Shaomin Li
Judy Wu
Old Dominion University
Norfolk, VA, USA
1
Corruption and economic development
 Dominant
economic theory:
corruption is bad
for economic
development (see
review article by
Svensson, 2003).
2
Corruption and economic growth
 The
empirical
evidence on
the
corruptionefficiency
relationship
is mixed.
3
The puzzle of corruption and economic
growth
 The “East Asian paradox” (Rock & Bonnett, 2003)
 Past attempts to solve the puzzle
 The “efficiency enhancing” corruption argument (Leff,
1964; Lui, 1985, Wedeman, 2002).
4
Studies on the causes and effects of
corruption
 Judge, et al (2008) reviewed 42 empirical studies and
found:
 Measurements of corruption vary widely. The most
used measure is the CPI developed by Transparency
International.
 More studies focus on the causes of corruption than
those on the effects of corruption.
 Economic explanatory variables are used the most,
political variables the second, the cultural variables the
third.
5
Trust--the missing link in explaining the
corruption-efficiency relationship
 Trust: “willingness to rely on an exchange partner in whom
one has confidence” (Moorman et al. 1993).
 Particularized vs. generalized trust
 The role of trust in corruption
 The separation of time and space in corrupted transactions
requires some trust between the briber and the corrupt
official.
 The outcome of corruption with/without trust
 Predatory vs. efficiency enhancing corruptions
 How can a society develop a high level of trust
 Good political and economic institutions
 Expansive social network
6
Our main arguments
 H1: corruption has a negative effect on economic
growth
 H2: trust has a positive effect on economic growth
 H3: the effect of corruption on economic growth is
moderated by trust. There is a interaction effect
between corruption and trust on economic growth. In
countries with a higher level of trust, the negative
effect of corruption will be mitigated.
7
Empirical evidence
 Case study
 Statistical test
8
Corruption, trust, economic growth:
China vs. the Philippines
Country
GDP
annual
growth
rate (%)
(19902000)
GNI per
capita
(2001)
Corruption
perception index
(10=best,
1=worst)
Trust
(1999(2000)
2004)
Philippines
3.3
1050
2.8
8.6
China
10.3
890
3.1
54.5
9
Corruption in China
 The existence of wide and thick informal social
networks in the society
 A high level of trust
 From particularized to generalized trust (evidence from
Tang, 2005)
 How bribery-corruption relationship is formed
 The case of Motorola’s “slush fund” in China

“The terms of the deal was…a ten million-dollar discretionary
fund. Hands off, no questions asked. Don’t ask where the
money goes,…We know exactly what he was up to, and exactly
how successful he would be…” (Gutmann, 2004, p124).
10
How bribe is paid…
 “I [the briber] invite my client [corrupt official] to a
well-known Cantonese restaurant with several
branches in Beijing. The meal costs an astronomical
20000 rmb [$2,400] for two. On the way out, the
restaurant passes a gift to my client and the client is
told he or she can exchange the gift for cash if he or she
does not like it. The gift is then exchanged by my client
for about 10000 rmb. I have not discussed any such
exchanges with my client. But just in case people get
the wrong impression, the restaurant has covered
my car's license plate in the restaurant's parking lot.”
11
Types of bribery-corruption transactions
 According to Takungpao (2006):
 Bribery-corruption transaction has become
sophisticated:
 Globalization
 Future options
12
Corruption in the Philippines
 The state head controls the entry of an industry or
monopolizes it
 Impose a tax or surcharge on all
 Appoint his/her cronies to be in charge of the industry
 Steal the taxes/surcharges.
13
Evidence from the three most important
industries…
 The coconut industry (1970s)
 President Marcos imposed a tax
 Appointed his friend, Manuel Conjuangco, to collect it.
 Used the tax to subsidize mills owned by the two.
 The cigarette industry (1970s)
 Imposed 100% import duty on filters.
 90% duty reduction to a company owned by Marcos’ friend,
Herminio Disini. Disini in turn supplied the filter to Tan,
another Marcos friend.
 The sugar industry (1970s)
 Marcos order all sugar exports be monopolized by PEC,
controlled by his friend Robert Benidicto.
14
Statistical test
 Economic growth = a + b1(corruption) + b2(trust) +
b3(corruption*trust) + B(control variables) + e
 Data
 A pooled data set


