Does corruption grease or sand the wheels of growth?
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PiihlU Choice (2005)122: 69-97.
© Springer 2005.
Does corruption grease or sand the wheels of growth?
PIERRE-GUILLAUMEMEON' & KHALID SEKKAT-
Lcir^e, Univcrsilc Robcrl Schitnum. In.stitu! d'Etudes Politiques, 47 Ave de la Fn ret Noire,
670H2 Strasbourg Cedex, France; E-rtuul:picrre-guillaunu'.meon(Q''U'p.u-slrusbf'.fr;
-Dulbeu. Universite Libre de Bruxelles. 1050 Bruxeltes. Belgium: E-mail: k.Kekkat@ulb.ac.be
Accepted I October 2003
Abstract. This paper assesses the relationship between the impact of corruption on growth
and investment and the quality of governance in a sample of 63 to 71 countries between 1970
and 1998. Like previous studies, we find a negative effect of corruption on both growth and
investment. Unlike previous studies, we find that corruption has a negative impact on growth
independently from its impact on investment. These impacts are. however, different depending
on the quality of governance. They tend to worsen when indicators of the quality of governance
deteriorate. This supports the "sand the wheels'" view on corruption and contradicts the "grease
the wheels" view, which postulates that corruption may help compensate bad governance.
1. Introduction
Is corruptioti detrimental or beneficial to the economic activity? At first
sight the question seems ironic and even provocative. It is, however, still
controversial among economists.
Common wisdom views corruption as an impediment to development
and growth. This view was recently supported by the results of the literat-
ure aimed at quantifying the consequences of corruption and growth. That
literature was pioneered by Mauro (1995), who observed a significant negat-
ive relationship between corruption and investment that extended to growth.
Mauro (1995)"s findings were confirrned by Brutietti and Weder (1998) and
Mo (2001). As a result, international organizations (e.g. the IME, the World
Bank, the UN or the OECD) gave the fight against corruption high priority.
They took international initiatives (e.g. the UN resolution in 1998 or the 1999
OECD's "Convention on combating bribery") and urged States to criminalize
and deter the bribery of foreign office holders.
* We thank an anonymous referee for very helpful comments, which substantially im-
proved the paper. We also benefited from very useful discussions with participants to the
"Institutions, growth und development" conference in Perpignan. 2003, and the 2(X)..i Annual
Meeting of the European Public Choice Society, in Aarhus. and with seminar participants at
the University Robert Schuman of Strasbourg and the University Louis Pasteur of Strasbourg.
We acknowledge financial support from the Research Fund at the ULB.
70
In contrast, other researchers have suggested that graft may be beneficial.
Leys (1965) questioned "the problem about corruption". Bardhan (1997) re-
called episodes of the history of Europe and the US which illustrate situations
where corruption may have favored development by allowing entrepreneurs
to grow out of bribers. Furthermore, Beck and Maher (1986) and Lien (1986)
argued that comaption tnay raise efficiency. The most popular Justification
of the beneficial effects of corruption rests on the so-called "grease the
wheels" hypothesis. Put forward by Leff (1964), Huntington (1968) and Leys
(1965), that hypothesis suggests that corruption may be beneficial in a second
best world because of the distortions caused by ill-functioning institutions.
That argument is that an inefficient bureaucracy constitutes an impediment
to investment that some "speed" or "grease" money may help circumvent.
In a nutshell, the "grease the wheels" hypothesis states that graft may act
as a trouble-saving device, thereby raising efficiency hence investment and,
eventually, growth.
The empirical evidence on the negative impact of corruption on growth
and investment is not inconsistent witb the "grease the wheels" hypothesis.
The hypothesis implies that corruption may be beneficial in countries where
other aspects of governance are ineffective, but remain detrimental elsewhere.
Existing evidence shows that corruption is on average associated with lower
growth and investment but do not investigate to what extent such an associ-
ation depends on the quality of governance. Actually there is little evidence
allowing a rigorous rejection of the "grease the wheels" hypothesis. Mauro
(1995) has attempted to shed light of this issue by splitting his sample in
high red tape and low red tape sub-samples of countries. He did not find
any significant difference between the two sub-samples with respect to the
negative impact of corruption. However, the threshold for splitting the sample
was rather arbitrary (score of 5 or 7 of the red tape index) and the size of
the sub-samples became too small to allow the inclusion of control vari-
ables.' Kaufman and Wei (2000) tackled the issue from a different angle.
Using firm-level data, they tested whether corruption reduces the time that
firms spend negotiating with foreign countries' officials. Tbey found that
multinationals that pay more bribes also tend to spend more time negotiating
with foreign countries' officials, which contradicts the "grease the wheels"
hypothesis. To our knowledge, there were no other attempts to rigorously test
the "grease the wheels" hypothesis.
This paper tests systematically the "grease the wheels" hypothesis at a
macroeconomic level. It estimates the relationship between the impact of
corruption, on investment and growth, and a wide range of indicators of the
quality of governance. The results not only reject the "grease the wheels" hy-
pothesis but arc consistent with the reverse hypothesis: the "sand the wheels"
71
hypothesis. It seems that corruption becomes even more harmful when gov-
ernance is poor. In economics, there are well known situations where in the
presence of existing distortions an additional distortion may improve welfare.
Our hnding illustrates the opposite case where adding a distortion deteriorates
welfare.
