Interdependence of Preferential
Economic Policies across
Subjects
Peter Egger* & Georg Wamser
* ETH Zürich, CEPR
Workshop on PTAs and the WTO: A New Era
WTO, November 04, 2010
Motivation
Many Economic Integration Agreements
affect services; directly or indirectly:
• Some Goods Trade Agreements (customs
unions; free trade areas; single market
programme)
• Specific Service Trade Agreements under
auspices of WTO (economic integration
agreements; GATS commitments)
• Bilateral Investment Treaties
• Bilateral Tax Treaties
• Currency Unions including Pegs
A Snapshot of EIAs for 2005
Type of agreement
% of pairs
GTA
11.60
STA
11.62
DTT
20.54
BIT
6.27
CUP
2.73
Altogether, there are 124 countries and 7,873
pairs.
A Snapshot of EIAs for 2005
Countries
with/and
GTA
STA
BIT
DTT CUP None
GTA
STA
5.5
BIT
1.9
1.6
DTT
6.0
4.4
5.3
CUP
0.9
0.9
0.4
1.4
None
3.8
5.5
0.5
10.1
1.2
66.5
What’s Behind That Simple Table
Reality is a jungle of EIAs
(Spaghetti Bowl in 5-dimensional space):
25=32 combinations possible
The following ones are most frequent:
Agreements
Frequency (All Years?2005)
G
T
A
S
T
A
B
I
T
D
T
T
C
U
P
# of pairs
% of all EIAs
0
0
0
1
0
0
0
1
0
0
0
1
0
0
1
0
0
0
0
1
0
0
0
0
0
5,238
800
429
300
257
66.53
10.16
5.45
3.81
3.26
Questions
• Determinants of each type of EIA
(economic fundamentals)?
• How is membership correlated given
fundamentals?
• What are consequences of EIAs and their
combination?
• Which outcomes are affected?
This project
Step 1 – Endogenous selection into EIAs:
Estimate probability of a country to select itself
into individual agreements and combinations
thereof (multiple treatment selection)
Step 2 – Estimate treatment effects from
endogenous selection into agreements
and their combinations on:
 Goods trade
 Services trade
 FDI
Some data
Outcomes (bilateral):
Trade in goods
Trade in services
Stocks of foreign direct investment
Sample:
124 countries (124123 pairs)
16 years (1990-2005)
Goods Trade Inside and Outside
Countries
with/and
GTA
STA
BIT
DTT CUP None
else
GTA
STA
4.75
98.2
BIT
5.94
100
6.22
100
DTT
5.67
99.4
6.17
99.3
5.57
98.8
CUP
5.80
98.8
7.20
98.3
5.72
100
6.42
99.6
1.28
-.087
4.81
4.12
1.25
-.377
None
89.0
89.5
96.4
98.2
97.2
71.6
else
Means: log exports (top) and % of exports>0 (bottom).
Service Trade Inside and Outside
Countries
with/and
GTA
STA
BIT
DTT CUP None
else
GTA
STA
5.93
17.3
BIT
4.33
32.0
4.72
26.7
DTT
5.73
20.9
5.90
24.3
4.09
23.9
CUP
6.10
36.5
6.10
49.0
3.41
29.4
5.48
33.2
3.11
0
4.14
4.42
2.34
2.26
None
0.52
0
10.6
9.5
4.4
0.97
else
Means: log exports (top) and % of exports>0 (bottom).
FDI Stocks Inside and Outside
Countries
with/and
GTA
STA
BIT
DTT CUP None
else
GTA
STA
5.67
39.1
BIT
4.13
46.2
5.01
32.3
DTT
5.97
43.9
5.95
47.4
4.30
40.2
CUP
6.56
51.0
6.56
68.5
3.82
36.97
5.62
51.24
2.39
.620
4.55
4.46
3.61
None
7.4
1.8
33.7
27.3
11.9
else
Means: log FDI (top) and % of FDI>0 (bottom).
2.09
3.5
Summary Statistics for Outcome
Outcome
Mean
Std.Dev.
Pairs
Goods trade (US$)
.751
4.12
98,899
P(goods trade>0)
.779
.415
127,019
Service trade (US$)
4.00
2.34
3,548
P(service trade>0)
.083
.169
120,964
FDI stocks (US$)
3.76
3.53
10,538
P(FDI stocks>0)
.083
.276
126,859
Values are expressed in logs.
