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Weekly UpdatesINTRODUCTION
Data limitations and the complexity of the oil and gas industry have impeded the efforts of researchers to study and uncover the links between the rents generated by oil revenues and high levels of corruption as well as the corruption-development link in energy-rich economies. (1) The studies that have been undertaken in energy-rich countries (Aslaksen and Torvik, 2005; Auty, 2001; Damania and Bulte, 2003; Gylfason, 2004) argue that corruption could be blamed for the failure of a number of energy-rich economies to develop. This literature has not considered the multi-directional causality between resource richness, corruption and economic development. We intend to fill this gap in the literature by providing evidence on both the link between natural resource wealth and corruption and the lack of development, with special reference to energy-rich countries.
Our paper relates to several strands of the academic literature. First, it extends the literature on the corruption-development debate (Aslaksen and Torvik, 2005; Auty, 2001; Damania and Bulte, 2003; Gylfason, 2004) by relating the causes of corruption to some energy-specific variables.
Second, our paper is related to a more recent literature that studies the corruption--growth link using regional level analysis, especially for the region of the Middle East and North Africa (MENA) where the major energy reserves are located (World Energy Outlook, 2007). These studies include in their cross-country regressions a number of region-specific institutional variables such as bureaucratic quality and corruption in order to distinguish the impact of these variables on economic growth at a regional level. For example, Guetat (2006) attempts to distinguish the impact of corruption on growth in MENA countries from of its impact on countries in Latin America, Asia and sub-Sahara Africa. Their results suggest that corruption may hamper economic growth more in MENA countries. Gyimah-Brempong and de Camacho (2006) examine regional differences in the impact of corruption on economic growth in Africa, Asia and Latin America. They find a negative impact of corruption on the growth of income per capita, with the largest negative effect in Africa. Kutan et al. (2008) provide further empirical evidence on the impact of corruption on economic development in MENA and Latin American countries. They report significant differences in terms of the impact of corruption on economic development in both regions.
Third, the present paper relates to recent theoretical attempts that model the corruption-economic growth link conditional on the quality of political institutions. Aidt et al. (2008) show that corruption may have no significant impact on economic growth in a regime where political institutions are of low quality. However, it may hurt growth significantly when political institutions are of high quality. Our paper is related to theirs, as we estimate the impact of corruption on growth (and vice versa) conditional upon energy dependency variables, which play an important role in government policy. In addition, we test how democratic institutions affect growth and corruption in the presence of significant energy dependence.
Fourth, our paper is linked to the literature on the resource curse and rent-seeking behaviour of government bureaucracy in energy-rich countries (Sachs and Warner, 1995, 1999a; Auty, 1994; Gylfason et al., 1999, Leite and Weidmann, 1999; Kalyuzhnova, 2008). A recent study by Kalyuzhnova and Nygaard (2008) brings a different perspective to this literature. They consider corruption as an element of overall state capacity; in case-specific economies corruption may be an integral element of the functioning of the economic and political system. Finally, the paper relates to the literature on the effect of national oil companies on corruption (Olcott, 2007).
In the next section, we discuss the hypotheses to be tested and outline the empirical framework and strategy used. The subsequent section describes the data and presents the empirical evidence. The last section concludes the paper with some policy implications.
TESTABLE HYPOTHESES, EMPIRICAL FRAMEWORK AND ESTIMATION STRATEGY
In this section, we first discuss our testable hypotheses using arguments developed in the literature. Next, we summarise our empirical models and explain our estimation strategy.
