Testing for Structural Breaks at Unknown Time: A Steeplechase
Makram El-Shagi, Sebastian Giesen
Computational Economics,
No. 1,
2013
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 et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.
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Towards Unrestricted Public Use Business Microdata: The Synthetic Longitudinal Business Database
John M. Abowd, Ron S. Jarmin, Satkartar K. Kinney, Javier Miranda, Jerome P. Reiter, Arnold P. Reznek
International Statistical Review,
No. 3,
2011
Abstract
In most countries, national statistical agencies do not release establishment-level business microdata, because doing so represents too large a risk to establishments’ confidentiality. One approach with the potential for overcoming these risks is to release synthetic data; that is, the released establishment data are simulated from statistical models designed to mimic the distributions of the underlying real microdata. In this article, we describe an application of this strategy to create a public use file for the Longitudinal Business Database, an annual economic census of establishments in the United States comprising more than 20 million records dating back to 1976. The U.S. Bureau of the Census and the Internal Revenue Service recently approved the release of these synthetic microdata for public use, making the synthetic Longitudinal Business Database the first-ever business microdata set publicly released in the United States. We describe how we created the synthetic data, evaluated analytical validity, and assessed disclosure risk.
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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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Matching kleiner Stichproben. Ein Vergleich verschiedener Verfahren
Eva Dettmann
Südwestdeutscher Verlag fuer Hochschulschriften. Saarbrücken,
2009
Abstract
Die Anwendung moderner Evaluationsverfahren ist aus der wissenschaftlichen Politikberatung nicht mehr wegzudenken. Unabhängig davon ist die Idee dieser Methoden auf viele Gebiete der Ökonomie und der Sozialwissenschaften übertragbar. Da die konkrete Fragestellung ebenso wie die verfügbaren Informationen die Eignung eines Verfahrens für den praktischen Einsatz beeinflusst, fällt die Auswahl der “richtigen“ Methode oft schwer. Die Studie ist als Beitrag zur Entwicklung von Richtlinien für den praktischen Einsatz speziell von Matchingverfahren zu sehen, dessen Ziel darin besteht, die diskutierten Methoden einem breiten Anwenderkreis zugänglich zu machen. Charakteristisch dabei ist ein enger Bezug zur praktischen Anwendung, der auch die Rahmenbedingungen für die durchgeführte Simulation vorgibt. Die Ergebnisse zeigen, dass es sich lohnt, bei der Wahl eines Matchingansatzes „über den Tellerrand zu schauen“ und bisher nur in anderen Wissenschaftsbereichen genutzte Verfahren eventuell anzupassen und für die Bildung von Vergleichsgruppen nutzbar zu machen. Dies gilt insbesondere für die Wahl eines geeigneten Distanzmaßes.
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