Paul Beaudry and Bernd Lucke - Letting Di􀀋erent Views about Business Cycles Compete

Sep 18, 2026

Uploaded by Ben

Empirical macroeconomics discussion on estimating the origins of business cycles using five-variable vector error-correction models (VECM). The paper compares anticipated versus unanticipated TFP shocks, investment-specific technology shocks, preference shocks, and monetary policy shocks, emphasizing anticipated TFP shocks and cointegration restrictions. It uses time series for TFP, investment relative prices, stock prices, federal funds rates, and aggregate activity, concluding anticipated TFP shocks explain most fluctuations in U.S. activity and stock prices at business-cycle frequencies.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages18

Reading Time45 min

AccessFree to download

Background and Motivation

Unresolved question in macroeconomics

Prior SVAR long-run restrictions and technology shocks

Competing Evidence on Technology Shocks

SVAR and Bayesian DSGE findings

Forecast error variance and investment-specific technology

Identification and Link to Related Work

Beaudry and Portier (2006) identification scheme

News TFP shocks and impulse response similarity

Paper’s Core Approach and Main Result

Paul Beaudry and Bernd Lucke: “Letting Di􀀋erent Views about Business Cycles Compete” Discussion prepared by Stephanie Schmitt-Groh􀀓e Columbia University􀀃 June 17, 2009 This paper is a contribution to the empirical literature on the estimation of the sources of business cycles. It uses various 􀀌ve-variable vector-error-correction models (VECM) to estimate the relative importance of anticipated total factor productivity (TFP) shocks, unanticipated TFP shocks, investment speci􀀌c technology shocks, preference shocks, and monetary policy shocks. An innovation relative to the large related literature on structural vector autoregression based estimation of the sources of 􀀍uctuations is the focus on anticipated TFP shocks and on imposing cointegration relationships. Further, Beaudry and Lucke use time series on TFP, the relative price of investment, stock prices, federal funds rates, and a measure of aggregate activity in their estimation. This set of observables is slightly di􀀋erent than that used in the related literature. The main 􀀌nding of the paper is that anticipated TFP shocks explain the majority of 􀀍uctuations in aggregate activity and stock prices at business cycle frequencies in the United States. Many authors have studied the question what the sources of short-run 􀀍uctuations are. Yet this fundamental question in macroeconomics remains largely unresolved. John Cochrane (1994) in a piece written for the Carnegie Rochester Conference Series on Public Policy starts his article on this topic as follows: “What shocks are responsible for economic 􀀍uctuations? Despite at least two hundred years in which economists have observed 􀀍uctuations in economic activity, we still are not sure.” Fifteen years later in business cycle research this statement 􀀃 I would like to thank Ryan Chahrour and Ozge Akinci for excellent research assistance. is still a valid description of the state of the literature. Cochrane interpreted the 􀀌ndings of his (1994) study as suggesting that contemporaneous shocks to technology, money, credit, and oil cannot account for the majority of observed aggregate 􀀍uctuations.1 More recent SVAR based papers using long-run restrictions such as Gal􀀓􀀐 and Rabanal (2004) 􀀌nd, like Cochrane, a small role for permanent technology shocksin accounting for business cycle variations in hours and output. In table 2 of their paper Gal􀀓􀀐 and Rabanal report that the share of variance due to technology shocks lies between 7 and 37 percent for output and between 5 and 36 percent for hours. Most importantly under their favored interpretation, the technology shock accounts for less than 10 percent of the variance of output and hours. They therefore conclude that “Nevertheless, it is safe to state that the bulk of the evidence reviewed in the present paper provides little support for the initial claims of the RBC literature on the central role of technological change as a source of business cycles.” On the other hand, there are papers presenting evidence that suggests that technology shocks are the major source of 􀀍uctuations, and the Beaudry and Lucke paper 􀀌ts into this group. For example, the empirical paper of Fisher (2006), using SVAR methods, comes to the conclusion that neutral and investment speci􀀌c “technology shocks account for 73 percent of hours and 44 percent of outputs business cycle variation before 1982, and 38 percent and 80 percent afterward. The shocks also account for more than 40 percent of hours and 58 percent of outputs forecast errors over a three- to eight-year horizon in both samples. The majority of these e􀀋ects are driven by the investment shocks.” Using Bayesian methods to estimate a dynamic stochastic general equilibrium model, Smets and Wouters (2007) 􀀌nd that at least 30 percent of the forecasting error variance of output is attributable to a combination of neutral and investment speci􀀌c technology shocks, with the majority of this share explained by neutral technology shocks. Justinia

FAQs

What econometric method does the paper use to estimate the sources of business-cycle fluctuations?

It uses five-variable vector error-correction models (VECM) to estimate the relative importance of multiple shock types, including different TFP shock categories and monetary policy shocks.

Which shock category does the paper identify as most important for business-cycle fluctuations?

Anticipated total factor productivity (TFP) shocks explain the majority of fluctuations in aggregate activity and stock prices at business cycle frequencies in the United States.

How does the discussion position the paper relative to earlier SVAR and RBC-related findings?

It contrasts earlier work suggesting technology shocks play only a small role with evidence that technology-related shocks can account for large shares of variation, placing Beaudry and Lucke within the latter group.

Sep 18, 2026

Uploaded by Ben