The rest of the paper is organized as follows. The next section presents
the theoretical underpinnings of the "grease the wheels" and the "sand the
wheels"" hypotheses. Section 3 describes the econometric approach. Section
4 presents the results. Section 5 concludes.
2. The "grease the wheels" versus the "sand the wheels" hypothesis
The debate on the impact of corruption on economic performance goes bey-
ond a "moralistic view" that unequivocally condemns corruption.- The moral
judgement on corruption may bias the understanding of its economic con-
sequences. One strand of the literature argues that corruption may take place
in parallel with a low quality of governance and can. therefore, reduce the
inconvenience of such low quality. This is the "grease the wheels"" hypothesis.
Another strand stresses that although bribery may have benefits if the quality
of governance is low, it may as well impose additional costs in the same
circumstances. The existence of such costs provides a rationale for the "sand
the wheels" hypothesis.
The core of the debate on the "grease" vs. the "sand the wheels" hypo-
theses lies in the combination of corruption with a low quality of governance.
While there are many aspects of governance that corruption may grease or
sand, the literature has mainly focused on two. One concerns the ill func-
tioning of bureaucracy (i.e. its failure to accomplish assigned goals: see Leff,
1964) while the other refers to policy options by public authority. The extent
to which corruption can grease or sand the wheels in the presence of a low
quality of governance is discussed below.
2.1. The "}>rea.se ihe wheels" hypothesis
The ill functioning of the bureaucracy is considered as the most prominent
inefficiency that corruption could grease. Huntington (1968) stated: "In terms
of economic growth, the only thing worse than a society with a rigid, over-
centralized, dishonest bureaucracy is one with a rigid, overcentralized, honest
bureaucracy". There are various aspects of ill functioning of the bureau-
cracy that can be compensated by comjption. A first one concerns slowness.
Using a formal economic model. Lui (1985) showed that corruption could
efficiently lessen the time spent in queues. The reason is that bribes could
72
give bureaucrats an incentive to speed up the process, in an otherwise slug-
gish administration (see also Leys, 1964). Furthermore, Huntington (1968)
argued that corruption could help surmount tedious bureaucratic regulations
and foster growth. According to him. such a phenomenon had been observed
in the 187O's and 188O's in the United States, where corruption by railroad,
utility and industrial corporations resulted in faster growth.
Another consequence of an ill-functioning bureaucracy concerns the qual-
ity of civil servants. Leys (1964) and Bailey (1966) argued that corruption can
amend a bureaucracy by improving the quality of its civil servants. If wages
in govemment service are insufficient, the existence of perks may constitute
a complement that may attract able civil servants who would have otherwise
opted for another hne of business.
Finally, Beck and Maher (1986) and Lien (1986) suggested that corruption
may enhance the choice of the right decisions by officials. If bureaucrats
do not have enough information or are not competent for some decisions,
corruption can replicate the outcome of a competitive auction. They formally
showed that when attributing a govemment procurement contract the ranking
of bribes can replicate the ranking of firms by efficiency. Moreover, if some
investment projects are dependent on the attribution of a license, corruption
may be an efficient way of selecting such projects. Here again, conoiption
in the attribution of a government license is very similar to a competitive
auction. The intuition (Leff. 1964) is that licenses tend to be allocated to the
more generous bribers, who can be the more efficient. Hence, the capacity to
offer a bribe is correlated with talent.
Tuming to the other aspect of governance, some authors praise corruption
for its role in allowing economic agents to escape the consequences of some
policies. Bailey (1966) for instance argues that if bribes could help private
agents to evade a public policy designed to solve a particular problem, they
may thereby allow them to find an overlooked and better-suited solution. This
may in tum allow an improvement of the policy's outcome even in terms of
the government's objectives. Leff (1964) and Bailey (1966), also argue that
graft may simply be a hedge against bad public policies. This is particularly
true if institutions are biased against entrepreneurship. due for instance to an
ideological bias. By simply impeding inefficient regulations, cormption may
then limit their adverse effects. It may also result in an alteration of the policy
in a way that is friendlier to growth.
It has also been argued that graft may in some circumstances improve
the quality of investments. This is the case (Leff, 1964) when government
spendings are inefficient. If cormption is a means of tax evasion, it can reduce
the revenue of public taxes. Provided the bribers can invest efficiently, the
overall efficiency of investment will be improved. In addition to the quality
73
of investments, some authors argue that cormption may also raise the level of
investment. For instance, Leff (1964) asserts that cormption may constitute
a hedge against other risks originating from the political system, such as ex-
propriation or violence. If cormption helps tnitigating those risks, investment
will turn out less risky and may accordingly increase.
All the above-mentioned arguments share the presumption that cormption
may positively contribute to growth and development, because it compensates
the consequences of a defective bureaucracy and bad policies. One may nev-
ertheless wonder whether cormption creates or reinforces other inefficiencies
and whether bribers are always taking more efficient decisions than public
authority. Although bribery may have benefits in a weak institutional envir-
onment, it may as well impose additional costs in the same circumstances.
The existence of such costs provides a rationale for the "sand the wheels"
hypothesis.
