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Three Essays on Structural Macroeconomics

Havnurkar, Parth
Thesis/Dissertation; Online
Havnurkar, Parth
Otrok, Chris
Mukoyama, Toshihiko
Young, Eric
I analyze the effect of an anticipated change to the level of technology (news shocks) on the aggregate labor market. I isolate the news shock associated with technology (capacity utilization adjusted measure of Total Factor Productivity) using a Structural Vector Auto Regression (SVAR) model. I find a significant response along both the intensive and extensive margins of employment. Specifically, I find that vacancies posted and hours worked jump up at the impact of a positive shock and that they stay bounded away from zero at a horizon of 10 years. In contrast, I find that the unemployment rate jumps down at impact and also remains bounded away from zero. Similarly, I find that the labor force participation rate jumps down at impact though the response is insignificant at longer horizons. Anticipation of a 1 percent increase in technology in 1 year causes an immediate jump in vacancies of 1.1 percent, of .058 percent in hours worked, a reduction of 1.45 percent in the unemployment rate and a reduction of .039 percent in the participation rate. Finally, I use the identified technology news time series to study its connection to an important part of the labor market: new business creation. I find that the index of new business is granger-causal for positive news shocks indicating that the standard assumption of exogenous technological advancement in empirical and theoretical macro modeling needs reworking.
University of Virginia, Department of Economics, PHD (Doctor of Philosophy), 2013
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PHD (Doctor of Philosophy)
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