Institute for Monetary and Financial Stability (IMFS)
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In this paper we investigate the comparative properties of empirically-estimated monetary models of the U.S. economy using a new database of models designed for such investigations. We focus on three representative models due to Christiano, Eichenbaum, Evans (2005), Smets and Wouters (2007) and Taylor (1993a). Although these models differ in terms of structure, estimation method, sample period, and data vintage, we find surprisingly similar economic impacts of unanticipated changes in the federal funds rate. However, optimized monetary policy rules differ across models and lack robustness. Model averaging offers an effective strategy for improving the robustness of policy rules.
In the aftermath of the global financial crisis, the state of macroeconomicmodeling 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 outlines relatively easy to implement reforms for the supervision of transnational banking-groups in the E.U. that should not be primarily based on legal form but on the actual risk structures of the pertinent financial institutions. The proposal also aims at paying close attention to the economics of public administration and international relations in allocating competences among national and supranational supervisory bodies. Before detailing the own proposition, this paper looks into the relationship between sovereign debt and banking crises that drive regulatory reactions to the financial turmoil in the Euro area. These initiatives inter alia affirm effective prudential supervision as a pivotal element of crisis prevention. In order to arrive at a more informed idea, which determinants apart from a perceived appetite for regulatory arbitrage drive banks’ organizational choices, this paper scrutinizes the merits of either a branch or subsidiary structure for the cross-border business of financial institutions. In doing so, it also considers the policy-makers perspective. The analysis shows that no one size fits all organizational structure is available and concludes that banks’ choices should generally not be second-guessed, particularly because they are subject to (some) market discipline. The analysis proceeds with describing and evaluating how competences in prudential supervision are currently allocated among national and supranational supervisory authorities. In order to assess the findings the appraisal adopts insights form the economics of public administration and international relations. It argues that the supervisory architecture has to be more aligned with bureaucrats’ incentives and that inefficient requirements to cooperate and share information should be reduced. Contrary to a widespread perception, shifting responsibility to a supranational authority cannot solve all the problems identified. Resting on these foundations, the last part of this paper finally sketches an alternative solution that dwells on far-reaching mutual recognition of national supervisory regimes and allocates competences in line with supervisors’ incentives and the risk inherent in crossborder banking groups.
Motivated by the U.S. events of the 2000s, we address whether a too low for too long interest rate policy may generate a boom-bust cycle. We simulate anticipated and unanticipated monetary policies in state-of-the-art DSGE models and in a model with bond financing via a shadow banking system, in which the bond spread is calibrated for normal and optimistic times. Our results suggest that the U.S. boom-bust was caused by the combination of (i) too low for too long interest rates, (ii) excessive optimism and (iii) a failure of agents to anticipate the extent of the abnormally favorable conditions.
This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed’s Greenbook projections. Point forecasts of some models are of similar accuracy as the forecasts of nonstructural large dataset methods. Despite their common underlying New Keynesian modeling philosophy, forecasts of different DSGE models turn out to be quite distinct. Weighted forecasts are more precise than forecasts from individual models. The accuracy of a simple average of DSGE model forecasts is comparable to Greenbook projections for medium term horizons. Comparing density forecasts of DSGE models with the actual distribution of observations shows that the models overestimate uncertainty around point forecasts.
In this paper, I introduce lumpy micro-level capital adjustment into a sticky information general equilibrium model. Lumpy adjustment arises because of inattentiveness in capital investment decisions instead of the more common assumption of non-convex adjustment costs. The model features inattentiveness as the only source of stickiness. I find that the model with lumpy investment yields business cycle dynamics which differ substantially from those of an otherwise identical model with frictionless investment and are much more consistent with the empirical evidence. These results therefore strengthen the case in favour of the relevance of microeconomic investment lumpiness for the business cycle.
In the aftermath of the global financial crisis and great recession, many countries face substantial deficits and growing debts. In the United States, federal government outlays as a ratio to GDP rose substantially from about 19.5 percent before the crisis to over 24 percent after the crisis. In this paper we consider a fiscal consolidation strategy that brings the budget to balance by gradually reducing this spending ratio over time to the level that prevailed prior to the crisis. A crucial issue is the impact of such a consolidation strategy on the economy. We use structural macroeconomic models to estimate this impact focussing primarily on a dynamic stochastic general equilibrium model with price and wage rigidities and adjustment costs. We separate out the impact of reductions in government purchases and transfers, and we allow for a reduction in both distortionary taxes and government debt relative to the baseline of no consolidation. According to the model simulations GDP rises in the short run upon announcement and implementation of this fiscal consolidation strategy and remains higher than the baseline in the long run. We explore the role of the mix of expenditure cuts and tax reductions as well as gradualism in achieving this policy outcome. Finally, we conduct sensitivity studies regarding the type of model used and its parameterization.
The complexity resulting from intertwined uncertainties regarding model misspecification and mismeasurement of the state of the economy defines the monetary policy landscape. Using the euro area as laboratory this paper explores the design of robust policy guides aiming to maintain stability in the economy while recognizing this complexity. We document substantial output gap mismeasurement and make use of a new model data base to capture the evolution of model specification. A simple interest rate rule is employed to interpret ECB policy since 1999. An evaluation of alternative policy rules across 11 models of the euro area confirms the fragility of policy analysis optimized for any specific model and shows the merits of model averaging in policy design. Interestingly, a simple difference rule with the same coefficients on inflation and output growth as the one used to interpret ECB policy is quite robust as long as it responds to current outcomes of these variables.
We examine both the degree and the structural stability of inflation persis tence at different quantiles of the conditional inflation distribution. Previous research focused exclusively on persistence at the conditional mean of the inflation rate. Economic theory, however, provides various reasons -for example downward wage rigidities or menu costs- to expect higher inflation persistence at the upper than at the lower tail of the conditional inflation distribution.
Based on post-war US data we indeed find slower mean reversion in response to positive than to negative shocks. We find robust evidence for a structural break in persistence at all quantiles of the inflation process in the early 1980s. Inflation persistence has decreased and become more homogeneous across quantiles. Persistence at the conditional mean became more informative about the degree of persistence across the entire conditional inflation distribution. While prior to the 1980s inflation was not mean reverting in response to large positive shocks, our evidence strongly suggests that since the end of the Volcker disinflation the unit root can be rejected at every quantile including the upper tail of the conditional inflation distribution.