Contagion Corruption and Financial Development: Evidence from a Panel of Regions

DSA ConferenceAberdeen, UK

14th October 2011.

Muhammad Tariq Majeed& Ronald MacDonald

University of Glasgow, UK

Introduction• Corruption is a serious issue and a major obstacle to

development.

• According to World Bank more than US$ 1 trillion is paid in bribes each year

• Countries that tackle corruption could increase per capita incomes by a staggering 400 percent .

• "Fighting corruption is a global challenge”.

• Corruption in European countries, on average, has increased 22% over last two decades (Majeed, 2011)

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Outline • Theory

• Research Questions

• Model

• Data Description and Sources

• Results

• Academic Contribution

• Conclusion

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Theory

Lack of competition, in product or/and financial markets, increases corruption because rent seeking activities increase in the absence of competition. Theoretical studies predict an ambiguous effect of competition on corruption. On the one hand, lack of competition generates rents (supra normal profits) for entrepreneurs, thereby motivating bureaucrats to ask for bribery (Foellmi and Oechslin (2007). On the other hand, the presence of these rents increases the values of monitoring the bureaucracy in a society (Ades and Di Tella (1999).

Since neighbour countries share similar political cultures and institutions, cross-border spill over effects of corruption are likely outcome.

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Research Questions

(1) Does financial liberalization reduce corruption?

(2)Is the relationship between high financial liberalization and corruption perhaps non-monotonic?

(3) Do corruption in neighbouring countries, regional panels and past levels of corruption matter in shaping the link?

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Model

1.....321 ittitititititit XFLPCYC

Equation 3 includes another key determinant of corruption, the military in politics (MP), that has recently been introduced by Majeed and MacDonald (2010).

Where (i= 1… N; t=1… T), Cit is a perceived corruption index, PCYit is per capita income to measure the level of economic development, FLit represents the degree of financial liberalization, Xit represents a set of control variables based on the existing corruption literature. The expected sign for the key parameter of interest, β2, is negative.

Equation 2 introduces non-monotonic form to capture the possible present of a threshold level of financial liberalization in shaping the relationship between financial development and corruption.

Equation 4 models contagion nature of corruption where wij is an adjacency-related weight. α is an intercept while β is a K ×1 parameter vector for the covariates collected in xi. Two parameter, λ and ρ, measure the intensity (strength) of interdependence, where λ denotes the spatial lag and ρ represents the spatial correlation in the residuals.

2.....42

321 ittititititititit XFIFIPCYC

3.....542

321 ittitititititititit XMPFIFIPCYC

4.....;11 j

N

j ijiij

N

j iji wpXcwC

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Variables Sources

Corruption International Country Risk Guide

Military in Politics

Inflation IFS database.Credit as % of GDP

M2 as % of GDP

Economic Development

World Bank database.Trade Liberalization

Government Spending

Remittances

Data

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Data: Scatter plots for Spatial Corruption0

24

6C

orr

uptio

n In

dex

0 1 2 3Spacious Weighted Index 5 Year Average Lag (1999-2003)

Spacious analysis of Corruption

Brunei

China

Hong Kong

Indonesia

Japan

Malaysia

Myanmar

Papua New Guinea

Philippines

Singapore

ThailandVietnam

12

34

5C

orr

uptio

n In

de

x

0 100 200 300 400High Financial Intermediation

1984-2007

East Asia and PacificHigh Financial Intermediation

02

46

8T

ransp

are

ncy

Inte

rnatio

nal C

orr

uptio

n I

ndex

0 100 200 300 400Financial Liberalization

Fitted values tii

Financial Liberalization and Corruption (1996-2007)

01

23

4W

orld B

ank C

orr

uption I

ndex

0 100 200 300 400Financial Liberalization

Fitted values WBC

Financial Liberalization and Corruption (1996-2007)

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Table 1: Corruption and FL: Regional Panel EstimationVariables Dependent Variable: Corruption

