Does Oil Cause Corruption? Test of an Institutional Explanation
Nurjamal Omurkanova
ECPR Joint Sessions of WorkshopsSt. Gallen, SwitzerlandApril 12-17, 2011
Draft paper. Comments are welcome, but please do not quote or circulate without author’s permission.
Abstract
Poverty is one of the biggest problems the world faces today. Thereby, Kaufman
(2007) claims that corruption causes poverty. In a similar vein, Barack Obama at the
United Nations Summit described corruption as "a single greatest barrier to
prosperity" and "a profound violation of human rights". Further, Aslaksen (2007)
argues that oil augments corruption. Following this logic, the oil-producing countries
should be more corrupt and poorer as well. However, there are oil-producing
countries in the world that are economically highly developed and have very small
corruption rates. Then, what can explain this variation?
I hypothesise that whether oil leads to more corruption is conditional on the quality of
institutions. That is, the weaker the quality of institutions is, the stronger the
corrupting effect of oil would be. For the empirical tests (in 130 countries over 20
years) I will use index of institutional quality based on rules like accountability,
transparency and rule of law. Thereby, power distribution, freedom of press and
judicial independence will be used as proxies for these institutions. Consequently, as
it is argued that institutions are endogenous both to oil and to corruption I will apply
instrumental variable tests to control for simultaneity.
1. Problem and Research Question
Poverty is one of the biggest challenges the world faces today. There are
millions of people who live on less than US$ 1.25 a day1. Fighting poverty is listed
first among seven Millennium Development Goals (MDGs) set by 189 world leaders
in New York in 2000. It is argued that corruption is the main reason why there is
insufficient progress in achieving the MDGs2. Barack Obama (2010)3 describes
corruption as the "single greatest barrier to prosperity" and "a profound violation of
human rights". In a similar vein, Kaufman (2007) argues that the causal arrow runs
from corruption to poverty. Besides, Aslaksen (2007) demonstrates that oil increases
corruption. Combining these two arguments one would assume that oil-producing
countries should be on average more corrupt and they should be on average poorer
as well. However, that is not always the case. There are oil-producing countries in
the world, which are economically highly developed and have very small corruption
rates.
For instance, Canada accounts for the world's 2nd largest proved oil reserves4
and is the world's 6th largest oil producer5. Further, G8 member Canada is highly
industrialized and economically developed. According to the CIA 2010 World
Factbook, Canada is the 26th richest country in the world with a GDP per capita of US
$38.100. However, Canada ranks 6th in 2010 Corruption Perception Index (CPI)6. In
contrast, the Russian Federation which is the world's largest oil producer7 and a G8
member state as well, with a GDP per capita of US $15.100, is one of the most
corrupt countries in the world (a score of 2.1 in the 2010 TI CPI).
Based on these two examples one might assume that the level of economic
development is responsible for high corruption rates in oil-producing countries.
However, the United Arab Emirates possesses the world's 5th largest oil reserves
and it is the world's 10th largest oil producer, and it is even richer than Canada (US
1 World Development Indicators, World Bank.2 The Anti-Corruption Catalyst: Realising the MDGs by 2015. Transparency International, September 2010.3 The statement was made at the United Nations Summit in New York, 20-22 September 2010. 4 Thus, 13 percent of the world's oil is under Canada. But the majority of these reserves are difficult to process. These reserves are in the form of oil sand, which should be specially treated to convert it into crude oil before it can be refined into usable products. CIA World Factbook5 International Energy Agency, 2010 Key World Energy Statistics, www.iea.org 6 Transparency International 2010 Corruption Perception Index (CPI). The 2010 CPI measures the degree to which public sector corruption is perceived to exist in 178 countries around the world. It scores countries on a scale from 10 (very clean) to 0 (highly corrupt).7 International Energy Agency, 2010 Key World Energy Statistics
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$40.000 GDP per capita). Nevertheless, the United Arab Emirates' corruption score
is 6.3, which is worse than Canada’s. What factors then can explain the variation in
corruption rates among the oil-producing countries?
So far, it is claimed that corruption is one form of rent seeking (Murphy,
Shleifer and Vishny 1993)8. Oil and gas resources are supposed to enable even
higher rents (Ades and Di Tella 1999). As a result, natural resources lower economic
performance because they foster rent seeking (Sala-i-Martin and Subramanian
2003). Murshed (2004) examines the link between resource abundance and
economic growth and, therefore, highlights the importance of institutions. He points
out that oil and minerals retard democratic and institutional development, which in
turn restrains economic growth. Thus, the growth effect of oil depends on the
institutional quality. For instance, during the resource booms politicians can choose
different macroeconomic policies. Those policies determine the growth effect of
natural resources. Most importantly, the choice of policies is contingent on the quality
of institutions (Robinson, Torvik and Verdier 2006). Hence, this study further
analyses the link between oil and corruption to explain differences in corruption levels
among the oil-producing countries. This study specifically aims to find out whether
there is a conditional relationship between oil and corruption dependent on the
quality of institutions.
To answer the above-mentioned questions, I will conduct a cross-national
time-series analysis of the link between oil and corruption. It will be a global analysis
with a special focus on the post-communist countries. In doing so, this study, on the
one side, tests the existing theories and, on the other side, aims to provide a new
explanation of the nature of the relationship between oil and the spread of corruption
with the help of new empirical analyses.
In the following I will review the state of the art and specify the gap in the
literature. Subsequently, I will elucidate my theoretical argument and state my
hypotheses. I will further introduce the research design, describe the data and justify
the methodology I use.
