Poster Paper: Bridge Employment: A Skill- and Occupation-Biased Retirement Trend?

Saturday, November 4, 2017
Regency Ballroom (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Zeewan Lee, University of Southern California

It is a widely-known fact that the historical decline of labor force participation of older workers has long been reversed. In the last two decades, we have been witnessing new trends in retirement: phased-retirement and unretirement. It has been argued by the scholars studying the phenomena that such types of retirement are largely predictable ex ante, and are not direct consequences of economic shocks. Phased-retirement and unretirement—or ‘bridge employment’—deserves much scholarly attention in that aging workers’ growing inclinations toward bridge employment not only influence workers themselves on personal levels (i.e. retirement income security) but also the overall structure and productivity of a nation’s labor force. Despite its growing prevalence across the globe, much of the bridge employment of older workers remains an enigma. Scholars studying the phenomenon are yet to agree upon the common causal mechanisms that lead workers to delay full-retirement. In order to contribute to the literature, I propose to touch upon some of the less-discussed facets of bridge employment. In this study, I assess whether there are differences in workers’ tendencies to engage in bridge jobs based on their occupational classifications that distinguish between (1) white-collar and blue-collar and (2) high- and low-skilled workers.

Data is drawn from the public and restricted portions of the Health and Retirement Study (HRS), a panel data that contains information of aging workers in the United States from 1992 to 2012. In this study, analyses have been conducted based on a multinomial logistic regression model that assumes and treats time-invariant heterogeneity among the HRS survey participants. The preliminary result suggests that workers with strong expertise and white-collar jobs are more likely to secure bridge jobs than their counterparts. Moreover, such workers are to be more prone to finding bridge jobs within the industries in which they originally belonged—while others seem to be pressured to secure jobs that are outside their original industries and are thus irrelevant to their skillsets. Such dynamics are expected to hold valid even after controlling for covariates such as workers’ demographics, health, pension, social security income, family structure, etc. The results from the said model will be compared to those of another model that is designed to resolve time-variant endogeneity—stemming from workers’ possible self-selection of jobs—using appropriate instruments in a panel IV model. Lastly, in an attempt to identify a causal element that facilitates such occupation- and skill-biased retirement trends, I will conclude this study by discussing a possibility of technology and innovation’s playing major roles.