Discussion Paper No.

604

CORRUPTION AND ITS ALTERNATIVES:
A TAKEOFF THEORY OF GOOD GOVERNANCE

Evan Osborne

May 2004

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Corruption and Its Alternatives: A Takeoff
Theory of Good Governance
Evan Osborne
Wright State U. Dept. of Economics and Osaka U. Institute of Social and Economic
Research
3640 Col. Glenn Hwy.
Dayton, OH 45435(937) 775 4599
(937) 775 2441 (Fax)evan.osborne@wright.edu

Abstract
Corruption is a function of its return relative to engaging in productive activities.
This paper presents an approach for thinking about the institutional features of societies
and the resulting amount of corruption. The empirical results suggest that politicalcompetition is more important than competition in information-producing industries.
The rent-seeking view of the relation between government and corruption is rejected infavor of the Becker (1983) model of political competition. The paper suggests thatsocieties that continually stay open to productivity-enhancing activities will eventuallyenter a takeoff stage of anti-corruption efforts analogous to the eventual improvement inincome distribution that occurs in successful industrialization.

Corruption is a topic that has soared in importance in the development community
in recent years. Its role as an impediment to modernization has been empirically
documented by Mo (2001) and Mauro (1995). Its capacity to distort public resource-use
decisions has been demonstrated by Tanzi and Davoodi (2000), and has been interpreted
as rent-seeking by Krueger (1974). Its endogenous generation has been traced in
Mohtadi and Roe (2003) and Barreto (2000). Another influential theoretical approachhas been that of Murphy, Shleifer and Vishny (1993, hereafter MSV), who in the
Hirshleifer (1991) tradition depict the amount of rent-seeking as a function of the relative
return to appropriative as opposed to productive activity.
The relation between technological progress and corruption is one that merits
more study. This relation, suggested by but not explicitly explored in earlier work, has
powerful implications for corruption control. It suggests that policies that increase
productivity can endogenously control corruption by decreasing the desirability of
producing rent-seeking opportunities. This paper derives precise conditions whereby
progress in productive technology makes corruption control more worthwhile, and tests
whether these conditions hold. The empirical results allow for re-interpretation of the
expected effectiveness of corruption control at various stages of development. Sections 1
and 2 explore endogenous corruption where production is available as an alternative,
Section 3 tests the model and Section 4 re-interprets corruption control in light of thefindings.

1. The returns to parasitism
One empirical fact about corruption readily suggests itself – that it is inversely

1related to a nation’s per capita income. Figure 1 plots the 2003 ratings of the anticorruption group Transparency International – ranging from zero to ten, with zero themost corrupt – against per capita income in 2000, obtained from the World Bank’s World
Development Indicators database. The relationship is somewhat concave, with aregression of the TI score on per capita GDP and per capita GDP squared included forcomparison.1 Rich countries are corrupt, poor ones are not, and there are a striking
number of countries with almost minimal per capita income and high degrees ofcorruption. Roughly half the countries in the world, in other words, are in a low-income,high-corruption equilibrium, one of two outcomes predicted by the MSV model. The
relation between income and corruption has been explored empirically by Paldam (2002)
using a single-equation model.
Ctry labels: TI rating
9.7

Fitted values
FIN
ISL
SGP SWE

NZL

NLD

GBR
CAN
AUS
HKG
IRL

CHL
ISR
ESP

DNK
NOR

CHE

LUX

AUT
GER
BEL
USA
FRA

JPN

PRT

BWA
ESTURYMYS
TUN HUNLTU
NAM TTOJOR
BLZZAFMUS SAU
CRI
BLR

1.3

SVN

CYP

KWT

ITA

KOR
GRC

BGR
BRA
CZE
JAM
LVASVK
SLV
COL
PER
HRV
MEX
POL
SYR
CHN
LKA
PAN
DOM
EGY
MAR
BHR
THA
GHA
SEN
TUR
WBG
IRN
LBN
ARM
MLI
ROM
MWI
IND
RUS
MOZ
DZA
NIC
MDG
YEM
PHL
ETH
TZA
GMB
ZMB
PAK
ALB
ARG
GUM
KAZ
UZB
MDV
VEN
VNM
YUG
MKD
ZWE
HND
UKR
BOL
SDN
ECU
COG
SLE
UGA
ONG
CIV
KGZ
IDN
KEN
GEO
AGO
AZE
CMR
PRY
HTI
NGA
BGD

56372

115.881
Per capita GDP

Figure 1: Corruption and per capita income.
1. The regression is 2.484125 + 0.0003286 PCGDP – 4.23E-09 PCGDP2 (n = 122, F =322.50, R2 = 0.8247.

