Johannes Beutel

Principal Economist at Deutsche Bundesbank. Research on asset pricing, expectations, household finance, climate finance

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Publications

Stock Price Booms and Expected Capital Gains

with Klaus Adam and Albert Marcet 

American Economic Review, 2017, 107( 8):2352-2408

Working Paper, Code and Data

Presentations: Columbia University, University College London, London School of Economics, Yale University, Harvard University, Northwestern University, Stony Brook, IMF, University of Chicago, New York University, London Business School, Banque de France and Chicago Fed Conference on Asset Price Bubbles, 2017 AEA Meetings

Policy Coverage: Bubbles Tomorrow, Yesterday, but Never Today? (John C. Williams), Financial Stability and Monetary Policy: Happy Marriage or Untenable Union? (John C. Williams) 

Investors’ subjective capital gains expectations are a key element explaining stock price fluctuations.  Survey measures of these expectations display excessive optimism (pessimism) at market peaks (troughs). We formally reject the hypothesis that this is compatible with rational expectations. We incorporate subjective price beliefs with such properties into a standard asset-pricing model with rational agents (internal rationality). The model gives rise to boom-bust cycles that temporarily delink stock prices from fundamentals. It quantitatively replicates many asset-pricing moments, including the observed strong positive correlation between the price dividend ratio and survey return expectations, which cannot be matched by rational expectations. 

Can a Financial Transaction Tax Prevent Stock Price Booms? 

with Klaus Adam, Albert Marcet and Sebastian Merkel

Journal of Monetary Economics, 2015, 76:S90-S109

Working Paper

Presentations: JME Gerzensee Conference 2014, Deutsche Bundesbank, European Central Bank, CSEF-CIM-UCL Conference 2015, Barcelona Summer Forum on Finance and Macroeconomics 2015, Expectations in Dynamic Macroeconomic Models Conference 2015

Policy Coverage: Financial Literacy and Financial Stability (Claudia Buch) 

We present a stock market model that quantitatively replicates the joint behavior of stock prices, trading volume and investor expectations. Stock prices in the model occasionally display belief-driven boom and bust cycles that delink asset prices from fundamentals and redistribute considerable amounts of wealth from less to more experienced investors. Although gains from trade arise only from subjective belief differences, introducing financial transactions taxes (FTTs) remains undesirable. While FTTs reduce the size and length of boom-bust cycles, they increase the likelihood of such cycles, thereby overall return volatility and wealth redistribution. Contingent FTTs, which are levied only above a certain price threshold, give rise to problems of equilibrium multiplicity and non-existence.

Toothless Tiger With Claws? Financial Stability Communication, Expectations, and Risk-taking 

with Norbert Metiu and Valentin Stockerl

Journal of Monetary Economics2021, 120:53-69

Preprint, Working PaperOnline Appendix 

We study the effects of central bank communication about financial stability on individuals’ expectations and risk-taking. Using a randomized information experiment, we show that communication causally affects individuals’ beliefs and investment behavior, consistent with an expectations channel of financial stability communication. Individuals receiving a warning from the central bank expect a higher probability of a financial crisis and reduce their demand for risky assets. This reduction is driven by downward revisions in individuals’ expected Sharpe ratios due to lower expected returns and higher perceived downside risks. In addition, these individuals deposit a smaller fraction of their savings at riskier banks.

Does Machine Learning Help us Predict Banking Crises? 

with Sophia List and Gregor von Schweinitz

Journal of Financial Stability, 2019,  45:100693

Working Paper, Code

Policy Coverage: Deutsche Bundesbank Financial Stability Review 2017, 2018, 2019, 2021, 2022, German Financial Stability Committee 2018     

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.

Working Papers

with Shifrah Aron-Dine, Monika Piazzesi, and Martin Schneider

Link to NBER DP.  Most recent version by clicking on title. Submitted.

Presentations: Harvard Business School, Wharton Business School, Stanford University,  European Central Bank, University of Chicago Capstone Conference 22, Joint BoC-ECB-New York Fed Conference on Expectations Surveys 22, Bundesbank Spring Conference 23, FRBSF Climate Economics Virtual, International Conference on Household Finance 23, Amsterdam Macro Workshop 23, FIRS 2024

This paper studies green investing in a quantitative asset pricing model with heterogeneous investors calibrated using high-quality, representative survey data of German households. We find substantial heterogeneity in green taste for both safe and risky green assets throughout the wealth distribution. Model counterfactuals show nonpecuniary benefits and hedging demands currently make green equity more expensive for firms. Yet, these taste effects are dominated by optimistic expectations about green equity returns, lowering firms' cost of green equity to a greenium of 1%. Looking ahead, we use our model to trace out the aggregate effects of information provision in an RCT and find green equity investment could potentially double when information about green finance spreads across the population. Regarding safe green assets, our model counterfactuals show that if green deposits could be offered at a 50 basis point interest rate spread, aggregate green investments in the economy could quadruple in the medium run.

with Michael Weber

Revise and Resubmit at the Journal of Finance. 

Chicago Booth Research Paper No. 22-08. Latest Version by clicking on title (UPDATED: September 2024). 

