Balanced trade in services methodology

1. THE OECD-WTO BALANCED
TRADE IN SERVICES
DATASET (BATIS)
Regional-Global Trade in Value Added Webinar, June 2021
Antonella Liberatore
Trade and Productivity Division
OECD Statistics and Data Directorate

2. Building BATIS - outline
Data
collection
• Data collection & cleaning
Data
estimation
• Back-casting, forecasting, interpolations to
fill in partially-reported series
• Gravity-model based estimates for
completely missing information
Overall
consistency
• Rescaling to reported world totals, RAS-ing
Trade
balancing
• Symmetry-index weighted average of
reported and mirror flows
• First OECD-WTO BATIS
dataset published in 2017
(BPM5)
• Second BATIS dataset
published in 2021
• 202 reporters and
partners
• 12 service items
(BPM6)
• 2005-2019
2

3. Building BATIS: TOP-DOWN approach
3
Total services
with partner
world
Service items
with partner
world
Total services
at bilateral
level
Service items
at bilateral
level
TOTAL SERVICES
1. Manufacturing services on inputs owned by
others
2. Maintenance and repair services
3. Transport
4. Travel
5. Construction
6. Insurance and pension services
7. Financial services
8. Charges for the use of intellectual property
9. Telecommunication, computer and
information services
10. Other business services
11. Personal, cultural and recreational services
12. Government goods and services n.i.e.

4. 1) Data collection and cleaning
Source data 1: world dataset
4
World trade in services (average of exports and imports)
• Data with partner world
comes from the WTO-
UNCTAD-ITC trade in
services dataset (primary
sources: Eurostat, OECD,
IMF, national sources)
• Includes some estimations,
adjustments and corrections
• This dataset provides the
‘boundaries’ for Batis
0
1000
2000
3000
4000
5000
6000
7000
bn
USD
reported estimated

5. 5
Share of bilaterally specified trade
Total services
2018: 66%
2005: 32%
(Figures refer to the average of exports and imports)
1) Data collection and cleaning
Source data 2: bilateral dataset
Sources for bilateral data:
• OECD – Trade in services by
partner country
• Eurostat (annual trade in services
dataset + quarterly BoP)
• National sources (including ad-
hoc info – e.g. for travel)
• UNSD - UN Service Trade

6. Government
6
Manufacturing Maintenance Transport
Travel Construction Insurance
Financial services IP services Telecoms...
Business services Personal, cultural...
bilaterally specified trade as % of world total, 2018
1) Data collection and cleaning
Problems with the reported bilateral data
A) Low coverage B) Asymmetries
% points
asymmetry = 0 8.6
asymmetry below 5% 7.4
asymmetry between 5 and 30% 30.9
asymmetry above 30% 38.4
one flow is zero, the other isn't 14.5
inconsistent signs 0.2
𝑎𝑠𝑦𝑚𝑚𝑒𝑡𝑟𝑦 =
=
𝑎𝑏𝑠(𝑣𝑎𝑙𝑢𝑒 −𝑚𝑖𝑟𝑟𝑜𝑟 𝑣𝑎𝑙𝑢𝑒)
𝑣𝑎𝑙𝑢𝑒+𝑚𝑖𝑟𝑟𝑜𝑟 𝑣𝑎𝑙𝑢𝑒
* 100

7. 1) Data collection and cleaning
Asymmetries in the world dataset
7
Exports and imports of travel
and other business services well
aligned at world level
• Transport imports >> exports
• Financial services imports << exports
• Insurance imports >> exports

8. • All negative values except for insurance removed
• Ad-hoc correction for negative insurance
– (a few) implausible values removed
– “Plausible” cases:
• reported negative flows set to zero and total services recalculated
accordingly
• for the trading partner, the corresponding amounts are added to the
mirror flow and total services are recalculated
• Inconsistencies between total services and subcategories
removed
1) Data collection and cleaning
Data cleaning
8

