Housing Consumption and Macroprudential Policies in Europe: An Ex Ante Evaluation
Antonios Mavropoulos, Qizhou Xiong
IWH Discussion Papers,
Nr. 17,
2018
Abstract
In this paper, we use the panel of the first two waves of the Household Finance and Consumption Survey by the European Central Bank to study housing demand of European households and evaluate potential housing market regulations in the post-crisis era. We provide a comprehensive account of the housing decisions of European households between 2010 and 2014, and structurally estimate the housing preference of a simple life-cycle housing choice model. We then evaluate the effect of a tighter LTV/LTI regulation via counter-factual simulations. We find that those regulations limit homeownership and wealth accumulation, reduces housing consumption but may be welfare improving for the young households.
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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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On DSGE Models
Lawrence J. Christiano, Martin S. Eichenbaum, Mathias Trabandt
Journal of Economic Perspectives,
Nr. 3,
2018
Abstract
The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.
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The Effects of Fiscal Policy in an Estimated DSGE Model – The Case of the German Stimulus Packages During the Great Recession
Andrej Drygalla, Oliver Holtemöller, Konstantin Kiesel
Abstract
In this paper, we analyse the effects of the stimulus packages adopted by the German government during the Great Recession. We employ a standard medium-scale dynamic stochastic general equilibrium (DSGE) model extended by non-optimising households and a detailed fiscal sector. In particular, the dynamics of spending and revenue variables are modeled as feedback rules with respect to the cyclical component of output. Based on the estimated rules, fiscal shocks are identified. According to the results, fiscal policy, in particular public consumption, investment, transfers and changes in labour tax rates including social security contributions prevented a sharper and prolonged decline of German output at the beginning of the Great Recession, suggesting a timely response of fiscal policy. The overall effects, however, are small when compared to other domestic and international shocks that contributed to the economic downturn. Our overall findings are not sensitive to the allowance of fiscal foresight.
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Central Bank Transparency and the Volatility of Exchange Rates
Stefan Eichler, Helge Littke
Abstract
We analyze the effect of monetary policy transparency on bilateral exchange rate volatility. We test the theoretical predictions of a stylized model using panel data for 62 currencies from 1998 to 2010. We find strong empirical evidence that an increase in the availability of information about monetary policy objectives decreases exchange rate volatility. Using interaction models, we find that this effect is more pronounced for countries with a lower flexibility of goods prices, a lower level of central bank conservatism, and a higher interest rate sensitivity of money demand.
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Central Bank Transparency and Cross-border Banking
Stefan Eichler, Helge Littke, Lena Tonzer
Journal of International Money and Finance,
2017
Abstract
We analyze the effect of central bank transparency on cross-border bank activities. Based on a panel gravity model for cross-border bank claims for 21 home and 47 destination countries from 1998 to 2010, we find strong empirical evidence that a rise in central bank transparency in the destination country, on average, increases cross-border claims. Using interaction models, we find that the positive effect of central bank transparency on cross-border claims is only significant if the central bank is politically independent and operates in a stable economic environment. Central bank transparency and credibility are thus considered complements by banks investing abroad.
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The Dynamic Effects of Works Councils on Labour Productivity: First Evidence from Panel Data
Steffen Müller, Jens Stegmaier
British Journal of Industrial Relations,
Nr. 2,
2017
Abstract
We estimate dynamic effects of works councils on labour productivity using newly available information from West German establishment panel data. Conditioning on plant fixed effects and control variables, we find negative productivity effects during the first five years after council introduction but a steady and substantial increase in the councils’ productivity effect thereafter. Our findings support a causal interpretation for the positive correlation between council existence and plant productivity that has been frequently reported in previous studies.
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Tail-risk Protection Trading Strategies
Natalie Packham, Jochen Papenbrock, Peter Schwendner, Fabian Wöbbeking
Quantitative Finance,
Nr. 5,
2017
Abstract
Starting from well-known empirical stylized facts of financial time series, we develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness, we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalized innovations. These generalized innovations may for example follow a Student t, a generalized hyperbolic, an alpha-stable or a Generalized Pareto distribution (GPD). Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods. A number of robustness tests including application to other assets further underline the effectiveness of the strategy. Finally, by empirically testing for second-order stochastic dominance, we find that risk averse investors would be willing to pay a positive premium to move from a static buy-and-hold investment in the DAX future to the tail-risk protection strategy.
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Inflation Dynamics During the Financial Crisis in Europe: Cross-sectional Identification of Long-run Inflation Expectations
Geraldine Dany-Knedlik, Oliver Holtemöller
IWH Discussion Papers,
Nr. 10,
2017
Abstract
We investigate drivers of Euro area inflation dynamics using a panel of regional Phillips curves and identify long-run inflation expectations by exploiting the crosssectional dimension of the data. Our approach simultaneously allows for the inclusion of country-specific inflation and unemployment-gaps, as well as time-varying parameters. Our preferred panel specification outperforms various aggregate, uni- and multivariate unobserved component models in terms of forecast accuracy. We find that declining long-run trend inflation expectations and rising inflation persistence indicate an altered risk of inflation expectations de-anchoring. Lower trend inflation, and persistently negative unemployment-gaps, a slightly increasing Phillips curve slope and the downward pressure of low oil prices mainly explain the low inflation rate during the recent years.
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Impulse Response Analysis in a Misspecified DSGE Model: A Comparison of Full and Limited Information Techniques
Sebastian Giesen, Rolf Scheufele
Applied Economics Letters,
Nr. 3,
2016
Abstract
In this article, we examine the effect of estimation biases – introduced by model misspecification – on the impulse responses analysis for dynamic stochastic general equilibrium (DSGE) models. Thereby, we use full and limited information estimators to estimate a misspecified DSGE model and calculate impulse response functions (IRFs) based on the estimated structural parameters. It turns out that IRFs based on full information techniques can be unreliable under misspecification.
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