2.2. The ''sand the wheels" hypothesis
Starting with the ill functioning of bureaucracy, the positive impact of cor-
mption on slowness rests on the assumption that a civil servant can speed up
an "exogenously" slow process. However, cormpt civil servants lnay cause
delays that would not appear otherwise, just to get the opportunity to extract
a bribe (Myrdal, 1968). Moreover, the ability of civil servants to speed up
the process can be very limited when the administration is made of a suc-
cession of decision centers. In this case, civil servants at each stage can have
some form of veto power or some capacity to slow down a project. Using
industrial organization models, Shleifer and Vishny (1993) show that the cost
of cormption can be higher when, say to get an authorization for a project,
many independent agents are involved than when only one is. Bardhan (1997)
reports that an Indian high official once declared that he could not be sure to
be able to move a file faster but could immediately stop it. The increased num-
ber of transactions due to graft may well offset the increased efficiency with
which transactions are carried out (Jain, 2001). Under these circumstances
one distortion adds up to the others instead of compensating thein, which is
precisely the meaning of the "sand the wheels hypothesis"
At an aggregate level, the impact of corruption on the quality of civil
servants is questionable. Kurer (1993) argued that corrupt officials have an
incentive to create other distortions in the economy to preserve their illegal
source of income. For instance, a civil servant may have an incentive to ra-
tion the provision of a public service just to be able to decide to whom to
allocate that service in exchange for a bribe. Similarly a civil servant also
has the incentive to limit new servants' (especially competent ones) access to
key positions in order to preserve the rent form corruption. While individual
74
bribers can indeed improve their own situation thanks to a perk, nothing is
gained from corruption at the aggregate level.
The argument that corruption may enhance the choice of the right de-
cisions is also subject to doubt. There are reasons to believe that agents paying
the highest bribe iire not always able to improve efficiency. Rose-Ackerman
(1997) argues that a firm may be able to pay the highest bribe simply because
it compromises on the quality of the goods it will produce if it gets a license.
Mankiw and Whinston (1986) show that entry on a market may be beneficial
for the firm but detrimental for welfare. In these cases, entry is, in general,
subject to an authorization. Although entry is detrimental for welfare, the firm
can find it profitable to pay the bribe to get the authorization and enter the
market. Finally, if the profitability of a license is uncertain, the winner of the
auction may be the more optimistic rather than the most efficient, a situation
that is known as the "winner's curse". In these cases, corruption is not the
best way to award a license. Thus, even if the analogy between corruption
and a competitive auction holds, there are situations where the winner is not
enhancing efficiency.
Tuming to the second category of institutional deficiencies (i.e. policy
options by public authority), the argument in favor of corruption can be
counter-balanced in various respects. The argument according to which
corruption may raise both the quantity and the quality of investment is ques-
tionable. There is evidence that this may not be true for public investment.
Empirical evidence shows that higher corruption is associated with higher
public investment (Tanzi and Davoodi, 1997) and that this results in a diver-
sion of public spending towards less efficient allocations (Mauro. 1998). In
other words, corruption results in a greater amount of public investments in
unproductive sectors, which is unlikely to improve efficiency and result in
faster growth.
One may also doubt that corruption may be a hedge against risk in a polit-
ically uncertain environment. This may only be true if corruption does not
imply additional risk-taking. However, corruption is not a simple transaction.
As it is illegal, the commitment to comply with the terms of the agreement
may indeed be very weak, which may lead to opportunism, especially on
the bribee's part. As Bardhan (1997) points out, the inherent uncertainty of
corrupt agreements may simply make the efficiency-enhancing mechanisms
ineffective. This presumption is supported by the results obtained by Campos
et al. (1999) and Lambsdorff (2003) who observe that the unpredictability of
corruption has an impact on investment and capital infiows that is independ-
ent from the impact of the level of corruption. As a result, it is likely that
corruption may increase the risks associated with a weak rule of law instead
of compensating it.
75
3. The econometric approach
The above analysis has shown that the core of the "grease" vs. the "sand
the wheels" debate is not whether cormption reduces investment and growth
in general. Instead, the concern is whether corruption increases or decreases
investment and growtb when the quality of governance is low. When the qual-
ity of govemance is low, if corruption mitigates the negative effect of such a
situation, investment and growth will be higher with corruption than without
it. i.e. it greases the wheels. Alternatively, if corruption magnifies the negative
effect of such a situation, investment and growth will be lower, i.e. cormption
sands the wheels. Although the situation of a country with a high quality of
govemance is not directly addressed in tbis literature, it seems reasonable
to assume that investment and growth should be lower with cormption than
without it. In this case corruption entails costs and has no imperfection to
grease. The rest of the section describes the econometric model and data sets
used for the analysis.
3.1. The model
Since the seminal works by Kormendi and Meguire (1985), Barro(]991) and
Mankiw et al. (1992). the modern growth literature, although quite dense, has
focused on a common specification: cross-countries regression. Studies of
the institutional and political determinants of growth have also widely used
the same technique.^ It has then become standard to express the average rate
of per capita growth (or the average rate of investment) of a given period
as a combination of a few explanatory variables. The economic variables
that are typically included to explain long run macro-economic relationships
are: GDP per capita in the initial year of the period under study, average
population growth, initial school enrolment, investment ratio and a measure
of openness to trade. Depending on the purpose of the empirical analysis
additional explanatory variables (e.g. war, ethnicity, corruption) are incor-
porated. The objective of the present study is to examine how the quality
of governance affects the impact of cormption on investment and growth.
Hence, two additional sets of explanatory variables are considered. One refers
to corruption indices while the other concems measures of the quality of
govemance.
