Federal Reserve Board
Washington, DC 20551
Institutional Affiliation: Federal Reserve Board
Information about this author at RePEc
NBER Working Papers and Publications
|May 2007||Assessing Structural VARs|
with Lawrence J. Christiano, Martin Eichenbaum
in NBER Macroeconomics Annual 2006, Volume 21, Daron Acemoglu, Kenneth Rogoff and Michael Woodford, editors
|July 2006||Assessing Structural VARs|
with Lawrence J. Christiano, Martin Eichenbaum: w12353
This paper analyzes the quality of VAR-based procedures for estimating the response of the economy to a shock. We focus on two key issues. First, do VAR-based confidence intervals accurately reflect the actual degree of sampling uncertainty associated with impulse response functions? Second, what is the size of bias relative to confidence intervals, and how do coverage rates of confidence intervals compare with their nominal size? We address these questions using data generated from a series of estimated dynamic, stochastic general equilibrium models. We organize most of our analysis around a particular question that has attracted a great deal of attention in the literature: How do hours worked respond to an identified shock? In all of our examples, as long as the variance in hours worked ...
|January 2004||The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology|
with Lawrence J. Christiano, Martin Eichenbaum: w10254
We investigate what happens to hours worked after a positive shock to technology, using the aggregate technology series computed in Basu, Fernald and Kimball (1999). We conclude that hours worked rise after such a shock.
Published: Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 381-395, 04/05. citation courtesy of
|July 2003||What Happens After a Technology Shock?|
with Lawrence J. Christiano, Martin Eichenbaum: w9819
We provide empirical evidence that a positive shock to technology drives per capita hours worked, consumption, investment, average productivity and output up. This evidence contrasts sharply with the results reported in a large and growing literature that argues, on the basis of aggregate data, that per capita hours worked fall after a positive technology shock. We argue that the difference in results primarily reflects specification error in the way that the literature models the low-frequency component of hours worked.