Meeting User needs cost-effectively Toward increased coherence in the international Trade by Enterprise Characteristics (TEC) framework

1. Meeting User needs cost-
effectively
Toward increased coherence in the international
Trade by Enterprise Characteristics (TEC) framework
Nordic Statistical Association 2013
14th – 16th august 2013

2.  Increased user-demands for trade data disseminated at the
micro-level
 The question is not solely “what do countries trade?” but “what
kind of enterprises is behind that trade?” (size, activity,
ownership etc.)
 Respond: the Trade by Enterprise Characteristics (TEC)
database since 2005
 Links micro-data from ITGS with the Statistical business
register (SBS), however:
 Despite high degree of coherence, several methodological
challenges remain unsolved
 Services are not included but STEC-database in pipeline
Short introduction and outline
2

3.  The paper include two different issues regarding
Trade by Enterprise Characteristics
 This presentation will present these two issues
independently:
1. The issue of complex enterprises and estimated trade
2. The issue of adapting the TEC framework to the ITSS
Short introduction and outline
3

4.  SBR’s handling of complex enterprises is insufficient
for this purpose
 “Complex enterprises” identified by use of the
superior number (UHO-system) which is unique to
the Danish ITGS
 The UHO system provides an automated method for
identifying complex enterprises by providing a
linkage of legal units that are financially interrelated
(“enterprise group”) through the allocation of a
superior number (UHO-number).
Treatment of complex enterprises
4

5.  508 complex enterprises (out of ~8000 enterprises)
with 1986 legal numbers
 26 pct. of total exports, 22 pct. of total imports
 Most have only two legal numbers (291) but 58 have
more than 5 legal numbers
 These complex enterprises often report trade on a
legal number with no or very few employees; and
often legal units within the same complex enterprise
have many employees but no trade
→ A lot of trade is matched with a “wrong” legal
number in the SBR
Treatment of complex enterprises
5

6.  Suggested solution
The high-number of complex enterprises combined
with a relatively low number of “very complex
enterprises” suggests that a two-string approach
combining an automated process with a manual
“check-and-adjust” follow-up on the most
complicated enterprises is appropriate
Treatment of complex enterprises
6

7. Step 1: Establish the link between traders and enterprises on a monthly basis.
Step 2: Use the one-to-one and many-to-one linkages to calculate the median
trade M (import and export taken together) per person employed per
activity group.
Step 3: For all traders in one-to-one or many-to-one linkages between traders
and enterprises allocate monthly trade to the one and only identified
enterprise.
Step 4: For all enterprise in one-to-many linkages between traders and
enterprises calculate an estimated trade E by multiplying M with the
number of persons employed by the enterprise.
Step 5: For all traders in one-to-many linkages between traders and
enterprises allocate trade proportionally to E over all identified
enterprises.
Treatment of complex enterprises
7

8.  ~10 pct. of the total sum of estimated trade is
allocated to specific UHO-numbers, i.e. estimated
trade is currently impossible to allocate to the
enterprise level
 The estimation-process as such is based on
individual UHO-numbers…
 …but the subsequent allocation of estimated trade to
specific countries and goods is not, which impedes
the allocation of such trade to individual enterprises
Allocation of estimated trade to
appropiate legal numbers
8

9.  Allocation of estimated trade to the enterprise-level
should be secured through an improvement of the
current system for allocation of estimated trade to
specific countries and goods.
 When all estimated trade is allocated to specific
UHO-numbers, it can then be allocated further to
legal units by the automated process.
Allocation of estimated trade to
appropiate legal numbers
9

10.  Conclusions
 The issues of complex enterprises and allocation of
estimated trade when compiling TEC data need to be
addressed to secure a more robust TEC statistics
 Not least seen in the light of new data requirements (export
intensity and more detailed classification by activity sector)
Complex enterprises and estimated
trade
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11.  Different sources in the ITGS and the ITSS
 …leads to new challenges
 Distributing estimated trade to enterprises not included in
the sample
 Representivity of population
Adapting TEC framework on the ITSS
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12.  Short presentation of the sources for the ITSS
Adapting TEC framework on the ITSS
12
ITS survey
Travel
statistics
ITGS
Other sources
ITSS
Total population
~40.000 enterprises
Survey
~1.500
enterprises

