THE OPTIMAL MONETARY RESPONSE TO TECHNOLOGY SHOCKS

I. INTRODUCTION During the past decade, many economists adopted the view that shocks to the aggregate production function, or technology shocks, represent the dominant source of fluctuations in the United States economy. As noted by Shapiro [1987], a number of elements came together to shape this view. Most important, a series of severe supply shocks hit the economy during the 1970s; standard Keynesian models, with their emphasis on the demand side, had great difficulty tracking the economy's response to these shocks. The view solidified after Kydland and Prescott [1982] demonstrated that many features of the business cycle can be replicated in a model where technology shocks are the only source of fluctuations. Kydland and Prescott's work launched the now extensive literature on real business cycles, surveyed by McCallum [1989]. The observation that supply-side disturbances are important in generating business cycles, however, need not imply that monetary factors play no role in accounting for variations in economic activity. Greenwood and Huffman [1987] and Cooley and Hansen [1989] add cash-in-advance constraints to otherwise standard real business cycle models as a simple way of including the nominal sector. In these cash-in-advance models, monetary shocks have little effect on the cyclical behavior of real variables; these models preserve the emphasis on technology shocks in explaining the business cycle. Nevertheless, the models show how sustained inflation can affect the real economy by acting as a distortionary tax on productive activity. The models of Greenwood and Huffman and Cooley and Hansen imply that optimal monetary policy involves a steady contraction of the money supply that keeps the nominal interest rate at zero, as called for by Friedman [1969]. This optimal policy makes no attempt to respond to technology shocks. Instead, it simply removes the distortionary inflation tax. More recently, Cho and Cooley [1992], Yun [1994a], and Dow [1995] have investigated the effects of introducing various forms of price rigidity into monetary versions of the real business cycle model. Technology shocks continue to play a major role in these studies, but the presence of nominal rigidities allows monetary shocks to affect the business cycle as well. In fact, these studies show that the addition of price rigidity improves the model's ability to match the cyclical properties of the data. This paper complements these studies by deriving the implications of nominal price rigidity for optimal monetary policy. I begin by outlining a model that shares the basic features of those cited above, including technology shocks, a cash-in-advance constraint, and nominal price rigidity. In the model, both technology and monetary shocks have important effects on aggregate output and employment. Unlike flexible-price cash-in-advance models, for instance, the model developed here gives rise to a Phillips curve relationship between money and output. The model is used to answer the following question: Does the presence of nominal price rigidity rationalize a monetary policy that responds actively to technology shocks, or does the optimality of Friedman's constant money growth rule still apply? The results show that optimal policy does, in fact, exploit the monetary authority's ability to influence the real economy when prices are sticky. That is, the optimal policy is activist. On the other hand, the results also show that the Friedman rule, while no longer optimal, comes very close to the optimum in welfare terms. In this sense, the main policy implication of flexible-price cash-in-advance models appears robust to the introduction of nominal price rigidity. Section II presents the model; section III describes the key features of its equilibrium. Section IV derives the optimal activist policy and compares its performance to that of the Friedman rule. Section V concludes. II. THE MODEL The Economic Environment Infinitely lived households, firms, and a monetary authority populate an economy where time periods are indexed by t = 0,1,2,. …