8 Svensson (2005) defines corruption mainly as bribes. The author argues that corruption and rent-seeking are not the same, although often interchangeable. According to Svensson, "rent-seeking is the socially costly pursuit of rents, often created by governmental interventions in the economy, while bribes are technically a transfer."
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2. Definition of the main concepts
2.1. Oil and Gas Resources
Natural resources are categorized into renewable and non-renewable
resources. Both oil and natural gas belong to the non-renewable energy resources.
In the wake of the energy supply shortages and the search for alternative energy
resources, oil (“black gold”) and gas (“blue fuel”) are in a very high demand. It is
therefore obvious why energy security is among the top priorities in the national
security programs of the nation-states worldwide.
The literature differentiates between point and diffuse natural resources.
Diffuse resources are natural resources that are geographically extended (e.g.
agricultural lands and forests) and therefore not easy to control. Point resources, in
contrast, are known to be spatially concentrated and can possibly be controlled by
certain groups with relative ease. More importantly, point resources are those
primarily associated with a resource curse (Mehlum, Moene and Torvik 2006, Leite
and Weidmann 2002, Sala-i-Martin and Subramanian 2003, Isham et al. 2003). Both
oil and natural gas relate to the point resources (Wick 2008).
According to the Reference Scenario of International Energy Agency (IEA)9, oil
and gas prices will rise continuously. For instance, the average IEA crude oil import
price in 2008 was US $3 per barrel. The price is assumed to reach US $87 per bbl. in
2015, US $100 per bbl. by 2020 and US $115 per bbl. by 2030 (in year-2008 dollars).
It means that the oil-producing countries will get even larger revenues from oil and
gas production. In this connection a critical question to ask: will these revenues
contribute to economic and social development or will they strengthen corruption?
2.2. Corruption
Corruption is defined as "a misuse of public office for private gain" (Treisman
2000; Sandholtz et al. 2000). In a similar vein, Kaufmann (1997, 117) defines
corruption as a theft of public resources. Further, corruption is neither a characteristic
of a social system or an institution, nor a trait of an individual, but rather an illegal
exchange (Oxford dictionary of politics 2009, 123; Sandholtz et al. 2000). Svensson
9 World Energy Outlook 2009 Fact Sheet: Energy Price Assumptions. Price volatility will continue, but the days of cheap energy are over. http://www.worldenergyoutlook.org/docs/weo2009/fact_sheets_WEO_2009.pdf
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(2005, 20) argues that corruption is an outcome of a country’s institutions, or put
differently, corruption is a response to the rules prevalent in a society.
Rose-Ackermann (2007) distinguishes between low-level (also labelled as
bureaucratic or petty corruption) and high-level (also labelled as political, systematic,
administrative or 'grand') corruption. Low-level corruption occurs when officials or
private individuals use basic laws and regulations for personal benefit. Systematic
corruption is, by contrast, performed by high level state officials and politicians and
thus implicates the whole governmental structure from top to bottom. This latter form
of corruption has also been categorized as 'state capture'. 'State capture' occurs as
purchase of laws and regulations by senior state officials who take advantage of their
office to formulate and adopt laws and regulations in order to privilege specific client
groups (Heywood 2009, 363-364).
2.3. Institutions
Institutions are “the rules of the game in a society” (North 1999, 3). In this line,
Bueno de Mesquita et al. (2003) indicate that institutions determine the way the
political system works. Thus, institutions influence political selection and political
survival. Institutions serve as restraints that force politicians to make certain
decisions.
Another important feature to be emphasized is the structure of the game. It is
critical whose choices are affected by the rules (North 2003). Skocpol (1973, 16)
argues that "the significant question to ask is [...] who controls the political
mechanism and how they are organized."
Alongside with the rules of the game, there are also players in the game.
Groups of individuals brought together for a common purpose build organizations.
Organizations can vary from political to educational bodies. However, in the matter of
cause-and-effect chain, institutions affect both what organizations come into
existence and the way they evolve (North 1999, 4-5).
3. Resource Curse Debate
Resource curse debate is an object of a large theoretical and empirical
literature which has developed rapidly during the last two decades. Per se
abundance in natural resources is generally perceived to be a blessing since natural
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resources are a highly potential source of economic enrichment. It is therefore
paradoxical why “more of a good thing could be bad” (Wick and Bulte 2009, 140). Put
simply, it is puzzling why richness in natural resources is associated with a curse.
The following chapter introduces three main pillars of the resource curse debate. In
particular, it presents results of empirical studies on linkage between resource
abundance and (1) persistence of autocratic political regimes, (2) slow economic
growth and (3) a higher probability of civil war onset.
3.1. Resource Abundance and Political Regimes
Oil income is both an exogenous and endogenous factor. On the one hand,
the income generated through the production of oil is defined by the quantity and
quality of petroleum available, i.e. by the country's geological endowment. On the
other hand, oil income depends on the investments into the oil industry. Following
this logic, the geological endowment is an exogenous variable, although investments
are endogenous to the country's economic development and quality of institutions.
Thus, "countries that are wealthier, more open to foreign investment, and provide
better legal protection for investors, are likely to invest more into their petroleum
industries," (Ross 2009, 4).
In this connection Ross (2001, 2009) claims that cases of coexistence of high
oil incomes and democracy are spuriously correlated due to the omitted variables,
namely rule of law, sound property rights and higher education levels. The omitted
variables are assumed to affect both the attraction of investments into the oil and gas
industry and the strengthening of democracy. Nevertheless, Ross precludes any third
variables "that would foster both more oil income and less democracy" (Ross 2001,
14). However, it might be exactly because of those omitted variables that in some
countries oil rents are associated with autocratic regimes, economic decline and
corruption. For example, a weak rule of law, non-transparent and non-accountable
institutions can easily enable an increase in oil production while using these
revenues to suppress democratization further.
