Research
Publications
Long-Term Inflation Expectations and the Transmission of Monetary Policy Shocks: Evidence from a SVAR Analysis
with Dieter Nautz (Journal of Economic Dynamics and Control)
download: accepted manuscript, journal version, replication files
Abstract: This paper investigates the role of long-ter m inflation expectations for the monetary transmission mechanism and the conduct of monetary policy in a structural VAR framework. In contrast to earlier studies, we find that U.S. long-term inflation expectations respond significantly to a monetary policy shock. In line with a re-anchoring channel of monetary policy, long-term inflation expectations play an important role for the transmission of monetary policy shocks to the rate of inflation. Structural scenario analysis suggests that the response of monetary policy to expectations shocks contributes to the stabilization of inflation and unemployment.
Presented at:
2021 Freie Universität (FU) Seminar "Empirical Macroeconomics" (online)
2020 Seminar "Topics in Time Series Analysis" (Oberbarnim); DIW Berlin Graduate Center Winterworkshop (online)
Working Papers
Time-varying Credibility, Anchoring and the Fed’s Inflation Target
download: FU Discussion Paper version, current draft at SSRN
Abstract: This paper analyzes the time-varying credibility of the Fed’s inflation target in an empirical macro model with asymmetric information, where the public has to learn about the actual inflation target from the Fed’s interest rate policy. To capture the evolving communication strategy of the Fed, I allow the learning rule and the structural shock variances to change across monetary policy regimes. I find that imperfect credibility is pronounced during the Volcker Disinflation and to a lesser extend in the aftermath of the 2008 Financial Crisis. The announcement of the 2% target in 2012 did not affect the learning rule strongly but reduced the variance of transitory monetary policy shocks. The results caution against equating long-term inflation expectations of professionals with the perceived inflation target.
Presented at:
2022 23rd IWH-CIREQ-GW Macroeconometric Workshop: Inflation: Modelling, Forecasting and Monetary Policy Reactions
2021 IAAE Annual Conference (online); Seminar "Topics in Time Series Analysis" (Oberbarnim); EEA Annual Conference (online)
2020 FU Berlin Seminar "Empirical Macroeconomics"
2019 13th RCEA Bayesian Workshop (Larnaca); Seminar "Topics in Time Series Analysis" (Oberbarnim); DIW Berlin Graduate Center Summerworkshop (Potsdam)
Unveiling Common Factors in Time-Varying Volatilities of VARs: A Data-Driven Approach with Applications to Macroeconomic Data
available at SSRN submitted at the Journal of Applied Econometrics
Abstract: This paper presents a new approach for modeling common factors in time-varying volatilities within Vector Autoregressions (VARs). The model uses Savage-Dickey density ratios to determine the number of factors from data and enables an economic interpretation of factors via checking exclusion restrictions. The model performs well in recovering volatility structures in simulation experiments. I then apply it to re-evaluate volatility drivers of US long- and short-term inflation expectations, as well as to a medium-sized VAR of 20 US macroeconomic and financial variables. In both applications, the model effectively captures the volatility patterns with remarkable parsimony, relying on only a few common factors.
Presented at:
2023 IAAE Annual Conference (Oslo); FU Berlin Seminar "Topics in Time Series Analysis" (Oberbarnim);
Work in Progress
Sequential Detector Statistics for Speculative Bubbles
joint with Jörg Breitung
Abstract: We propose a heteroskedatsiticy-robust LBI statistic to test the hypothesis of a unit root against the alternative of an explosive root, commonly referred to as a speculative bubble. Compared to existing alternatives like Dickey-Fuller type tests, the proposed LBI test has a standard limiting distribution and higher power especially in the empirically relevant case of a ``mildly" explosive root. By calibrating the test to a specific value under the alternative, the power of the test can be further improved and comes remarkably close to the power of the point optimal test. To detect bubbles in practice, we propose a sequential scheme based on a rolling window. We demonstrate the usefulness of the new procedure in simulations and applications to financial market data.
Nowcasting German GDP in Real Time
joint with Jörg Breitung and Luis Winter
Abstract: Timely and accurate information on Gross Domestic Product (GDP) is of paramount importance in economic analysis, particularly due to the lag in its official publication. In this paper, we construct GDP nowcasts in real time by leveraging the release schedule of a rich dataset of over 50 monthly economic indicators, including classical, sentiment-based, and unconventional metrics like the German toll index. We compare the nowcasting performance Factor models, Large Bayesian Vector Autoregressions (VARs), the Bayesian Lasso, and a dynamic version of the Chow-Lin method in a unifying Bayesian mixed-frequency state-space framework. To the best of our knowledge, this is the first thorough comparison of these models for German GDP nowcasting. Furthermore, we generate a monthly series of German GDP and plan to automate the procedure for frequent updates and nowcasts in the future, accessible via a dedicated website.
The Short and Long of Euro Area Survey Inflation Expectations: A Factor Model Approach
joint with Aidan Meyler
Abstract: We explore two different factor model approaches for summarizing the information content of Euro Area (EA) inflation expectations from various surveys. The data set consists of 149 series of EA inflation expectations of different horizons and from different economic (e.g. professional forecasters, households, firms). The first approach uses all available information in a dynamic factor model and the second approach uses a Nelson-Siegel style term-structure factor model for a smaller set of expectations with exact forecasting horizons. Both models are estimated in a Bayesian framework, allowing for missing observations. While the first approach yields superior forecasts of actual inflation at short horizons, the term-structure model outperforms popular benchmark at medium horizons of up to 8 quarters ahead.
Identifying The Government Spending Multiplier with Elasticity Bound Restrictions
joint with Emanuel Gasteiger
Abstract: We show that information in the form of an bound restriction on the output elasticity of government spending can identify the government spending multiplier (GSM) together with uncontroversial sign restrictions. In contrast, a sign restriction on the output elasticity of spending is generally not enough. Information on the elasticity bound could come from narrative evidence, cross-sectional estimations or from benchmarks in the literature. In an illustrative application to US data, we derive a bound restriction (that includes zero) from a large set of proxies for non-fiscal shocks from the literature. Imposing the restriction in a otherwise sign-restricted VAR sharpens inference about the GSM considerably. On impact the GSM is not different from unity.