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We document that the durable goods sector is much more interest-sensitive than the nondurables sector, and then investigate the implications of these sectoral differences for monetary policy. We formulate a two-sector general equilibrium model that is calibrated both to match the sectoral responses to a monetary shock derived from our empirical VAR and to imply an empirically realistic degree of sectoral output volatility and comovement. While the social welfare function involves sector-specific output gaps and inflation rates, the performance of the optimal policy rule can be closely approximated by a simple rule that targets a weighted average of aggregate wage and price inflation. In contrast, a rule that stabilizes a more narrow measure of final goods price inflation performs poorly in terms of social welfare.

In past decades, macroeconomists were acutely aware of the extent to which monetary policy can have disparate effects across the various sectors of the economy.1 Such differences were particularly evident during the U.S. disinflationary episode of 1981–1982, when high real interest rates induced dramatic declines in auto sales and residential construction. Nevertheless, recent empirical research has mainly focused on the aggregate effects of monetary policy shocks, while normative studies of policy rules have typically utilized models consisting of a single productive sector.2 The objective of this paper is to assess the implications of sectoral heterogeneity for the design of welfare-maximizing monetary policy rules. As a prelude to the normative analysis, we document that the durable consumption goods sector is much more interest-sensitive than the rest of the economy. In particular, we perform vector autoregression (VAR) analysis of quarterly U.S. national accounts data, disaggregated into spending and prices for our broad measure of consumer durables (which includes residential investment) and for all other items. Using fairly standard identifying assumptions, we find that a monetary policy innovation has a peak impact on consumer durables spending that is several times larger than the impact on other expenditures. We proceed to formulate a dynamic general equilibrium model with two sectors that produce durable and nondurable consumption goods, respectively. The model incorporates nominal inertia in the form of fixed-duration staggered wage and price contracts in each sector. The structural parameters are calibrated so that the each sector's output response to a monetary innovation roughly matches the VAR impulse response functions. Using estimated time-series processes for each sector's total factor productivity and for government spending, the model also exhibits an empirically realistic degree of sectoral output volatility and comovement. Following the seminal analysis of Rotemberg and Woodford (1997), we obtain a quadratic approximation to the social welfare function, and show that the deviation of welfare from its Pareto-optimal level depends on the variances of sectoral output gaps and on the cross-sectional dispersion of wages and prices in each sector. Finally, we characterize the properties of the optimal policy under commitment, and compare its performance with simple rules that respond only to aggregate variables. In this setting, sectoral heterogeneity presents a clear challenge to monetary policy: with only a single instrument, the central bank cannot simultaneously stabilize the output gaps of both sectors. We show that the optimal policy places a disproportionately large weight on the durables sector (that is, relative to its small share in the economy); nevertheless, the cross-sectional dispersion of wages and prices and the volatility of the output gap in the durables sector are several times higher than in the nondurables sector and account for a relatively large fraction of welfare deviations from the Pareto-optimal level. In evaluating the performance of simple monetary policy rules, we find that strict price inflation targeting induces relatively high volatility in sectoral output gaps—especially in the durables sector—and hence performs very poorly in terms of social welfare. Given that the welfare function involves sector-specific variables, one might expect to obtain relatively poor welfare outcomes from any rule that responds solely to aggregate variables. In fact, however, we find that the optimal policy is closely approximated by a simple rule that targets an appropriately-weighted average of aggregate price and wage inflation; this rule may be viewed as a generalized form of inflation targeting in which the underlying basket includes an index of labor costs (Erceg et al., 2000 and Mankiw and Reis, 2003). The remainder of this paper is organized as follows: Section 2 presents empirical evidence on sectoral responses to monetary policy shocks. Section 3 outlines the dynamic general equilibrium model, and Section 4 describes the solution method and parameter calibration. Section 5 discusses the second-order approximation to the welfare function. Section 6 examines characteristics of the optimal policy, and evaluates the performance of alternative policy rules. Section 7 concludes.

Our analysis indicates that it may not be necessary for a well-designed monetary policy rule to respond to sector-specific variables, even if social welfare depends explicitly upon them. In particular, while it seems clear that aggressive stabilization of final goods prices is undesirable, our results suggest that a somewhat broader concept of inflation-targeting in which the underlying basket is composed of an index of both final goods prices and aggregate labor costs may perform well. With the appropriately chosen weights on aggregate price and wage inflation, such a policy comes close to stabilizing aggregate output at potential. Furthermore, given the estimated distribution of shocks, the level of sectoral output dispersion is reasonably close to that implied by the optimal full-commitment rule. Such a rule is clearly easier to implement and convey to market participants than the full-commitment rule. Moreover, while it achieves a similar outcome as a rule that directly targets the (true) aggregate output gap, it does not require direct knowledge of the level of potential output. Our finding that simple aggregate rules can perform well may seem surprising given that certain features of our model framework—including the inability of resources to move across sectors—would appear to favor a rule involving sector-specific variables. In future research, it will be desirable to explore this further by allowing for intersectoral factor mobility subject to adjustment costs, and also by incorporating other empirically realistic dynamic complications (such as endogenous capital accumulation by firms). Finally, it will be interesting to consider the implications of alternative shocks, including shocks that arise in an open-economy setting.