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A model for accessing international firm-level data Eric J. Bartelsman Vrije Universiteit Amsterdam and Tinbergen Institute Prepared for OECD/Eurostat.

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Presentation on theme: "A model for accessing international firm-level data Eric J. Bartelsman Vrije Universiteit Amsterdam and Tinbergen Institute Prepared for OECD/Eurostat."— Presentation transcript:

1 A model for accessing international firm-level data Eric J. Bartelsman Vrije Universiteit Amsterdam and Tinbergen Institute Prepared for OECD/Eurostat Conference Luxembourg – October 26, 2006 This work is partially funded by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, "Policy Support and Anticipating Scientific and Technological Needs".

2 Overview of Presentation l What: International comparisons of micro-based indicators l Why: Meets urgent policy needs l How: New statistical regulations; remote execution; remote access l Who: Networked researchers, NSOs, Trusted third parties l Discussion: pros/cons; costs/benefits

3 Using Microdata for Analysis l Policy analysis lSNA / Final Expenditures & GDP: demand management policy lIndicators for structural policy and policy evaluation: microdata l Academic research lEstimation of behavioral responses l Microdata at NSOs lImprove quality of output lReduce response burden lProvide facilities for outsiders

4 International Comparisons l Not possible to stack data from all countries l Cross-country variation in intl microdata research provides: l valuable lessons for policy makers lidentification of effects for academics

5 SC LMD EUKLEMS Longitudinal Micro Data National Accounts Industry Data Single country Macro and Sectoral Timeseries Surveys, Business Registers Multiple countries N.A. Available Data Sources DMD EUKLEMS+

6 Recent Intl Microdata Research l There is demand for international comparisons of micro-based indicators: lFirm-level projects for OECD, WB, IADB, Eurostat lIntl Wage flexibility project (FRB/ECB) lIPUMS lLuxembourg Income Studies

7 Firm-Level Projects l Distributed micro-data analysis l Harmonized collection of indicators from longitudinal micro-level business datasets lFirm Demographics: Entry/Exit, Survival lProductivity: higher moments, conditional moments, special tabulations (by size, ownership status, etc)

8 Firms produce not countries or industries l Variation in firm-level productivity within industry or country l A country could have a long tail problem: l Or a lack of world class firms: Global frontier country2 country1 long tail Mean productivity may not be a sufficient policy indicatorMean productivity may not be a sufficient policy indicator

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11 Productivity and market contestability

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13 How to generate indicators? l Eurostat regulation lAfter international debate on definitions, NSOs must supply the requested indicators l Distributed micro-data analysis lNetworked collection, through remote execution (or remote access)

14 Researcher Policy Question Research Design Program Code Publication Network Metadata Network members Cross-country Tables NSOs Distributed micro data research Provision of metadata. Approval of access. Disclosure analysis

15 Network for International Microdata l Remote execution using meta-data at center, and network of NSO contacts lCoordination issues l Secure remote access to confidential data at trusted center lTechnical issues lLegal issues

16 Participants in Network l Policy analysts and academics lAnswered research questions lSpillovers from knowledge; launching customer l NSOs lMeet user needs; fits within organizational goals; learn from best practice; improve reputation lProvide facility; Provide expertise and experience l OECD lImproved comparability of stats; answered policy questions lProvide institutional support; contribute to analytical capabilities

17 Issues for Discussion l What are dangers to NSOs and how to minimize lConfidentiality lProvider of undisputed data lCostly sink of resources l What are benefits to community and how to maximize lLow marginal costs for research output lTurnaround time lowered lLearning from broad-based experience


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