9. 1) Data collection and cleaning
Data cleaning – treatment of negative insurance
REPORTED
Exports of France from
Ireland
Imports of Ireland from
France
Total services 4537 2792
Insurance -263 634
Example of correction for negative insurance - trade between France and Ireland, 2015
(values in million USD. Source: Eurostat.)
CORRECTED
Exports of France from
Ireland
Imports of Ireland from
France
Total services 4799 3054
Insurance 0 897
• Corrections explicitly flagged (E6)
• At the balancing stage, the imputed zero values are given low weight
9

10. 2) Data estimation
Partially reported information
10
• Derivations (parent-
child relationships)
• Back-casting,
nowcasting and
interpolation to fill
partially reported time
series
reporter partner flow indicator year value methodology
ITA ESP IMP S 2005 4361 E8.2
ITA ESP IMP S 2006 4895 E8.2
ITA ESP IMP S 2007 5819 E8.2
ITA ESP IMP S 2008 6411 E8.2
ITA ESP IMP S 2009 5166 E8.2
ITA ESP IMP S 2010 4954 R_EURO
ITA ESP IMP S 2011 5702 R_EURO
ITA ESP IMP S 2012 4749 R_EURO
ITA ESP IMP S 2013 4433 R_EURO
ITA ESP IMP S 2014 4840 R_EURO
ITA ESP IMP S 2015 4283 R_EURO
ITA ESP IMP S 2016 4375 R_EURO
ITA ESP IMP S 2017 5106 R_EURO

11. 2) Data estimation
Completely missing time series: gravity models
𝑿(𝑴)𝒊𝒋𝒕 = 𝒆𝒙𝒑 𝜷𝟎 + 𝜷𝟏 𝒔𝒊𝒛𝒆𝒊𝒕 + 𝜷𝟐𝒔𝒊𝒛𝒆𝒋𝒕 + 𝜷𝟑 𝒕𝒓𝒂𝒅𝒆 𝒄𝒐𝒔𝒕𝒔𝒊𝒋 + 𝜷𝟒𝒐𝒕𝒉𝒆𝒓 𝒑𝒓𝒆𝒅𝒊𝒄𝒕𝒐𝒓𝒔𝒊𝒋𝒕 ∗ 𝜺𝒊𝒋𝒕
• Exports (imports) of total services modeled to depend on:
– Size of the two trading partners, proxied by their nominal GDPs
– Trade cost variables (distance, contiguity, colonial relationship, common language)
– Linear time trend
– Additional independent variables used to improve the predictive power of the models
• Trade in services with partner world (in the corresponding category)
• Total bilateral merchandise exports (imports)
• Tourist arrivals (departures)
• Reporter’s GDP per capita (as proxy for reporter FE)
• Partner FE
• Poisson pseudo-maximum likelihood estimator used (PPML)
• Reduced models used when additional independent variables are not
available
11

12. 2) Data estimation
Completely missing time series: estimation strategy
12
Full model
(M1.1)
Reduced
model
(M1.2)
Reduced
model
(M1.3)
Reduced
model
(M1.4)
Reduced
model
(M1.5)
Distance X X X X X
Contiguity X X X X X
Common language X X X X X
Colony X X X X X
GDP reporter X X X X X
GDP partner X X X X X
GDP per capita (reporter) X X X X X
Trade in services with world X X X X X
Merchandise trade (bilateral) X X
Tourist arrivals/departures X X
Time trend (linear) X X X X X
Partner FE X X X X
Exports
% of total estimated observations 54.2 1.6 35.2 6.2 2.8
% of total estimated value 77.9 0.1 21.2 0.4 0.4
Imports
% of total estimated observations 10.6 45.4 6.0 35.3 2.8
% of total estimated value 22.6 52.2 10.0 14.8 0.4
Summary of the model specifications for the prediction of missing total services

