Centre for Evidence-based Policy Advice
Centre for Evidence-based Policy Advice (IWH-CEP) The Centre for Evidence-based Policy Advice (IWH-CEP) of the IWH was founded in 2014. It is a platform that bundles and…
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Data Protection Policy We take the protection of your personal data very seriously and treat your personal data with confidentiality and in compliance with the provisions of law…
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IWH FDI Micro Database
IWH FDI Micro Database The IWH FDI Micro Database (FDI = Foreign Direct Investment) comprises a total population of affiliates of multinational enterprises (MNEs) in selected…
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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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Globalisation in Europe: Consequences for the Business Environment and Future Patterns in Light of Covid-19
Sergio Inferrera
IWH-CompNet Discussion Papers,
No. 2,
2021
Abstract
In this paper, I study the consequences of globalisation, as measured by the involvement of firms in GVC, on the business environment. In particular, I focus on concentration and productivity, firstly by estimating robust elasticities and then isolating the exogenous component of the variation in the participation in GVC. To this aim, I exploit the distance between industries in terms of upstreamness and downstreamness along the supply chain. The evidences suggest that involvement in international supply chains is positively related to concentration at the sector level and positively associated with aggregate productivity, an effect that is driven by the firms at the top of the productivity distribution. Finally, I relate these findings to the current pandemic, going beyond the lack of official statistics and estimating GVC participation for 2020 at the country-level through real time world-seaborne trade data, providing evidences on the re-absorption of the Covid shock in several European economies.
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flexpaneldid: A Stata Command for Causal Analysis with Varying Treatment Time and Duration
Eva Dettmann, Alexander Giebler, Antje Weyh
Abstract
>>A completely revised version of this paper has been published as: Dettmann, Eva; Giebler, Alexander; Weyh, Antje: flexpaneldid. A Stata Toolbox for Causal Analysis with Varying Treatment Time and Duration. IWH Discussion Paper 3/2020. Halle (Saale) 2020.<<
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) and its Stata implementation, the command flexpaneldid. The approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations (like investment grants or other subsidy schemes). Introducing more flexibility enables the user to consider individual treatment and outcome periods for the treated observations. The flexpaneldid command for panel data implements the developed flexible difference-in-differences approach and commonly used alternatives like CEM Matching and difference-in-differences models. The novelty of this tool is an extensive data preprocessing to include time information into the matching approach and the treatment effect estimation. The core of the paper gives two comprehensive examples to explain the use of flexpaneldid and its options on the basis of a publicly accessible data set.
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SMEs and Access to Bank Credit: Evidence on the Regional Propagation of the Financial Crisis in the UK
Hans Degryse, Kent Matthews, Tianshu Zhao
Journal of Financial Stability,
2018
Abstract
We study the sensitivity of banks’ credit supply to small and medium size enterprises (SMEs) in the UK with respect to the banks’ financial condition before and during the financial crisis. Employing unique data on the geographical location of all bank branches in the UK, we connect firms’ access to bank credit to the financial condition (i.e., bank health and the use of core deposits) of all bank branches in the vicinity of the firm for the period 2004–2011. Before the crisis, banks’ local financial conditions did not influence credit availability irrespective of the functional distance (i.e., the distance between bank branch and bank headquarters). However, during the crisis, we find that SMEs with banks within their vicinity that have stronger financial conditions faced greater credit availability when the functional distance is close. Our results point to a “flight to headquarters” effect during the financial crisis.
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Is the 'Central German Metropolitan Region' Spatially Integrated? An Empirical Assessment of Commuting Relations
Albrecht Kauffmann
Urban Studies,
No. 9,
2016
Abstract
The 'Central German Metropolitan Region' is a network of cities and their surroundings, located in the three East-German states of Saxony, Saxony-Anhalt and Thuringia. It was founded to bring the bundled strengths of these cities into an inter-municipal cooperation, for making use of the possible advantages of a polycentric region. As theory claims, a precondition for gains from polycentricity is spatial integration of the region. In particular, markets for high skilled labour should be integrated. To assess how this precondition is fulfilled in Central Germany, in the framework of a doubly constrained gravity model the commuting relations between the functional regions of the (until 2013) 11 core cities of the network are analysed. In particular for higher educated employees, the results display that commuting relations are determined not only by distance, but also by the state borders that cross the area.
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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,
No. 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,
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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