1) The document discusses using matched employer-employee data from Belgium to analyze how demand shocks are passed through firms' production networks and affect wages. 2) Preliminary analysis has found that firms pass through some of their own sales shocks to average wages and employment levels over time. 3) Initial results also show differences in how wage shocks are passed through to blue-collar versus white-collar workers.

1. Rent sharing across
Production network
Emmanuel Dhyne, Global Forum on Productivity, Sydney
20/07 – 21/07 2019

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
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The NBB datawarehouse
Firms regiter
Annual
account
register
VAT
declarations
International
trade
Social security
declarations
Balance of
paiement
survey
VAT domestic
customer
declarations

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)
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Matched employer-employee data in Belgium

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)
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Cross-road bank of Social Security

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
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Accessing to cross-road bank dataset

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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
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
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
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
Results

11. 11
Within firm pass-through (across time)

12. 12
Within firm pass-through (across time)

13. 13
Within firm pass-through (across time)

14. 14
Blue vs white collars

15. 15
Blue vs white collars

16. 16
Blue vs white collars

17. 17
Across firm pass-through (across time)

18. 18
Across firm pass-through (across time)

19. 19
Heterogeneous pass-through across sectors

20. 20
Heterogeneous pass-through across sectors

21. 21