Presentations: Harvard Business School, University of Oxford,  UC Berkeley, Washington University St. Louis, Deutsche Bundesbank,  Federal Reserve Bank of San Francisco,  ECB-FRBNY Conference on Survey Expectations 2021, ifo Conference on Macroeconomics and Survey Data 2022, UBC Winter Finance Conference 2022, UKY Finance Conference 2022, CEPR Workshop on Household Finance 2022,  FIRS 2022,  CEBRA 2022,  SAFE Asset Pricing Workshop 2022,  AFA 2023

We causally test alternative theories of expectation formation and asset pricing. Using a randomized information experiment we show overreaction is a key feature of individuals' belief formation. Individuals excessively extrapolate past returns and earnings growth into future returns. The average response to the price-earnings ratio is opposite to the academic consensus and individuals' reaction to stock market news depends on their perceived importance. Conditional on their beliefs, individuals' sensitivity of risky portfolio shares is consistent with the standard Merton model of portfolio choice. Our evidence suggests belief overreaction and heterogeneous subjective mental models as key ingredients to asset pricing models. 

with Valentin Stockerl

NEW VERSION JULY 2024. 

Presentations: FRBNY-BoC-ECB Conference on Survey Expectations 23, Uni Bonn 24

We provide the first large-scale survey-based evidence on tail risk beliefs. Inconsistent with a static form of tail risk neglect, individuals assign large probabilities to tail events such as a financial crisis, a new pandemic, a China-Taiwan conflict, a severe energy crisis, or a Cyber attack with systemic consequences. They expect large GDP declines and substantial stock market declines, conditional on these events. However, our evidence supports dynamic tail risk neglect, as predicted by diagnostic beliefs. Extrapolation in response to news is a causal mechanism, that is able to generate pro-cyclical tail beliefs, i.e. lower perceived tail risk during booms. Moreover, individuals who view the boom state as representative, underreact to bad news. Tail risk beliefs causally affect individuals' inclination to invest into housing, equity, or precious metals. The direction of the effect depends on the type of tail event, hence tail risk is not one-dimensional, and safe haven assets are event-specific. We construct novel measures of individuals’ memory database and show they are linked to individuals’ downside tail beliefs. Our results suggest memory as a micro-foundation for diagnostic beliefs as a fruitful avenue for modeling tail beliefs and their financial implications. 

with Ehsan Azarmsa

NEW VERSION November 2024. (SSRN DP)

Presentations: Oxford-CEPR Central Bank Communication RPN Workshop 2024, Research in Behavioral Finance Conference at VU Amsterdam 2024

Behavioral biases in investors' expectations can lead to a decoupling of asset prices from fundamentals, raising the possibility of financial instability. Central bank communication could be a tool to mitigate these issues, but there is no theoretical guidance on how and when  to communicate  when some investors do not form expectations rationally. We develop a communication model that flexibly accounts for such deviations from rationality and allows for heterogeneity in investors' belief formation. We find that in the presence of these heterogeneities, communication may hinder risk-sharing  and lead to over- or under-production of risky assets.  Full disclosure is optimal only when investors update their beliefs in a way that is sufficiently homogeneous and close to the rational benchmark. Otherwise, no disclosure is optimal. Our results further suggest that it is more effective to communicate during normal periods, before investors' beliefs become too entrenched. We also discuss the effectiveness of communication relative to other policy tools, such as interest rate and macroprudential policies.

The Global Financial Cycle and Macroeconomic Tail Risks

with Lorenz Emter, Norbert Metiu, Esteban Prieto and Yves Schüler.

REVISED VERSION December 2023 (submitted)

Presentations: European Central Bank, Deutsche Bundesbank, Central Bank of Ireland, Trinity College Dublin, 4th ESCB Research Cluster 3 Workshop, EEA 2020

Media Coverage: Financial Times Article "How to Powell-proof your economy, per the Bundesbank"

Policy Coverage: Deutsche Bundesbank Monthly Report (July 2021) 

We study the link between the global financial cycle and macroeconomic tail risks using quantile vector autoregressions. Contractionary shocks to financial conditions and monetary policy in the United States cause elevated downside risks to growth around the world. By tightening financial conditions globally, these shocks affect the left tail of the conditional output growth distribution more strongly than the center of the distribution. This effect is particularly pronounced for countries with less flexible exchange rate arrangements, higher foreign currency exposures, and higher levels of private sector leverage, suggesting that exchange rate policies and macroprudential policies can mitigate downside risks to growth.

Social Distancing and the Macrofinancial Consequences of Natural Disasters

with Friederike Fourné and Norbert Metiu

SSRN Discussion Paper, 2021 (currently under revision)

We use the Covid-19 pandemic as a natural experiment to estimate the effects of a global disaster shock on economic activity, international trade, and financial markets. To identify the shock, we exploit cross-country variation in the timing and intensity of pandemic-induced social distancing at daily frequency. An unexpected reduction in human mobility relative to pre-pandemic levels leads to significant declines in high-frequency measures of global economic activity, such as daily nitrogen dioxide concentrations and daily maritime trade carried by large cargo ships. Global stock markets decline, and sovereign credit spreads persistently widen after the pandemic disaster shock.

Discussions

Dynamics of Subjective Risk Premia 

(by Stefan Nagel and Zhengyang Xu)

European Finance Association Meeting, August 2022

Google Scholar Profile

Link to my Google Scholar Profile 

Contact Information

Deutsche Bundesbank

Mainzer Landstrasse 46

60325 Frankfurt am Main, Germany

johannes.beutel(at)bundesbank.de

Disclaimer

This is my personal research website. All Information and any links found on this website do not necessarily reflect the views of the Deutsche Bundesbank or its staff.