Instead, Ross explains a strong relationship between oil income and
authoritarian rule by the means of the rentier effect. According to him, a rentier effect
is the combination of low taxes and high government spending (Ross 2009, 16). The
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rentier effect consists of spending10, taxation and a group formation effect. At the
same time and in contrast to his earlier argumentation, Ross (2001, 337) argues that
the rentier effect takes place in countries where the governments have an arbitrary
power to spend public money (oil and gas revenues). In other words, because of the
unlimited power, leaders in authoritarian regimes will opt for immediate gains from
the oil industry, i.e. for more oil income. Moreover, with the help of oil income they
will suppress any political opposition in order to stay in power.
To summarize, I will assume that poor institutions enable both more oil income
and less democracy. Accordingly, the repression effect happens by reason of
authoritarian governments that easily manage to employ public assets to suppress
any springs of constructive opposition. For instance, Bellin (2004) and Jensen and
Wantchekon (2004) address political survival and robustness of the authoritarian
regimes in the Middle Eastern and North African states. Inter alia, Bellin highlights
the presence of strong coercive apparatuses11 and repression traditions in such
countries. To maintain the massive coercive apparatuses ruling elites in these
countries enjoy exceptional access to the rents which are largely recovered by oil
and gas resources. Therefore, Bellin emphasizes the importance of "impartial and
effective state institutions" (Bellin 2004, 152) since he expects them to help
democratic transition and consolidation in the Middle East and North Africa.
Similarly, Treisman (2010) shows that oil does not doom Russia to
authoritarianism. Even so, oil does have a minor and indirect impact on the political
regime in the country. Accordingly, booms in oil prices in certain periods bring the
country to economic growth. In the periods of high popularity, a president can make
significant changes to the system and determine the path of a country's development.
Thus, decisive is not the amount of oil rents, but the quality of institutions
constraining the likelihood of undemocratic changes.
10 The rentier effect consists of a spending, the taxation and a group formation effect. The spending effect takes place when government use revenues from oil and gas industries in order to buy political support. The taxation effect occurs when the governments in oil rich countries lower taxes and as a result enjoy weakening of a public demand for democratic accountability. The group formation effect comes about when ruling elites in authoritarian oil-producing countries inhibit formation of independent groups which could somehow threaten theirs political survival. Moreover, the governments can also finance quasi-independent organizations to serve as a facade for freedom of opinion (Ross 2009, 20-21). 11 The region's states still remain the world leaders in the share of GDP (4.9% in 2007) spending on the defence issues (Bellin 2004, 147; The Military Balance 2009 Executive Summary of the International Institute for Strategic Studies).
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3.2. Resource Abundance and Economic Growth
3.2.1. Institutional Quality and Economic Growth
The significance of institutions is commonly accepted, yet there are different
approaches in defining whether institutions have a causal effect on a country’s
development or are a mere result of it. It is puzzling whether institutional quality
contributes to the growth, or whether growth causes institutional improvements. The
empirical evidence on this issue is controversial. For example, Acemoglu, Robinson,
and Johnson (2005) highlight the importance of institutions which shed light on
different patterns of economic development throughout the world. In other words, the
quality of institutions determines economic outcomes. Similarly, Olson (1996, 18)
illustrates that a great deal of variance in nations' wealth can be explained by the
differences in the quality of their institutions and economic policies. In contrast to this,
Boix and Stokes (2003) argue that the causal arrow runs from economic growth to
high quality institutions. Glaeser et al. (2004) propose another argument. They claim
that human capital serves both economic development and institutional
improvements. Thus, for instance, policies securing property rights could be
implemented regardless of the type of political regime in a country. Even dictators
can adapt policies that lead to economic growth and minimize poverty. Consequently,
institutional quality rises as a country becomes richer (Glaeser et al. 2004, 298).
Kaufmann and Kraay (2002) highlight two kinds of developments. First, they
argue that better governance increases per capita income. Second, they show that
this causal chain does not run both ways, in the sense that higher per capita income
does not necessarily result in better governance. The authors show that there can be
even a negative effect of economic growth on the quality of governance. This applies
especially to countries with bad distributional institutions. More precisely, the authors
consider ‘state capture’ to occur where elites benefit from misgovernance (Kaufmann
and Kraay 2002, 223-224).
Furthermore, Knack and Keefer (1998) show the importance of good
institutions in convergence between poor and advanced economies. They illustrate
that despite investments in human and physical capital poor countries cannot catch
up with wealthy economies due to the insufficient institutional quality. Consequently,
poor countries grow much more slowly and "the poor are getting poorer" (Knack and
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Keefer 1998, 591). Thus, good quality institutions cause economic growth. The
authors control for reverse causality by running four different robustness tests. They
do not find any empirical support for the obverse hypothesis that economic growth
leads to institutional improvements.
3.2.2. Institutional Quality and Economic Growth in Resource Rich Countries
Natural resource abundance is supposed to retard economic growth (Sachs
and Warner 1995, 1997 and Isham et al. 2002). In this context, there is a well-known
‘Dutch disease’ argument in the literature on a resource curse. Oil industry produces
large revenues. It draws capital and labour away from the manufacturing sector. As a
result, manufacturing sector becomes less competitive. Large oil profits increase
national income and attract more foreign investments into the primary sector. Inflation
and over-valued real exchange rates follow currency devaluation. Thus, ‘Dutch
disease’ predicts a resource curse, i.e. a negative impact of resource abundance on
a country’s development. However, ‘Dutch disease’ argument cannot explain diverse
resource abundance effects across countries. There also exist resource rich
countries which experience economic growth.