2

The traditional explanation for this relationship is that corruption destroys growth,
so that fighting corruption is causally prior to successful industrialization. But suppose
the reverse is true – that growth causes corruption reduction. As societies become moreproductive,2 it is conceivable that a unit of resources devoted to appropriation becomes
more costly. If so, the members of society may find it less attractive or be willing toendure a greater burden to fight it.
A tantalizing hint of that possibility is depicted in figure 2. The vertical axis is
the 1996 TI rating, and the horizontal axis shows Solow residuals for a production
function based on Penn World Tables data of the logarithm of GDP on the logarithms ofthe capital stock and workers in the country. A fitted line of the regression of the ratingon the residual is also included, and the correlation between the residual and the TI rating
is 0.4222.3 Productivity is not the sole determinant of corruption, but it may matter inimportant ways.

2. The term “productivity” will denote the return to resources used in income production
rather than appropriation, unless otherwise noted.
3. The regression depicted is RATING = 1.5846 + .0733 RESID (p < .007, R2 = 0.1782, N=39), where RESID is a residual calculated from a standard Solow growth regression.
That regression is LOGQ = 3.5873 + 0.6456 LOGK + 0.3309 LOGL (R2 = 0.9542, N =60, both variables significant at p = 0.001). K is nonresidential capital per worker, and L
is the number of workers in the population (calculated using the figure from PWT 5.6 on
the percentage of workers in the population).

3

Country labels: 1996 TI rating

Fitted values

10.7505

CHE

NZL
DNK
SWE
FIN
NOR

CAN
AUS IRLNLD
GER

AUT
JPN

GBR

ISR

USA
HKG

FRA
BEL
POR

CHL

POL
KOR

GRC
TWN
ESP
TUR
THA

BOL
ECU
COL
PHL
IND

ARG

MEX ITA

VEN
KEN

NGA

.69

124.188

20.6026
Solow residuals

Figure 2 – Corruption and productivity.
The argument can be simply illustrated. Let the basic production function for the
economy be Y = Af(l). l is total input of labor to productive activity, and f has thestandard textbook properties of production functions. There are positive but diminishingreturns throughout, so that fl > 0, fll < 0. Assume also that f(0) = 0 and lim f (0) = ∞ . To
l → 0

illustrate the argument as parsimoniously as possible, assume that government has no rolein providing public services in and of themselves. Its only functions are to restrict theoptions in private production. This can be modeled by having the government be simply
a dispenser of permits. X is the number of such permits that exist. These can be thoughtof as inputs that must be purchased to enable production, even though they come at a costof deadweight loss in production. The model is thus of rent-seeking not just as diversion
of productive effort but as outright parasitism. Factors are not just diverted, but used
inefficiently. One might imagine that each permit is a weight that a worker must strap tohis back when entering the workplace. The permits stand for real economic phenomena

4

involving artificially inefficient factor use – requirements to do business with the family
members of government officials or with other firms who have also paid bribes, to pay
extra for domestic products shielded from foreign competition, etc. Assume then that
production once permits exist is actually Y' ≡ Af(l)[1 – t(X)], where X is the number of
permits and t′ > 0, t′′ < 0 and t(0) = 0.
Permits are paid for like labor, out of produced income. And like output,
they are generated by applying the only scarce resource, labor, according to X =g(e; α), with ge > 0, gee < 0. α is a shift-parameter vector that is negatively related
to the marginal productivity of effort in creating permits, so that geα < 0. It can bethought of as the extent to which social institutions mitigate against successful
rent-seeking.
The economy operates under a full employment constraint:

e + l = N,(1)with N the economy’s labor endowment. Government is thus not a single entity that
pursues some objective (e.g., maximizing welfare, payoffs to supporters or votes), but anoutlet for entrepreneurial endeavor like productive activity.
Total income produced accrues either to laborers or to permit producers:

Y = wee + wll.

(2)5

we and wl are the wages in each activity. They will be equal to the value ofmarginal product:

we = pge(.),(3)

wl = Afl(.)[1 – t(X)].

(4)

p is the price of permits, measured against the numeraire, income. The model isclosed by imposing the equilibrium condition that the marginal return to labor in the two
activities is equal:

we = wl.

(5)

Given the exogenous α, there are thus eight unknowns – the wage rates we and wl,
the permit price p, total consumption C, total labor devoted to each activity e and l,permits produced X and output produced Y. Some important figures for the analysis here
are the total number of permits in equilibrium X*, the equilibrium amount of effort
devoted to permit production e*, and the loss of output relative to the equilibrium with nopermits:

Y = Af(N) – Af(l*)[1 – t(X*)].