In econometric terms, examining whether growth and investment increase
or decrease with cormption when the quality of governance is low implies
testing how the latter affects the coefficient of corruption. Hence, the usual set
of explanatory variables in the growth {or investment) regression is comple-
mented by a cormption index and an interaction term defined as the product
76
of that cormption index by a proxy for the other deficiencies. This results in
the following specification for the growth rate of per capita income:
log(yT) - tog(yi,) = ff,) + ff, * log(yn) + ai * log(Sco) + a^ * [l
- log{pop())l + ^4 * log(inv) + 05 * log(open)
-\- [06 + cy * !og(gov)] * log(cor) + fi
(1)
where
— log(yo) is the average growth rate of per capita in-
come over the sample period
is the initial per capita income
log(Sco) is the initial level of schooling
log(popT) — log(popo) is the average growth rate of population over
the sample period
log(inv) is the average ratio of investment to GDP over
the period
log(open) is the degree of openness of the economy
log(cor) is the cormption index
log(gov) is the govemance indicator
fi is the error term
The investment specification is similar to Equation (1) except that the
dependent variable is the ratio of investment to GDP and that [log(popT) —
log(popo)] and log(inv) are not included.
The purpose of including per capita GDP in the first year of the sample
period is to take into account the absolute convergence effect highlighted
in the neo-classical growth model. If convergence has taken place, a\ < 0.
Similarly, population growth allows to take into account the negative (a^ < 0)
effect of demographic growth on the growth rate of per capita income.
We also use the enrolment ratio in primary or secondary school in the
initial year, defined as the ratio of total enrolment, regardless of age, over
the population of the age group that officially corresponds to the level of
education shown. It is a common proxy for human capital (Mankiw et al..
1992). An improvement in human capital should boost growth and investment
(^2 > 0).
Theory suggests that the impact of openness on growth should be positive
(Q'5 > 0) although the empirical literature has not strongly confirmed such
an effect. Openness is defined as the ratio of exports plus imports to GDP.
It is used as a proxy for the exposure of the economy to foreign markets.
77
Levine and Renelt (1992) have found that it was robustly correlated with the
investment share of GDP.
In this paper the parameters of interest arefffiand ay. Under the "grease the
wheels" hypothesis corruption should have a positive impact on the economic
activity if the quality of governance is very low. In the sample very low quality
of governance implies log(gov) close to 0. With log(gov) close to zero, ag
should be positive for cormption to have a positive impact on the economic
activity. With high quality of govemance the impact of cormption should
become negative. In order to get such an impact aj should be negative. Hence
the "grease the wheels" hypothesis will not be rejected Ma^, > 0 and a-j < 0.
Under the "sand the wheels" hypothesis, cormption is harmful for growth
and investment and becomes increasingly detrimental as governance deteri-
orates. In this case, when the quality of govemance is very low (log(gov)
close to 0) Of, should be negative for corruption to still have a negative im-
pact. For this impact to be more negative under low quality of governance
(log(gov) close to 0) than under high quality (log(gov) far above 0) aj should
be positive.
3.2. Data
In order to conduct tests we use three data sets: macroeconomic data,
cormption indices and govemance indicators.
3.2.1. Corruption data
While corruption is commonly defined as "the misuse of public power for
private benefits" (see e.g. Jain, 2001), its proper measurement is more diffi-
cult- Basically, one may classify available quantitative measures of cormption
that allow cross-country comparisons into three broad categories.
A first set of indicators uses pools of experts that assess the level of
cormption that prevails in a country. Very often, these ratings are produced
by private risk-rating agencies, such as Business Intemational Corporation,
whose index was used by Mauro (1995).
A second type of indicators is based on surveys of residents and are usually
carried out by intemational or non-govemmental organizations. The index
provided in the World Economic Fomm's Global Competitiveness Report
falls in this category and was used by Wei (2000).
A third category combines the indices belonging to the previous two cat-
egories. This has two main advantages."* On the one hand, as basic indicators
are by constmction subjective, they may be biased. Composite indices may
induce those biases to cancel out, therefore determining an average opinion
regarding corruption. On the other hand, as composite indices aggregate sev-
78
eral other indices, they can provide data for wider samples of countries, since
they allow one index to fill the gaps left by another
Given the above advantages, composite indices have been widely used
in the literature and will also be adopted in the present study. We use two
composite indices to assess the consequences of corruption. This allows us to
test the robustness of our results. The two indices are the Corruption Percep-
tion Index {henceforth CPl) published by Transparency International and the
corruption index provided by the World Bank {henceforth WB).''
The CPI index is available directly on the Transparency International web-
site. This index is computed yearly as an average of other indices. It ranges
from zero to eight, the latter corresponding to an absence of corruption. For
clarity, we computed and used the opposite of that index in our analysis so
that an increase in the index can be directly interpreted as an increase in the
level of corruption. To keep our sample as large as possible, we used the 1999
vintage of the CPI index that is provided for 99 countries.
Unlike the CPI index, the World Bank's corruption indicator is not an
average of other indices. Instead, it is estimated thanks to an unobserved
component model, that is described in Kaufman et al. {1999a). As regards
their composition, the CPI and the WB indices also differ insofar as they
aggregate slightly different sets of basic indicators of corruption.^ The two
indices therefore stand as two useful complements, since they aggregate two
different sets of indicators thanks to two different methods. The WB indicator
can be found in the Governance database posted on the World Bank's web-
site. It combines information relative to the 1997-1998 period and ranges
from -2.5 to +2.5. Like the CPI index, it is constructed so that an increase
in the index reflects a better control of corruption. Kaufman et al. (1999a, b)
accordingly sometimes refer to it as an indicator of probity. It was therefore
re-scaled so as to increase with the level of corruption.