For instance, Brunnschweiler (2009) demonstrates that in the post-communist
area there is no proof of the resource curse argument with regard to the linkage
between resource abundance and economic growth. The author argues that previous
studies (e.g. Sachs and Warner 1997 and 2001), which associate resource
abundance with bad institutions and slow growth use improper indicators (namely,
resource dependence) for resource wealth.
Further, Mehlum, Moene and Torvik (2006) show that the relationship between
resource abundance and economic growth depends on the institutional quality. The
authors argue that among resource abundant countries there are both growth losers
and growth winners. On one side there are countries like Botswana, Australia, and
Canada which have high economic growth rates. On the other side, there are
countries like Nigeria, Venezuela, Angola and Saudi Arabia, which are rich in
resources but nevertheless experience slow economic development. Hence,
Mehlum, Moene and Torvik (2006) differentiate between grabber friendly and
producer friendly institutions. The authors argue that the grabber friendly institutions
exist inter alia due to a weak rule of law, malfunctioning bureaucracy and corruption.
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Thus, by grabber friendly institutions, i.e. with institutions, which facilitate rent
seeking, resource abundance forces scarce entrepreneurial resources out of
production and into unproductive activities. In contrast, countries with producer
friendly institutions and rich natural resources attract investors into production and
hence speed up economic growth. "Institutions may be decisive for how natural
resources affect economic growth even if resource abundance has no effect on
institutions," (Mehlum, Moene and Torvik 2006, 3). Put simply, the existence of
strong institutions decreases the risk that richness in natural resources turns out to
be a curse (Kolstad 2009).
A number of further studies (Easterly and Levine 2003, Murshed 2004, Bulte,
Damania and Deacon 2005, Kapstein et al. 2008) also emphasize the importance of
institutional quality. Accordingly, a negative effect of natural resource abundance
occurs only via poorly functioning institutions. "Bad policies would be like a kind of
high fever from a bacterial infection. Packing the patient in ice would bring down the
fever but does not cure the infection." Thus, "correcting the policies without correcting
the institutions will bring little long-run benefit," (Easterly and Levine 2003, 37).
3.3. Resource Abundance and Civil War
Alongside with a negative effect of natural resource abundance on economic
growth and democratization process, the literature on resource curse also highlights
a link between resource wealth and civil wars. There exist two main arguments on
the causes of civil war onset in resource rich countries. The first one, the grievance
argument (Deininger 2003), points out that high inequality, ethnic fractionalization
and suppression of political freedoms lead to civil war onset. The second one, the
greed argument (Collier, Hoeffler and Söderbom 2004), suggests that rebels (or rebel
leaders) first of all want to enrich themselves. Accordingly, this is the main motive
why rebels are interested in civil war onset or its continuation (Wick and Bulte 2009,
141; Rosser 2006, 17). In the latter context, it is argued that natural resources can
well finance the duration of conflicts (De Soysa and Neumayer 2007). Further, the
literature points out that the linkage between resource abundance and civil war onset
depends on the type of natural resources. For instance, the point natural resources in
contrast to the diffuse resources are associated with both civil war onset and duration
of violent conflicts (Ross 2006, Wick and Bulte 2006). Last but not least, there are
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also studies which show that the causal arrow runs from conflicts to high resource
dependence and not the other way around, i.e. from the resource abundance to civil
war onset (Brunnschweiler and Bulte 2008).
Besides the main three pillars of the resource curse debate there is also a new
emerging one on the link between resource abundance and corruption increase.
Therefore, in the following I will present an overview of the state of the art on
corruption and its association with oil.
4. State of the Art
4.1. Systematic Research on Corruption
According to a general definition of corruption (Oxford dictionary of politics
2009, 123), “corruption […] is rather an illegal exchange”. In this regard, a need-to-
be-asked question is: what enables this “illegal exchange”? The following chapter will
therefore concentrate on the results of the most important studies on the causes and
effects of corruption.
To start with, institutional theories on corruption can be organized into two
groups. The first group deals with the role of economic and structural policies 12, the
second one emphasizes the role of institutions. The first group of institutional theories
underlines the importance of economic indicators, e.g. GDP per capita and human
capital, for the institutional improvements. Put simply, these theories regard
economic growth and education as the main explanatory parameters for corruption.
Thereby, they do not distinguish between corruption and institutional quality, since
they consider corruption to be an integral part of institutional quality. In contrast, the
second group of institutional theories analyses the role of institutions as the main
determinants of corruption. According to these theories, institutions are a set of rules
that put constraints on players (e.g. politicians, private companies and different
interest groups). Those rules define how well markets and political competition work.
Thus, the quality of institutions determines the extent to which corruption could
spread. To accentuate, corruption and institutional quality are not identical, but two
different concepts (Svensson 2005, 24-28).
12 In a similar vein, Sachs and Warner (1997) highlighted significance of "appropriate growth-oriented policies" to avoid a resource curse in resource-abundant countries (p.28).
10
Next, a debate on a causal mechanism between corruption and poverty
belongs to a classic chicken-and-egg problem (Fisman and Miguel 2008, 15). For
instance, according to Treisman (2002), poverty causes corruption. He argues that
post-communist countries are on average more corrupt. Following this we would
expect the poorest of the post-communist countries to be the most corrupt ones.
However, it is not always a case. Besides, Kaufmann (1997, 118; 2007) states the
opposite, namely that corruption causes poverty.
