Are Qualitative Inflation Expectations Useful to Predict Inflation?
Rolf Scheufele
Journal of Business Cycle Measurement and Analysis,
No. 1,
2011
Abstract
This paper examines the properties of qualitative inflation expectations collected from economic experts for Germany. It describes their characteristics relating to rationality and Granger causality. An out-of-sample simulation study investigates whether this indicator is suitable for inflation forecasting. Results from other standard forecasting models are considered and compared with models employing survey measures. We find that a model using survey expectations outperforms most of the competing models. Moreover, we find some evidence that the survey indicator already contains information from other model types (e. g. Phillips curve models). However, the forecast quality may be further improved by completely taking into account information from some financial indicators.
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Distance Functions for Matching in Small Samples
Eva Dettmann, Christian Schmeißer, Claudia Becker
Computational Statistics & Data Analysis,
No. 5,
2011
Abstract
The development of ‘standards’ for the application of matching algorithms in empirical evaluation studies is still an outstanding goal. The first step of the matching procedure is the choice of an appropriate distance function. In empirical evaluation situations often the sample sizes are small. Moreover, they consist of variables with different scale levels which have to be considered explicitly in the matching process. A simulation is performed which is directed towards these empirical challenges and supplements former studies in this respect. The choice of the analysed distance functions is determined by the results of former theoretical studies and recommendations in the empirical literature. Thus, two balancing scores (the propensity score and the index score) and the Mahalanobis distance are considered. Additionally, aggregated statistical distance functions not yet used for empirical evaluation are included. The matching outcomes are compared using non-parametric scale-specific tests for identical distributions of the characteristics in the treatment and the control groups. The simulation results show that, in small samples, aggregated statistical distance functions are the better choice for summarising similarities in differently scaled variables compared to the commonly used measures.
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Has the Euro Increased International Price Elasticities?
Oliver Holtemöller, Götz Zeddies
IWH Discussion Papers,
No. 18,
2010
published in: Empirica
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown, Durbin, and Evans (1975) and Zeileis (2004), Nyblom (1989) and Hansen (1992), and Andrews, Lee, and Ploberger (1996). Power and size properties are derived using Monte Carlo simulations. Results emphasize that mostly the CUSUM type tests are affected by the presence of heteroscedasticity, whereas the individual parameter Nyblom test and AvgLM test are proved to be highly robust. However, each test is significantly affected by leptokurtosis. Contrarily to other tests, where skewness is far more problematic than kurtosis, it has no additional effect for any of the endogenous break tests we analyze. Concerning overall robustness the Nyblom test performs best, while being almost on par to more recently developed tests in terms of power.
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Testing for Structural Breaks at Unknown Time: A Steeplechase
Makram El-Shagi, Sebastian Giesen
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown, Durbin, and Evans (1975) and Zeileis (2004), Nyblom (1989) and Hansen (1992), and Andrews, Lee, and Ploberger (1996). Power and size properties are derived using Monte Carlo simulations. Results emphasize that mostly the CUSUM type tests are affected by the presence of heteroscedasticity, whereas the individual parameter Nyblom test and AvgLM test are proved to be highly robust. However, each test is significantly affected by leptokurtosis. Contrarily to other tests, where skewness is far more problematic than kurtosis, it has no additional effect for any of the endogenous break tests we analyze. Concerning overall robustness the Nyblom test performs best, while being almost on par to more recently developed tests in terms of power.