(6)

6

Note that it is possible to have a golden equilibrium in which no permits areissued (e* = 0) and income is maximized. But given the assumptions about f the contrary
result is not possible. In other words, there is no possibility of a perfectly corrupt society.
The economic interpretation for this result is that for at least some interval labor must be
used for production so that there is some output to be distributed to permit owners.
Denmark had a score of 10.0 in the 1998 TI ratings, which the organization characterizes
as “perfectly corruption free.” No nation, in contrast, has thus far received a score ofzero. A sufficient condition for the golden equilibrium is that ge(0, α) < Afl(N). Thiscondition is more likely as α is greater. If it does not hold than an interior solution
obtains.
Several results follow directly from analysis of the above framework. First,
corruption is a negative function of α. Second, there will be co-movements in theequilibrium size of the state X* and the equilibrium amount of corruption e* as α varies.
The weaker are the exogenous constraints on the productivity of permit-creation, thebigger its relative return and hence the larger the relative division of N among l and e.
This result is explicitly derived in Krueger (1974), and is the central point of Tullock(1967). Thus, states with higher (lower) α should have both more (less) government
interference and more (less) corruption. This result requires that the two variables be
considered in a simultaneous framework. The idea that corruption and government areboth endogenous also appears in Erlich and Lui (1999).

2. Corruption and productivity
Another important implication is that more technologically advanced societies

7may have less corruption, for at least one and possibly two reasons. In the usual way,technological progress in production is modeled as an increase in A. Totallydifferentiating (6) and rearranging terms yields

dYdldt ( X ) dX
= f ( N ) − f (l )[1 − t ( X )] − Af (l )[1 − t ( X )]+ Af (l )
.
dA
dA
dX dA

(7)

The change in Y will always have two components. The first is due to the direct

opportunity cost of a given amount of rent-seeking. Output must be created using lessthan the full employment endowment N because labor in the amount e* is unavailable for
production because it has been diverted to creation. This distance, the diversion effect, isgiven by A[f(N) – f(e*)]. This is the effect emphasized historically in the rent-seeking
literature. The second source of inefficiency, the millstone effect, is caused byproduction away from the frontier with the smaller labor pool. It occurs because permit
production destroys some part of potential income. The diversion effect moves
production back along the production frontier, and the millstone effect moves theequilibrium within it.
An increase in A increases the marginal return to production labor, and so labor isreallocated from e to l. Permit production declines, and the diversion effect is
unequivocally smaller, as represented in (7) by f (l )[1 − t ( X )]dl
. However, the directiondAof the change in the millstone effect, and hence the total loss Y , is ambiguous. On the

one hand less effort is being diverted from production, and fewer permits are being
produced, so the tax on production t(X*) is smaller. In (7) this is given by8Af (l )dt ( X ) dX
dt ( X ) dX dl, which can be restated as − Af (l ). On the other hand, thedX dA
dX de dAsmaller fraction is being taken of greater output, and so in absolute terms it is still
possible for Y to grow. This positive effect of higher productivity on Y is given by theremaining terms in (7), f ( N ) − f (l )[1 − t ( X )] .
Whether or not the total amount of corruption increases or decreases because of
the increase in A thus becomes an empirical question, but permit production
unambiguously declines. The answer depends first on the responsiveness of g to changes
in e. The more concave g is, the less reallocation of e will be needed to restore wageequality in the two sectors. This means that the absolute value of the diversion effect islower and the likelihood that the total millstone effect on output, and hence the two
effects combined, is negative is greater. An analogous argument holds for the concavity
of f: the less concave it is, the less reallocation of labor between the sectors occurs. Iflarge, discrete changes in A occur, this increases the income-destroying portion of themillstone effect, and hence makes it more likely that the deadweight loss from corruption
increases. Note that this is a contrast to MSV, who find that an improvement inproductivity cannot lead to an increase in appropriation.
Other than in MSV, the relation between the state of production technology andthe social cost of corruption has not been emphasized in the literature. Even in MSV theestablishment and strengthening of property-rights protection, which establishes the
productivity of rent-seeking effort and is so important in that model, is largely
unexplored. Here, nations with more advanced division of labor or production
technology may have more to lose from corruption. In a society with low productivity,
the effort spent seeking permits may be diverted from, for example, street peddling. But
9in an advanced society, permit-generating effort will be diverted from productive activityof far greater value owing to complex division of labor and the presence of large amounts
of productivity-enhancing technology, e.g. from a semiconductor factory. It is hence iscertainly more costly on a per-unit basis and may be more costly in total.
This is a significant claim because of the light it sheds on the relation between
corruption and prosperity. While it is well-established that corruption harms economic
growth, it is also true that increasing the gains to exchange will lower the return tocorruption. Depending on the nature of the collective-choice process, the greater losses
to corruption in a more productive society may result in a greater investment in its
control. The stylized fact of the coincidence of prosperity and clean governance may not
be simply a function of corruption deterring growth, but of lack of growth providing little
motivation for investment in fighting corruption, and a great deal of motivation forengaging in it. If the model is an accurate description of the corruption process, nations
with higher productivity will empirically have less corruption and will be wealthier, notjust because they are more productive but because there is less deadweight loss frompermit-seeking.