Previous studies have also addressed the effect of different institutional
designs on corruption. According to this, the level of corruption depends on the
constitutional designs and electoral rules: presidential vs. parliamentary regimes,
federal vs. unitary systems, proportional vs. majoritarian representation rules
(Persson, Roland and Tabellini 1997; Persson, Tabellini and Trebbi 2003; Kunicova
and Rose-Ackerman 2005; Alt and Lassen 2008). For instance, Kunicova and Rose-
Ackerman (2005, 597) show that the closed party lists in conjunction with the
decentralized presidential systems are associated with higher corruption rates since
those rules make monitoring of the corrupt officials by the voters and opposition
parties more difficult. Alt and Lassen (2008) on the example of the American states
demonstrate the importance of a system of checks and balances and of having an
accountable judiciary. According to their findings, a mechanism of checks and
balances has a stronger effect in limiting corruption in a divided government, where
the executive and legislature branches controlled by different political parties. In a
case of a unified government, where the government cannot or does not always
control itself, an elected Supreme Court contributes to less corruption.
Similarly, Shleifer and Vishny (1993) highlight the importance of accounting
systems in preventing corruption. In accordance with their findings, political
competition enables stronger public control over the government's activities. On
contrary, regulatory discretion and monopolistic powers of bureaucrats facilitate
corruption strongly (Kaufmann 1997, Ades and Di Tella 1999). Therefore, the authors
stress both political and market competition as powerful instruments in fighting
corruption.
In their recent paper Kaufmann and Vicente (2011) introduce a three-
equilibrium-pattern argument: with no-corruption, legal and illegal corruption models.
The authors explain the strength of corruption based on the power of population
(proxied by equality), the cost of destruction from unrest (proxied by initial income)
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and the cost of overwhelming of elite-built institutional barriers (proxied by political
accountability). According to their findings, the level of political accountability is
decisive in moving from legal corruption model to no-corruption outcome. Hence, it is
obvious that the political accountability is detrimental in eradicating corruption.
4.2. Oil’s Effect on Corruption
Other authors detect a relationship between natural resources and corruption.
For example, Ades and Di Tella (1999) assume that higher oil and mineral rents lead
to higher corruption rates. However, the authors show that even if the effect of fuel
and minerals was positive, it was insignificant.
One can also draw a parallel between the effect of natural resource
abundance and foreign aid on education, growth, democracy and civil war. Under
the condition of bad institutions, oil and gas revenues and foreign aid funds can
easily be appropriated by corrupt politicians (Fisman and Miguel 2008, 13; Cabrales
and Hauk 2010).
In a similar vein, Bhattacharyya and Hodler (2009) demonstrate that resource
rents cause corruption if and only if there are democratic institutions of poor quality.
The authors associate good democratic institutions with the responsiveness of the
elected governments. The strong democratic institutions mean that governments
could stay in power only with a public support.
To summarize, on the one side, there are studies which use corruption as one
of the components of the index of institutional quality in explaining resource curse.
On the other side, there are studies which employ quality of institutions as main
determinants of corruption (e.g. Brunetti and Weder 2003, Kolstad and Wiig 2008,
Kaufmann and Vicente 2011). In doing so, the latter studies, however, have used
different institutions separately. I will identify the likely corrupting effect of oil on
institutional quality. Besides, I will create an index of institutional quality based on
three factors: political accountability, rule of law and transparency.
5. Theoretical Assumptions and Research Hypothesis
The literature argues that present corruption rates are predetermined by the
country's level of economic development in the last 300 years (Treisman 2006).
Accordingly, countries that were rich in 1700 (e.g. China and Netherlands) are
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supposed to have less corruption today. Thus, there should be a strong link between
economic development and corruption. However, China's wealth 300 years ago and,
moreover, its rapid economic development during the last three decades do not
predict its still high corruption indexes today.
Bueno de Mesquita and Downs (2005) show that economic growth can well
serve the interests of the autocratic leaders. In other words, economic growth has
been used for the political survival of the authoritarian regimes. The authors show
how in countries like China, Russia, Venezuela and Cuba autocratic leaders design
rules to pursue their interests. Thereby, the decisive thing was (and still continues to
be) that autocrats managed to keep opposition weak, i.e. under control by limiting
opponents' strategic coordination (Buena de Mesquita and Downs 2005, 80-82).
In a similar vein, a proverb says "fish rots from its head down." It means that
bad leadership leads to a bad organization or that a corrupt organization is the result
of a corrupt ruler or leader. Yet, it cannot be merely limited to the governor or ruling
elite. As Lord Acton13 argues, "power tends to corrupt; absolute power corrupts
absolutely. Great men are almost always bad men.” To summarize, unless there are
constraints to make the work of governments transparent, power will corrode
everyone. For this reason, the quality of a government cannot be judged by
considering only personal characteristics of leaders. The quality of institutions also
has to be evaluated.
Knack and Keefer (1998) show that weak institutions advance political
corruption by entrepreneurs. To survive on the markets, entrepreneurs are forced to
use their ties with governmental bodies, i.e. political rather than economic criteria. As
a result, corruption and nepotism come into play. Similarly, Lederman, Loayza and
Soares (2004, 11) argue that institutions are "ultimate determinants of corruption
because they shape the incentives facing governmental officials." In the authors’
opinion, political institutions influence corruption in two ways: by political
accountability and by the structure of provision of public goods. Accordingly,
democratic institutions like parliamentary systems and freedom of press bring
corruption down. More importantly, transparency and accountability applied
separately cannot help much in mitigating corruption. Only taken together they can
have a powerful effect (Lindstedt and Naurin 2005).