53 countries in two time periods.
76 observations in total

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 Dependent Variable: annual economic growth rate
 Main independent variables:
 Corruption. CPI 1996 and 2002 (Transparency
International).
 Trust. World Value Survey (Inglehart, 1994-2005). 2
waves: 1994-1999 and 1999-2004.
 Control variables:




GNI per capita (World Bank, 1994-1999 and 2000-2005).
Schooling (Barro and Lee, 1995 and 2000)
Political system (Freedom House, 1996 and 2002)
Time, 1994-1999 and 2000-2005.
16
correlation coefficients
Mean
S.D.
GDPpgr
CORRUPT
TRUST
GNIp
SCHOOL
GDPpgr
2.94
2.56
CORRUPT
4.70a
2.53
-.220
(.056)
TRUST
28.86
15.53
.290*
(.011)
-.588**
(.000)
GNIp
12.91
12.65
.132
(.257)
-.872**
(.000)
.599**
(.000)
SCHOOL
8.04
2.29
.179
(.123)
-.625**
(.000)
.417**
(.000)
.627**
(.000)
STATUS
.07
0.25
-.016
(.893)
.241*
(.036)
.146
(.208)
-.254*
(.027)
-.304*
(.008)
TIME
.61
.49
.219
(.057)
.010
(.928)
-.004
(.976)
.042
(.722)
-.067
(.568)
STATUS
.016
(.363)
17
Regression result
Dependent variable: log(GDPpgr)
Independent
variables
Model 1a
Model 2a
Model 3a
Model 1b
Model 2b
Model 3b
CORRUPT
-.010
(.008)
-.001
(.009)
-.043***
(.014)
-.025* (.013)
-.020
(.012)
-.059*** (.016)
.003**
(.001)
.010***
(.002)
.003** (.001)
.011***
(.002)
TRUST
.001***
(.000)
CORRUPT*T
RUST
GNIp
.001*** (.000)
-.004
(.003)
-.005**
(.003)
-.005**
(.002)
SCHOOL
.004
(.009)
.001
(.009)
.002
(.008)
.007
(.009)
.004
(.009)
.004
(.008)
STATUS
-.025
(.065)
-.080
(.069)
-.130**
(.065)
-.031
(.065)
-.103
(.068)
-.150**
(.064)
TIME
.057*
(.031)
.059*
(.031)
.055*
(.028)
.063**
(.031)
.068**
(.030)
.063**
(.028)
Intercept
2.865***
(.064)
2.863***
(.062)
2.650***
(.081)
2.811***
(.073)
2.786***
(.071)
2.582***
(.085)
N
76
76
76
76
76
76
.103
.153
.293
.129
.203
.337
2.040*
2.533**
4.776***
2.071*
2.936**
4.936***
R Square
F-statistics
18
Regression result (cont’d)
Log (GDPpgr) = 2.582 +
(-.059+.001TRUST)*CORRUPT+.011*TRUST.005*GNIp+.004*SCHOOL-.150*STATUS+.063*TIME
+error,
 If trust => 0, then effect of corruption on growth is 0.17%.
 Every 10% increase in trust => reduce the negative
effect of corruption by 0.03%.
 H3 is supported.
19
Concluding remarks
 The negative effect of corruption on economic growth can
be mitigated by a high level of trust in a country.
 The boundary between particularized and generalized
trust
 Consequences of efficiency enhancing corruption
 It enriches the corrupt officials pockets;
 Gives them incentives to increase state power.
 It improves the bribing firm’s profitability.
 It impoverishes the state coffers.
 => the government has strong monopolistic power, a
weakened treasure, and an efficient and wealthy business
class.
20
Implications
 Policy implications for eradicating corruption
 The difficulty of cleaning corruption in societies with
high level trust.
 Firms have little incentives to report corruption
(“corruption with theft” by Shleifer and Vishiny).
 Strong and thick social network makes “whistle blowing”
difficult).
 The “futures option” type of corruption.
21
Implications (cont’d)
 What can be done?
 Firms?
 Governments?
 International organizations?
 Further research?
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