Twenty-First Annual Conference on Macroeconomics

Article excerpt

The NBER's twenty-first Annual Conference on Macroeconomics, organized by NBER Research Associates Daron Acemoglu, MIT, Kenneth Rogoff, Harvard University, and Michael Woodford, Columbia University, took place in Cambridge on April 7 and 8. The program was:

Lawrence J. Christiano and Martin Eichenbaum, Northwestern University and NBER, and Robert Vigfusson, Federal Reserve Board, "Assessing Structural VARs"

Discussants: Patrick Kehoe, Federal Reserve Bank of Minneapolis, and Mark W. Watson, Princeton University and NBER

Steven J. Davis, University of Chicago and NBER; John C. Haltiwanger, University of Maryland and NBER; and Ron Jarmin and Javier Miranda, U.S. Census Bureau, "Volatility and Dispersion in Business Growth Rates: Publicly Traded versus Privately Held Firms"

Discussants: Chris Foote, Federal Reserve Bank of Boston, and Eva Nagypal, Northwestern University

Lars Ljungqvist, Stockholm School of Economics, and Thomas J. Sargent, New York University and NBER, "Indivisible Labor, Human Capital, Lotteries and Personal Savings: Do Taxes Explain European Unemployment?"

Discussants: Olivier J. Blanchard, MIT and NBER, and Edward C. Prescott, Arizona State University and NBER

Troy Davig, Federal Reserve Bank of Kansas City, and Eric M. Leeper, Indiana University and NBER, "Fluctuating Macro Policies and the Fiscal Theory" (NBER Working Paper No. 11212)

Discussants: Jordi Gall, MIT and NBER, and Christopher A. Sims, Princeton University and NBER

Mikhail Golosov, MIT and NBER, Aleh Tsyvinski, Harvard University and NBER; and Ivan Werning, MIT and NBER, "New Dynamic Public Finance: a User's Guide"

Discussants: Peter A. Diamond, MIT and NBER, and Kenneth L. Judd, Stanford University and NBER

Monika Piazzesi, University of Chicago and NBER; and Martin Schneider, Federal Reserve Bank of Minneapolis, "Equilibrium Yield Curves"

Discussants: Pierpaolo Benigno, New York University and NBER, and John Y. Campbell, Harvard University and NBER

Christiano, Eichenbaum, and Vigfusson analyze the quality of VAR-based procedures for estimating the response of the economy to a shock. They focus on two key questions. 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 to their nominal size? They address these questions using data generated from a series of estimated dynamic, stochastic general equilibrium models. They organize most of their 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 their examples, as long as the variance in hours worked attributable to a given shock is above the remarkably low number of 1 percent, structural VARs perform well. This is true regardless of whether identification is based on short-run or long run restrictions. Confidence intervals are wider in the latter case. Even so, long run identified VARs can be useful for discriminating between competing economic models.

Davis, Haltiwanger, Jarmin, and Miranda study the distribution of growth rates among establishments and firms in the U.S. private sector from 1976 onwards. To carry out their study, they exploit the recently developed Longitudinal Business Database (LBD), which contains annual observations on employment and payroll for all business establishments and firms. Their main finding is a large secular decline in the cross-sectional dispersion of firm growth rates and in the average magnitude of firm level volatility. Measured in the same way as in other recent research, the employment-weighted mean volatility of firm growth rates in the private sector has declined by more than 40 percent since 1982. …

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