Aid-for-Trade on exports - World Bank Internet Error Page

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Aid-for-Trade and Export
Performance:
The Case of Aid in
Services
Esteban Ferro, Alberto Portugal
& John S. Wilson
7 December 2010
The World Bank
1
Outline
1.
2.
3.
4.
5.
Motivation
Literature review
Identification strategy.
Data and Results
Final Remarks
2
2
1. Motivation


Aid for Trade (AfT) is a “high level” initiative initiated by the
WTO/OECD:
“Aid for Trade aims to help developing countries,
particularly least-developed countries, develop the traderelated skills and infrastructure that is needed to implement
and benefit from WTO agreements and to expand their
trade”.
Scant evidence on the impact of AFT on export
performance in developing countries.
3
Aid for trade popular among donors and
multilateral agencies…
1st Global Review of Aid-For-Trade (Geneva
2007)
Heads of multilateral agencies:
From left to right: Luis Alberto Moreno, IADB - Edouard Dayan, UPU - Dominique Strauss-Kahn, IMF - Rajat Nag, ADB - Patricia Francis,
ITC - Abdoulie Janneh, UNECA - Pascal Lamy, WTO - Angel Gurría, OECD - Valentine Rugwabiza, WTO - Kemal Dervis, UNDP - Robert
Zoellick, World Bank - Juan Somavia, ILO - Donald Kaberuka, AfDB
4
AFT through Time
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
0
5,000
10,000 15,000 20,000 25,000
Aid for Trade (1990-2008)
AFT_infrastructure
AFT_regulation
AFT_capacity
Source: estimates from OECD-CRS database.
5
Correlation of AFT and Exports (1)
25
30
20
Industry Aid vs. Industry Exports (1990-2008)
25
20
20
15
Fitted values' R =0.171
15
ln_aid
10
10
2
5
5
ln(exports)
15
ln(exports)
25
30
AFT_Total vs. Exports (1990-2008)
5
10
15
20
ln_aid
2
Fitted values' R =0.033
6
Correlation of AFT and Exports (2)
Total AFT/GDP vs. Exports/GDP (2008)
8
30
AFT_Total vs. Exports (2008)
BLZ
7
CHN
MYS
GNQ
TTOAGO
LBY THA
OMN
BRB
ATG
KNA
LBR
VUT
GUY
5
6
PNG
VNM
SLB
TGO
CRI
GAB
SUR
TCD
GIN
SYC
NGA
CHL
DZAECU
PHL
HND
NIC VCT
ZAF
SWZ TUN BOL CIVLSO
CHN
ZAR
IDN
ATG
PRY
MOZ
DJI
PAN
JOR
MEX
ZMB
GHA DMA
LAO
ARG
SDN
PER
CMR
MAR
URY
MUS
NAM
GTM
LKA
BWA INDFJI
BRB
SLVEGY
JAM
SLE
COL
BGD
KEN
TUR
MDV
BTN
BRA
WSM
KNA DOM
KIR
SEN
MDG
PAK
LCA
LBN
TZA
BEN
CAF
MWI
NPL
UGA
COM
GMB
GRD
BFA
RWA
TON
NER
4
20
OMN
TTO GNQ
ln(exports / GDP)
25
MEX
MYS
BRATHA
IDN IND
TUR
ZAF
ARG
CHL
DZA NGA PHL
AGO
LBY
VNM
COL
PER
EGY
ECU
MAR
CRI
TUNPAK BGD
SDN
COG
GAB GTM DOMPNG CIVLKA
URY PAN
JORHND
BOL KEN
CMR
PRY
TCD
GHA
SLV
ZMB
ZAR
MOZ
LBN
JAM NIC
BLZ
MUSBWA
NAM
GIN LAO
TGO SEN TZA
SUR
SW Z
GUY LBR
NPLMDG UGA
FJI
BEN
LSO VUT
SYC
BFA
SLB
MWI
SLE
DJI
VCT
NER
MDV
RWAMLI
CAF
BTNGNB
LCA
DMA
WSM
BDI
GMB
CPV
GRD
COM
COG
TONKIR
BDI
CPV
MLI
3
15
GNB
12
14
16
18
20
22
0
1
ln_aid
2
Fitted values R =0.151
2
ln(aid / GDP)
3
4
2
Fitted values R =0.067
Potential reverse causality: does Aid cause exports?
or does exports cause Aid?
7
code/ sector name
Infrastructure
210 Transport & Storage
220 Communications
230 Energy
Production Capacity
240 Banking & Financial Services
250 Business & Other Services
311 Agriculture
312 Forestry
313 Fishing
321 Industry
Agro-industries
Wood industries
Textiles
Chemicals
Non metallic products
Basic Metals
Non-ferrous metals
Machinery
Transport equipment
Energy manufacturing
Industrial policy, , R&D
322 Mineral Resources & Mining
Trade Policies and Regulations
Total
1990-2008
2008
Disburs. (USD mill) Disburs. (USD mill)
114,118
57%
13,112
51%
61,633
31%
7,494
29%
7,508
4%
461
2%
44,977
22%
5,157
20%
82,101
41%
11,982
46%
13,053
7%
2,892
11%
9,319
5%
1,943
8%
32,163
16%
4,668
18%
4,567
2%
534
2%
2,836
1%
341
1%
15,561
8%
1,362
5%
821.20
0.4%
86.16
0.4%
240.26
0.1%
2.48
0.0%
100.39
0.1%
9.86
0.0%
2,125.18
1.1%
45.27
0.2%
324.50
0.2%
0.84
0.0%
253.02
0.1%
1.87
0.0%
28.45
0.0%
0.27
0.0%
352.35
0.2%
22.90
0.1%
622.52
0.3%
2.76
0.0%
670.49
0.4%
1.45
0.0%
8,681.74
4.7%
844.20
3.8%
4,602
2%
241
1%
4,378
2%
795
3%
200,596
100%
25,888
100%
8
2. Literature review
Aid-for-Trade on exports

