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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.
Das Working Paper bietet die zusammenfassende Stellungnahme von Prof. Volker Wieland zum Ankaufprogramm der Europäischen Zentralbank für Anleihen des öffentlichen Sektors (Public Sector Purchase Programme, PSPP) am Bundesverfassungsgericht am 30.07.2019. Dabei liegt der Schwerpunkt auf der Frage der Einordnung des PSPP als monetäre, geldpolitische Maßnahme und der Verhältnismäßigkeit des Programms und seiner Umsetzung. Ebenfalls wird kurz auf die weiteren Fragen zur Umsetzung, insbesondere Ankündigung, Begrenzung und Abstand zum Primärmarkt für Staatsanleihen eingegangen.
The ruling of the German Federal Constitutional Court and its call for conducting and communicating proportionality assessments regarding monetary policy have been the subject of some controversy. However, it can also be understood as a way to strengthen the de-facto independence of the European Central Bank. The authors shows how a regular proportionality check could be integrated in the ECB’s strategy that is currently undergoing a systematic review. In particular, they propose to include quantitative benchmarks for policy rates and the central bank balance sheet. Deviations from such benchmarks can have benefits in terms of the intended path for inflation while involving costs in terms of risks and side effects that need to be balanced. Practical applications to the euro area are provided
This paper summarizes key elements of the German Federal Constitutional Court’s decision on the European Central Bank’s Public Sector Asset Purchase Programme. It briefly explains how it is possible for the German Court to disagree with the ruling of the Court of Justice of the European Union. Finally, it makes suggestions concerning a practical way forward for the Governing Council of the ECB in light of these developments.
Mit einem um die Behandlungskapazität des Gesundheitssystems erweiterten epidemiologischen SIRD-Modell werden Mechanismen und Dynamik einer Virusepidemie wie Corona anhand von stilisierten politischen Reaktionsmustern (Ignore, Shutdown, Ignore-Shutdown-Relax) simuliert. Ferner werden aus dem Modell Lehren für die statistische Analyse von Corona gezogen, wie die Aussagekraft publizierter Verdopplungszeiten und Reproduktionszahlen. Die Dunkelziffer unbestätigter Fälle und die im Epidemieverlauf variable Genauigkeit von medizinischen Infektionstests werden diskutiert. Zur Messung der medizinischen Kosten von Corona sowie für regionale und internationale Vergleiche wird ein Schadensindex der verlorenen Lebenszeit vorgeschlagen. Zuletzt geht die Arbeit kurz auf die ökonomischen Kosten von Corona in Deutschland ein.
We analyze cyclical co-movement in credit, house prices, equity prices, and longterm interest rates across 17 advanced economies. Using a time-varying multi-level dynamic factor model and more than 130 years of data, we analyze the dynamics of co-movement at different levels of aggregation and compare recent developments to earlier episodes such as the early era of financial globalization from 1880 to 1913 and the Great Depression. We find that joint global dynamics across various financial quantities and prices as well as variable-specific global co-movements are important to explain fluctuations in the data. From a historical perspective, global co-movement in financial variables is not a new phenomenon, but its importance has increased for some variables since the 1980s. For equity prices, global cycles play currently a historically unprecedented role, explaining more than half of the fluctuations in the data. Global cycles in credit and housing have become much more pronounced and longer, but their importance in explaining dynamics has only increased for some economies including the US, the UK and Nordic European countries. We also include GDP in the analysis and find an increasing role for a global business cycle.
We propose a simple modification of the time series filter by Hamilton (2018) that yields reliable and economically meaningful real-time output gap estimates. The original filter relies on 8-quarter-ahead forecast errors of a simple autoregression of log real GDP. While this approach yields a cyclical component of GDP that is hardly revised with new incoming data due to the one-sided filtering approach, it does not cover typical business cycle frequencies evenly, but short business cycles are muted and medium length business cycles are amplified. Further, the estimated trend is as volatile as GDP itself and can thus hardly be interpreted as potential GDP. A simple modification that is based on the mean of 4- to 12-quarter-ahead forecast errors shares the favorable real-time properties of the Hamilton filter, but leads to a much better coverage of typical business cycle frequencies and a smooth estimated trend. Based on output growth and inflation forecasts and a comparison to revised output gap estimates from policy institutions, we find that real-time output gaps based on the modified Hamilton filter are economically much more meaningful measures of the business cycle than those based on other simple statistical trend-cycle decomposition techniques such as the HP or the Bandpass filter.
The term structure of interest rates is crucial for the transmission of monetary policy to financial markets and the macroeconomy. Disentangling the impact of monetary policy on the components of interest rates, expected short rates and term premia, is essential to understanding this channel. To accomplish this, we provide a quantitative structural model with endogenous, time-varying term premia that are consistent with empirical findings. News about future policy, in contrast to unexpected policy shocks, has quantitatively significant effects on term premia along the entire term structure. This provides a plausible explanation for partly contradictory estimates in the empirical literature.
In the course of the crisis, the European System of Central Banks (ESCB) has acted several times to support the EU Member States and banking systems in financial distress by purchasing debt instruments: Covered Bonds Programmes (CBP), Securities Market Programmes (SMP), Long Term Refinancing Operations (LTRO), and Targeted Long Term Refinancing Operations (TLTRO), followed by the Outright Monetary Transactions (OMT) and then the Extended Asset Purchase Programmes (EAPP) – colloquially labelled as Quantitative Easing (QE).
Initially, the support measures of the ESCB might have to be judged as monetary policy but the selectivity of OMT and – even more – SMP in conjunction with the transfer of risks to the ESCB speak against it.