Embed
Email

Oxford Seminar Legal Corruption Presentation

Document Sample
Oxford Seminar Legal Corruption Presentation
Legal Corruption

Daniel Kaufmann

Pedro C. Vicente









Oxford University

November 9, 2005

Conventional Definition of Corruption



• Abuse (usually taken as an illegal act)…

• of public office (a public-sector centered

definition)…

• for private gain.

But what about…

• A private individual buying a law (legal in a

number of countries, through allowed

lobbying), or…

• A private-sector firm employing a well-

known former politician to its advisory

council.

Question of the Paper

• Challenge conventional definition of corruption,

instead positing a broader notion to understand…

• What are the main simple determinants of the

world pattern of legal and illegal corruption

– Original political economy model of corruption,

presenting a simple explanation

– Use of broad range of different empirical counterparts

for testing, namely

• Newly available empirical measures of legal corruption,

from a worldwide firms’ survey in 104 countries

• Other external data sources

The Model

• Infinitely repeated complete information game

• 3 agents with individual ability a

• Every period an auction of a “favor” takes place

– Initial auctioneer is pre-defined

– Winner is next period auctioneer

– Bidders submit contract offers

• Auctioneer raises a at a given period; others

raise 0 (let’s call the loser population)

• Corruption



Date 0 Date 1 Date 2 Date 3

Auctioneer Bidders Auctioneer Bidders Auctioneer Bidders Auctioneer Bidders



1 2 2 1 1 2 2 1



3 3 3 3

• Auctioneer may choose to buy Legal Barriers

(proportion ϖ of transferred earnings)

– Legal Barriers inflict “myopia” on the loser, i.e.

her utility horizon is the present period

• (collective action undermined)

• Population may start an insurrection at the

end of period

– Insurrection is successful if λ(.)> λ ; o/w prob. ε

– λ(.) function depending on:

• General ability a (idea: potential for destruction)

• Raised amounts α by pop in last 3 periods (idea:

potential to “arm an army” by pop)

• Stage Game

Auctioneer

Decides

Bidders

Auctioneer Whether to Population Decides for

Submit

Decides Winner Build Legal Insurrection or Peace

Contract

Barriers

Offers

Time Line (Stage Game)

• Payoffs: ∞



– For all agents: ∑ [ δ i (1 − s ) w i ] , where we is

t e



t=0

end-of-period wealth

• For the Auctioneer: w = w + τ + a − ϖ

e b





• For the Winner: w = w + τ

e b





• For the Loser: w = w

e b





• Contract Incompleteness (CI):

– in the sense that (1-s) cannot be negotiated – it

has to be consumed

Equilibrium

• Inequality high (1/α) / Ability (a) low

⇒Insurrections started, corruption, no legal barriers

(unstable)

Intuition: CI=>power is best; pop almost (unstable) no threat;

• Inequality low / Ability high

– Accountability (ϖ) low

⇒No Insurrections started, corruption, legal barriers

(unstable?)

Intuition: pop is threat; worth spending ϖ; inequality increases

(possible instability in the long run)

– Accountability (ϖ) high

⇒No Insurrections started, no corruption, no legal barriers

(stable)

Intuition: pop threat, legal barriers too expensive; pop offered

insurrection payoff=>rotation of all agents (stable)

Testable Implications

Table 1:

Ability (Productivity) Low High

Exogenous /Equality



Accountability Low High Low High



Legal Corruption No No Yes No



Endogenous Illegal Corruption Yes Yes No No



Insurrections Yes Yes No No





• Three patterns of interaction of exogenous vs.

endogenous variables

Data

• New Dataset with proxies for Legal Corruption:

– Executive Opinion Survey (EOS) – Global Competitiveness

Report 2004-2005, World Economic Forum

• mail-based survey, 8729 firms, 104 countries

• Broad range of proxies for other variables (both from

EOS and other databases)

• Endogenous Variables

• Illegal Corruption:

– EOS Financial Honesty of Politicians

– EOS Frequency of Illegal Political Contributions

– EOS Frequency of Diversion of Public Funds Due to Corruption

– EOS Frequency of Bribery as State Capture

– KKM Control of Corruption (2002)

• Legal Corruption:

– EOS Favoritism in Policy and Procurement

– EOS Frequency of Legal Political Contributions

– EOS Influence in Laws and Regulations

» Adjust by Rule of Law: EOS Frequency of Bribery in Judicial

Decisions and KKM Rule of Law (2002)

• Insurrections:

– EOS Common Crime

– iJET Risk of Travel (2004)

– EIU - Armed Conflict, Violent Demonstrations, Violent Crime, Social

Unrest (2003)

– Civil War Dummy - constructed from Gleditsch et al, 2001 (1990-01)

• Parameters (Exogenous Variables)