Helble, Mann & Wilson (2010)

Brenton & von Uexkull (2009)

Cali & Te Velde (2009)
AfT on trade costs (DB: time/container cost,
#documents) :
 Busse et al. (2010):
 Cali and te-Velde (2009)
Aid Effectiveness: large literature, ex

Rajan & Subramanian (2009 & forthcoming)

Brueckner (2010)
9
3. Identification Strategy



Problem: potential reverse causality
 Biased estimates
Potential IV for AFT: civil liberties,
immunization rates, gender health access?
 IV at country level.
 Limited instruments.
Identification strategy:


exploit Aid on services.
use US I-O data on intensity of services on
downstream goods.
10
Estimation
ln Exp ijt   ij   it   jt 

k

 k ServiceInt ensity ki  ln AFTService kjt
  ijt
i: industry (Agro-ind,
Wood-ind, Textiles,
Chemicals, Non metallic
prod., Basic Metals, Nonferrous metals, Machinery,
Transport Equip.)
j: exporter( aid recipient):
106 countries
Total requirement of
services k in dollar of
manufacture i
Aid in
Services k
k: services (Transport &
Storage, ICT, Energy,
Banking & Financial
Services, Business
Services)
t: year:1990-2008
11

Data

OECD-CRS database: disbursed flows of AFT from 33
donors (including multilateral donors) over 1990-2008.

Input-Output Total Requirement tables
 production required, directly and indirectly, from each industry
& commodity to produce a dollar of final good.
12
Results
Table 1- Impact of aid to services on manufacturing exports
1
ln(trade)
trans_int X aid_trans
ict_int X aid_ict
energy_int X aid_energy
bank_int X aid_bank
2
ln(trade)
3
ln(trade)
4
ln(trade)
0.21
[0.154]
-0.259
[0.383]
0.549**
[0.243]
1.018*
[0.556]
5
ln(trade)
6
ln(trade)
7
ln(trade)
0.13
[0.155]
-0.231
[0.381]
0.817***
[0.169]
-0.959*
[0.569]
0.483*
[0.247]
1.716***
[0.269]
0.912*
[0.560]
2.482***
[0.788]
bus_int x aid_bus
0.351
0.371*
1.349***
[0.222]
[0.220]
[0.334]
Country-Sector Effect
Yes
Yes
Yes
Yes
Yes
Yes
No
Country-Year Effect
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Sector-Year Effect
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Observations
17678
17678
17678
17678
17678
17678
17678
R-squared
0.95
0.95
0.95
0.95
0.95
0.95
0.82
Robust standard errors in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. Dependent
variable is ln( exports). Service sector intensities are estimated using US Total Input Requirements.
13
Results
Table 2- Impact of aid to services on manufacturing exports
Robustness Checks
trans_int X aid_trans
ict_int X aid_ict
energy_int X aid_energy
bank_int X aid_bank
bus_int x aid_bus
Observations
R-squared
Baseline
1
0.13
[0.155]
-0.231
[0.381]
0.483*
[0.247]
0.912*
[0.560]
0.371*
[0.222]
17678
0.95
ARG_Intensities
2
0.015
[0.168]
0.156
[1.493]
0.491***
[0.183]
3.453**
[1.452]
-0.679***
[0.252]
17678
0.95
By income level
Year>1999
3
0.343
[0.267]
-1.617**
[0.807]
0.819**
[0.393]
2.691***
[0.906]
-0.211
[0.342]
9480
0.96
low
4
0.062
[0.361]
0.64
[0.749]
0.575
[0.503]
1.743
[1.095]
-0.371
[0.435]
6298
0.92
mid-low
5
-0.15
[0.290]
-0.417
[0.580]
0.800*
[0.478]
1.457*
[0.809]
0.541
[0.437]
6185
0.96
mid-high
6
0.551**
[0.225]
-1.357**
[0.690]
0.059
[0.333]
0.088
[1.085]
0.856**
[0.414]
3998
0.97
Robust standard errors in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%. Dependent variable is ln(
exports). Service sector intensities are estimated using US Total Input Requirements except for column (2) where Argentina’s Total
Input Requirements are used. All regressions control for country-sector, country-year, and sector-year effects.
14
Final Remarks and Future Research

Extend the input-output linkages to estimate:




Impact of aid on additional upstream sectors
(other than services)
On exports of downstream goods (other than
manufactures)
Implement the identification strategy with
country-specific Input-Output matrices.
Additional robustness checks (lags of aid,
samples of countries, years)
15
To be continued…
Many thanks!
16
Identification Strategy
Aid to Service Sectors (Inputs)
210 - Transport and Storage
220 - Communications
230 - Energy
240 - Banking and Financial Services
250 - Business and Other Services
Export Performance in Manufacturing
- Agro-industries
- Wood-industries
- Textiles
- Chemicals
- Basic Metals
- Non-Ferrous Metals
- Machinery
- Transport Equipment
- Non-metallic mineral products
17
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