3.2.2. Governance data
To test the "grease the wheels" vs. the "sand the wheels" hypotheses, one
needs quantitative estimates of other dimensions of governance. Like corrup-
tion, the other aspects of governance hardly lend themselves to an objective
evaluation. They are proxied through surveys of experts or residents that are
inherently subjective.
Kaufmann et al. {1999b) have applied the unobserved component model
used for corruption to construct indicators of governance. They classified
available indicators of governance into five clusters and aggregated them
into five composite indices. Each composite indicator refers to a different
dimension of governance. It ranges from -2.5 to +2.5, higher values signaling
better governance. The composition of indicators being described in detail in79
Kaufmann et al. (1999b). we will simply recall the definitions of each aspect
of governance that those indicators aim at quantifying.
The first indicator, called ''voice and accountability", measures "the ex-
tent to which citizens of a country are able to participate in the selection of
governments". It accordingly assesses the openness of the political system.
The "lack of political violence" indicator "measures perceptions of the
likelihood that the government in power will be destabilized or overthrown
by possibly unconstitutional and/or violent means". This indicator therefore
provides an assessment of the political risk associated with a country.
The third indicator, named "government effectiveness", concerns the
"perceptions of the quality of public service provision, the quality of the
bureaucracy, the competence of the civil servants, the independence of the
civil service from political pressures, and the credibility of the government's
commitment to policies".
The "regulatory burden" indicator captures "the incidence of market un-
friendly policies such as price controls or inadequate bank supervision, as
well as perceptions of the burden imposed by excessive regulation". The last
indicator is devoted to the "rule of law" and refers to "the extent to which
agents have confidence in and abide by the rules of society".
3.2.3. Economic data
Economic data are from the Growth Development Network database of the
World Bank. More precisely, data concerning GDP per capita growth, invest-
ment, population growth, and openness to trade, were found in the "macro
time series 2001" data set of the Worid Bank. School enrolment ratios were
taken from the "social indicators and fixed factor 2001" database. The sample
spans the 1970-1998 period and covers developed and developing coun-
tries from different regions of the World. Due to missing data, the total
number of observations used in any regression ranges from 63 to 71. Ap-
pendix B presents the list of countries and the corresponding corruption and
governance indicators.
Economic variables are averaged over the sample period. As pointed out
by Easterly et al. (1993), it is not sure that the variation over time of country
characteristics adds much explanation to the regressions. This is especially
true when corruption indices are included in the set of explanatory variables.
It can indeed be argued that corruption is a long-term institutional issue that
evolves slowly. Moreover, as Paldam (2002) suggests, indices of corruption
are likely to evolve even more slowly than the phenomenon that they are
supposed to gauge.^ Those indices are typically based on surveys and it
is likely that respondents, who may be experts, firm managers or general
citizens, found their answers on their past experience that is typically built80
over several years. The resulting inertia of corruption indices consequently
precludes any meaningful analysis of their variations over time, al least until
longer time series are available.
Furthermore, Transparency Intemational insists upon the fact that the
composition of the sample of cormption indicators that are aggregated to
compute the CPI index evolves over time, which makes year-to-year compar-
isons of a country's score risky. Thus the evolution of the score may simply
result from changes in sample and methodology.^ Finally, some indices, like
the World Bank's are only available for a single year.
4. The empirical analysis
The equations are estimated using Generalized Least Squares to correct for
heteroscedasticity. Following Mankiw et al. (1992), all variables are taken in
logarithm.'' As the WB index takes values between -2.5 and +2.5, we replaced
log(WB) by log(3.5-WB) in the regressions. Similarly, we replaced Iog(CPI)
by Iog{ 11 - CPI). The interaction terms were defined as the product of a trans-
formed corruption index by log(3.5-governance), where "govemance" stands
for governance indicators drawn from the World Bank database. Given these
transformations, higher values of the corresponding explanatory variables
mean higher level of corruption and higher quality of governance.
4.1. Per capita GDP growth rate
A preliminary investigation of the "grease the wheels" and the "sand the
wheels" claims consists of examining how the impact of corruption varies
depending on the quality of govemance. This is done by estimating Equation
1 without the interaction term (i.e. setting ctl = 0) over different sub-samples.
The sub-samples are constmcted as follows. The observations in the initial
sample are sorted according to the quality of govemance (from the lowest to
the highest level). The first sub-sample includes the first 40 observations. The
second includes observations number 2 to 41 and so forth. The regression
over each sub-sample gives an estimated coefficient of cormption. Plotting
the successive coefficients of cormption. sheds light on the validity of the
"grease the wheels" and the "sand the wheels" hypotheses. If the former is
valid the resulting curve should be decreasing, i.e. the coefficient becomes
more and more negative as one moves from low to high quality of governance.
If the latter is valid the curve should be increasing.
For illustration, we conducted the investigation using the WB index of
cormption and the rule of law index of govemance. The results are presented
in Figure 1. The curve is clearly increasing, suggesting that the "sand the81
wheels" claim is right. However, in order to get firmer support for such
a claim one should rigorously test whether the change in coefficients is
significant or not. This is the purpose of Table I.