3. The empirical model
The implications
Several empirical questions arise from the above framework, beyond the mostelementary one of the relation between technological advances and corruption. The firstis an older controversy descended from the fatalistic Virginia school of public choice.
Krueger (1974) and MSV depict a rent-seeking trap in which extensive government

10intervention raises the return to appropriation, which draws labor away from production
and causes the production of yet more intervention. Government activity beyond theprotection of property rights will cause more corruption. If a rent-seeking trap developsof the sort predicted by Krueger and MSV, government size will increase corruption, andcorruption too will increase government spending. There is also a particular variant withrespect to democracy. For example, Cheung (1998) argues that it promotes not just poor
economic performance but corruption as well, as politicians auction off government
favors to factions in an electorate ill-prepared to appreciate the costs of such measures.
On the other hand the Chicago school of public choice argues that governance,and democratic governance in particular, is a means to provide public services thatcoexist with rent-seeking in a manner that minimizes the latter. Politicians andbureaucrats are subject to competitive pressures, which may differ in type but not in
fundamental nature from those of market traders. Excessively costly intervention
provokes competition from political traders – electoral candidates, potential appointees tothe bureaucracy, etc. – who bid down both the level of intervention and the level ofbribery and other costs associated with it. In other words, political markets behave inexactly the same way as any other markets. The argument is laid out most famously in
Becker (1983), and finds echoes in Olson (2000). Collective choice determines spending,which then determines lower corruption. An extension that has proven particularly
influential is Wittman (1989), who argues that democracy in particular improves thecompetitiveness of the political process, and hence should enhance efficiency, defined
not around income maximization but preferences of the citizenry.

11

If the Chicago hypothesis is correct, we would expect that institutional features ofsocieties that lower the cost of political competition – i.e., that lower g' – would lower theamount of corruption. Such features might include open immigration and emigration
laws, freedom of thought (in press, speech and religion), and limits on the ability of thestate to prosecute political opposition. The Wittman variant would also suggest that
democratic means for deciding political power should promote more effective corruption
control.
The two schools of thought also have different implications for the meaning ofgovernment spending. In Virginia-school thinking it is simply rents successfully sought,
while in Chicago-school thinking it is something that arises from public desires for social
insurance, construction of public goods or other widely desired goals beyond propertyrights protection.
The dynamics of government size over time are themselves the subject of an
extensive empirical literature. The claim that national per capita income increases
demand for government spending, regulation and production has been investigated anumber of times. Among the papers that investigate the growth of spending, a key
controversy is whether the demand for such spending is income-elastic. While thegrowth of government spending as countries have gotten wealthier has been noted in thepast (Peltzman, 1980), the large empirical literature on whether the latter causes theformer is mixed. For example, Kolluri et al. (2000) and Thornton (1999) find that it does
and Afxentiou and Serletis (1996 IEJ) find otherwise. In any event, the theory is
sufficiently entrenched to indicate that any empirical model in which government

12

spending is a left-hand variable indicates that per capita income be included on the righthand side.
The Empirical Specification
Several versions of the following basic simultaneous empirical model are used totest the above implications:

CORRUPTION = a0 + a1 GOV + a2 PCS + a3 OPEN + a4 COMPETITION +a5 FRACTION + a6 CULTURE(8a)

GOV = b0 + b1 CORRUPTION + b2 PCGDP + b3 POLRIGHTS +b4 URBAN + b5 AVGSCHOOL(8b)

PCGDP = c0 + c1 CORRUPTION + c2 PCS(8c)

The estimation is by three-stage least squares. CORRUPTION is the sum of two
World Bank measures of governance quality, “corruption control” and “rule of law,” for2002. These survey-based data are available at
http://info.worldbank.org/governance/kkz2002/tables.asp. A higher number denotes
better governance. GOV is government consumption spending as a fraction of GDP,
which is a proxy for rent-seeking in Virginia-school thinking and a desired outcome ofcollective choice, to be protected from the impact of corruption, in Chicago-school
theory. PCS is the number of personal computers per 1000 population in 2000, andproxies for A. It is from the World Bank’s World Development Indicators. OPEN is