• Ability (Productivity):

– Lagged logGDP per capita (1984)

• Equality:

– 100-Gini Coefficient (2002)

– EOS Equality in Healthcare

• Accountability:

– EOS Freedom of Press

– Freedom House:

» Civil Liberties (2003)

» Press Freedom (2004)

– KKM Voice and Accountability (2002)

– Government Fractionalization (2000) from DPI - Database of Political

Institutions, Beck et al, 2001

Simple Empirical Tests: Averages

• From first two rows in Table 1

– differences lower-upper quartiles/halves in terms

of income p/c or equality higher for illegal

corruption than for legal corruption

• From third row in Table 1

– Insurrection proxies are higher in lower income

p/c or equality groups of countries

• Note that differences are higher using 1st vs.

other quartiles than using halves

⇒we focus on the first

Simple Empirical Tests: Correlations

• From first two rows and first three columns in

Table 1

– If we take differences legal-illegal corruption and

take out lowest legal corruption countries

⇒ Clear positive correlations across countries should

arise with income p/c and equality

• From third row in Table 1

⇒ Clear negative correlations should arise with

income p/c and equality

• From first row in Table 1

– If we take legal corruption vs. accountability:

⇒ Clear negative correlations should arise for high

income p/c or equality first quartiles

⇒ Over all countries, we should see higher correlations

(in the sense of less negative)

An Econometric Model for

Testing

LK = i1 + aDGDP0 + bDEQUAL + cDACC + dDACC * DGDP0 + eDACC * DEQUAL (1)

IK = i4 + fDGDP0 + gDEQUAL + hDACC + iDACC * DGDP0 + jDACC * DEQUAL (2)

INSURR = i7 + kDGDP0 + lDEQUAL + mDACC + nDACC * DGDP0 + oDACC * DEQUAL (3)



• Restrictions on coefficients:

Eq(1): ⎡ a ⎤ ⎡+ ⎤ Eq(2): ⎡ f ⎤ ⎡−⎤ Eq(3): ⎡ k ⎤ ⎡− ⎤

⎢ b ⎥ ⎢+ ⎥ ⎢ g ⎥ ⎢− ⎥ ⎢ l ⎥ ⎢− ⎥

⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥

⎢ c ⎥ = ⎢0⎥ ⎢ h ⎥ = ⎢0⎥ ⎢m⎥ = ⎢ 0 ⎥

⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥

⎢d ⎥ ⎢− ⎥ ⎢ i ⎥ ⎢0⎥ ⎢ n ⎥ ⎢0⎥

⎢ e ⎥ ⎢−⎥

⎣ ⎦ ⎣ ⎦ ⎢ j ⎥ ⎢0⎥

⎣ ⎦ ⎣ ⎦ ⎢ o ⎥ ⎢0⎥

⎣ ⎦ ⎣ ⎦

• Eq(1) - Legal corruption proxies: we take diffs to

illegal corruption and lack of rule of law

Equation (1) - Legal Corruption (using differences)

Dependent Variable -------> Legal Corruption

Accountability Freedom of Press EOS Q5.06

Choice of Equality Gini

Empirical EOS Legal

Legal Corruption EOS Q4.12 EOS Q4.14 EOS Q5.14D

Measures Corruption

(Difference) EOS EOS EOS EOS

Adjustment Q5.12E Q5.12G

KKMRL KKMCC

Q5.12G

KKMRL KKMCC

Q5.12G

KKMRL KKMCC



coef. 0.55** 0.88** 0.13* 0.11 0.73 0.13 0.12 1.05** 0.10 0.09

DGDP

std. err. 0.24 0.42 0.07 0.08 0.48 0.10 0.10 0.41 0.09 0.10

coef. 0.34* 1.05*** 0.31*** 0.30*** 1.01** 0.26*** 0.25*** 0.67** 0.16** 0.15*

DEQUAL

std. err. 0.20 0.34 0.06 0.06 0.39 0.08 0.08 0.33 0.07 0.08

Explanatory coef. 0.22 0.04 0.03 0.05 0.26 0.08 0.10 0.17 0.03 0.04

DACC

Variables std. err. 0.22 0.39 0.07 0.07 0.44 0.09 0.10 0.38 0.08 0.09

coef.

DGDPDACC

std. err.

coef. -0.50 -1.28** -0.35*** -0.36*** -1.30* -0.33** -0.34** -0.63 -0.14 -0.15

DEQUALDACC

std. err. 0.33 0.58 0.10 0.11 0.66 0.13 0.14 0.56 0.13 0.13

Number of Observations 85 85 85 85 85 85 85 85 85 85

R2Adjusted 0.15 0.13 0.25 0.21 0.09 0.12 0.10 0.18 0.05 0.03

Fit (Testable Implications) +- OK EXACT EXACT EXACT EXACT EXACT EXACT +- OK +- OK +- OK





Notes: All regressions have GDP as GDP pc 1984; dummies take value 1 for the first quartile of the corresponding variable. *, **, ***, correspond to the

levesl of statistical significance 10%, 5%, and 1%, respectively.