There are four specifications. The basic specification includes all the ex-
planatory variables in Equation (1) except the interaction temi. Each of the
other three specifications includes the interaction term. The results are repor-
ted for three govemance indicators: Rule of law. govemment effectiveness
and lack of violence. To save on space, the results with the regulatory burden
and the voice and accountability indicators are not reported. The coefficients
of the interaction terms with these indicators are never significant neither in
the growth equation nor in the investment equation. This suggests that the
accountability of political leaders and the quality of the regulatory framework
do not modify the impact of cormption on growth.
The basic specification explains about 50% of the variation in growth
rates. Across specifications, all coefficients have the expected sign, although
not always significantly. Initial GDP per capita enters the regressions with
a negative sign and is in general significant, which means that we observe
the usual convergence effect. The coefficient of primary school enrolment is
correctly signed but always insignificant. Population growth enters the regres-
sions negatively and is generally insignificant. Openness has a positive sign
but is always insignificant. Finaiiy, the average investment ratio is always
significant and exhibits a positive coefficient, much in line with Levinc and
Renelt (1992)"s result.
As regards cormption, both indices appear in the regressions with a neg-
ative coefficient. While the coefficient of the CPI is non-significant at the
10% level, the WB"s is significant at \%. This means that cormption tends to
hamper growth. This result confirms previous studies that observed the same
relationship (Mauro, 1995 or Mo, 2001). It should be stressed, however, that
corruption has a significant negative coefficient even when the investment
ratio is included among the regressors. This suggests that beyond its potential
negative impact on the accumulation of capital, cormption directly impacts
growth. This result contrasts with Mauro (]995)'s who found no significant
relationship between cormption and growth once investment was included
among the explanatory variables. Mo (2001) found a significant relationship
between cormption and growth even after controlling for the investment ratio
but the coefficient of cormption becomes insignificant when human capital is
taken into account.
There are two possible explanations to the finding that cormption neg-
atively affects growth independently of its potential impact on investment.
The first one concems public investment that can be used for bribees" private
use, or be concentrated in sectors that allow the greatest extraction of bribes82
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(see e.g. Mauro, 1998. or Tanzi and Davoodi, 1997). The second one concerns
incentives. Corruption may also distort the allocation of entrepreneurial talent
and give an incentive to allocate agents' energy to rent seeking instead of
other productive activities, like innovative activities in particular, as Bardhan
(1997) suggests. It may also raise the share of the informal sector, as observed
by Johnson etal.{ 1998).
When interaction terms are taken into account the results for control vari-
ables remain broadly unchanged. In contrast, the goodness of fit improves.
The adjusted R~, which takes account of the number of regressors, increases
markedly. With the rule of law and the government effectiveness indicators
the regressions explain up to 60% of variation in the growth rate, which
represents an increase of ten percentage points with respect to the basic
specification. The impact of corruption becomes significant with both gov-
ernance indicators and the magnitude of the coefficients is systematically
larger than with the basic specification. This is interpreted against the pooling
of countries regardless of the quality of their institutions
With the rule of law and the government effectiveness indicators all in-
teraction terms have a positive sign and are significant. This means that
had governance increases the cost of corruption or that, inversely, good
governance alleviates the cost of corruption. Therefore, corruption does not
appear as a way to circumvent bad governance (e.g. ineffective administration
or cumbersome bureaucracy) but as a way to make it more painful. In other
words, the results of our regressions tend to reject the "'grease the wheels"
hypothesis. Consequently, curtailing corruption is most beneficial to countries
suffering from a weak rule of law or low government effectiveness. One can
conclude that neglecting the role of other dimensions of governance leads to
underestimate the consequences of corruption on growth.
Regressions that include an interaction term between corruption and lack
of violence do not perfonn better than the basic specification. The interaction
term never enters the relationship significantly and the level of corruption
measured by the CPI index remains insignificant. Moreover the explanatory
power of both regressions does not increase.
To summarize, the regressions that include the interaction of corruption
with the rule of law and government effectiveness exhibit consistent results.
Both improve the goodness of fit with respect to the basic specification. Both
indicators of corruption are significant with the expected negative sign. This
is noteworthy, as the CPI index could not pass the 10% significance test in
the basic specification. The lack of significance of this variable in the basic
specification can thus be attributed to the omission of the interaction term that
blurred the relationship between corruption and growth.86
The coefficient on the interaction term is always positive and significant
for both measures of govemance. It therefore appears that a weak rule of law
or a !ow govemment effectiveness tend to make corruption more detrimental
to growth. It follows that the results of this section reject the "grease the
wheels" hypothesis. Thus, when one looks at the impact of corruption on
growth, one finds that it does not act as a substitute for govemment effective-
ness or the rule of law. Instead, bad govemance tends to increase the adverse
effect of corruption on growth.
Additional tests were conducted to check that our main result (i.e. the
significance and sign of the comiption/governance interaction term) is robust
to change in specification. For instance, the introduction of other interac-
tion terms of the explanatory variables may equally improve the quality of
estimation and even remove the significance of the cormption/govemance in-
teraction term. The choice of an additional interaction term draws on the new
growth literature, a central issue of which is the catch-up process by which
lagging countries converge to the performance of leading ones. Following an
infiuential strand of the literature, such aprocessdependsontheability of lag-
ging countries to successfully imitate new technologies. This in turn depends
on human capital (see Benhabib and Spiegel, 1994, 2(X)2. for discussions). In
our framework, the implication is that an interaction term between initial in-
come and human capital variables is a potential relevant explanatory variable.
