Wealth and Consumption After Job Displacement

Income drops permanently after an involuntary job displacement, but it has never been clear what happens to long run wealth in the USA. Upon displacement, wealth falls 14% relative to workers of the same age and similar education from the Panel Study of Income Dynamics (PSID). Their wealth is still 18% lower 12 years after the event. A standard life cycle model calibrated to US data with permanent decreases in income after displacement behaves differently than these findings. The agents in the model also experience a large drop in wealth but they recover. The biggest culprit for these differences is small and statistically insignificant changes to consumption in the PSID whereas agents in the model decrease their consumption considerably. Extending the model to include habit formation reconciles some of these differences by generating similar long run effects on wealth. This allows for the examination of wealth at death through the lens of the model.

Linkages among automation, job displacement and reshoring: evidence from the Bangladeshi apparel industry

Purpose This paper aims to evaluate the impact of automation on job displacement and reshoring in the apparel industry. It also compares with predictions on the same subject matter by the existing literature and, thus, provides future research agenda for further studies. Design/methodology/approach Primary data were collected through 27 semi-structured in-depth interviews. The grounded theory was used for thematic and network analyzes, which traced the drivers and barriers, as well as the impact of automation and reshoring. Findings Initially, automation decreases human interactions in any specific production section. However, it increases productivity, quality and cost advantages, which invoke growth and further employment in clothing firms. The employment of unskilled workers decreases in the long run when automation is well adopted in the system. Automation does not stimulate reshoring but may support relocation initiatives of production sites around the centers of global value chains (GVCs). This GVC-based relocation may create job displacement in apparel manufacturing nations in Asia while bringing employment opportunities to Sub-Saharan African countries, Europe and North America. Originality/value Little empirical research has been conducted on the impact of automation on the apparel industry. This study predicts that human interventions will dominate the sewing of fashionable and sophisticated apparel products while automation may replace many human workers for basic garment items in the foreseeable future.

Explaining Wage Losses after Job Displacement: Employer Size and Lost Firm Wage Premiums

This paper investigates whether wage losses after job displacement are driven by lost firm wage premiums or worker productivity depreciations. We estimate losses in wages and firm wage premiums, the latter being measured as firm effects from a two-way fixed-effects wage decomposition. Using new German administrative data on displacements from small and large employers, we find that wage losses are to a large extent explained by losses in firm wage premiums and that premium losses are largely permanent. We show that losses strongly increase with pre-displacement employer size. This provides an explanation for large and persistent wage losses reported in previous displacement studies typically focusing on large employers, only.

Job Displacement Insurance and (the Lack of) Consumption-Smoothing

We study the spending profile of workers who experience both a positive transitory income shock (lump-sum severance pay) and a negative permanent income shock (layoff). Using de-identified expenditure and employment data from Brazil, we show that workers increase spending at layoff by 35 percent despite experiencing a 14 percent long-term loss. We find high sensitivity of spending to cash-on-hand across consumption categories and for several sources of variation, including predictable income drops. A model with present-biased workers can rationalize our findings, and highlights the importance of the timing of benefit disbursement for the consumption-smoothing gains of job displacement insurance policies. (JEL D12, G51, J65, J63, O12)

Job Loss, Credit, and Crime in Colombia

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)

A Human Blueprint for AI Coexistence

The positive coexistence of humans and AI is possible and needs to be designed as a system that provides for all members of society, but one that also uses the wealth generated by AI to build a society that is more compassionate, loving, and ultimately human. It is incumbent on us to use the economic abundance of the AI age to foster the values of volunteers who devote their time and energy toward making their communities more caring. As a practical measure, to protect against AI/robotics’ labor saving and job displacement effects, a “social investment stipend” should be explored. The stipend would be given to those who invest their time and energy in those activities that promote a kind, compassionate, and creative society, i.e., care work, community service, and education. It would put the economic bounty generated by AI to work in building a better society, rather than just numbing the pain of AI-induced job losses.