Do IMF and World Bank Influence Voting in the UN General Assembly?

1
Do IMF and World Bank Influence Votingin the UN
General Assembly?

• Axel Dreher and Jan-Egbert Sturm
• International Political Economy Society
  Inaugural Conference November 17-18, 2006

2
Is voting in the UN General Assembly important?

• US Department of State (1985, Report to
  Congress) Examining UN votes makes it possible
  to make judgments about whose values and views
  are harmonious with our own, whose values are
  consistently opposed to ours, and whose practices
  fall in between
• Secretary of State letters of instruction to new
  US ambassadors (quoted in Andersen et al., 2004)
  A countrys behavior at the UN is always
  relevant to its bilateral relationship with the
  United States

3
Literature overview
G7
UN Voting
a
d
b
c
IMF / WB
4
Hypotheses

• Cultural and political proximity increases voting
  coincidence
• Countries depending on foreign support are more
  likely to vote in line with G7 countries
• (?) Bilateral foreign aid increases the
  probability that a recipient country votes in
  line with the donor
• Trade flows increase/decrease the probability
  that a country votes in line with its partner
  country
• (?) IMF and World Bank loans increase the
  probability that a recipient country votes in
  line with the institutions major shareholders

5
Main Hypothesis

• (?) IMF and World Bank loans increase the
  probability that a recipient country votes in
  line with the institutions major shareholders
• IBRD International Bank for Reconstruction and
  Development
• IDA International Development Association

IMF World Bank
Concessional net flows amount agreed net flows(IDA)
Non-concessional net flows amount agreed net flows(IBRD)
6
Main Hypothesis

• (?) IMF and World Bank loans increase the
  probability that a recipient country votes in
  line with the institutions major shareholders
• World Bank
• Number of technical loans programs starting
• Number of adjustment programs starting
• Number of other programs starting
• IMF
• Start of EFF and SBA program (non-conc.)
• Start of SAF and PRGF program (conc.)

7
Data

• Years 1970-2002
• Recipient-countries up to 188
• Donor-countries each individual G7 country
  weighted-average G7

8
Comparing inline voting behavior across donor
countries, 1970-2002
CAN
FRA
GBR
DEU
ITA
JPN
USA


Canada (CAN)
0.95
0.96
0.92
0.99
0.97
France (FRA)
0.98
0.91
0.97
0.91
UK (GBR)
0.92
0.97
0.92
Germany (DEU)
0.93
0.89
Italy (ITA)
0.96
Japan (JPN)
United States (USA)
0.79

• Variables corrected for country- and
  year-specific effects
• Each cell based on ca. 5,000 country/year
  observations

9
Voting coincidence across different regions

CAN
DEU
FRA
GBR
ITA
JPN
USA

G7

• Regional classification based on CIA World Fact
  Book

10
Extreme Bounds Analysis

• Estimate equation of the following form Yit
  ?Mit ?Fit ?Zit uit
• Re-specify Z-vector holding M and F constant
• Go through all combinations of the Z vector
• Examine all estimated ? coefficients
• Levine and Renelt (1992) look at extremes
• Sala-i-Martin (1997) look at distribution
• How to specify baseline model (M-vector)?
• General-to-specific methodology (Temple, 2000)

11
Results for baseline model

• Voting coincidence increases when
• cultural and political proximity increases
  (hypothesis 1)
• dependence upon foreign support increases
  (hypothesis 2)

12
Testing the main hypothesis for the G7
IMF

World Bank

13
Testing the main hypothesis for the USA
IMF


World Bank

conc. flows
0.045
IDA flows (conc.)
0.318
(0.36)
(3.25)
conc. flows agreed
0.011
(0.23)
non-conc. flows
0.152
IBRD flows(non-conc.)
0.851
(1.49)
(3.90)
non-conc. flows agreed
0.133
(1.80)
SAF PRGF (conc.)
0.005
techn. projects
0.003
(0.88)
(1.05)
EFF SBA (non-conc.)
0.006
adjust. projects
0.003
(1.79)
(1.39)
other projects
0.001
(1.73)
14
CDF(0) Results of EBA
CAN
FRA
GBR
DEU
ITA
JPN
USA
G7
Baseline variables (4,525 regressions per cell)

National capability
0.93
0.99
0.99
0.90
0.96
1.00
0.99
0.97
Democracy -1
1.00
0.98
0.98
1.00
1.00
1.00
0.94
0.96
15
Testing the extended models
CAN
FRA
GBR
DEU
ITA
JPN
USA
G7


p-value Hausman test
2
Adj. R
Obs
Cnt
Period
IMF EFF SBA
IBRD flows
WB adjust. projects
16
Robust to changes in dependent variable?

• How to define voting coincidence?
• Barro Lee BothYes BothNo Abs.
• Thacker BothYes BothNo ½ Abs.
• Kegley Hoock BothYes BothNo
• Which votes to count?
• Also almost unanimous votes?
• All votes or only Keyvotes?
• Include dominant topics? (Israel 20 of all
  votes)
• How to weigh the past?
• No weights, or slowly decaying weights

17
Conclusions Hypotheses 1 to 4

• The probability that a recipient country votes
  in line with the donor
• significantly increases with cultural proximity
• significantly increases with dependency on
  foreign support
• is not significantly related to bilateral foreign
  aid
• is somewhat related to bilateral trade flows

18
Conclusions Main Hypothesis

• Concessional loans are not correlated with voting
  coincidence in the UN General Assembly
• Non-concessional IMF and World Bank programs and
  loans matter for voting in the UN General
  Assembly
• number of IMF EFF and SBA programs
• flow of World Bank IBRD loans
• Also the start of World Bank adjustment programs
  matter
• For the US, only IBRD loans matter for the voting
  behavior of recipient countries