Compnet Training Program
CompNet Training Program Structure The course is made for autonomous online learning. It is structured in three modules : Beginners, Intermediate and Advanced. Each of them…
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9th vintage
9th Vintage CompNet Dataset The CompNet dataset includes a set of micro-aggregated indicators to enhance policy and academic analysis on competitiveness and productivity. All the…
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Research Articles
Research Articles Explore cutting-edge research based on CompNet’s micro-aggregated firm-level data and related analytical tools. These articles cover empirical and theoretical…
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Research Clusters
Three Research Clusters Each IWH research group is assigned to a topic-oriented research cluster. The clusters are not separate organisational units, but rather bundle the…
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Reassessing EU Comparative Advantage: The Role of Technology
Filippo di Mauro, Marco Matani, Gianmarco Ottaviano
IWH-CompNet Discussion Papers,
No. 2,
2024
Abstract
Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.
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Reassessing EU Comparative Advantage: The Role of Technology
Filippo di Mauro, Marco Matani, Gianmarco Ottaviano
IWH Discussion Papers,
No. 26,
2024
Abstract
Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.
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East Germany
The Nasty Gap 30 years after unification: Why East Germany is still 20% poorer than the West Dossier In a nutshell The East German economic convergence process is hardly…
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Policy Output
Reports › CompNet’s flagship and special reports provide in-depth, data-driven analysis on productivity, competitiveness, and related economic trends, using the latest CompNet…
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Job Market Candidates
Job Market Candidates Marius Fourné Marius Fourné is a PhD candidate in Economics at the Halle Institute for Economic Research (IWH) and Martin Luther University of…
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The IAB Job Vacancy Survey: Establishment survey on labor demand and recruitment processes, waves 2000 to 2021 and subsequent quarters 2006 to 2022
Erik-Benjamin Börschlein, André Diegmann, Nicole Gürtzgen, Alexander Kubis, André Pirralha, Laura Pohlan, Martin Popp, Franka Vetter
FDZ-Datenreport,
06
2024
Abstract
The IAB Job Vacancy Survey is a quarterly and representative establishment survey on labor demand and recruitment processes in Germany. The survey identifies the overall stock of vacancies in the German labor market, including those vacancies that are not reported to the Federal Employment Agency (FEA). The first module of the questionnaire collects information about the number and structure of vacancies, future personnel requirements, about the current economic situation and the expected development of participating establishments. The second module enquires about employer attitudes and firm use of current labor market instruments as well as the employer handling of people disadvantaged in the labor market. The third module asks for information about the last new hire and the last case of a failed recruitment effort. The Research Data Centre of the Federal Employment Agency offers the data sets of the survey waves from 2000 onwards.
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