Evaluating point and density forecasts of DSGE models : [Version 13 März 2012]

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

Estimating Monetary Policy Reaction Functions Using Quantile Regressions

Monetary policy rule parameters are usually estimated at the mean of the interest rate distribution conditional on inflation and an output gap. This is an incomplete description of monetary policy reactions when the parameters are not uniform over the conditional distribution of the interest rate. I use quantile regressions to estimate parameters over the whole conditional distribution of the Federal Funds Rate. Inverse quantile regressions are applied to deal with endogeneity. Realtime data of inflation forecasts and the output gap are used. I find significant and systematic variations of parameters over the conditional distribution of the interest rate.monetary policy rules; IV quantile regression; real-time data

The changing dynamics of US inflation persistence : a quantile regression approach : [Version 4 September 2012]

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

Forecasting and policy making

This chapter investigates the use of economic forecasting in policy making. Forecasts are used in many policy areas to project the consequences of particular policy measures for policymakers’ targets. After reviewing some important forecasts of fiscal authorities and central banks, we proceed to focus on the role of forecasts in monetary policy. A formal framework serves to differentiate the role of forecasts in simple feedback rules versus optimal control policies. We then provide empirical evidence that central bank policies in the United States and the euro area are well described by interest rate rules responding to forecasts of inflation and economic activity rather than outcomes. Next, we provide a detailed exposition of methods for producing forecasts and the associated forecasting models. Practical applications with U.S. or euro area data are reported. Particular issues discussed include the use of economic structure in interpreting forecasts and the implementation of different conditioning assumptions regarding future policy that play a role in practice. We also compare the accuracy of model and expert forecasts and measure the degree of forecast heterogeneity. Finally, we utilize macroeconomic models to study the interaction of forecasting and policy by evaluating the performance and robustness of forecast versu

Aufsätze über Konjunkturmodelle, Prognosen und Geldpolitik

This dissertation introduces in chapter 1 a new comparative approach to model-based research and policy analysis by constructing an archive of business cycle models. It includes many well-known models used in academia and at policy institutions. A computational platform is created that allows straightforward comparisons of models’ implications for monetary and fiscal stabilization policies. Chapter 2 applies business cycle models to forecasting. Several New Keynesian models are estimated on historical U.S. data vintages and forecasts are computed for the five most recent recessions. The extent of forecast heterogeneity for models and professional forecasts is analysed. Chapter 3 extends the forecasting analysis to a long sample and to the evaluation of density forecasts. Weighted forecasts are computed using a variety of weighting schemes. The accuracy of forecasts is evaluated and compared to professional forecasts and forecasts from nonstructural time series methods. Chapter 4 adds a new feature to existing business cycle models. Specifically, a medium-scale New Keynesian model is constructed that allows for strategic complementarities in price-setting. The role of trade integration for monetary policy transmission is explored. A new dimension of the exchange rate channel is highlighted by which monetary policy directly impacts domestic inflation. Chapter 5 tests whether simple symmetric monetary policy rules used in most business cycle models are a sufficient description of reality. I use quantile regressions to estimate policy parameters and find asymmetric reactions to inflation, the output gap and past interest rates.In den letzten Jahren sind viele makroökonomische Modelle zur Erkärung der Dynamik wichtiger ökonomischer Variablen entwickelt worden. Dynamische stochastische allgemeine Gleichgewichtsmodelle, die konsequent von mikroökonomischen Optimierungsproblemen privater Haushalte und Unternehmen hergeleitet werden, sind zum Hauptanalyseinstrument der modernen Konjunkturtheorie geworden. Diese Modelle werden nicht nur von Forschern an Universitäten, sondern auch von Ökonomen an Zentralbanken, Ministerien und internationalen Politikorganisationen wie dem internationalen Währungsfonds oder der Europäischen Kommission entwickelt und verwendet. Gäbe es einen breiten Konsenz über ein Referenzmodell, das gegenüber anderen Ansätzen hinsichtlich seiner theoretischen Fundierung und empirischen Validierung zu bevorzugen wäre, so könnte dieses für einheitliche Politikanalysen und -empfehlungen verwendet werden. Bisher ist jedoch kein Konsens hinsichtlich der makroökonomischen Modellierung absehbar. ..

Evaluating point and density forecasts of DSGE models

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.DSGE models; forecasting; model uncertainty; forecast combination; density forecasts; real-time data; Greenbook

Does trade integration alter monetary policy transmission?

This paper explores the role of trade integration—or openness—for monetary policy transmission in a medium-scale New Keynesian model. Allowing for strategic complementarities in price-setting, we highlight a new dimension of the exchange rate channel by which monetary policy directly impacts domestic inflation. Although the strength of this effect increases with economic openness, it also requires that import prices respond to exchange rate changes. In this case domestic producers find it optimal to adjust their prices to exchange rate changes which alter the domestic currency price of their foreign competitors. We pin down key parameters of the model by matching impulse responses obtained from a vector autoregression on U.S. time series relative to an aggregate of industrialized countries. While we find evidence for strong complementarities, exchange rate pass-through is limited. Openness has therefore little bearing on monetary transmission in the estimated model

Evaluating point and density forecasts of DSGE models

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

Estimating Monetary Policy Reaction Functions Using Quantile Regressions

Monetary policy rule parameters are usually estimated at the mean of the interest rate distribution conditional on inflation and an output gap. This is an incomplete description of monetary policy reactions when the parameters are not uniform over the conditional distribution of the interest rate. I use quantile regressions to estimate parameters over the whole conditional distribution of the Federal Funds Rate. Inverse quantile regressions are applied to deal with endogeneity. Realtime data of inflation forecasts and the output gap are used. I find significant and systematic variations of parameters over the conditional distribution of the interest rate

Evaluating point and density forecasts of DSGE models

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