611 Tappan Ave
Department of Economics
611 Tappan Ave, Room 238
Ann Arbor, MI 48109-1220
Institutional Affiliation: University of Michigan
Information about this author at RePEc
NBER Working Papers and Publications
|October 2014||Annuitized Wealth and Post-Retirement Saving|
with John Laitner, Daniel Silverman: w20547
We introduce a tractable model of post-retirement saving behavior in which households have a precautionary motive arising from uninsured health status risks. The model distinguishes between annuitized and non-annuitized wealth, emphasizes the importance of asset composition in determining optimal household behavior, and includes an extension allowing late-in-life exchange transactions among relatives. We consider three puzzles in micro data - rising cohort average wealth of retirees, lack of demand for market annuities, and the relative scarcity of bequests - and show that our model can provide intuitive explanations for each.
|November 2013||Macroeconomic Determinants of Retirement Timing|
with Yuriy Gorodnichenko, Jae Song: w19638
We analyze lifetime earnings histories of white males during 1960-2010 and categorize the labor force status of every worker as either working full-time, partially retired or fully retired. We find that the fraction of partially retired workers has risen dramatically (from virtually 0 to 15 percent for 60-62 year olds), and that the duration of partial retirement spells has been steadily increasing. We estimate the response of retirement timing to variations in unemployment rate, inflation and housing prices. Flows into both full and partial retirement increase significantly when the unemployment rate rises. Workers around normal retirement age are especially sensitive to variations in the unemployment rate. Workers who are partially retired show a differential response to a high unemploym...
|June 2009||Inequality and Volatility Moderation in Russia: Evidence from Micro-Level Panel Data on Consumption and Income|
with Yuriy Gorodnichenko, Klara Sabirianova Peter: w15080
We construct key household and individual economic variables using a panel micro data set from the Russia Longitudinal Monitoring Survey (RLMS) for 1994-2005. We analyze cross-sectional income and consumption inequality and find that inequality decreased during the 2000-2005 economic recovery. The decrease appears to be driven by falling volatility of transitory income shocks. The response of consumption to permanent and transitory income shocks becomes weaker later in the sample, consistent with greater self-insurance against permanent shocks and greater smoothing of transitory shocks. Comparisons of RLMS data with official macroeconomic statistics reveal that national accounts may underestimate the extent of unofficial economic activity, and that the official consumer price index may ov...
- Yuriy Gorodnichenko & Klara Sabirianova Peter & Dmitriy Stolyarov, 2009. "Code and data files for "Inequality and Volatility Moderation in Russia: Evidence from Micro-Level Panel Data on Consumption and Income"," Computer Codes 09-198, Review of Economic Dynamics.
- Yuriy Gorodnichenko & Klara Sabirianova Peter & Dmitriy Stolyarov, 2010.
"Inequality and Volatility Moderation in Russia: Evidence from Micro-Level Panel Data on Consumption and Income,"
Review of Economic Dynamics,
Elsevier for the Society for Economic Dynamics, vol. 13(1), pages 209-237, January.
citation courtesy of
|January 1997||Learning, Complementarities, and Asynchronous Use of Technology|
with Boyan Jovanovic: w5870
This paper deals with processes that require several complementary inputs subject to improvements in quality. If after a quality upgrade one of these inputs requires a period of learning before it can be used effectively, then in general it will pay to purchase the inputs at different dates -- the purchases will be asynchronous. That is so because it is wasteful to tie up funds in the other inputs which will be underutilized until the date learning is over. We provide evidence that technology has been used asynchronously in the automobile industry, in the television broadcasting industry, in electricity supply, and in railways, and we argue that our model helps explain this evidence.