Appendix A presents the estimation results of two variants of Equation I. One
replaces the interaction term between corruption and govemance (rule of law)
by the interaction term between initial income and human capital. The other
incorporates both interaction terms. The results show that the coefficient of
the new interaction term is never significant and that, while the introduction of
the interaction term between corruption and governance improves the quality
of fit. the introduction of the new one does not. Moreover, the introduction
of the new interaction term does not impact the significance and sign of the
corruption/govemance interaction term. To sum up. the latter result together
with those in Figure 1 and Table I lend strong support to the validity of the
"sand the wheels" hypothesis.
4.2. The investment ratio
Before tuming to the econometric analysis of the investment ratio, we con-
ducted a similar preliminary investigation as in Section 4.1. The results are
presented in Figure 2 and also favor the validity of the "sand the wheels"
claim. The curve is clearly increasing implying that the coefficient of corrup-
tion becomes less and less negative as one moves from low to high quality of
govemance. The results in Table 2 allow to rigorously test those hypotheses.87
1
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The speciticatiotis are similar to those in Table 1. The basic specification
explains about one third of the variance in the investment ratio. Apart from
openness, all control variables exhibit the expected coefficient and are signi-
ficant. The initial GDP per capita in the base year exhibits a negative sign,
which is In line with the standard convergence hypothesis. School enrolment
enters all the regressions with a positive and significant sign, thereby re-
emphasizing the role of human capital in fostering investment. Similarly, both
corruption indices exhibit the expected negative sign and have a significant
impact on investment. This observation confirms previous studies like Mauro
(1995), Brunetti and Weder (1998), Campos et al. (1999) or Mo (2001).
The inclusion of interaction terms does not affect the impact of the con-
trol variables. All their coefficients remain consistent with the signs and the
significance found with the basic specification. Moreover, the model fits the
data better with approximately 40% of the variance explained, which raises
the percentage of the variance explained by up to ten percentage points.
As in the previous section, we examine the change in the coefficients of
the corruption indices and the signs of the interaction terms. The difference
between the basic specification and the others is quite similar to the one
in Table I. It appears that the magnitude of the coefficients of corruption
is systematically larger than with the basic specification. As before, this is
interpreted against the pooling of countries regardless of the quality of their
institutions.
The coefficients of corruption in the last three specifications reflect the
impact of corruption on investment in countries witb the worst govemance,
whereas the coefficients in the basic specification measure the average impact
of corruption on investment in the whole sample. Consequently, the higher
coefficients of corruption in the former cases imply that corruption hinders
investment more in countries whose governance is unsatisfactory than in the
rest of the sample. This statement is confirmed by the fact that the coeffi-
cients on the interaction terms are all positive and almost always significant.
This result means that corruption tends to further reduce investment as gov-
ernance deteriorates. Therefore, like for growth, the result for investment
rejects the "grease the wheels" hypothesis. Instead of alleviating the cost
of bad govemance, corruption impedes investment even more in countries
whose govemance is defective. Note that a robustness check, similar to the
one with the growth equation, was conducted and also gives strong support
to our conclusion (see Appendix A).
It must be stressed that, unlike in Table 1, the results hold fbr both indices
of corruption and for the three indicators of govemance."* The only exception
is the interaction between the CPI index and government efficiency. Accord-
ingly, the results of Table 2 consistently suggest that corruption is a stronger91
impediment to growtii in countries that suffer from a low rule of law, bad
government effectiveness and political violence. Our data therefore seem to
(it the "sand the wheels" rather than the "grease the wheels" hypothesis.
5. Conclusion
In this paper, we tried to disentangle the interplay between corruption, invest-
ment and growth, and the other dimensions of governance to test the "grease
the wheels" hypothesis against the "sand the wheels" one. We do so by adding
interaction variables to the set of variables that are usually used to explain
investment and growth in cross-section analyses. Our results strongly reject
the "grease the wheels" hypothesis in favor of the "sand the wheels" one.
We tind that a weak rule of law, an inefficient government and political
violence tend to worsen the negative impact of corruption on investment.
Moreover, we observe that corruption slows growth down even more in coun-
tries suffering from a weak rule of law and an inefficient government, even
when one controls for investment. We therefore conclude that corruption
not only impacts growth through reduced accumulation of capital but also
through other channels that have yet to be determined. The results imply that
reducing corruption would be more profitable to countries where other as-
pects of governance are poor, which stands in sharp contiast with the opinion
of those who view corruption as a lubricant.
Formal and in depth analysis of those channels by which corruption im-
pacts growth paves the way for future research. Moreover, the assessment
of the level of corruption and the measurement of the quality of institutions
are still at the beginning and should be improved. Our analysis will con-
sequently have to be carried out again in the future to take advantage of the
improvements in those measures and of the availability of longer time series.
Notes
1. See also Ades and di Telia (1997).
2. The expression ••morali.stic approach" was used by Nye (t967) or Leys (1965).
3. Brunetli (1997) provides a useful survey of thai literature.
4. They however share a common drawback that is thai the definition of what they refer to
as corruption must remain fairly evasive, because each basic index uses a slightly differ-
ent, though converging, definition. For instance, they do not allow making a distinction
between "petty" and "grand" corruption.
5. We also used Wei (2000)"s index but do not report the results. This index did not perform
as well as the others in the regressions.
