University of British Columbia
Institutional Affiliation: Interdisciplinary Center (IDC) Herzliya
Information about this author at RePEc
NBER Working Papers and Publications
|January 2016||How Exporters Grow|
with Doireann Fitzgerald, Stefanie Haller: w21935
We document how export quantities and prices evolve after entry to a market. Controlling for marginal cost, and taking account of selection on idiosyncratic demand, there are economically and statistically significant dynamics of quantities, but no dynamics of prices. To match these facts, we estimate a model where firms invest in customer base through non-price actions (e.g. marketing and advertising), and learn gradually about their idiosyncratic demand. The model matches quantity, price and exit moments. Parameter estimates imply costs of adjusting investment in customer base, and slow learning about demand, both of which generate sluggish responses of sales to shocks.
|October 2014||What Should I Be When I Grow Up? Occupations and Unemployment over the Life Cycle|
with Martin Gervais, Nir Jaimovich, Henry E. Siu: w20628
Why is unemployment higher for younger individuals? We address this question in a frictional model of the labor market that features learning about occupational fit. In order to learn the occupation in which they are most productive, workers sample occupations over their careers. Because young workers are more likely to be in matches that represent a poor occupational fit, they spend more time in transition between occupations. Through this mechanism, our model can replicate the observed age differences in unemployment which, as in the data, are due to differences in job separation rates.
Published: Martin Gervais & Nir Jaimovich & Henry E. Siu & Yaniv Yedid-Levi, 2016. "What Should I Be When I Grow Up? Occupations and Unemployment over the Life Cycle," Journal of Monetary Economics, . citation courtesy of
|December 2013||Technological Learning and Labor Market Dynamics|
with Martin Gervais, Nir Jaimovich, Henry E. Siu: w19767
The search-and-matching model of the labor market fails to match two important business cycle facts: (i) a high volatility of unemployment relative to labor productivity, and (ii) a mild correlation between these two variables. We address these shortcomings by focusing on technological learning-by-doing: the notion that it takes workers time using a technology before reaching their full productive potential with it. We consider a novel source of business cycles, namely, fluctuations in the speed of technological learning and show that a search-and-matching model featuring such shocks can account for both facts. Moreover, our model provides a new interpretation of recently discussed "news shocks."
Published: Martin Gervais & Nir Jaimovich & Henry E. Siu & Yaniv Yedid‐Levi, 2015. "Technological Learning And Labor Market Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 27-53, 02. citation courtesy of