30 Jounal of Economic Perspectives fact 4: Fixed business investment eventually declines in response to a monetary tightening, but its fall lags behind those of housing and consumer durables and, ndeed, behind much of the decline in production and interest rates Responses to Policy Shocks: Evidence from Vector Autoregressions These four facts are illustrated by Figures 1-3, which show the dynamic re- sponses of various economic aggregates to an unanticipated tightening of monetar policy. Figures 1-3 are generated by the technique of"vector autoregression. A vector autoregression, or VAR, is a system of ordinary least-squares regressions, in which each of a set of variables is regressed on lagged values of both itself and th other variables in the set. VARs have proved to be a convenient method of sum- marizing the dynamic relationships among variables, since, once estimated, they can be used to simulate the response over time of any variable in the set to either an"own"disturbance(that is, a disturbance to the equation for which the variable is the dependent variable) or a disturbance to any other variable in the system The VARs that we employ here include various combinations of macroeconomic variables and, additionally, the federal funds interest rate. Following Bernanke and Blinder(1992), Christiano, Eichenbaum and Evans(1994a, b)and others, we em- ploy the federal funds rate as an indicator of the stance of monetary policy; this means that we identify the disturbances to the funds-rate equation in the vaR as shocks to monetary policy, and we interpret the responses of other variables in the system to a funds-rate shock as the structural responses of those variables to an unanticipated change in monetary policy. Because we are interested in observing ine timing of responses to monetary shocks, we use monthly data. The sample period on which Figures 1-3 are based is January 1965 through December 1993 (subsample results are similar) GDP"igure l is based on a VAR system that includes the log of real GDP, the log of the deflator, the log of an index of commodity prices and the federal funds rate(in ercentage points), in that order. Real GDP and the gDp deflator are included as broad sures of economic activity and prices, and the commodity price index is intended to control for oil price shocks and other supply-side factors influencing output and The use of VARs in macroeconomics was pioneered by Sims(1980); for a comprehensive recent di cussion, see Watson(1994) "Bernanke and Blinder(1992)argue that the Fed has often used the funds rate which is the interest te prevailing in the market for bank reserves, as its primary policy indicator(particularly before 1979) Bernanke and Mihov(1995)estimate a model of the Feds operating procedures and find that funds. te targeting describes Fed behavior particularly well prior to 1979 and from 1988 to the present. In the results discussed here are not dependent on using the funds rate as the monetary policy indicator; similar results are obtained when using reserves-based indicators(see, for example, Strongin 1992)or indicators developed through historical analysis(for example, Romer and Romer, 1989) t We constructed monthly data for real GDP and the GDP deflator by interpolation methods, using a f monthly series to provide the within-quarter information. Bernanke and Mihov( 1995)offer Results using noninterpolated monthly output and price data-for example, the industrial pr index and the CPI (excluding shelter)-yield very similar results. Twelve lags of each variable onstant term are included in each equation of the VAR.30 Journal of Economic Perspectives Fact 4: Fixed business investment eventually declines in response to a monetary tightening, but its fall lags behind those of housing and consumer durables and, indeed, behind much of the decline in production and interest rates. Responses to Policy Shocks: Evidence from Vector Autoregressions These four facts are illustrated by Figures 1-3, which show the dynamic re￾sponses of various economic aggregates to an unanticipated tightening of monetary policy. Figures 1-3 are generated by the technique of "vector autoregression." A vector autoregression, or VAR, is a system of ordinary least-squares regressions, in which each of a set of variables is regressed on lagged values of both itself and the other variables in the set. VARs have proved to be a convenient method of sum￾marizing the dynamic relationships among variables, since, once estimated, they can be used to simulate the response over time of any variable in the set to either an "own" disturbance (that is, a disturbance to the equation for which the variable is the dependent variable) or a disturbance to any other variable in the system.4 The VARs that we employ here include various combinations of macroeconomic variables and, additionally, the federal funds interest rate. Following Bernanke and Blinder (1992), Christiano, Eichenbaum and Evans (1994a,b) and others, we em￾ploy the federal funds rate as an indicator of the stance of monetary policy; this means that we identify the disturbances to the funds-rate equation in the VAR as shocks to monetary policy, and we interpret the responses of other variables in the system to a funds-rate shock as the structural responses of those variables to an unanticipated change in monetary policy.5 Because we are interested in observing the fine timing of responses to monetary shocks, we use monthly data. The sample period on which Figures 1-3 are based is January 1965 through December 1993 (subsample results are similar). Figure 1 is based on a VAR system that includes the log of real GDP, the log of the GDP deflator, the log of an index of commodity prices and the federal funds rate (in percentage points), in that order. Real GDP and the GDP deflator are included as broad measures of economic activity and prices,6 and the commodity price index is intended to control for oil price shocks and other supply-side factors influencing output and 'The use of VARs in macroeconomics was pioneered by Sims (1980); for a comprehensive recent dis￾cussion, see Watson (1994). 5Bernanke and Blinder (1992) argue that the Fed has often used the funds rate, which is the interest rate prevailing in the market for bank reserves, as its primary policy indicator (particularly before 1979). Bernanke and Mihov (1995) estimate a model of the Fed's operating procedures and find that funds￾rate targeting describes Fed behavior particularly well prior to 1979 and from 1988 to the present. In any case, the results discussed here are not dependent on using the funds rate as the monetary policy indicator; similar results are obtained when using reserves-based indicators (see, for example, Strongin, 1992) or indicators developed through historical analysis (for example, Romer and Romer, 1989). 6 We constructed monthly data for real GDP and the GDP deflator by interpolation methods, using a variety of monthly series to provide the within-quarter information. Bernanke and Mihov (1995) offer details. Results using noninterpolated monthly output and price data-for example, the industrial pro￾duction index and the CPI (excluding shelter) -yield very similar results. Twelve lags of each variable and a constant term are included in each equation of the VAR