6. The interested reader may find an exhaustive description of the composition of each
indicator in Lambsdorff (1999) and Kaufman et al. (1999b).92
7. Paldam (2002) points out thai iiniiLial inovements in the CPI index are less than 0.1 puinl.
8. Transparency International's caution goes as far as refusing to present scores from various
years in a single table to prevent misleading comparisons.
9. We also tested another specification where the levels of institutional variables instead of
their logarilhms were taken into account. This did not affect our results.
10. Hence the impact of political violence on growth works through its effect on investment.
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Appendix B. List of countries in the sample and their corruption and govemance indicators
Corruption Govemance
Country CPI WB Lack of Govemment Rule of law
violence effectiveness
Angola -0.86 -1.78 -1.39 -1.23
Argentina 3.-0 27,0 51.0 26.0 32.
Australia 8,7 1.6 1.18 1.46 1.6
Auslria 7,6 1.46 1,38 1.22 1.81
Belgium 5.3 0.67 0,82 0.88 0.8
Burkina Faso -0.37 -0.52 -0.06 -0,35
Bangladesh -0.29 -0,4 -0.56 -0.93
Bolivia 2.5 -0.44 -0,14 -0.22 -0.35
Botswana 6.1 0.54 0.74 0.22 0.5
Canada 9.2 2.06 1.03 1.72 1.55
Chile 6.9 1.03 0,45 1.17 1.09
China 34 -0.29 0,48 0.02 -0.04
Cote d'lvoire 2.6 -0.08 -0,14 -0.18 -0.33
Cameroon 1.5 -1.1 -0.72 -0.64 -1.02
Colombia 2.9 -0.49 -1.29 -0.06 -0.78
Costa Rica 5.1 0.58 0,91 0.55 0.55
Denmark 10.2 13.1 29.1 72.1 69.
Ecuador 2,4 -0.82 -0.47 -0.56 -0.72
Egypt 3.3 -0.27 -0.07 -0.14 0,13
Spain 6.6 1.21 0.58 1.6 1.03
Ethiopia -0.44 0.14 -0,15 0,27
Finland 9.8 2.08 1.51 1,63 1.74
France 6.6 1,28 0.65 1.28 1.08
United Kingdom 8,6 1.71 0.92 1,97 1.69
Ghana 3.3 -0.3 -0.1 -0.29 -OOl
Greece 4.9 0.82 0.21 0.56 0,5
Guatemala 3.2 -0.82 -0,75 -0.23 -1,11
Hong Kong 7.7 1.31 0.92 1.25 1.33
Honduras 1.8 -0.94 -0.33 -041 -0.9
Indonesia L7 -0.8 -1.29 -0.53 -0.92
India 2.9 -0.31 -0.04 -0.26 0.16
Ireland 7.7 1.57 1.43 1.36 1.39
Iceland 9.2 1.83 1.25 1.5 1,47
Israel 6.8 1.28 -0.46 0.69 0.97
Italy 4.7 0.8 1,16 0.77 0.86
Jamaica 3.8 -0.12 -0,34 -0.48 -0.73
Japan 6.0 72.1 15.0 84.1 42.97
Appendix B. Continued
Corruption Governance
Country CPl WB Lack of Government Rule of law
violence effectiveness
Kenya 2.-0 65.-1 l.-O 9.-1 22.
Korea/Rep 3.8 0.16 0.16 0.41 0.94
Luxembourg 8,8 1.67 1.4 1.67 1.62
Morocco 4.1 0.13 0.09 0.27 0.68
Mexico 3.4 -0.28 -0.35 0.18 -0.47
Mozambique 3.5 -0.53 -0.53 -0.33 -1.05
Mauritius 4.9 0.34 1.14 0.17 1.28
Malaysia 5.1 0.63 0.55 0.71 0.83
Nigeria 1,6 -0.95 -1.05 -1.32 -1.1
Nicaragua 3.1 -0.84 -0.32 -0.55 -0.73
Netherlands 9.2 03.1 48.2 03.1 58.
Norway 8.9 1.69 L4I L67 1.83
New Zealand 9.4 2.07 1,42 1.57 1.82
Pakistan 2.2 -0.77 -0,65 -0.74 -0.76
Peru 4.5 -0.2 -0.53 0.17 -0.52
Philippines 3.6 -0.23 0.27 0.13 -0.08
Portugal 6.7 1.22 1.39 1.15 1.08
Paraguay 2.-0 96.-0 57.-1 1.-0 7.
Senegal 3.4 -0.24 -0.87 0.05 -0.1
Singapore 9.1 1.95 1.39 2.08 1.94
E| Salvador 3,9 -0.35 -0.02 -0.26 -0.66
Sweden 9.4 2.09 1.41 1.57 1,62
Thailand 3.2 -0.16 0.25 0.01 0.41
Tunisia 5.0 02,0 66.0 63.0 65.
Turkey 3.6 -0.35 -0.94 -0.41 -0.01
Taiwan/China 5.6 0.63 0.94 1.29 0.93
Tanzania 1.9 -0.92 0.57 -0.49 0.16
Uganda 2.2 -0.47 -0.98 -0.25 -0.01
Uruguay 4.4 0.43 0.35 0.62 0.27
Venezuela/RB 2.6 -0.72 -0.25 -0.85 -0.66
South Africa 5.0 3.-0 53.-0 Ol.-O 35.
Zambia 3.5 -0.61 O.-O 4.-0 4.
Zimbabwe 4.1 -0.32 -0.54 -1.13 -0.15
Note. Countries in bold enter the investment equation only.You can also read
