surveys are used to describe how the characteristics of displacement are changing to include more college educated, white collar, and nonmanufacturing workers. For many workers, the long-term earnings losses following displacement are large due to the loss of firm-specific human capital. More research is needed on the questions of the causes of job displacement and on the efficacy of employment and training programs.

scholarly journals Job Ladders and Earnings of Displaced Workers

2017 ◽  
Vol 9 (2) ◽  
pp. 1-31 ◽  
Author(s):  
Pawel Krolikowski
Keyword(s):  
Displaced Workers ◽  
Job Displacement ◽  
Wage Dispersion ◽  
Earnings Losses ◽  
Displaced Worker

Workers who suffer job displacement experience surprisingly large and persistent earnings losses. This paper proposes an explanation for this robust empirical puzzle in a model of search with a significant job ladder and increased separation rates for the recently hired. In addition to capturing the depth and persistence of displaced worker earnings losses, the model matches: employment-to-nonemployment and employer-to-employer probabilities by tenure; the empirical decomposition of earnings losses into reduced wages and employment; observed wage dispersion; and the distribution of wage changes around a nonemployment event. (JEL J31, J63, J64)

Poor health as a potential risk factor for job loss due to automation: the case of Norway

2017 ◽  
Vol 75 (3) ◽  
pp. 227-230 ◽  
Author(s):  
Philipp Hessel ◽  
Solveig Christiansen ◽  
Vegard Skirbekk
Keyword(s):  
Potential Risk ◽  
Job Loss ◽  
Linear Models ◽  
Well Being ◽  
Poor Health ◽  
Job Displacement ◽  
Average Risk ◽  
Negative Consequences ◽  
Generalised Linear Models ◽  
Health And Well Being

ObjectiveThis study aimed to quantify the extent to which health characteristics of workers are related to the potential risk of experiencing job displacement due to automation.MethodsLinking the 2015 Norwegian Statistics on Income and Living Conditions survey (n=6393) with predicted probabilities of automation by occupation, we used Kruskal-Wallis tests and multivariate generalised linear models to assess the association between long-standing illnesses and risk of job automation.ResultsIndividuals with long-standing illnesses face substantially greater risks of losing their job due to automation. Whereas the average risk of job automation is 57% for men and 49% for women with long-standing illnesses, the risk is only 50% for men and 44% for women with limitations (p<0.001). Controlling for age, having a long-standing illness significantly increases the relative risk of facing job automation among men (risk ratio (RR) 1.13, 95% CI 1.09 to 1.19), as well as women (RR 1.11, 95% CI 1.05 to 1.17). While, among men, the association between long-standing illness and risk of job automation remains significant when controlling for education and income, it becomes insignificant among women.ConclusionsIndividuals with poor health are likely to carry the highest burden of technological change in terms of worsening employment prospects because of working in occupations disproportionally more likely to be automated. Although the extent of technology-related job displacement will depend on several factors, given the far-reaching negative consequences of job loss on health and well-being, this process represents a significant challenge for public health and social equity.

scholarly journals Two-Sided Learning with Applications to Labor Turnover and Worker Displacement

2008 ◽  
Vol 228 (5-6) ◽  
Author(s):  
Gerard A. Pfann ◽  
Daniel S. Hamermesh
Keyword(s):  
Dynamic Model ◽  
Job Loss ◽  
Recent Literature ◽  
Displaced Workers ◽  
Labor Turnover ◽  
Job Displacement ◽  
Worker Displacement ◽  
Value Of Learning ◽  
Role Of Information

SummaryWe make several extensions to the recent literature on job loss while modernizing the very early job-displacement literature. After constructing a dynamic model of two-sided learning between a firm and its workers, we estimate it using personnel data from Fokker Aircraft that cover the path of layoffs and quits through its bankruptcy in March 1996. We find that the firm learns about workers' loyalty (demonstrating the role of information in repeated cooperative principal- agent relationships), while workers do not learn (consistent with earlier empirical results on American workers). The type of data that we use also generates information on the value of learning and on whether and how the characteristics of workers who remain until the firm's death differ from those of all affected workers. It thus allows us to measure the increases in the firm's value from learning about its workers' behavior and to infer the extent of biases in estimating losses from displacement from samples restricted to displaced workers.