Equation (2) - Illegal Corruption

Dependent Variable -------> Illegal Corruption

Accountability Freedom of Press EOS Q5.06

Choice of

Equality Gini

Empirical

Measures EOS EOS EOS

Illegal Corruption EOS Q4.02 EOS Q4.13

Q5.11 Q5.12E Q5.12F

coef. -1.22*** -1.24** -1.26*** -1.00* -1.44*** -1.23*** -0.96***

DGDP

std. err. 0.34 0.51 0.39 0.59 0.34 0.32 0.28

coef. 0.42 0.14 0.25 -0.02 0.05 0.08 -0.04

DEQUAL

std. err. 0.27 0.23 0.32 0.27 0.27 0.26 0.23

Explanatory coef. -0.52 -0.60 -0.33 -0.26 -0.97*** -0.69** -0.69**

DACC

Variables std. err. 0.31 0.37 0.37 0.43 0.31 0.29 0.26

coef. -0.27 -0.75

DGDPDACC

std. err. 0.66 0.76

coef. -0.86* -0.91* -0.33 -0.40 -0.31

DEQUALDACC

std. err. 0.46 0.54 0.46 0.44 0.39

Number of Observations 85 85 85 85 85 85 85

R2Adjusted 0.50 0.48 0.40 0.39 0.61 0.53 0.52

Fit (Testable Implications) EXACT EXACT - OK



Notes: All regressions have GDP as GDP pc 1984; dummies take value 1 for the first quartile of the corresponding variable. *,

**, ***, correspond to the levesl of statistical significance 10%, 5%, and 1%, respectively.

Equation (3) - Insurrections



Dep. Variable --> Insurrections

Accountability Freedom of Press EOS Q5.06

Choice of

Equality Gini

Empirical

Measures EOS EIU EIU EIU

Insurrections iJET EIU 3003

Q5.09 3001 3002 3005

coef. -1.30*** -1.46*** -0.98*** -0.49 -0.96* -0.73* -0.67 -0.80*

DGDP

std. err. 0.44 0.38 0.26 0.67 0.58 0.40 0.59 0.44

coef. 0.11* -0.33* -0.39* -0.94*** -0.73*** -0.90*** -0.79*** -0.14

DEQUAL

std. err. 0.35 0.17 0.21 0.30 0.26 0.32 0.27 0.35

Explan. coef. -0.23 -0.40 -0.17 -0.80 -0.87** -0.67* -0.61 -0.77*

DACC

Variables std. err. 0.40 0.27 0.24 0.49 0.42 0.37 0.43 0.40

coef. 0.92* 0.67 0.72 0.02

DGDPDACC

std. err. 0.48 0.86 0.74 0.77

coef. -0.56 0.31 0.34 -0.44

DEQUALDACC

std. err. 0.60 0.35 0.56 0.61

Nr. of Observations 85 85 85 80 80 80 80 80

R2Adjusted 0.30 0.37 0.35 0.16 0.28 0.31 0.31 0.31

Fit (Test. Imp.) EXACT - OK EXACT EXACT - OK - OK EXACT - OK



Notes: All regressions have GDP as GDP pc 1984; dummies take value 1 for the first quartile of the corresponding variable.

*, **, ***, correspond to the levesl of statistical significance 10%, 5%, and 1%, respectively.

Main Findings

• Some accounting:

– Eq(1): 14 EXACT, 51 OK (exc. EXACT), out of 100

– Eq(2): 17 EXACT, 19 OK, out of 50

– Eq(3): 22 EXACT, 38 OK, out of 60

• Eq(1):

• Favoritism in Procurement and Legal Political Contributions;

Gini; Freedom of Press

• Eq(2):

• All except Diversion of Public Funds Due to Corruption; DPI

Fractionalization of Government

• Eq(3):

• EOS Common Crime; DPI Fractionalization of Gov

Concluding Remarks

• Simple model to explain basic pattern of legal/illegal

corruption

– General notion of corruption, founded at the micro level

– Income/equality determine basic political threat

– Accountability determines ability to undermine collective action by

population

• General validity of the model from testing with wide

range of empirical measures for the relevant

concepts

– Newly available legal corruption measures

• Possible Policy Messages:

• “It takes two to tango”

• We may be forgetting that some high income (namely G7)

countries have high (legal) corruption

• Accountability: may be key in determining development


Related docs
Other docs by worldbank
By registering with docstoc.com you agree to our
privacy policy

You are almost ready to download!

You are almost ready to download!