I am on the academic job market in 2013-14, and will be attending the ASSA meetings in Philadelphia, January 3-5, 2014.
I am Ph.D. candidate in economics at the University of Michigan and will be on the job market in 2013-14. My research focuses on the work, saving, and benefit claiming decisions of near-retirement households. My job market paper explores how Social Security's spouse and survivor benefits alter work decisions within a household as a married couple approaches retirement. These benefits are a large chunk of Social Security's annual expenditures (approx. $112 billion), but their impact on the household's work decision has been largely ignored. I estimate a structural model of work, saving, and claiming decisions that incorporates detailed Social Security earnings histories and individual pension plans to explore how altering the incentives created by spouse and survivor benefits would change a husband and wife's work and retirement decisions.
My work with Social Security has also highlighted another growing demographic challenge with big implications for individuals near-retirement: the rising rate of divorce at older ages. In separate work, I am using birth cohorts from the Health and Retirement Study spanning from the 1920s to 1950s to explore the implications of divorce on re-entry into the labor force and delayed retirement.
In future work, I will explore the role of occupational shifts across birth cohorts in driving changes in the age of retirement and benefit claiming. I am also excited to expand my structural model of near-retirement households to understand the role of family ties in encouraging dissavings during retirement, and exploring the interaction of disability programs and marital separation, a pattern that I have discovered is quite strong in my empirical work.
Finally, I continue to be fascinated with the growing potential of computer clusters and GPUs for solving high-dimensional problems in economics and business. Working with Brian Wu (Ross Business School at Univ. of Michigan), we have developed an innovative method for incorporating complementarities into complex models of organizational adaptation (e.g. how Apple can makes decisions to optimize its global performance when the business choices made by the iPad division augment or canabilize the performance by other divisions, like personal computers). I can see a future in using the methodology of organizational adaptation in complex landscapes to understand financial learning among individuals nearing retirement - a complex process that almost everyone will one day endure!