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Rent sharing across Production network

Emmanuel Dhyne - Global Forum on Productivity - 20-21 June 2019, Sydney

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Rent sharing across Production network

  1. 1. Rent sharing across Production network Emmanuel Dhyne, Global Forum on Productivity, Sydney 20/07 – 21/07 2019
  2. 2. ◆ Firm level data from 1995 onwards. ◆ Various datasets connected by unique firm level identifier : VAT number ◆ Administrative and fiscal data sources ◆ Network data only available from 2002 ◆ Allows a full description of the domestic and foreign sales of Belgian firms ◆ FDI and domestic participations are covered to identify (inter)national groups 2 Source(s): 1 Footnote 2 Footnote The NBB datawarehouse Firms regiter Annual account register VAT declarations International trade Social security declarations Balance of paiement survey VAT domestic customer declarations
  3. 3. ◆ 2 sources : ◇ National Statistical Institute : - multiple cross-section, structure of earning survey (used f.i. by Rycx and co-authors for various projects). - Small sample of firms and employees ◇ Cross-road bank of Social Security - Centralize administrative datasets from Social security institutions from 1997 for main social security agencies, from 2003 for administrative data sources - Covers all the population of firms / individuals - Allows to follow the situation of individuals over time (change in status, change of employers, wages) and some characteristics (limited number - gender, age, location, citizenship, work experience, education) 3 Source(s): 1 Footnote 2 Footnote Matched employer-employee data in Belgium
  4. 4. ◆ Used to analyse several policy relevant issues ◇ At the Bank : Du Caju, Fuss, Wintr (2009) : wage rigidity in Belgium (part of the ESCB Wage dynamic network) using 1/3 of the Belgian labor force ◇ Outside the Bank : evaluation of specific labor market policies by Belgian academics (see CBSS website for a list of research projects based on their data) 4 Source(s): 1 Footnote 2 Footnote Cross-road bank of Social Security
  5. 5. ◆ Restricted to Belgian researchers (universities, research centers) ◆ Either accessible on site (allows to get access to the universe of workers) ◆ Or access to subsamples anonymized by the CBSS ◆ Provided to the researchers, for a given project during a given time period, conditional on approval by the Statistical Secrecy Committee ◆ Extensions requires new contracts ◆ Costs are charged to the researchers ◆ Long process (1 year from initial contacts to the signature of the contract) ◆ External data sources can be merged by the CBSS before anonymization 5 Source(s): 1 Footnote 2 Footnote Accessing to cross-road bank dataset
  6. 6. 6 Source(s): 1 Footnote 2 Footnote The NBB production network + CBSS data ◆ Add CBSS data to the NBB data warehouse ◆ Sample of firms : Belgian firms with at least 10 FTE during one year between 2002-2014 ◆ For each sampled firms with at least 10 FTE : avg wage by worker type (gender, age, education, status) ◆ + Sample of 500,000 individuals that worked at least one quarter in a sampled firm during the 2002-2014 period ◆ For each individual : his/her wage and employment history over the 2002-2014 period, employer id, individual characteristics (gender, age, education, status, working experience)
  7. 7. 7 Source(s): 1 Footnote 2 Footnote Pass-through within and across the boundaries of firms (ongoing, very preliminary) ◆ Follow up of Tintelnot et al. (2019) on the pass-through of import shocks in the domestic network ◆ Motivation : ◇ Increases in outsourcing and fragmentation of production - Increases efficiency through specialisation - Transforms rent sharing between firms and workers ◆ Analyse the firms’ demand shocks transmission to wages (own shock and shocks affecting suppliers / customers) ◇ Who benefits from demand shocks ?
  8. 8. 8 Source(s): 1 Footnote 2 Footnote The NBB production network + CBSS data ◆ Sample of firms : Belgian firms with at least 10 FTE during one year between 2002-2014 ◆ For each sample firms with at least 10 FTE : avg, wage by worker type (gender, age, education, status) ◆ + Sample of 500,000 individuals that worked at least one quarter in a sampled firm during the 2002-2014 period ◆ For each individual : his/her wage and employment history over the 2002-2014 period, employer id, individual characteristics (gender, age, education, status, working experience)
  9. 9. 9 Source(s): 1 Footnote 2 Footnote Empirical strategy ◆ Estimate individual firm responses in labor costs, avg. wage, employment to changes in sales (instrumented by foreign demand shocks affecting firm i and all his direct and indirect customers). ◆ Estimate suppliers responses in terms of deliveries to Belgian firms and imports to changes in sales
  10. 10. 10 Results
  11. 11. 11 Within firm pass-through (across time)
  12. 12. 12 Within firm pass-through (across time)
  13. 13. 13 Within firm pass-through (across time)
  14. 14. 14 Blue vs white collars
  15. 15. 15 Blue vs white collars
  16. 16. 16 Blue vs white collars
  17. 17. 17 Across firm pass-through (across time)
  18. 18. 18 Across firm pass-through (across time)
  19. 19. 19 Heterogeneous pass-through across sectors
  20. 20. 20 Heterogeneous pass-through across sectors
  21. 21. 21

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Emmanuel Dhyne - Global Forum on Productivity - 20-21 June 2019, Sydney

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