13

imports plus incoming foreign direct investment as a percentage of GDP. It is included
on the assumption that more pressure from globalization of the economy results inendogenously better governance.
COMPETITION is a combination of two variables that measure how easy it is tobring political pressure to bear to lower corruption. POLRIGHTS is the Freedom Housemeasure of political rights, which ranges from one to seven, with one denoting the mostfreedom. This variable is widely used in empirical work, but for present purposes it isworth investigating it in some detail. A country’s rating depends on the extent to which
public officials are chosen by election, whether electoral competition is meaningful,whether elected officials have significant power, whether citizens can organize into
effective political groups, whether the country is free from domination by traditional or
military hierarchies, and whether minorities have self-governance and/or substantial
participation in government. INFOSOC is the 2003 compilation of a measure created by
Norris (2001, Table 3.2) of the combination of old and new media available in a country– of the penetration of newspapers, radio, television and stationary and mobile telephones
plus the percentage of the population that regularly uses the Internet, the percentage thatuses personal computers and the number of Web hosts.
POLRIGHTS and INFOSOC measure two different aspects of the cost ofchanging government policy, including anti-corruption efforts. The former measures thecost to citizens of opposing a policy once they have made a decision on its merit, and thelatter measures how costly it is to gain the information necessary to make the decision.4

4. The argument that freedom of thought, i.e. of speech, religion and the press, is a way
to make information markets more competitive has been made by Posner (2003).

14

Because it is more narrowly defined, INFOSOC is a superior arrangement than Freedom
House’s companion measure to POLRIGHTS, which measures civil liberties and is
widely used in other work. While the civil-liberties measure is partly based on “freedomof expression, assembly, association, education, and religion, it also incorporates a“generally equitable system of the rule of law.” 5 It is thus best seen as a measure of bothan input and an output in the framework here.
FRACTION is the combination of the measures of ethnic, linguistic and religious
fractionalization generated by Alesina (2003). If greater tribal fractionalization raises thecosts of coordination across tribal lines to fight corruption or facilitates the creation ofsmaller tribally defined groups around which to organize, greater fractionalization can in
the framework here increase the marginal productivity of permit-production effort.6 That
paper finds that, on a simple correlation basis, this index is positively correlated withcorruption. Finally, CULTURE stands for vectors of cultural dummies that attempt toaccount for global differences in preferences that might make corruption more or lessundesirable. While the model assumes that corruption is undesirable because it lowers
income, it is possible that corrupt practices yield offsetting utility. Such a cultural source
for corruption has been theoretically posited by Huang and Wu (1994) and Montaner(2000), though theoretically discounted by Paldam (2002). There are three attempts tomeasure such differences, based on geography, colonial heritage or modal religion.
Dummies are included in the first specification for sub-Saharan Africa, Spanish-speaking
5. Quoted descriptions are from Freedom House (2003).
6. For an analysis of widespread tribal fractionalization proving productive for rentseeking in India see Osborne (2001).

15

Latin America, the former Soviet Union and members of the Arab League. The second
specification includes dummies for Anglo-American, French or Iberian colonial heritage.
The third uses dummies taking the value one if the modal religion is Protestant
Christianity (including Anglicanism), Catholicism or Islam, the three religions with
sufficient representation in the data set to merit inclusion. PCGDP and URBAN are the2000 values of per capita income and the percentage of the population that is urban, fromthe WDI.
(8a) includes, in addition to the causation from government to corruption positedby the rent-seeking literature, three elements of α – political competition, information
production and fractionalization. PCS measures A. If the MSV model is correct it should
be positively signed. In addition to including the amount of government spending to test
for the simultaneous rent-seeking trap, (8b) contains variables recommended by some of
the growth-of-government literature, which contends that public spending expands inhigher-income and more urbanized (Peltzman, 1980; Kau and Rubin, 2002) nations. (8c)is the equation for equilibrium income, Af(l*)[1-t(X*)].
Results are reported in Table 1. Because INFOSOC and POLRIGHTS are highly
correlated (ρ = -.5870), a model without POLRIGHTS in (8a) is also reported for each
cultural specification. With respect to the prime issue raised in the above analysis, in all
specifications a higher level of technological productivity is associated with lesscorruption. Other issues are clarified as well. The result of Alesina (2003) is somewhat
robust to the extension here, in that FRACTIONALIZATION is significant at at least theten-percent level in five of the six specifications. POLRIGHTS is significant in all
specifications in which it is included.

