IWH-FDI-Mikrodatenbank
IWH-FDI-Mikrodatenbank Die IWH-FDI-Mikrodatenbank (FDI = Foreign Direct Investment) umfasst eine in der Projektlaufzeit ständig aktualisierte Grundgesamtheit von…
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Correlation Scenarios and Correlation Stress Testing
Natalie Packham, Fabian Wöbbeking
Journal of Economic Behavior and Organization,
January
2023
Abstract
We develop a general approach for stress testing correlations of financial asset portfolios. The correlation matrix of asset returns is specified in a parametric form, where correlations are represented as a function of risk factors, such as country and industry factors. A sparse factor structure linking assets and risk factors is built using Bayesian variable selection methods. Regular calibration yields a joint distribution of economically meaningful stress scenarios of the factors. As such, the method also lends itself as a reverse stress testing framework: using the Mahalanobis distance or Highest Density Regions (HDR) on the joint risk factor distribution allows to infer worst-case correlation scenarios. We give examples of stress tests on a large portfolio of European and North American stocks.
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Intangible Capital and Productivity. Firm-level Evidence from German Manufacturing
Wolfhard Kaus, Viktor Slavtchev, Markus Zimmermann
IWH Discussion Papers,
Nr. 1,
2020
Abstract
We study the importance of intangible capital (R&D, software, patents) for the measurement of productivity using firm-level panel data from German manufacturing. We first document a number of facts on the evolution of intangible investment over time, and its distribution across firms. Aggregate intangible investment increased over time. However, the distribution of intangible investment, even more so than that of physical investment, is heavily right-skewed, with many firms investing nothing or little, and a few firms having very large intensities. Intangible investment is also lumpy. Firms that invest more intensively in intangibles (per capita or as sales share) also tend to be more productive. In a second step, we estimate production functions with and without intangible capital using recent control function approaches to account for the simultaneity of input choice and unobserved productivity shocks. We find a positive output elasticity for research and development (R&D) and, to a lesser extent, software and patent investment. Moreover, the production function estimates show substantial heterogeneity in the output elasticities across industries and firms. While intangible capital has small effects for firms with low intangible intensity, there are strong positive effects for high-intensity firms. Finally, including intangibles in a gross output production function reduces productivity dispersion (measured by the 90-10 decile range) on average by 3%, in some industries as much as nearly 9%.
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Subsidized Vocational Training: Stepping Stone or Trap? – Assessing Empirical Effects using Matching Techniques
Eva Dettmann, Jutta Günther
Swiss Journal of Economics and Statistics,
Nr. 4,
2013
Abstract
Using replacement matching on the basis of a statistical distance function we try to answer the question of whether subsidized vocational training is related to a negative image effect for the graduates. The results show that young people with equal qualifications acquired during subsidized vocational training are disadvantaged solely due to the kind of education they have received. The probability of finding adequate employment is lower than in the control group. Besides the 'general effect' of support we also find less favorable job opportunities for those who attended 'external' as compared to 'workplace-related' training.
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Distance Functions for Matching in Small Samples
Eva Dettmann, Christian Schmeißer, Claudia Becker
Computational Statistics & Data Analysis,
Nr. 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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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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Subsidized Vocational Training: Stepping Stone or Trap? An Evaluation Study for East Germany
Eva Dettmann, Jutta Günther
IWH Discussion Papers,
Nr. 21,
2009
Abstract
The aim of this paper is to analyze whether the formally equal qualifications acquired during a subsidized vocational education induce equal employment opportunities compared to regular vocational training. Using replacement matching on the basis of a statistical distance function, we are able to control for selection effects resulting from different personal and profession-related characteristics, and thus, to identify an unbiased effect of the public support. Besides the ‘total effect’ of support, it is of special interest if the effect is stronger for subsidized youths in external training compared to persons in workplace-related training. The analysis is based on unique and very detailed data, the Youth Panel of the Halle Centre for Social Research (zsh).
The results show that young people who successfully completed a subsidized vocational education are disadvantaged regarding their employment opportunities even when controlling for personal and profession-related influences on the employment prospects. Besides a quantitative effect, the analysis shows that the graduates of subsidized training work in slightly worse (underqualified) and worse paid jobs than the adolescents in the reference group. The comparison of both types of subsidized vocational training, however, does not confirm the expected stronger effect for youths in external vocational education compared to workplace-related training.
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Technology Clubs, R&D and Growth Patterns: Evidence from EU Manufacturing
Claire Economidou, J. W. B. Bos, Michael Koetter
European Economic Review,
Nr. 1,
2010
Abstract
This paper investigates the forces driving output change in a panel of EU manufacturing industries. A flexible modeling strategy is adopted that accounts for: (i) inefficient use of resources and (ii) differences in the production technology across industries. With our model we are able to identify technical, efficiency, and input growth for endogenously determined technology clubs. Technology club membership is modeled as a function of R&D intensity. This framework allows us to explore the components of output growth in each club, technology spillovers and catch-up issues across industries and countries.
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Cross-Border Bank Contagion in Europe
Reint E. Gropp, M. Lo Duca, Jukka M. Vesala
International Journal of Central Banking,
Nr. 1,
2009
Abstract
We analyze cross-border contagion among European banks in the period from January 1994 to January 2003. We use a multinomial logit model to estimate, in a given country, the number of banks that experience a large shock on the same day (“coexceedances”) as a function of common shocks and lagged coexceedances in other countries. Large shocks are measured by the bottom 95th percentile of the distribution of the daily percentage change in distance to default of banks.We find evidence of significant cross-border contagion among large European banks, which is consistent with a tiered cross-border interbank structure. The results also suggest that contagion increased after the introduction of the euro.
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Capital Stock Approximation using Firm Level Panel Data: A Modified Perpetual Inventory Approach
Steffen Müller
Jahrbücher für Nationalökonomie und Statistik,
Nr. 4,
2008
Abstract
Many recent studies exploring conditional factor demand or factor substitution issues use firm level panel data. A considerable number of establishment panels contains no direct information on the capital input, necessary for production or cost function estimation. Incorrect measurement of capital leads to biased estimates and casts doubt on any inference on output elasticities or input substitution properties. The perpetual inventory approach, commonly used for long panels, is a method that attenuates these problems. In this paper a modified perpetual inventory approach is proposed. This method provides more reliable measures for capital input when short firm panels are used and no direct information on capital input is available. The empirical results based on a replication study of Addison et al. (2006) support the conclusion that modified perpetual inventory is superior to previous attempts in particular when fixed effects estimation techniques are used. The method thus makes a considerable number of recently established firm panels accessible to more sophisticated production function or factor demand analyses.
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