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Cross-border Exposures and Financial Contagion
Hans Degryse, Muhammad Ather Elahi, Maria Fabiana Penas
International Review of Finance,
No. 2,
2010
Abstract
Integrated financial markets provide opportunities for expansion and improved risk sharing, but also pose threats of contagion risk through cross-border exposures. This paper examines cross-border contagion risk over the period 1999–2006. To that purpose we use aggregate cross-border exposures of 17 countries as reported in the Bank for International Settlements Consolidated Banking Statistics. We find that a shock that affects the liabilities of one country may undermine the stability of the entire financial system. Particularly, a shock wiping out 25% (35%) of US (UK) cross-border liabilities against non-US (non-UK) banks could lead to bank contagion eroding at least 94% (45%) of the recipient countries' banking assets. We also find that since 2006 a shock to Eastern Europe, Turkey and Russia affects most countries. Our simulations also reveal that the ‘speed of propagation of contagion’ has increased in recent years resulting in a higher number of directly exposed banking systems. Finally, we find that contagion is more widespread in geographical proximities.
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Money and Inflation: The Role of Persistent Velocity Movements
Makram El-Shagi, Sebastian Giesen
Abstract
While the long run relation between money and inflation is well established, empirical evidence on the adjustment to the long run equilibrium is very heterogeneous. In the present paper we use a multivariate state space framework, that substantially expands the traditional vector error correction approach, to analyze the short run impact of money on prices. We contribute to the literature in three ways: First, we distinguish changes in velocity of money that are due to institutional developments and thus do not induce inflationary pressure, and changes that reflect transitory movements in money demand. This is achieved with a newly developed multivariate unobserved components decomposition. Second, we analyze whether the high volatility of the transmission from monetary pressure to inflation follows some structure, i.e., if the parameter regime can assumed to be constant. Finally, we use our model to illustrate the consequences of the monetary policy of the Fed that has been employed to mitigate the impact of the financial crisis, simulating different exit strategy scenarios.
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Is there a Superior Distance Function for Matching in Small Samples?
Eva Dettmann, Claudia Becker, Christian Schmeißer
Abstract
The study contributes to the development of ’standards’ for the application of matching algorithms in empirical evaluation studies. The focus is on the first step of the matching procedure, the choice of an appropriate distance function. Supplementary o most former studies, the simulation is strongly based on empirical evaluation ituations. This reality orientation induces the focus on small samples. Furthermore, ariables with different scale levels must be considered explicitly in the matching rocess. The choice of the analysed distance functions is determined by the results of former theoretical studies and recommendations in the empirical literature. Thus, in the simulation, two balancing scores (the propensity score and the index score) and the Mahalanobis distance are considered. Additionally, aggregated statistical distance functions not yet used for empirical evaluation are included. The matching outcomes are compared using non-parametrical scale-specific tests for identical distributions of the characteristics in the treatment and the control groups. The simulation results show that, in small samples, aggregated statistical distance functions are the better
choice for summarising similarities in differently scaled variables compared to the
commonly used measures.
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Estimation Uncertainty in Credit Risk Assessment: Comparison of Credit Risk Using Bootstrapping and an Asymptotic Approach
Henry Dannenberg
IWH Discussion Papers,
No. 3,
2009
Abstract
For credit risk assessment, probability of default and correlation have to be estimated simultaneously. However, these estimates are uncertain. To assess this uncertainty the literature has discussed the use of asymptotic confidence regions. This kind of region though needs a long credit history for exact assessment. An alternative method to generate a confidence region for a short credit history is bootstrapping. Hence, it could be more appropriate to assess estimation uncertainty with bootstrapping than with asymptotic methods if only a short credit history is available. Based on a simulation study, it is analyzed how many periods should be available for assessing credit risk – taking account of estimation uncertainty – if bootstrapping and a Wald confidence region shall achieve similar results. This article shows that more than 100 cycles have to be available for similar results.
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Economic Stimulus Packages and their Effects – A Simulation with the IWH Macroeconometric Model
Rolf Scheufele
Wirtschaft im Wandel,
No. 1,
2009
Abstract
This article deals with the macroeconomic effects of different economic stimulus packages. It evaluates several measures including direct tax cuts, a reduction of the contribution payment to social security, an increase in government spending and a temporary cut of the value added tax rate. Further, the measures of the latest economic stimulus packages are assessed and it is found that their effects on production and employment are only of moderate size.
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