16

The results of the variables representing the competitiveness of political markets
are striking. In the specifications with both variables POLRIGHTS is significant in the
expected direction while INFOSOC is only significant (in the expected direction) once,
when it is the only political-market competition variable included. This result suggeststhat political competition is extremely important in promoting better governance, and that
information sufficient to allow citizens to agitate for it prevails even when penetration of
new and old media is not particularly pronounced. It may be that the necessary
information about corruption’s nature, scope and particulars can emerge even without
such conventional measures of its availability, so that the means to act on the information
is of primary importance. Political markets, in other words, can function well (at least
with respect to corruption) even when the market size of the formal informationgenerating industry is not large.
As for the cultural dummies, the only constant finding is that LATIN is significant
and negatively signed. Religious and colonial-heritage variables are never significant.
Nations with Latin backgrounds tend to have more than the expected amount ofcorruption, other things equal. Figure 3 plots the actual amount of corruption versus what
would be expected without the Latin penalty for Latin countries in the data set, i.e. thepredicted value from the structural-form estimation of (8a) in the full specification
without accounting for the Latin dummy. The average Latin country in the sample is45.3 percent more corrupt than would be expected (n = 9). This anomaly, the only
consistent cultural result, remains to be explained. Other than that, corruption appears to
be a phenomenon of income maximization rather than intrinsic preferences.

17

45-degree line

Ctry: Expected Corruption

4.38

CRI
URY
COL
ARG
NIC
HND
ECU
PRY

PER

-3.24
4.38

-3.24
World Bank Governance Index

Figure 3 – Expected corruption for Latin nations.
Also of interest is the failure to confirm the standard version of the rent-seeking
model as it applies to government spending. Both corruption and government spending
are typically significant in the simultaneous framework. But unlike rent-seeking theory
predicts, the signs are positive. The quality of governance is always a positive andsignificant predictor of the amount of spending, while spending is in three of six
specifications a significant predictor of quality of governance. In other words, nations
that have greater government spending tend to spend more on corruption control for agiven level of productivity, and nations with better governance are willing to engage inmore government spending. This suggests that government spending grows for reasons
external to corruption, but if it is bigger because of social preferences then societies may
find it worthwhile to invest more in corruption control, a topic explored in Section 4
below. The results, combined with the positive effect of more effective politicalcompetition on corruption control, provides support for optimistic models of political18

competition generally and electoral competition in particular as means to control the
deadweight losses of government spending.

4. Interpretation and Speculation
The results are suggestive on a number of counts with respect to the causes andeffects of corruption. One finding is that the relation between corruption and government
spending is the opposite of what traditional models of rent-seeking would predict if theformer is an output of the latter, other things equal. In addition, Fig. 1 suggests that
wealthy nations that devote large percentages of national income to extensive welfare
states are also among the least corrupt. That is a phenomenon that begs explanation.
Given that large amounts of income are transferred via the government in such programs
as state pensions and health-care systems, why are these societies, with so many tempting
rent-seeking targets, not more corrupt than they are? The answer may be that large
government spending, particularly in an advanced society, carries a corruption penalty
that is too high. If corruption also causes each unit of government spending to be subject
to corruption-induced waste, more corruption implies that these costs, too, are greater. It
is then easier to justify spending more resources on the prevention of such waste bygreater enforcement of property rights. The role of an independent judiciary as suggested
by Landes and Posner (1975) provides one plausible means of corruption control,
although the lack of any measures of judicial independence prevents a direct test of an
association between government spending and such independence.
The findings may also explain what has come to be known as the “Tullock
paradox.” Rent-seeking scholars have puzzled for years over the seemingly small

