Alok Johri

Dynamic complementarities: A quantitative analysis

This paper considers the importance of dynamic complementarities as an endogenous source of propagation in a dynamic stochastic economy. Dynamic complementarities link the stocks of human and organizational capital, which are influenced by past levels of economic activity, to current levels of productivity. We supplement an otherwise standard dynamic business cycle model with both contemporaneous and dynamic complementarities. The model is calibrated using estimates of these effects. Our quantitative analysis identifies empirically relevant dynamic complementarities as a source of propagation for both technology and taste shocks.

Persistent real exchange rates

This paper revisits three features of the data that are widely known: (a) there exists a high correlation between bilateral nominal and real exchange rates; (b) real exchange rate movements are highly persistent; and (c) real exchange rates are highly volatile. The paper attempts a joint, albeit partial, rationalization of these facts in an environment where prices are preset for only one quarter and there are no staggered contracts. The key innovation is that we augment a standard two-country open economy model with learning-by-doing in production at the firm level. This induces monopolistically competitive firms to endogeneize the productivity effect of their price setting behavior. Specifically, firms endogenously choose not to adjust prices by the full proportion of a positive monetary shock in order to take advantage of the productivity benefits of higher production. We show that the calibrated model can quantitatively reproduce significant fractions of the aforementioned facts.

Search, Money, and Prices

It is well known that models in which money is used as a medium of exchange to lubricate trading, frictions display multiplicity of equilibria. I show that the amount of activity varies as the value of money differs across these equilibria when production opportunities involve random fixed costs. When money has high value, trade is more profitable; therefore, there will be more agents engaged in trade relative to equilibria in which money has lower value. The higher-activity equilibria display higher production not only because more is produced and exchanged per transaction but also because more transactions occur per period. This Diamond-style result is obtained without increasing returns in the matching technology. Copyright 1999 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

PROCYCLICAL SOLOW RESIDUALS WITHOUT TECHNOLOGY SHOCKS

Most Real Business Cycle models have a hard time jointly explaining the twin facts of strongly pro-cyclical Solow residuals and extremely low correlations between wages and hours. We present a model that delivers both these results without using exogenous variation in total factor productivity (technology shocks). The key innovation of the paper is to add learning-by-doing to firms technology. As a result firms optimally vary their prices to control the amount of learning which in turn influences future productivity. We show that exogenous variation in labour wedges (preference shocks) measured from aggregate data deliver around fifty percent of the standard deviation in the efficiency wedge (Solow residual) as well as realistic second moments for key aggregate variables which is in sharp contrast to the model without learning-by-doing.

Markups and the seasonal cycle

Monthly, non-seasonally adjusted data are used to study markup behavior at the seasonal and business cycle frequency. The shift in focus to the monthly frequency provides an identification mechanism which helps to rule out several competing models for markup variation that would have been plausible at lower frequencies. Considerable support for collusive pricing is found by examining the monthly behavior of markups in 2-digit U.S. manufacturing industries. In particular, the hypothesis that given current demand, markups should increase when demand is expected to increase in the future is confirmed by the data.

Learning Efficiency Shocks, Knowledge Capital and the Business Cycle: A Bayesian Evaluation

We incorporate shocks to the efficiency with which firms learn from production activity and accumulate knowledge into an otherwise standard real DSGE model with imperfect competition. Using real aggregate data and Bayesian inference techniques, we find that learning efficiency shocks are an important source of observed variation in the growth rate of aggregate output, investment, consumption and especially hours worked in post-war US data. The estimated shock processes suggest much less exogenous variation in preferences and total factor productivity are needed by our model to account for the joint dynamics of consumption and hours. This occurs because learning efficiency shocks induce shifts in labour demand uncorrelated with current TFP, a role usually played by preference shocks. At the same time, knowledge capital acts like an endogenous source of productivity variation in the model. Measures of model fit prefer the specification with learning efficiency shocks.