13. 13
2) Data estimation
Completely missing time series: cross validation
• Sample randomly split into training set
(70%) and the test set (30%)
• Models fit on the training set and then
coefficients used to predict the test set
• Prediction accuracy measured by the
mean absolute error (MAE)
• ‘priors’ confirmed by the exercise: the
full model (preferred specification)
M1.1 better predicts trade on average
• Accuracy of all models improves when
trade with partner world is included
(bottom panel)

14. • Gravity models are deliberately parsimonious and do not include
any policy variables among the predictors
• Separate models are run for each flow and service category
• Only one model was used for each country pair
• Choice of the model driven in general by data availability in the
matrix of regressors, but expert judgement used in some specific
cases
– If merchandise trade too erratic/concentrated in energy products =>
excluded
– If partner fixed effects based on very few, quite specific bilateral
relationships => excluded 14
2) Data estimation
A few more comments on the gravity estimations

15. Reported and estimated figures in the bilateral dataset,
exports and imports, 2005-2019
Total services 12 sectors
% value % count % value % count
Reported 55.9 10.2 49.2 3.3
Derivations from reported data 0.3 1.2 0.2 24.4
Corrections 0.4 0.0 0.0 0.0
Interpolations, back and
nowcasting
16.8 8.7 16.8 2.6
Gravity model estimates 26.5 79.9 33.8 69.6
TOTAL 100.0 100.0 100.0 100.0 15
2) Data estimation
Creating a complete matrix

16. 3) Ensuring overall consistency
Rescaling & RASing
1. Rescaling to the reported world totals
1. No bilaterals reported: gravity model predictions rescaled to fit with
reported world totals
2. (Some) bilaterals reported, consistent with world totals: reported values
kept as such, additional estimates rescaled
3. (Some) bilaterals reported, but NOT consistent with world totals:
reported values and additional estimates rescaled
2. Final bi-proportional rescaling (RAS) to eliminate any residual
discrepancy and ensure complete internal consistency of the
export and import matrices
16

17. • Balanced value = weighted average of
reported and mirror flow:
1. First-layer weighing based on a symmetry index
• a measure of how much a country ‘agrees’ on average
with its trading partners (varies by exporter,
importer, year, flow and item)
• NEW calculation method developed in cooperation
with Eurostat-Figaro team
2. Second-layer weighing takes into account the
quality of the estimates (reported data > back-
forecasting > gravity models)
• Total services balanced first, then
individual categories balanced in terms of
shares to ensure consistency
17
Symmetry indices, total services exports,
selected leading traders
0.5 0.6 0.7 0.8 0.9 1.0
BRA
LUX
IND
NLD
BEL
SWE
CHN
IRL
KOR
AUT
CHE
ITA
FRA
GBR
CAN
DEU
USA
JPN
AUS
ESP
2005
2018
4) Balancing
Methodology

18. 4) Balancing
Illustration
18
reporter partner
value
export
methodology symmetry index
methodology
weight
A B 10 reported 0.8 1
reporter partner
value
mirror
methodology symmetry index
methodology
weight
B A 20 gravity 0.4 0.5
𝐵𝑎𝑙𝑎𝑛𝑐𝑒𝑑 𝑣𝑎𝑙𝑢𝑒
10 ∗ 0.8 ∗ 1 + (20 ∗ 0.4 ∗ 0.5)
0.8 ∗ 1 + (0.4 ∗ 0.5)
= 12

19. Reported vs balanced trade, leading economies
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
IND LUX KOR BEL CAN FRA SWE IRL CHN JPN AUT ESP BRA NLD GBR ITA USA DEU AUS CHE
Balanced/Reported
imports exports
balanced
>
reported
balanced
<
reported
Total services, 2005-2019
19