Key hypotheses to be tested
One of the key arguments regarding corruption in energy-rich countries relates to the behaviour of the state bureaucracy with regard to a country's resource endowment. The nature of exploration and production in the oil and gas industry creates a high concentration of capital expenditures, generates a high level of resource revenue for the government, and through this provides ample opportunities for corruption and rent-seeking behaviour by the government bureaucracy. In fact, all 34 less-developed oil-rich countries 'share one striking similarity: they have weak, or, in some cases, non-existent political and economic institutions' (Birdsall and Subramanian, 2004, p. 78). Corruption and rent seeking by government officials connected to the oil industry could be 'exacerbated by use of "off-budget" accounts (including those established by national oil companies)' (ODI/UNDP, 2006, p. 14). Thus the existence of regulations and a state bureaucracy to enforce them as well as entire political regimes in energy-rich countries are open to corruption. Thus, we argue that political institutions may hurt or improve corruption conditional upon the level of energy dependency, formulating the following hypotheses specific to energy-rich economies:
Hypothesis 1. Corruption is higher in energy-rich countries where state bureaucracy is high or ease of doing business is low.
Hypothesis 2. Democratic regimes foster corruption in countries with significant energy dependency.
Corruption may also be affected by education level or human capital stock in a given country. Gylfason (2001) shows that public spending on education in resource-rich countries is inversely related to the share of natural capital in national wealth across countries because natural capital tends to crowd out human capital. Hence, we develop our third hypothesis as follows:
Hypothesis 3. Energy-abundant countries with low level of education are likely to be more corrupt.
Another key argument discussed in the literature is the link between economic growth, resource richness and corruption. The few studies analysing the poor economic performance of resource-rich economies (Auty, 2001; Gylfason, 2001) overlooked the important possibility of bi-causality, where poor economic performance causes corruption and corruption causes economic decline. Using a dynamic general equilibrium model of economic growth, Blackburn et al. (2005) derive a theoretical link between corruption, economic development and a number of other variables. They show that the relationship between corruption and economic growth is both negative and bi-causal in general. From these arguments we derive our fourth hypothesis:
Hypothesis 4. There is a negative and bi-causal relationship between corruption and growth in energy-rich economies.
It is possible that corruption may not affect the growth rate of GDP, but just its level. Hence, we derive the following final hypothesis:
Hypothesis 5. There is negative and bi-causal relationship between corruption and economic development, measured by the level of GDP per capita, in energy-rich economies.
Empirical models
We estimate two sets of two equations, the first set for the growth rate of real GDP per capita and corruption, and the other one for the level of real GDP per capita and corruption. In the economic growth equation, our focus variable is corruption and energy-specific variables. We also use several control variables to account for the other potential determinants of economic growth. Regarding the latter, standard growth theory (ie Solow, 1956; Barro and Sala-i-Martin, 1991) and new growth theory suggest that capital accumulation and human capital are important factors determining long-term growth (Aghion and Howitt, 1992; Romer, 1990). We therefore expect a positive coefficient for these variables. As proxies for capital accumulation, we use government expenditures, gross fixed capital formation, foreign direct investment (FDI) and infrastructure (percentage of total roads paved). In addition, following some recent studies we have included democracy and openness variables in estimations and these studies have presented evidence that better democratic systems and a higher level of openness increase growth significantly (Bardhan, 1997; Durham, 1999; Rodrik, 2000; Sachs and Warner, 1999b, Tavares and Wacziarg, 2001). Democracy is used to measure institutional quality and openness is utilised as a measure of country's openness to foreign trade. Hence, we expect positive coefficients for these two variables as well.
For the corruption equation, following our testable hypotheses, we include the growth rate of real GDP per capita (level of GDP per capita in the second set), education, democracy, ease of doing business and energy-specific variables. The expected signs of these variables are discussed above when we developed our hypotheses. In addition, we use the following control variables: openness, democracy index, general government final consumption expenditure as percentage of GDP, economic freedom and external debt. In terms of the signs of coefficients, we expect that countries that are more open, having a smaller ratio of government expenditure in GDP, more economic freedom and less external debt should have lower levels of corruption. The intuition for the inclusion of these variables into our regression equations and expected signs come from some related studies mentioned earlier (Aidt, 2003; Aidt et al., 2008; Mehlum et al., 2006; Papyrakis and Gerlagh, 2004; Sachs and Warner, 1995, 1999b).
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