13 Lord Acton, Letter to Bishop Mandell Creighton, 1887.13
Further, there are also some studies which show a positive link between oil
and corruption. For example, Aslaksen (2007) introduces new measures of resource
dependence and uses panel data with fixed effects exploring the link between natural
resource abundance and corruption for up to 132 countries for the time period 1982-
2006. She demonstrates that more oil leads to an increase in corruption in
government. Leite and Weidmann (1999) also argue that abundance in natural
resources creates opportunities for rent-seeking activities and is strongly decisive in
determining corruption rates. However, at the same time, the authors stress the
importance of strong (or at least strengthened) institutions at the moment of natural
resource discoveries as a key to restrain the associated negative growth effects of
corruption. In the less developed countries quality of institutions have even greater
value as natural resource discoveries could have a much higher impact on corruption
if confronted with weaker institutions (Leite and Weidmann 1999, 31).
Similarly, Sala-i-Martin and Subramanian (2003) and Naim (2004) recommend
policies which are designed to improve the quality of public institutions. In particular,
Sala-i-Martin and Subramanian advocate more transparency and accountability while
making publicly all resource revenues and expenditures.
To summarize, institutions do matter in explaining variation of manifold effects
oil and gas rents could produce in a polity. Thus, the effect oil and gas revenues
could have on development indices depends on the quality of institutions in a given
country. Accordingly, I hypothesise that oil and gas revenues would contribute to
more corruption only in polities where poor quality institutions prevail.
H: Oil increases corruption if and only if the quality of institutions is poor.
6. Research Design
6.1. On aggregate indexes
Keefer (2009, 452)14 claims that aggregate indexes are difficult to interpret.
Although the coefficients could be significant, one cannot be sure about the factors
that cause a certain effect. Thus, to understand and better explain variation in
possibly corrupting effect of the oil revenues it is better not to restrain our research
14 For instance, Kaufmann and Vicente (2011) also emphasize the value of disaggregated data on corruption: firm-level instead of country-level data structures.
14
only to democracies and democratic institutions. Wright (2008) pinpoints the
importance of going beyond the accustomed dichotomy between democratic and
autocratic regimes. Whilst reinforcing the importance of political institutions in limiting
the power of autocratic leaders, Wright has demonstrated that there is a variation
between authoritarian regimes as well. Consequently, one has to assume that this
assumption also holds for differences within democracies. Therefore, it makes sense
to control for the conditional effect of oil on corruption cross-nationally and without
restricting our analyses to democracies and autocracies.
By the same token, according to Hallagan (2010), the variance in corruption
depends on the choice of institutions in dictatorships. Hallagan developed two
alternative models to show how "taxes" could be collected. The models display
different kinds of organizations, which in their term differently influence corruption in a
country. In his opinion, policy choice and choice of institutions determine conditions,
which can either facilitate or restrict corruption. For instance, even if a dictator
chooses the civil servants model to fight corruption and provide for transparency,
there are some crucial limitations for the success of this model. Because of the
dictator's "unlimited" power, i.e. absence of other political institutions that to constrain
such an arbitrary rule, the model of civil servants is to fail. Hence, organizations of
good quality can be easily paralysed unless they are protected by corresponding
institutions and do not depend on the leader's will.
To test the strength of disaggregated versus aggregated indexes in explaining
the observed variation in corruption scores among oil-producing countries, I will run
regression both on the individual parameters and on the (“aggregated”) index of
institutional quality. The index of institutional quality will be based on three
parameters, namely: accountability, rule of law and transparency. To address
collinearity and endogeneity concerns, I search for smaller and simpler proxies for
the institutional quality indicators.
6.2. Dependent Variable. Data on Corruption
There are three commonly used datasets available on corruption. The first
one, prepared by the Political Risk Services, is the corruption index of the
International Country Risk Guide (ICRG). There are two datasets that have different
starting points. The IRIS-3 dataset includes data for the period 1982-1997, and the
15
Researcher Dataset (ICRG T3B) accommodates data for the period 1984-2008
(Aslaksen 2007). The second one, published by Transparency International, is the
Corruption Perception Index. This index includes data for the time period from 1996
to 2009. The third dataset is on the Control of Corruption released by Kaufmann,
Kraay and Mastruzzi (2009). This measure reveals data for the time period from 1996
to 2008. Data for 1996-2000 was issued every second year, and starting from 2002 it
has being released on a yearly basis. All these three datasets, even if they employ
different data collection strategies, are highly correlated. The main difference
between these datasets is the years and countries they cover (Svensson 2005).
Notwithstanding small changes in the corruption index over time, the ICRG
dataset contains information on significant regime changes in some political systems
(e.g. in Latin America and Eastern Europe). This is to enable controlling for the
effects of the variables of interest, that is, the effects of political institutions on
corruption (Lederman, Loayza and Soares 2004).
To test my hypotheses I will use the corruption index developed by the
Political Risk Services. This index measures corruption within a political system and
takes into account actual or potential corruption in the form of excessive patronage,
nepotism, job reservations, 'favor-for-favors', secret party funding, and suspiciously
close ties between politics and business. The corruption index ranges from 0 to 6,
with higher values indicating less corruption. Lower scores indicate that "high
government officials are likely to demand special payments," and that "illegal
payments are generally expected throughout lower levels of government" in the form
of "bribes connected with import and export licenses, exchange controls, tax
assessment, police protection, or loans."