20. • Disseminated via searchable databases: OECD and WTO
• Or bulk data download (OECD and WTO):
– Data file
– Codes file
– Methodological paper
BATIS: how to access and interpret the data
20
Reporter Partner Flow Item Year Reported_value Final_value
Final_value_
Methodology
Balanced_value
A B IMP S 2019 180M1.1 135
B A EXP S 2019 100 120R_NAT 135
Reported After adjustments
Estimated
After balancing
Source or
estimation
method

21. • Reported, final and balanced values
– Final values are consistent with what
published at national level with partner
world
– Balanced values considered as the best
possible quantification of the true trade
flows
• Caution around the use of estimates
(e.g. shall I use the values estimated via
gravity in another gravity model?)
– Robustness checks are encouraged (e.g. start
will all observations and filter out estimates
(coded “E_”) and/or model predictions
(coded “M_”): do the results hold?)
Use of BATIS
21
0
10
20
30
40
50
60
70
80
imports exports
bn
USD
Bermuda, total services,
(2018)
reported balanced

22. • Future updates
– Biannual releases
– More detailed sectoral breakdown?
– Mode of Supply dimension?
• Ongoing work on facilitating bilateral meetings to tackle
asymmetries at the source
• Any effort at national/regional level can be absorbed in Batis
Questions/feedback: Antonella.Liberatore@oecd.org
Steen.Wettstein@wto.org
Next steps
22

23. 1. Bilateral asymmetry indicator computed as
𝐴𝑖𝑗𝑘𝑡 =
| 𝑋𝑖𝑗𝑘𝑡 − 𝑀𝑗𝑖𝑘𝑡|
𝑋𝑖𝑗𝑘𝑡 + 𝑀𝑗𝑖𝑘𝑡
2. Asymmetry index computed for each exporter i, importer j, service category
k and year t as the trade-weighted average of the bilateral asymmetry
indicator
𝜃𝑖𝑘𝑡 = σ𝑗 𝐴𝑖𝑗𝑘𝑡
𝑋𝑖𝑗𝑘𝑡+𝑀𝑗𝑖𝑘𝑡
σ𝑗(𝑋𝑖𝑗𝑘𝑡+𝑀𝑗𝑖𝑘𝑡)
and 𝜑𝑗𝑘𝑡 = σ𝑖 𝐴𝑖𝑗𝑘𝑡
𝑋𝑖𝑗𝑘𝑡+𝑀𝑗𝑖𝑘𝑡
σ𝑖(𝑋𝑖𝑗𝑘𝑡+𝑀𝑗𝑖𝑘𝑡)
3. 3-year moving average of the complement to 1 of the asymmetry index
(symmetry index) used as weight to derive the balanced trade value
𝑆𝐼𝑖𝑘𝑡 = 1 − 𝜃𝑖𝑘𝑡 and 𝑆𝐼𝑗𝑘𝑡 = (1 − 𝜑𝑗𝑘𝑡)
23
Annex: the balancing procedure in more detail (1/2)

24. 4. Second-layer weighing based on the quality of the estimation methods
• w=1 for reported data
• w=0.75 for high quality estimates (back-forecasting, interpolations)
• w=0.5 for gravity model estimates
• w=o.25 for reported data that are considered implausible or incorrect
5. Final balancing formula
𝑇𝑖𝑗𝑘𝑡 =
𝑆𝐼𝑖𝑘𝑡 ∗ 𝑤 ∗ 𝑋𝑖𝑗𝑘𝑡 + 𝑆𝐼𝑗𝑘𝑡 ∗ 𝑤 ∗ 𝑀𝑗𝑖𝑘𝑡
𝑆𝐼𝑖𝑘𝑡 ∗ 𝑤 + 𝑆𝐼𝑗𝑘𝑡 ∗ 𝑤
NB: procedure applied to total services first, then to service categories in terms of
shares:
I. Calculate the share of each individual service category in the (unbalanced) total services flows
II. Balance those shares at bilateral level using above procedure
III. Apply the balanced shares to the balanced value for total services
24
Annex: the balancing procedure in more detail (2/2)