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A model for accessing international firm-level data

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Title: Werknemer -- Ondernemer Author: Eric J. Bartelsman Last modified by: Administrator Created Date: 2/17/2003 8:07:20 PM Document presentation format – PowerPoint PPT presentation

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Title: A model for accessing international firm-level data


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

3
Using Microdata for Analysis
  • Policy analysis
  • SNA / Final Expenditures GDP demand management
    policy
  • Indicators for structural policy and policy
    evaluation microdata
  • Academic research
  • Estimation of behavioral responses
  • Microdata at NSOs
  • Improve quality of output
  • Reduce response burden
  • Provide facilities for outsiders

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

5
Available Data Sources
Longitudinal Micro Data
National Accounts Industry Data
Macro and Sectoral Timeseries
Surveys, Business Registers
Single country
  • SC LMD

EUKLEMS
N.A.
Multiple countries
6
Recent Intl Microdata Research
  • There is demand for international comparisons of
    micro-based indicators
  • Firm-level projects for OECD, WB, IADB, Eurostat
  • Intl Wage flexibility project (FRB/ECB)
  • IPUMS
  • Luxembourg Income Studies

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

8
Firms produce not countries or industries
  • Variation in firm-level productivity within
    industry or country
  • A country could have a long tail problem
  • Or a lack of world class firms

country1
long tail
  • Mean productivity may not be a sufficient policy
    indicator

country2
Global frontier
9

10
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11
Productivity and market contestability
12
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13
How to generate indicators?
  • Eurostat regulation
  • After international debate on definitions, NSOs
    must supply the requested indicators
  • Distributed micro-data analysis
  • Networked collection, through remote execution
    (or remote access)

14
Distributed micro data research
Policy Question Research Design
Researcher
Program Code
Publication
Metadata
Cross-country Tables
Network
Network members
Provision of metadata. Approval of
access. Disclosure analysis
NSOs
15
Network for International Microdata
  • Remote execution using meta-data at center, and
    network of NSO contacts
  • Coordination issues
  • Secure remote access to confidential data at
    trusted center
  • Technical issues
  • Legal issues

16
Participants in Network
  • Policy analysts and academics
  • Answered research questions
  • Spillovers from knowledge launching customer
  • NSOs
  • Meet user needs fits within organizational
    goals learn from best practice improve
    reputation
  • Provide facility Provide expertise and
    experience
  • OECD
  • Improved comparability of stats answered policy
    questions
  • Provide institutional support contribute to
    analytical capabilities

17
Issues for Discussion
  • What are dangers to NSOs and how to minimize
  • Confidentiality
  • Provider of undisputed data
  • Costly sink of resources
  • What are benefits to community and how to
    maximize
  • Low marginal costs for research output
  • Turnaround time lowered
  • Learning from broad-based experience
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