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Understanding the effect of technology shocks in SVARs with long-run restrictions |
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| Institution: | 1. Pamplin School of Business, University of Portland, Portland, OR 97203, USA;2. Department of Finance and Real Estate, Colorado State University, Fort Collins, CO 80523, USA;1. Department of Economics, Mihaylo College of Business and Economics, California State University Fullerton, Fullerton, CA 92834, United States;2. Department of Economics, University of Western Ontario, London, ON N6A 5C2, Canada;1. Department of Materials Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;2. Delft University of Technology, EEMCS Faculty, Delft, The Netherlands |
| Abstract: | This paper studies the statistical properties of impulse response functions in structural vector autoregressions (SVARs) with a highly persistent variable as hours worked and long-run identifying restrictions. The highly persistent variable is specified as a nearly stationary persistent process. Such a process appears to be particularly well suited to characterize the dynamics of hours worked because it implies a unit root in a finite sample but is asymptotically stationary and persistent. This is typically the case for per capita hours worked which are included in SVARs. Theoretical results derived from this specification allow us to explain most of the empirical findings from SVARs which include US hours worked. |
| Keywords: | SVARs Long-run restrictions Locally nonstationary process Technology shocks Hours worked |
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