Universitätspublikationen
Refine
Year of publication
Document Type
- Working Paper (175)
- Part of Periodical (11)
- Report (8)
- Article (7)
- Book (2)
- Doctoral Thesis (1)
Has Fulltext
- yes (204) (remove)
Is part of the Bibliography
- no (204)
Keywords
- monetary policy (13)
- DSGE (7)
- Federal Reserve (6)
- Monetary Policy (6)
- Numerical accuracy (6)
- Solution methods (6)
- Bayesian estimation (5)
- DSGE models (5)
- Geldpolitik (5)
- banking union (5)
Institute
- Institute for Monetary and Financial Stability (IMFS) (204) (remove)
On the accuracy of linear DSGE solution methods and the consequences for log-normal asset pricing
(2021)
This paper demonstrates a failure of standard, generalized Schur (or QZ) decomposition based solutions methods for linear dynamic stochastic general equilibrium (DSGE) models when there is insufficient eigenvalue separation about the unit circle. The significance of this is demonstrated in a simple production-based asset pricing model with external habit formation. While the exact solution afforded by the simplicity of the model matches post-war US consumption growth and the equity premium, QZ-based numerical solutions miss the later by many annualized percentage points.
Rising temperatures, falling ratings: the effect of climate change on sovereign creditworthiness
(2021)
How will a changing climate impact the creditworthiness of governments over the very long term? Financial markets need credible, digestible information on how climate change translates into material risks. To bridge the gap between climate science and real-world financial indicators, the authors simulate the effect of climate change on sovereign credit ratings for 108 countries, creating the world’s first climate-adjusted sovereign credit rating. The study offers a first methodological approach to extend the long-term rating to an ultra-long-term reality, aiming at long-term investors, but also regulators and rating agencies.
Central banks normally accept debt of their own governments as collateral in liquidity operations without reservations. This gives rise to a valuable liquidity premium that reduces the cost of government finance. The ECB is an interesting exception in this respect. It relies on external assessments of the creditworthiness of its member states, such as credit ratings, to determine eligibility and the haircut it imposes on such debt. The authors show how such features in a central bank’s collateral framework can give rise to cliff effects and multiple equilibria in bond yields and increase the vulnerability of governments to external shocks. This can potentially induce sovereign debt crises and defaults that would not otherwise arise.
Did the Federal Reserves’ Quantitative Easing (QE) in the aftermath of the financial crisis have macroeconomic effects? To answer this question, the authors estimate a large-scale DSGE model over the sample from 1998 to 2020, including data of the Fed’s balance sheet. The authors allow for QE to affect the economy via multiple channels that arise from several financial frictions. Their nonlinear Bayesian likelihood approach fully accounts for the zero lower bound on nominal interest rates. They find that between 2009 to 2015, QE increased output by about 1.2 percent. This reflects a net increase in investment of nearly 9 percent, that was accompanied by a 0.7 percent drop in aggregate consumption. Both, government bond and capital asset purchases were effective in improving financing conditions. Especially capital asset purchases significantly facilitated new investment and increased the production capacity. Against the backdrop of a fall in consumption, supply side effects dominated which led to a mild disinflationary effect of about 0.25 percent annually.
Using a nonlinear Bayesian likelihood approach that fully accounts for the zero lower bound on nominal interest rates, the authors analyze US post-crisis business cycle dynamics and provide reference parameter estimates. They find that neither the inclusion of financial frictions nor that of household heterogeneity improve the empirical fit of the standard model, or its ability to provide a joint explanation for the post-2007 dynamics. Associated financial shocks mis-predict an increase in consumption. The common practice of omitting the ZLB period in the estimation severely distorts the analysis of the more recent economic dynamics.
Einen Überblick über neueste Forschungsergebnisse der Wissenschaftler am IMFS, Berichte von Konferenzen und Vorträgen sowie ausführliche Informationen zum derzeit größten Forschungsprojekt Macroeconomic Modeling and Comparison Initiative (MMCI) bietet der IMFS-Jahresbericht 2019, der jetzt veröffentlicht ist. Darüber hinaus gibt IMFS-Professor Michael Haliassos im Interview einen Einblick in seine Arbeit zum Finanzverhalten der privaten Haushalte und die ehemaligen Mitarbeiter Philipp Lieberknecht und Felix Strobel berichten, wie sie im Berufsleben auf ihrer Forschung am IMFS aufbauen können.
Auf rund 100 Seiten zeigt der Bericht die Highlights des Jahres, alle Mitarbeiter sowie die Projekte, Publikationen sowie die Veranstaltungen des IMFS, darunter „The ECB and Its Watchers“ zu finden. Der Jahresbericht ist auf Englisch erschienen und steht im PDF-Format zur Verfügung.
Household finance
(2020)
Household financial decisions are complex, interdependent, and heterogeneous, and central to the functioning of the financial system. We present an overview of the rapidly expanding literature on household finance (with some important exceptions) and suggest directions for future research. We begin with the theory and empirics of asset market participation and asset allocation over the lifecycle. We then discuss house-hold choices in insurance markets, trading behavior, decisions on retirement saving, and financial choices by retirees. We survey research on liabilities, including mortgage choice, refinancing, and default, and household behavior in unsecured credit markets, including credit cards and payday lending. We then connect the household to its social environment, including peer effects, cultural and hereditary factors, intra-household financial decision making, financial literacy, cognition and educational interventions. We also discuss literature on the provision and consumption of financial advice.
In this paper we adapt the Hamiltonian Monte Carlo (HMC) estimator to DSGE models, a method presently used in various fields due to its superior sampling and diagnostic properties. We implement it into a state-of-theart, freely available high-performance software package, STAN. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model using US data. Our results and sampling diagnostics confirm the parameter estimates available in existing literature. In addition, we find bimodality in the Smets-Wouters model even if we estimate the model using the original tight priors. Finally, we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm to create a powerful tool which permits the estimation of DSGE models with ill-behaved posterior densities.
In this paper we adopt the Hamiltonian Monte Carlo (HMC) estimator for DSGE models by implementing it into a state-of-the-art, freely available high-performance software package. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model on US data. Our results and sampling diagnostics confirm the parameter estimates available in existing literature. In addition we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm which permits the estimation of DSGE models with ill-behaved posterior densities.