19amount of rent-seeking expenditures relative to the size of the rents being sought. Mostof the evidence has been anecdotal, with Tullock himself (1997) citing a large number ofexamples from the U.S. But societies that invest a great deal in the rule of law both lower
the returns to rent-seeking and insure that the rents that are parceled out are more stable,
thus discouraging endless cycles of rent-seeking warfare. While the paradox has always
focused on the seemingly implausibly high benefit/cost ratios for the winners in avigorous rent-seeking market, it is worth remembering that for every winner there may be
many losing pressure groups. Strategies that raise α will also cause each of these groups
to spend few resources in its unsuccessful efforts. The most important effect of cleaner
governance is thus to insure that the combined amount spent by winners and losers issmall.
The results also suggest that there is an under-emphasized dynamic andendogenous aspect to corruption. While it is surely true that corruption hampers
economic growth, it is also true that rapid growth and rising prosperity increase
the social cost of corruption. If the market for governmental authority is at least
somewhat competitive, whether via elections or not, then as nations prosper theirpolitical systems should begin to weed out the most corrupt practices accordingly.
If α is lowered over time by such a Becker (1983)-type competitive process, therelatively high amount of corruption in poorer societies may be due not just to thedeleterious effects of corruption on growth but to the fact that the costs, politicaland otherwise, of the investments needed to protect against it are not yet justified
by the benefits. If education, modern technology efficiently applied and thedivision of labor advance sufficiently rapidly to enable rapid growth then the20corruption tax may grow so costly that political competition overcomes the inertia
of existing rent-seeking pressures and brings about political changes to reduce it.
If not countries may stagnate in the rent-seeking trap.
History is replete with anecdotes of better governance and prosperity
coinciding. While he does not make the connection, Barzun (2000) notes that
Venice was by a substantial margin the best-governed state in late-Renaissance
Europe, even as it was the most commercial. The puzzle of governance in
Renaissance Italy has also drawn the attention of Putnam (1993). Southern Italy
was governed vertically, with a feudal hierarchy extending down from the king,while Northern Italy was governed horizontally, with mutual defense pacts
between relatively equal community associations. But the usual assumption isthat causation runs from government structure to prosperity – better governanceled to more wealth creation. However corruption control, with its enforcement
requirements and the need to provide adequate compensation to civil servants, is
not free, and its cost may have to be justified for a welfare-maximizing
government to find it worthwhile.
The pattern of corruption may well have an endogenous timeline as acountry industrializes, just as income distribution has been demonstrated to have
(Kuznets, 1968). There may be a takeoff point for anti-corruption efforts that is
analogous to and indeed may trail by some consistent margin the better-known
takeoff stage in industrialization. Once there is a widespread introduction ofenough productivity-enhancing shocks the two effects of cleaner governanceenhancing growth and higher productivity enhancing corruption control may

21

reinforce one another. Anecdotal evidence on societies suddenly making
substantial efforts to control corruption is common. Singapore and Hong Kong,which are now thought of as model states with respect to corruption control, wereactually quite corrupt until reforms were launched in the mid-1960s in the formercase and the early 1970s in the latter, after rapid growth had begun but well before
it had ended. Similar launches of anti-corruption efforts have been documented
for the United Kingdom, the first industrial power, in the mid-nineteenth century
and for the U.S. later in that century (Rose-Ackerman, 1999). If the dating ofthese efforts is accurate it appears that they all occurred after the industrialization
process was well underway. Miwa and Ramseyer (2000) present an example
from the other side in which Japanese firms in the early twentieth century, whenindustrialization was still young, established arbitration procedures to avoid avery corrupt judiciary.
The ability to use government to transfer wealth is in some sense
instability in property rights, in that the right to use property in exchange isconstrained. The firm that requires a license to import (especially if it must pay a
bribe to get one) finds its ability to exchange resources it owns in voluntary
exchange for that import limited and more costly. The domestic monopolist
protected by bribes lowers the purchasing ability of the labor time of its
customers. The problem of corruption control may be just an example of thebroader Demsetz (1967) analysis of property rights evolving only when thebenefits to establishing them justify the costs of enforcing them.

225. Conclusion
Development is about dynamics and transformation. Thus how corruption
might evolve over time is a question of great interest. The introduction of modern
technology and economic organization brings with it all manner of well-known
changes – migration to the cities, declining fertility, etc. The cost of corruption issomething else that changes over time. Raising the relative return to production
may cause an endogenous decrease in rent-seeking activity. Further, if
government officials have self-interest that promotes corruption but the society as
a whole has an interest in controlling it, these two functions trade off. That
corruption is a negative function of the cost of creating opportunities for it is acentral finding of this paper. The implication is that policies that promote
productivity, e.g. improvements in education and public health or liberalized
economies, can generate incentives for investing in the rule of law. This is in noway to diminish the importance of organized anti-corruption campaigns in poor
countries, but just as with environmental and safety regulation in there are limits
to the ability of the state to achieve goals by passing laws, limits that are much
more compelling in impoverished nations.

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27

WBSUM
INTERCEPT
GOV
PCS
OPEN
FRACTIONINFOSOCPOLRIGHTS
AFRICA
ARAB
LATIN
USSR
R2
Χ2
N
WBSUM
INTERCEPT
GOV
PCS
OPEN
FRACTIONINFOSOCAFRICA
ARAB
LATIN
USSR
R2
Χ2
N

-1.418555(-1.28).1296418*(2.03).006269***(4.23)-.0027672(-1.11)-.3747026*(-2.20).0133384(1.16)-.1890665*(-2.24).1708384(0.60).414682(0.92)-.8088764**(-3.17)-1.007727**(-2.83).8272
416.1654***69-3.382208***(-3.19).2010441**(2.68).0044369*(2.55)-.002575(-1.01)-.256598(-1.36).0277866*(1.99).1075546(0.35)-.0699911(-0.17)-.6418411*(-2.13)-.8740332*(-2.38).6932
213.0734***
69

