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Abstract:
I present empirical evidence of how the U.S. economy, including per-capita hours worked, responds to a technology shock. In particular, I present results based on permanent changes to a constructed direct measure of technological change for U.S. manufacturing industries.
Based on empirical evidence, some claim that hours worked declines and never recovers in response to a positive technology shock. This paper�s empirical evidence suggests that emphasizing the drop in hours worked is misdirected. Because the sharp drop in hours is not present here, the emphasis rather should be on the small (perhaps negative) initial response followed by a subsequent large positive response. Investment, consumption, and output have similar dynamic responses.
In response to a positive technology shock, a standard flexible price model would have an immediate increase in hours worked. Therefore, such a model is inconsistent with the empirical dynamic responses. I show, however, that a flexible price model with habit persistence in consumption and certain kinds of capital adjustment costs can better match the empirical responses.
Some recent papers have critiqued the use of long run VARs to identify the dynamic responses to a technology shock. In particular they report that, when long run VARs are applied to data simulated from particular economic models, the point estimates of the impulse responses may be imprecisely estimated. However, based on additional simulation evidence, I find that, although the impact response may be imprecisely estimated, a finding of a delayed response is much more likely when the true model response also has a delayed response.
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Keywords
macroeconomic models, vector autoregressions, impulse responses, weak instruments, long-run identification assumption
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