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This note argues that in a situation of an inelastic natural gas supply a restrictive monetary policy in the euro zone could reduce the energy bill and therefore has additional merits. A more hawkish monetary policy may be able to indirectly use monopsony power on the gas market. The welfare benefits of such a policy are diluted to the extent that some of the supply (approximately 10 percent) comes from within the euro zone, which may give rise to distributional concerns.
Inflation-targeting central banks have only imperfect knowledge about the effect of policy decisions on inflation. An important source of uncertainty is the relationship between inflation and unemployment. This paper studies the optimal monetary policy in the presence of uncertainty about the natural unemployment rate, the short-run inflation-unemployment tradeoff and the degree of inflation persistence in a simple macroeconomic model, which incorporates rational learning by the central bank as well as private sector agents. Two conflicting motives drive the optimal policy. In the static version of the model, uncertainty provides a motive for the policymaker to move more cautiously than she would if she knew the true parameters. In the dynamic version, uncertainty also motivates an element of experimentation in policy. I find that the optimal policy that balances the cautionary and activist motives typically exhibits gradualism, that is, it still remains less aggressive than a policy that disregards parameter uncertainty. Exceptions occur when uncertainty is very high and in inflation close to target.
The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.
In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development.
This paper considers the desirability of the observed tendency of central banks to adjust interest rates only gradually in response to changes in economic conditions. It shows, in the context of a simple model of optimizing private-sector behavior, that such inertial behavior on the part of the central bank may indeed be optimal, in the sense of minimizing a loss function that penalizes inflation variations, deviations of output from potential, and interest-rate variability. Sluggish adjustment characterizes an optimal policy commitment, even though no such inertia would be present in the case of a reputationless (Markovian) equilibrium under discretion. Optimal interest-rate feedback rules are also characterized, and shown to involve substantial positive coefficients on lagged interest rates. This provides a theoretical explanation for the numerical results obtained by Rotemberg and Woodford (1998) in their quantitative model of the U.S. economy.