6.3. Independent Variables
(1) Data on Oil and Gas Resources
The data on oil and gas resources is from the World Development Indicators
and the World Bank Adjusted Net Savings dataset. This dataset covers 149 countries
for the time period from 1970 to 2006. Additionally, I am going to use data from the
BP (Beyond Petroleum), Energy Information Administration (EIA), International
Energy Agency (IEA) and the World Factbook issued by Central Intelligence Agency
16
(CIA). These datasets provide data on global reserves, production and consumption,
stock and prices of oil and gas resources.
(2) Index of Institutional Quality
Mehlum, Moene and Torvik (2006) in their study on institutions and the
resource curse used the institutional quality index developed by Knack and Keefer
(1995). A number of further studies also employ index of institutional quality
(Robinson, Torvik and Verdier, 2006; Beck and Laeven, 2006; Cabrales and Hauk
2010). These indexes were created as an unweighted average of individual indexes
based on data from Political Risk Services or World Bank Governance Indicators
(e.g.: a rule of law, a bureaucratic quality index, a corruption in government index, a
risk of expropriation index and a government repudiation of contracts index 15). Thus,
these studies define corruption as one of the parameters of the institutional quality. In
contrast to these studies, I differentiate between the quality of institutions and
corruption. In my paper I aim to explain the likely corrupting effect of oil via
institutional factors. Therefore, I regress corruption on the institutional quality.
Further, to develop index of the institutional quality I employ rules like transparency,
accountability and rule of law.
(a) Transparency
According to Kaufmann and Bellver (2005) transparency leads to better socio-
economic performance and better human development indicators as well as to higher
competitiveness and lower corruption. Similarly, Kolstad and Wiig (2009) indicate that
transparency is a key in fighting corruption in resource-rich countries. Political elites
in these countries have an "exclusive" access to the resource rents and this is why
corruption is widespread there. When information is hardly accessible to the broad
audience, that is, only a few people have control over it, it is difficult to disclose
whether a bureaucrat is corrupt or not. In other words, in non-transparent systems
bad politicians or policies are less likely to be revealed and punished. Therefore,
transparency is decisive in limiting incentives of politicians to be involved in rent-
seeking activities. To summarize, corruption in oil-rich countries can be tackled in
different ways, whereas transparency reform is only one possibility, although a very 15 In the 2009 International Country Risk Guide dataset the last two indexes: a risk of expropriation index and a government repudiation of contracts index together with a payment delays index are included into the investment profile index.
17
important one. Hence, one should not lessen the significance of transparency, as
transparency can reduce corruption by helping make politicians more accountable to
the public.
To operationalize transparency I will use Freedom House data on Freedom of
Press. A free press is believed to be one of the most effective institutions in fighting
political corruption (Brunetti and Weder 2001, 1801). The data on freedom of press is
available for the time period from 1980 to 2009 for 196 countries. The index ranges
from 0 (best) to 100 (worst). The degree to which each country permits the free flow
of news and information determines the classification of its media as “free”, “partly
free”, or “not free”. Countries scoring 0 to 30 are regarded as having free media; 31
to 60, partly free media; and 61 to 100, not free media.
However, transparency on its own is not enough to reduce corruption (Kolstad
and Wiig 2009, Lindstedt and Naurin 2005). The authors claim, that effect of
transparency on corruption is conditional on education and accountability.
Accountability is of profound importance as there is a critical need for other agents
who can hold bad politicians accountable for the abuses of office.
(b) Accountability
The importance of political accountability has been also stressed by Robinson,
Torvik and Verdier (2006). The authors have highlighted the problem of predicting a
monotonic effect of resources on development. They argue that a good model should
explain why some resource rich countries prosper, while others grow slowly or even
experience economic decline. The authors pinpoint the importance of institutions and
especially the interaction between institutions and resources in explaining the above-
mentioned variances. The authors have developed a model of clientelism which
explains how politicians secure desirable election outcomes through inefficient
redistribution16 of resource rents. Thus, politicians seek political support by offering
jobs in the public sector. In other words, public patronage is actively employed. In
contrast, in countries with accountable institutions politicians are constrained in their
abilities to use clientelism in order to manipulate election outcomes. Consequently,
by such institutional constellations resource booms would lead to economic
development.
16 This model is similar to the spending effect argument made by Ross (2001, 2009). 18
Kaufmann, Kraay and Mastruzzi (2009) developed six aggregate and
individual indexes to measure the quality of governance. Thereby, they have defined
governance as "traditions and institutions by which authority is exercised" (2009, 5).
Their governance indicators particularly include voice and accountability, government
effectiveness, political stability and absence of violence, rule of law, regulatory
quality, and control for corruption. Kaufmann, Kraay and Mastruzzi (2009) define
voice and accountability as an ability of people to select their governments and the
existence of freedoms of expression, of association and of a free media. In the
International Country Risk Guide (2009) there is a similar indicator called democratic
accountability which measures the responsiveness of government to its people.
Thereby, the ICRG indicator is based on the type of governance which takes account
of an alternating democracy, dominated democracy, de-facto one-party state, de-jure
one-party state and autarchy. The ICRG indicator for accountability ranges from 0 to
6, with higher values indicating "better" accountability.
While taking into account endogeneity and collinearity concerns, I will use
Cingranelli & Richards’ electoral self-determination variable from their human rights
dataset as a proxy for the political accountability. This index ranges from 0 to 2, with
higher values being representative for a free and open political participation and a
citizens’ right to self-determination through free and fair elections in both law and
practice.
As I have mentioned it before, along with transparency and accountability I
use rule of law to account for institutional quality. In the following I introduce the
concept of the rule of law and describe data I employ as a proxy for this institution.
