DECONSTRUCTING THE SUCCESS OF REAL BUSINESS CYCLES

I. INTRODUCTION A major achievement of Real Business Cycle (RBC) models has been their success at elegantly explaining a remarkably large fraction of business cycle fluctuations in aggregate variables based solely on exogenous variation in productivity. In particular, the RBC literature has emphasized the ability of models driven by productivity shocks to explain the historically observed paths of macroeconomic variables, a method introduced by Plosser (1989). In a recent paper in the Handbook of Macroeconomics, King and Rebelo (1999) remark on the "dramatic" correspondence between simulations of the US economy produced by the RBC model and the actual data when productivity shocks are "remeasured" and the bare-bones model is augmented with the assumptions of indivisible labor and variable capital utilization. RBC models explain the comovement of a multiplicity of macroeconomic variables consumption, output, labor supply, investment, wages, productivity, etc.--with a single exogenous shock series. In other words, they reduce a more than five-dimensional problem to one dimension of unexplained variation. The contribution of the RBC methodology to the business cycle literature can be thought of in two parts. First, RBC models adopt a basic dynamic stochastic general equilibrium framework that has now become standard in the macroeconomics business cycle literature, including New Keynesian models. Second, the RBC literature emphasizes the importance of the productivity shock. This paper investigates the question of how much of the success of RBC, according to standard RBC evaluation techniques, arises from the basic form of the dynamic stochastic general equilibrium model versus the specific role of the productivity shock. The answer to this question says something both about the nature of the dynamic stochastic general equilibrium models used in macroeconomics as well as about the standard RBC tests used to evaluate these models. The models considered in this paper all have the basic form of the "high-substitution" RBC model developed by King and Rebelo (1999). I consider both the original form of this model, as well as a "Monetary Business Cycle" (MBC) version of the model augmented with a Calvo Phillips curve and a standard Taylor rule specification of monetary policy. I adopt the procedure of "remeasuring" the business cycle shocks to perfectly match the observed output series by King and Rebelo (1999). I consider the models' success at explaining the behavior of macroeconomic variables given a variety of specifications of shocks: productivity shocks, monetary shocks to the Taylor rule, cost-push shocks, and preference shocks. This exercise shows that any of the models with "remeasured" shocks is able to successfully explain the empirical dynamics of the real variables. The monetary model with remeasured shocks is, if anything, more empirically successful than the RBC model, since it is also able to explain the behavior of inflation and the nominal interest rate in the Volcker-Greenspan era. Thus, this paper adds concreteness to work by Hansen and Heckman (1996) and Fair (1992), suggesting that the RBC standards for evaluating models may be too weak by showing that important classes of business cycle models cannot be distinguished using standard RBC evaluation techniques. The MBC models considered in this paper have the same basic structure as the model presented in Rotemberg and Woodford (1997). The most closely related paper to the present work is perhaps the innovative paper by Hairault and Portier (1993), which evaluates the performance of a MBC model when presented with various combinations of estimated monetary and productivity shocks. Unlike the present paper, however, the success of the models is evaluated according to their second moment properties. The paper proceeds as follows. Section II presents the model, which consists of a household sector, a firm sector and a central bank. …