scholarly journals Geographic Mobility and the Costs of Job Loss

2015 ◽  
Vol 15 (4) ◽  
pp. 1793-1829 ◽  
Author(s):  
Nicholas A. Jolly
Keyword(s):  
Job Loss ◽  
Panel Study ◽  
Displaced Workers ◽  
Early Years ◽  
Geographic Mobility ◽  
Lower Probability ◽  
Income Dynamics ◽  
Earnings Losses ◽  
Loss Experience

Abstract This paper uses data from the 1968 through 1997 survey waves of the Panel Study of Income Dynamics to analyze how the long-term costs of job loss vary by a worker’s post-displacement migration status. Results from the analysis show that those individuals who move within the first 2 years after a job loss experience lower earnings losses, lower reductions in hours worked, and smaller increases in time unemployed when compared to a group of displaced workers who are not geographically mobile during the early years following this life event. Workers who move within the first 2 years after displacement face a lower probability of homeownership when compared to their non-mobile counterparts. However, this lower probability is short-lived.

Damage Awards Using Intermediate Term Government Bond Funds vs. U.S. Treasuries Ladder: Tradeoffs in Theory and Practice

2012 ◽  
Vol 23 (1) ◽  
pp. 1-31 ◽  
Author(s):  
Joseph I. Rosenberg ◽  
Rick R. Gaskins
Keyword(s):  
Theory And Practice ◽  
Alternative Methods ◽  
Present Value ◽  
Damage Awards ◽  
Practical Result ◽  
Future Earnings ◽  
Lump Sum ◽  
Earnings Losses ◽  
Ex Post ◽  
Finance Theory

Abstract Valuing damage awards for personal injury or wrongful death requires the application of finance theory to achieve a practical result. Methods for discounting future earnings losses fall into two major categories: Current market rates, which offer greater objectivity, and historical rates, which theoretically offer greater stability of results by averaging away the effect of often volatile “current” market conditions. The purpose of this paper is to provide a unique ex post comparison of damage awards using distinctive current and historical rates methods that highlight the inherent differences between the two major discounting alternatives. Current market rates methods are represented by a Treasury bond ladder with no instrument rollover, using initial market rates for both discounting and investing damage awards. Historical rates methods are represented by intermediate term government bonds; historical average five-year Treasury yields are used for discounting the damage award, with annual bond rollover required afterwards to maintain the award investment in comparable instruments, creating realized total returns from investing. These alternative methods are compared, ex ante in terms of the present value of the awards, and also ex post, in terms of how well each method's award, based on the same projected lost earnings, is able to support paydowns based on actual lost earnings. Key findings include: (a) both methods result in widely varying lump sum awards; (b) the idea that historical rates offer greater stability of results over time is empirically unsupportable; (c) that a good measure of methodological accuracy is the relative variance in award present values observed by first discounting and then subsequently investing under each method using the same instruments; (d) that different economic conditions greatly affect the relative ex post accuracy of each method; and (e) that neither method is very accurate in projecting present value of earnings losses upon ex post analysis.

scholarly journals The Gender Gap in Earnings Losses after Job Displacement

2021 ◽  
Author(s):  
Hannah Illing ◽  
Johannes F. Schmieder ◽  
Simon Trenkle
Keyword(s):  
Gender Gap ◽  
Job Displacement ◽  
Earnings Losses

scholarly journals The Gender Gap in Earnings Losses after Job Displacement

2021 ◽  
Author(s):  
Hannah Illing ◽  
Johannes Schmieder ◽  
Simon Trenkle
Keyword(s):  
Gender Gap ◽  
Job Displacement ◽  
Earnings Losses
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