(c) Rule of Law
According to Bedner (2010, 50-51), rule of law has two main functions. The
first function is “to curb arbitrary and inequitable use of state power”, whereby “the
core idea is that the sovereign is bound by law”. The second function is “to protect
citizens’ property and lives from infringements or assaults by fellow citizens”. This
protection is to be regulated by the state. Thus, the rule of law as its name already
says, is an institution. This institution devises certain rules and constraints of the
game. For instance, "in the U.S. constitution the idea of rule of law is more frequently
expressed as government of laws, not of men" (Safire 2008, 634). "A rule of law is
contrasted with arbitrary power, as happens in a police state, or the personal whim of
19
a dictator. The essence is that 'judges' should decide only according to the rule laid
down, not according to their own sense of justice or personal preference" (Robertson
2002, 432). Thus, rule of law is "the assertion that a nation's leaders must abide by a
written constitutions or unwritten common law" (Safire 2008, 634).
Sachs and Warner (1997) have shown that the rule of law index and index for
bureaucratic quality of the ICRG dataset are highly correlated (0.98). However, they
have opted for the rule of law index as a "general index for the efficiency of legal and
government institutions" (p. 21). This index consists of two sub-components, each
comprising zero to three points. The Law sub-component is an assessment of the
strength and impartiality of the legal system, while the Order sub-component is an
assessment of popular observance of the law. Kaufmann, Kraay and Mastruzzi
(2009) have also designed a rule of law index. Their index measures the extent to
which agents have confidence in and abide by the rules of society, in particular the
quality of contract enforcement, the police, and the courts, as well as the likelihood of
crime and violence. Although the World Governance Indicators’ index of rule of law is
quite comprehensive, the problem with its use for my empirical analysis is the short
time span that covers time period from 1996-2008. Therefore, as a proxy for the rule
of law I use US State Department’s political terror scale. This variable varies from 1
to 5, with higher values meaning more political violence and terror. The data is
available for the time period from 1976 to 2008 for 186 countries.
6.4. Control Variables
Previous studies have identified a number of socio-economic and political
factors that control for corruption. In particular, Treisman (2006) provides a good
summary of different control variables. Economic development, education and
democracy score are the most commonly used control variables.
Based on my theoretical argument and empirical model I will use economic
development (GDP per capita) and years of schooling to control for the effect of oil
and gas on corruption increase.
7. Methodology
Aslaksen (2009) argues that cross-country analyses, used in earlier studies on
resource abundance and corruption, have a number of shortcomings. These studies
20
did not pay attention to the heterogeneity problem. Aslaksen shows that there are
different intercepts for different countries. Fixed effects are to allow analysis of the
within-country variation in oil rent and corruption rates as well as controlling for an
unobserved cross-country heterogeneity.
Therefore, she suggests using panel data with both time series and cross-
sectional variation (Aslaksen 2009, 14-15). Measure of corruption released by the
ICRG datasets is an ordinal variable and cannot be treated as a continuous variable.
Thus, as the ICRG measure of corruption is a discrete variable, the distance between
different units is not the same (Wooldridge 2009). Therefore, a linear regression
model cannot be used for the analysis of such a data, as it will often give misleading
results (Long 2005).
7.1. Model
If a relationship between two or more variables depends on the value of one or
more other variables then one has to deal with a conditional hypothesis (Brambor,
Clark and Golder 2005). To test conditional hypotheses we can apply multiplicative
interaction models. In these models conditional variables modify the effect of the
independent variable (X) on the dependent variable (Y). Therefore, to test my
hypotheses I will use an interaction term as well.
Corruptionit = αit + β1Oilit + β2Instit + β3Oil×Instit + β4Controlsit + eit
7.2. On the Endogeneity Problem
In single equation regression models there is a unidirectional relationship
between the dependent and independent variables. It means that the causality, if
any, runs from the independent (Xs) to dependent (Y) variable. However, there are
also cases when this type of link cannot be observed. Hence, it is quite possible that
the causal arrows run not only from Xs to Y, but Y can also influence Xs. In such a
case, a bilateral relationship between Y and Xs takes place. Consequently, one has
to use more than one regression equation in order to avoid a problem of biased
results. This type of regression model is known as a simultaneous equation
regression model. In other words, dependent and independent variables are
interdependent or causing each other simultaneously. Such jointly dependent 21
variables are known in statistics as endogenous variables (Gujarati and Porter 2010,
pp. 345-349). To sum up, an endogenous variable is "a variable that is an inherent
part of the system being studied and that is determined within the system. That is, an
endogenous variable is caused by other variables in a causal system," (Vogt 1993,
pp. 81-85).
Ross (2001, 2009) has asserted that institutions are endogenous to natural
resources. Mehlum, Moene and Torvik (2006, 16) have found that politicians could
be interested in weaker institutions in order to have more or less unlimited access to
resource rents, and for the same reason they could favour less democracy.
Nevertheless, Sachs and Warner (1997, 2001) have demonstrated that correlation
between resource abundance and institutions is weak and insignificant.
Given this controversy on the causal link between natural resource
abundance, institutional quality and corruption I will have to control for a bilateral
relationships between these variables with the help of special statistical techniques
and tests. In particular, I will use instrumental variable tests.
For instance, Dunning (2009, 8) shows that Acemoglu, Johnson, and
Robinson (2005) used colonial settler mortality rates as an instrumental variable for
current institutions whilst explaining the impact of institutional frameworks on the
economic performance. Thereby, Acemoglu, Johnson and Robinson emphasize that
the disease environments during the colonial years did not affect current economic
performance in former colonies directly. This effect takes place only through their
impact on current institutions.
22
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