Correlation Coefficients for Outcome
Outcome (binary)
(G)
(S)
(F)
Goods trade (G)
1.00
-
-
Service trade (S)
0.14
1.00
-
FDI stocks (F)
0.10
0.16
1.00
Outcome (logs)
(G)
(S)
(F)
Goods trade (G)
1.00
-
-
Service trade (S)
0.84
1.00
-
FDI stocks (F)
0.81
0.78
1.00
Multivariate Probit Regressions
Control variables
GTA
STA
DTT
BIT
SumGDPijt
.103***
-.072**
.696***
.474***
.457***
(.028)
(.029)
(.029)
(.036)
(.036)
.110***
.015
.081***
.137***
.237***
(.031)
(.032)
(.026)
(.041)
(.029)
.067**
.337***
-.245****
-.015
-.444***
(.033)
(.034)
(.032)
(.039)
(.041)
-.107***
.042
-.054*
-.096**
-.206***
(.035)
(.036)
(.033)
(.049)
(.046)
-.386***
-.177**
-.068
.806***
.224**
(.080)
(.075)
(.069)
(.119)
(.105)
.049*
.004
-.034
-.357***
-.074**
(.029)
(.027)
(.023)
(.043)
(.032)
.047
.407***
-.220***
-.062
-.158**
(.068)
(.071)
(.058)
(.083)
(.076)
.038
.037
.0003
-.700***
.469***
(.056)
(.051)
(.053)
(.076)
(.073)
-.386***
.122***
-.500***
-.446***
-.228***
(.035)
(.037)
(.031)
(.042)
(.041)
.513***
.300***
-.327***
-.389**
-.040
(.100)
(.116)
(.114)
(.153)
(.144)
.515***
.026
.151**
-.180*
.537***
(.054)
(.061)
(.060)
(.106)
(.060)
SimGDPijt
SumPOPijt
SimPOPijt
SimGDPPCijt
SimGDPPCijt2
Remoteij
Drowklij
Distanceij
Common Borderij
Common Languageij
CUP
Multivariate Probit Regressions
Control variables (cont'd)
CONT
WTO 1
WTO 2
Landlocked 1
Landlocked 2
Cumdurat
Diffyear
D_durable
D_polity 2
GTA
STA
.333***
.492***
(.056)
DTT
BIT
CUP
.087*
-.075
.306***
(.061)
(.052)
(.074)
(.060)
-.243***
.366***
.289***
.853***
.283**
(.071)
(.115)
(.077)
(.190)
(.142)
.218***
.696***
.824***
1.48***
.490***
(.072)
(.116)
(.080)
(.190)
(.147)
.019
-.820***
.090**
.281***
-.156***
(.048)
(.060)
(.044)
(.060)
(.058)
.031
-1.57***
.278**
.585***
-.258
(.112)
(.155)
(.126)2
(.150)
(.177)
-.0001
-.0001
-.0001
-.00001
.00004
(.0001)
(.0001)
(.0001)
(.0001)
(.0001)
.001
-.004
.005
.002
-.003
(.004)
(.004)
(.003)
(.005)
(.006 )
-.006***
-.008***
.004***
.007***
-.002**
(.001)
(.001)
(.001)
(.001)
(.001)
-.016***
(.003)
-.010***
(.003)
-.007***
(.003)
-.002
(.004)
-.002
(.004)
Correlation of Disturbances
Countries
with/and
GTA
STA
DTT
BIT
GTA
STA
.460
DTT
.092
BIT
-.064 -.095 .478
CUP
.031
.025
.079
.024
.003
CUP
Outline of work for the summer
Estimation of treatment effects on outcome
by propensity score matching:
For goods trade, services trade, FDI stocks
each:
• Propensity of positive outcome (ext. margin)
• Log level (int. margin)
Using propensity score matching for
multiple treatments (and estimated
propensities from multivariate probit)
Estimating ATTs
32 EIA combinations (treatments) possible
More than an economist can digest and more
than the econometrician can estimate:
Of the 32 ATTs, 10 are based on more than
1,000 units both in the treatment and control
group
Next table focuses on the ATTs of the most
frequent combinations of “pills taken”
Average Treatment Effects on the
Treated (ATTs)
Treatment
G S
T T
A A
D
T
T
B C
I U
T P
Controls
G S
T T
A A
D
T
T
G-trade S-trade
B C
I U
T P
P Log P
Log
FDI
P Log
0 0 1 0 0 0 0 0 0 0
.061
2.22
.057
1.71
.161
1.570
0 1 0 0 0 0 0 0 0 0
.090
.226
-.003
--
-.016
-1.24
1 0 0 0 0 0 0 0 0 0
.131
1.80
.000
-.061
.037
.970
0 0 1 1 0 0 0 0 0 0
.036
2.90
.188
1.10
.236
1.67
1 1 0 0 0 0 0 0 0 0
.186
2.67
.004
5.26
.157
1.60
Significance:
~ 15%;
~ 10%;
~ 5%;
~ 1%;
~ insignificant.
Foregone Trade and FDI
Suppose every pair would use all modes
corresponds to Average Treatment Effect
(ATE) of “11110” relative to “00000”
World effects (for average/randomly drawn
pair) of
Margin
G-trade
S-trade
FDI
Extensive
.120
.474
.269
Intensive
4.44
1.46
2.53
Conclusions
• Estimated effects pertain to long run
• Short run (conditional on initial state) is
also accessible
• In general: standard errors larger for
intensive margin than for extensive margin
(less observations).
• Int.marg. effects relatively large but
– Estimates pertain mainly to DC-with-LDC.
– Have large standard errors.
Conclusions
• Clearly: more is better for
both ext. and int. margin of outcome
• Ext.-margin of S-trade and FDI depend
more on BIT and DTT than on GTA and
STA
• Policy makers who want to stimulate a
mix of G-trade, S-trade, and FDI will
have to pursue a mix of GTA-STA and
BIT-DTT