13.  Trade reported by ~1500 enterprises in the ITS
survey can be linked with SBR
 Covers roughly 80 pct. of total service trade
 Represent around 40000 enterprises
 Other sources cannot be linked with SBR
 Some cannot be linked due to the current method
- E.g. ITGS, government services and some insurance services
 Other due to nature of the transaction
- Mainly the travel account
Adapting TEC framework on the ITSS
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14.  A closer look at the ITS survey
 Directly reported trade covers ~85 pct. of the total trade in
the ITS survey (~68 pct. of the total ITSS)
 ~15 pct. has to be distributed to the rest of the population,
i.e. the ~38500 enterprises (40000 – 1500)
 No correlated administrative data source available to help
distribute the estimated trade
 Using a non-correlated variable, such as employees, has
certain drawbacks
- No “zero reporters” since all enterprises have employees
- Variance from the non-correlated variable is inherited by the ITS
Adapting TEC framework on the ITSS
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15.  What you cannot do when distributing with a non-
correlated variable
 Count the number of enterprises engaged in ITS
 Classify ITS by the non-correlated variable (e.g. by size if
number of employees are the non-correlated variable used
for the distribution of trade)
 Classify ITS by other variables that are highly correlated
with the variable used for the distribution of trade
 What you can do
 Classify trade on a more aggregated level that are not highly
correlated with the variable used for the distribution of trade
Adapting TEC framework on the ITSS
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16. Adapting TEC framework on the ITSS
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ITS survey – Trade by activity for 2010
NACE rev. 2 Import Export
Division Mill. DKK
A Agriculture, forestry and fishing 720 076 1 149 996
B Mining and quarrying 2 127 235 1 075 557
C Manufacturing 28 099 256 29 167 990
D Electricity, gas, steam and air conditioning supply 1 830 779 2 025 810
E Water supply; sewerage, waste management and remediation activities 102 853 250 789
F Construction 679 574 373 834
G Wholesale and retail trade; repair of motor vehicles and motorcycles 12 326 885 21 171 280
H Transportation and storage 135 667 463 193 802 038
I Accommodation and food service activities 523 956 C
J Information and communication 15 613 411 15 137 626
K Financial and insurance activities 9 668 767 6 386 485
L Real estate activities 1 073 651 518 929
M Professional, scientific and technical activities 8 843 855 13 190 761
N Administrative and support service activities 9 083 828 5 571 938
O Public administration and defence compulsory social security 2 739 659 1 345 873
P Education 475 920 221 081
Q Human health and social work activities 25 798 274 022
R Arts, entertainment and recreation 368 794 303 333
S Other service activities 253 755 303 107
U Activities of extraterritorial organisations and bodies C C
Unknown acitvity 3 900 061 4 496 905

17.  ITS survey updated roughly every 5 years
 Population is ”frozen” at a given year (current population is
from 2007)
 Mergers, exit, and entry change the composition of the
population over time
Adapting TEC framework on the ITSS
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Matching ITSS population with SBR
Enterprises not found in SBR 2010 3.710
Total number Enterprises in 2007 snapshot 40.653
Enterprises in SBR 2010 not represented by ITSS population 4.501
Enterprises matching SBR 2010 and ITSS population 35.063
Share of total enterprises in 2007 snapshot 86,2 %

18.  Conclusions
 ~68 pct. of the Danish ITSS can be directly linked with SBR
and produce unbiased TEC statistics
 ~12 pct. can be indirectly linked using a non-correlated
variable and can be used to produce some TEC statistics on
a more aggregated level depending on the variable used
 ~20 pct. cannot be linked with the SBR due to
methodological issues or by the nature of the trade
 ITS survey loses representivity over time but the effect is
quite small (1.3 pct. of total trade in 2010)
Adapting TEC framework on the ITSS
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