Table 1
Regression Results
Geography as cultureWith POLRIGHTSGOV
INTERCEPT
15.38464***(5.76)
WBSUM
3.891733***(3.45)
PCGDP-.0006735**(-2.61)POLRIGHTS.0537489(0.14)
URBAN.0854309*(2.22).1059
27.14104***
Without POLRIGHTSGOV
INTERCEPT
18.79233***(11.03)
WBSUM
34.435863***(4.12)
PCGDP-.0008045**(-3.27)POLRIGHTS-.3253623(-1.01)
URBAN.0651084*(1.78).0061
36.47703***

28

PCGDP
INTERCEPT 5502.004***(8.38)
PCS
29.84462***(4.48)
2272.393***
WBSUM(4.16).8913
568.0146***

PCGDP
INTERCEPT 5561.989***(8.49)
PCS
29.02824***(4.37)
2343.126***
WBSUM(4.30).8903
568.9656***WBSUM
INTERCEPT
GOV
PCS
OPEN
FRACTIONINFOSOCPOLRIGHTS
ANGLO
FRANCEIBERIA
R2
Χ2
N
WBSUM
INTERCEPT
GOV
PCS
OPEN
FRACTIONINFOSOCANGLOFRANCEIBERIAR2
Χ2
N-1.195998(-1.11).1077118*(1.67).0082935***(4.71).000366(0.10)-.4631047*(-2.31).0016048(0.13)-.1818573**(-2.74).2605764(0.87).3304371(1.04)-.4587754(-1.58).8337
381.0644***69-1.918384*(-1.74).0971011(1.45).00776608***(4.13).0015961(0.39)-.4289032*(-2.01).0144997(1.14).2497119(0.78).1556793(0.47)-.3361216(-1.08).8202
344.3236***
69

Table 1 (continued)
Colonial heritage as cultureWith POLRIGHTSGOV
INTERCEPT
13.40274***(5.76)
WBSUM
2.434738*(1.93)
PCGDP-.0003975(-1.44)POLRIGHTS-.0786562(-0.19)URBAN.0905269*(2.34).2352
21.67442***
Without POLRIGHTSGOV
INTERCEPT
18.79233***(11.03)
WBSUM
34.435863***(4.12)
PCGDP-.0008045**(-3.27)POLRIGHTS-.3253623(-1.01)
URBAN.0651084*(1.78).1905
25.66064***

29

PCGDP
INTERCEPT 5568.614***(7.22)
PCS
28.94224***(3.35)
WBSUM
2350.046***(3.24).8903
555.7198***

PCGDP
INTERCEPT 5561.989***(8.49)
PCS
29.02824***(4.37)
2343.126***
WBSUM(4.30).8857
558.6742***WBSUM
INTERCEPT
GOV
PCS
OPEN
FRACTIONINFOSOCPOLRIGHTS
CATHOLICPROTESTANT
ISLAM
R2
Χ2
N
WBSUM
INTERCEPT
GOV
PCS
OPEN
FRACTIONINFOSOCCATHOLICPROTESTANT
ISLAM
R2
Χ2
N

-.7609738(-0.59).0720183(0.84).0086001***(5.04).0018012(0.51)-.3019184*(-1.77).0055977(0.44)-.209615*(-2.49)-.3171243(-1.10)-.3725017(-0.97).2875778(0.57).8484
398.3437***69-3.047503*(-2.46).1570492(1.56).0066399**(3.15).0015362(0.42)-.1787926(-1.01).019743(1.26)-.1133079(-0.35)-.3263573(-0.83).0645997(0.14).7539
207.8016***69

Table 1 (continued)
ReligionWith POLRIGHTSGOV
INTERCEPT12.87168***(5.76)
WBSUM
2.030967*(1.93)
PCGDP-.0003246(-1.44)POLRIGHTS-.1206088(-0.30)
URBAN.0926311*(2.31).2525
21.19363***
Without POLRIGHTSGOV
INTERCEPT
18.79233***(11.03)
WBSUM
34.435863***(4.12)
PCGDP-.0008045**(-3.27)POLRIGHTS-.3253623(-1.01)
URBAN.0651084*(1.78).1992
23.51664***

30

PCGDP
INTERCEPT 5614.329**(6.95)
PCS
28.32376**(3.07)
WBSUM
2403.163**(3.09).8895
551.5256***

PCGDP
INTERCEPT 5561.989***(8.49)
PCS
29.02824***(4.37)
2343.126***
WBSUM(4.30).8868
5583.3751***