FL -0.004(-9.92)*

-0.001(-3.71)*

-0.002(-7.15)*

-0.002(-7.16)*

-0.002(-7.00)*

-0.002(-6.77)*

-0.002(-6.70)*

-0.002(-7.31)*

PCY -0.000(-4.22)*

-0.000(-3.40)*

-0.000(-2.72)*

-0.000(-3.51)*

-0.000(-6.79)*

-0.000(-2.35)*

-0.000(-3.77)*

Govt. Spending

-.04(-3.13)*

-.05(-4.97)*

-.04(-3.57)*

-.03(-3.5)*

-.04(-3.97)*

-.05(-5.59)*

-.05(-5.28)*

Rule of Law 0.4(7.15)*

-0.44(-10.12)*

-0.27(-4.97)*

-0.63(-15.25)*

-0.49(-12.53)*

-0.35(-6.90)*

-0.3(-3.30)*

TradeOpenness

0.01(12.29)*

0.01(11.43)*

0.01(10.01)*

0.01(10.49)*

0.01(8.89)*

0.02(11.29)*

Military in Politics

0.26(4.67)*

Govt. Stability

0.17(9.64)*

Investment Profile

0.115(7.72)*

Democracy 0.17(3.56)*

Internal conflict

-0.08(1.7)***

R 0.32 0.75 0.86 0.87 0.90 0.89 0.86 0.86

F 98.40 (0.000) 159.96 (0.000)

249.58 (0.000)

232.28 (0.000)

314.99 (0.000)

276.19 (0.000)

221.70 (0.000)

210.43 (0.000)

Observations 216 215 215 215 215 215 215 215

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Table 2:Corruption and Financial Liberalization: Non-linearity Variables Dependent Variable:

Corruption Index by TIDependent Variable: Corruption Index by WB

Dependent Variable: Corruption Index by ICRG

FL -0.018(-4.91)*

-0.014(-4.04)*

-0.008(-4.93)*

-0.006(-4.00)*

-0.006(-2.30)**

-0.004(-1.41)

PCY -0.000(-10.77)*

-0.000(-9.04)*

-0.000(-9.64)*

-0.000(-7.84)*

-0.000(-5.20)*

-0.000(-3.63)*

Economic Freedom

-0.26(-4.42)*

-0.26(-4.86)*

-0.16(-6.40)*

-0.17(-7.25)*

-0.25(-6.29)*

-0.26(-6.85)*

Govt. Spending

-.03(-1.60)***

-.009(-0.52)

-.015(-1.86)***

-.003(-0.45)

-.001(-0.07)

-.015(-1.22)

Rule of Law -0.34(-3.66)*

-0.19(-4.53)*

-0.24(-3.56)*

FL Square 0.000(4.22)*

0.000(3.67)*

0.000(4.16)*

0.000(3.58)*

0.000(2.20)**

0.000(1.60)

R 0.82 0.84 0.82 0.85 0.61 0.66

F 96.47 (0.000)

91.96 0.000)

100.37(0.000)

101.87 (0.000)

35.30 (0.000)

34.66 (0.000)

Observations

113 113 116 116 116 116

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Table 3 : Cross-border Effects of Corruption

Variables SWC(99-03) SWC(94-98) SWC(89-93) SWC(84-88)

SWC 0.21(2.31)*

0.19(2.41)*

0.19(2.43)*

0.19(2.42)*

PCY -0.000(-2.33)*

-0.000(-1.26)

-0.000(-1.26)

-0.000(-0.25)

Democracy -0.21(-3.89)

-0.25(-4.77)*

-0.16(-2.43)*

-0.27(-5.26)*

Bureaucracy Quality -0.30(-3.18)*

-0.24(-2.72)*

-0.26(-5.0)*

-0.21(-2.35)*

Rule of Law -0.24(-3.69)*

-0.35(-5.36)*

-0.36(-5.41)*

-0.41(-6.15)*

R 0.76 0.80 0.80 0.81

Observations 134 125 123 117

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

• The importance of financial market reforms in combating corruption has been highlighted in the theoretical literature but has not been systemically tested empirically.

• To best of our knowledge, this study provides a first pass at testing this relationship using both linear and non-monotonic forms of the relationship between corruption and financial liberalization.

• This study introduces the concept of regional panels.

Academic Contribution

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

The results imply that a one standard deviation increase in financial liberalization is associated with a decrease in corruption of 0.20 points, or 16 percent of a standard deviation in the corruption index.

The analysis also indicates the presence of a threshold implying that financial liberalization is beneficial only up to a threshold level and after the threshold is reached corruption increases.

Finally, results of the study show that a policy in a neighboring country that reduces corruption by one standard deviation in the past five to ten years will reduce corruption in the home country by 0.12 points.

Introduction Outlines Theory Research Questions Model Data Results Contribution Conclusion

Conclusion

Thank You!