The use of trade data at the firm level for
the analysis of Global Value Chain (GVC)
WPTGS
Part II – Trade, Globalisation and competitiveness
6 October 2010
OECD, Paris
Natale Renato Fazio, Stefano Menghinello, Carmela Pascucci and
Carla Sciullo
“Foreign trade and multinational enterprises statistics” Division
ISTAT
ITALY
Structure of this presentation
….Global Value Chains (GVS) have emerged as a new analytical
framework for a better understanding of the Globalisation of the
industry…………but can we measure them?
HOW FOREIGN TRADE DATA AT THE FIRM LEVEL
CAN CONTRIBUTE TO A QUANTITATIVE AND IN
DEPTH ASSESSMENT OF GVCs?
List of issues covered by this presentation
• The measurement issue in GVC analysis
• The role played by foreign trade aggregated figures
versus firm level data
• Is it feasible to develop GVC analysis using firm level
foreign trade data?
• Some empirical examples
• Conclusions
The measurement issue in GVC analysis
Global Value chain (GVC) has emerged in the business literature as a new
analytical framework. It clearly shows that not only multinational enterprises
(MNEs) but also specialised suppliers are key actors of global production
fragmentation
 It is closely linked to the globalisation of production filieres, international
networks of production, etc. Indeed, this concept is very sophisticated and
complex, since it also includes dimensions like market power, global
governance, etc
 It is an intrinsically dynamic and genuinely firm level concept:
“companies compete by continuously reshaping their position inside GVC”
 Measurement of GVC is still an open issue. Aggregated indicators are
based on foreign trade data and input output tables. Much of the firm level
empirical evidence is based on qualitative assessment (case studies) or is
model based with “weak” proxy variables.
The role played by foreign trade aggregated figures
versus firm level data
International trade data play a crucial role as aggregated figures in the
development of GVC indicators
 These indicators are based on intra-industry trade, intra-firm trade,
intermediates trade, trade unit values.
 However, these aggregated indicators cannot support more analytical and
complex analysis addressing strategic issue like “moving up in a GVC”
 Firm level foreign trade data can support more complex and flexible
analysis of GVC based on a “trade operator” perspective
 In particular, “trade operator” data are very detailed (single transaction data
including good characteristics, partner country) and can be linked to business
characteristics (business register) and economic performance indicators
(Structural business statistics micro-data). Information on the foreign “trade
operator” non resident partner is also a crucial asset to improve our
knowledge of GVC
 The analysis of GVC exclusively based on foreign trade operators data is
limited to “a truncated production network” where a resident company is
engaged in trade linkages with foreign companies only as direct GVC
partners.
Is it feasible to develop GVC analysis using firm level
foreign trade data?
Most EU member states have already developed figures on trade operator
business characteristics. There is an ongoing Eurostat project with the goal
of harmonising and expanding figures on business characteristics of trade
operators. Some key non EU OECD countries, like US, have already
developed similar figures.
The basic framework to develop these new figures, based on the link
between the trade operators register and the business register on all active
resident companies, is usually available in most OECD countries.
 Further information can be exploited from this framework and finalised
to the analysis of Global Value Chains
 A short-medium term goal can be the development of new figures on
trade operators characteristics finalised to measure companies potentially
engaged in GVCs: This is essentially a data reclassification problem
 A long term goal will involve more analytical analyses of firm level foreign
trade data addressing issues like “market power” and “moving up in a value
chain”
Some empirical examples
The project is still at a very preliminary stage of development. So no
“robust” analytical or policy implications can be inferred from what folllows.
However, preliminary empirical results seem to be very interesting and
can represent a relevant asset for the empirical analysis of GVC
 As a first step, we have essentially reclassified trade operators linked to
business register characteristics grouping trade flows by MIG. Different
business profiles of trade operators emerge from this analysis based on trade
characteristics from both export and import sides.
We focus on medium and large size companies (50 plus person
employed) actively engaged in external trade of intermediate goods from
both exports and imports. We assume that these companies are potentially
engaged in GVC
 We further expand this very preliminary analysis based on the dynamic of
firm level export and import unit values for a sample of companies
potentially engaged in GVC.
Italian medium and large size firms potentially engaged in
Global value chains
( companies active in trade of intermediate goods from both exports and
imports as a share of total M-L size companies active in exports trade)
MIGS_EXPORTS
MIGS_IMPORTS
Capital
Consumer
Consumer non
goods
durable goods
durable goods
0,0
0,0
0,0
Energy
0,2
Intermediate
goods
0,0
Intermediate goods
0,1
30,3
1,5
0,2
Capital goods
0,0
6,7
13,3
Consumer durable
goods
0,0
1,9
Consumer non
durable goods
0,0
Other
TOTAL
Energy
TOTAL
Other
0,0
0,2
1,2
8,1
41,4
0,2
0,3
8,9
29,4
0,3
2,0
0,2
3,5
7,9
3,2
0,3
0,0
11,4
5,6
20,5
0,0
0,1
0,3
0,0
0,0
0,3
0,6
0,3
42,2
15,7
2,4
13,0
26,3
100,0
Large and Medium size Italian firms active in trade in
intermediate goods by number of foreign resident trade
partners (intra-EU trade only)
IMPORT
1-3
4-5
6-10
11-20
21-49
>50
TOTAL
1-3
1,4
0,6
1,5
0,9
0,3
0,1
4,8
4-5
0,8
0,4
1,2
0,7
0,3
0,1
3,4
EXPORT
6-10
11-20
0,9
1,0
0,9
1,6
2,3
3,5
2,2
4,2
1,1
2,3
0,1
0,5
7,6
13,3
21-49
1,7
1,8
6,1
8,1
5,7
1,6
25,1
>50
TOTAL
2,1
7,9
3,3
8,6
9,2
23,8
14,5
30,8
12,8
22,6
3,8
6,3
45,7
100,0
Firm level dynamic of export and import unit values for a
sample of Italian LM size firms potentially engaged in
GVS
(unit value of the combined nomenclature code that is dominant
from the export side in firm level trade of intermediate goods)
EXPORT VMU growth
Negative
Positive
Total
IMPORT VMU growth
Negative
Positive
21,3
22,6
22,0
34,0
43,4
56,6
Total
43,9
56,1
100,0
Firm level dynamic of export and import unit values for a
sample of Italian LM size firms potentially engaged in
GVS
(unit value of the combined nomenclature code that is dominant
from the export side in firm level trade of intermediate goods)
EXPORT VMU
growth
Negative
Positive
Total
VMU GAP (EXPORTS-IMPORTS)
growth
Negative
Total
Positive
35,1
16,0
51,2
8,8
40,0
48,8
43,9
56,1
100,0
Conclusions
 Firm level foreign trade trade can significantly contribute to the empirical
analysis of global value chains.
 Most OECD countries have already set up a statistical framework for the
production of statistics on trade operators business characteristics.
 Based on an agreed methodology, additional figures focusing on companies
potentially engaged in GVC can be easily developed from this framework as a
data reclassification work
 More analytical work can be done based on firm level trade data in order to
explore complex issues like “moving up in a GVC”
 Further developments in this area will include additional linkages between
the register of foreign trade operators with both national based (SBS data and
economic accounts from administrative data sources) and international data
sources (for instance ORBIS for foreign resident trade partner characteristics
and performance indicators). So we can link firm level trade data (including
unit values) with value added….........