By LAWRENCE J. CHRISTIANO AND MARTIN EICHENBAUM *
Hours worked and the return to working are weakly correlated. Traditionally, the ability to account for this fact has been a litmus test for macroeconomic models. Existing real-business-cycle models fail this test dramatically. We modify prototypical real-business-cycle models by allowing government consumption shocks to influence labor-market dynamics. This modification can, in principle, bring the models into closer conformity with the data. Our empirical results indicate that it does. (JEL E32, C12, C52, C13, C51)
In this paper, we assess the quantitative implications of existing real-business-cycle (RBC) models for the time-series properties of average productivity and hours worked. We find that the single most salient shortcoming of existing RBC models lies in their predictions for the correlation between these variables. Existing RBC models predict that this correlation is well in excess of 0.9, whereas the actual correlation is much closer to zero. 1 This shortcoming leads us to add to the RBC framework aggregate demand shocks that arise from stochastic movements in government consumption. According to our empirical results, this change substantially improves the models’ empirical performance.
The ability to account for the observed correlation between the return to working and the number of hours worked has traditionally been a litmus test for aggregate economic models. Thomas J. Sargent (1987 p. 468), for example, states that one of the primary empirical patterns casting doubt on the classical and Keynesian models has been the observation by John T. Dunlop (1938) and Lorie Tarshis (1939) “alleging the failure of real wages to move countercyclically. ” The classical and Keynesian models share the assumption that real wages and hours worked lie on a stable, downward-sloped marginal productivity-of-labor curve. 2 Consequently, they both counterfactually predict a strong negative correlation between real wages and hours worked. Modern versions of what Sargent (1987 p. 468) calls the “Dunlop-Tarshis observation” continue to play a central role in assessing the empirical plausibility of different business-cycle models. 3 In discussing Stanley Fischer’s (1977)
* Christiano: Federal Reserve Bank of Minneapolis, Minneapolis, MN 55480; Eichenbaum: Northwestern University, Evanston, IL 60208, National Bureau of Economic Research, and Federal Reserve Bank of Chicago. This paper is a substantially revised version of NBER Working Paper No. 2700, “Is Theory Really Ahead of Measurement? Current Real Business Cycle Theories and Aggregate Labor Market Fluctuations. ” We thank Rao Aiyagari, Paul Gomme, Finn Kydland, Ed Prescott, and Mark Watson for helpful conversations. Any views expressed here are ours and not necessarily those of any part of the Federal Reserve System.
1 This finding is closely related to Bennett McCallum’s (1989) observation that existing RBC models generate grossly counterfactual predictions for the correlation between average productivity and output.
2 As John Maynard Keynes (1935 p. 17) says, “…I am not disputing this vital fact which the classical economists have (rightly) asserted as indefeasible. In a given state of organisation, equipment and technique, the real wage earned by a unit of labour has a unique (inverse) correlation with the volume of employment. ”
3 For example, Robert J. Barro and Herschel I. Grossman (1971) cite the Dunlop-Tarshis observation to motivate their work on disequilibrium theories. Also, Edmund S. Phelps and Sidney G. Winter, Jr. (1970 p. 310) and Franco Modigliani (1977 p. 7) use this observation to motivate their work on noncompetitive approaches to macroeconomics. Finally, Robert E. Lucas, Jr. (1981 p. 13) cites the Dunlop-Tarshis observation in motivating his work on capacity and overtime.