Institute for Monetary and Financial Stability (IMFS)
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Optimal monetary policy studies typically rely on a single structural model and identification of model-specific rules that minimize the unconditional volatilities of inflation and real activity. In their proposed approach, the authors take a large set of structural models and look for the model-robust rules that minimize the volatilities at those frequencies that policymakers are most interested in stabilizing. Compared to the status quo approach, their results suggest that policymakers should be more restrained in their inflation responses when their aim is to stabilize inflation and output growth at specific frequencies. Additional caution is called for due to model uncertainty.
For some time now, structural macroeconomic models used at central banks have been predominantly New Keynesian DSGE models featuring nominal rigidities and forwardlooking decision-making. While these features are widely deemed crucial for policy evaluation exercises, most central banks have added more detailed characterizations of the financial sector to these models following the Great Recession in order to improve their fit to the data and their forecasting performance. We employ a comparative approach to investigate the characteristics of this new generation of New Keynesian DSGE models and document an elevated degree of model uncertainty relative to earlier model generations. Policy transmission is highly heterogeneous across types of financial frictions and monetary policy causes larger effects, on average. The New Keynesian DSGE models we analyze suggest that a simple policy rule robust to model uncertainty involves a weaker response to inflation and the output gap in the presence of financial frictions as compared to earlier generations of such models. Leaning-against-the-wind policies in models of this class estimated for the Euro Area do not lead to substantial gains. With regard to forecasting performance, the inclusion of financial frictions can generate improvements, if conditioned on appropriate data. Looking forward, we argue that model-averaging and embracing alternative modelling paradigms is likely to yield a more robust framework for the conduct of monetary policy.
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.