Link Between Economic Growth And Corruption Economics Essay
In this paper I will aim to cover four main areas; firstly the theoretical relationship between economic growth and corruption, some empirical studies exploring this link, the recent growth experience of Asian countries and possible explanatory hypotheses given the high perceived corruption levels and then conclude with some policy implications of corruption especially in less economically developed countries.
Brooks (1909) notes that “in the whole vocabulary of politics it would be difficult to point out any single term that is more frequently employed than the word ‘corruption’” and yet, given its frequent use, not many are certain of its definition. Treisman (2000) defines corruption as, 'the misuse of public office for private gain' but it is evident that corruption can come in many differing forms, the implications of which ripple throughout the work done in this field. Bribery, extortion, fraud, speed money and embezzlement are just some forms of corruption (Klitgaard, 1991) and Mishra (2007) notes of the added legal and moral dimensions with the inclusion of terms such as 'illegal' and 'improper'. The latter can be of particular importance when people engage openly in seemingly corrupt acts, oblivious of the moral and legal implications. Corruption may not necessarily involve money such as gift giving, influence-peddling or future benefits resulting in the differences between a corrupt and a non-corrupt act becoming ill-defined and culturally bound (Balboa and Erlinda, 2006). For the purpose of this paper I will be using the basic definition as outlined by Treismann but clearly this is a simplification of a very large and conceptual ideology.
Measurement of Corruption
The UNDP's Guide to Measuring Corruption (2008) describes measurement of corruption as 'more of an art form than a precisely defined empirical process', and thus without a definitive structure and malleable in nature. Our inability to accurately measure corruption is most problematic when attempting to assess the relationship between macroeconomic variables, such as economic growth. The two most widely used perceptive measures available are Transparency International's Corruption Perception Index (CPI) and the World Bank's Control of Corruption Indicator, both of which are composite indicators made up of distinct component data sources that assess a broad and differing range of concepts (UNDP, 2008). Most cross-country studies are carried out using the CPI or the Business International Index because the data available for them is much broader compared to survey based data sources, despite the latter being arguably more useful.
Clearly the method of measuring corruption will impact on the empirical findings; perceptive measures can be problematic when it comes to understanding growth. Mishra (2007) notes that in cross-country studies there might be problems with endogeneity whereby a variable such as the impact of institutions might be affecting both economic growth and corruption simultaneously thereby making the task of finding the true effect of corruption on economic growth particularly difficult. There may also be systematic bias given suitable data is not available for a large set of countries over a prolonged period of time (important for understanding long term economic growth), measurement errors and omitted variable bias all of which should be taken into consideration when exploring the strength of corruption on economic growth. It should also be recognised that whilst we will be focusing on cross-country econometric models to explore this relationship, to fully understand the strength of corruption on economic growth a number of different measures of corruption should be considered (Kauffman, Kraay and Matruzzi, 2006).
Theoretical Relationship between Economic Growth and Corruption
Intuition might suggest that corruption and long run economic growth are negatively correlated; one might assume that the nature of corruption will slow and possibly even stop economic growth due to the negative externalities it undoubtedly produces. In this next section I will further examine aspects of the theoretical relationship between corruption and the strength of its effect on long run economic growth.
Murphy, Schliefer and Vishny (1993) argue that public rent seeking hampers innovation which in turn slows down investment thus negatively impacting economic growth. Public rent-seeking in this instance refers to the redistribution of rents from the private sector to the government bureaucrats who in turn affect the fortunes of the private sector. De Soto (1989) supports this by adding that to start a new business an innovator must acquire permits, tax documents and so on, the demand for which being inelastic creating a perfect opportunity for corruption. Innovators have no established lobbies, are often credit-constrained, innovative projects are typically long-term and involve slow accumulation of capital and moreover the projects are typically risky, all of which increases innovators' vulnerability to exploitation via corrupt bureaucrats. Empirically, Mahagaonkar (2008), who investigates the experience of African countries using data from the World Bank’s Enterprise Survey, found a strong and significant negative correlation between corruption and product innovation. This type of rent-seeking places a heavy tax on innovative activities and thereby sharply reduces long run economic growth (Bardhan, 1997).
Government intervention that requires the use of bureaucrats to make decisions reveals opportunity for bureaucratic corruption; Acemoglu and Verdier (2000) argue that this type of corruption severely affects the allocation of human capital from productive sectors to the less productive sectors within an economy, further negatively impacting long term economic growth. When the ‘allocational’ role of the state is undermined by a corrupt bureaucrat and the enforcement of contractual agreements fails, agents as a consequence avoid investment into more productive sectors on an economy and turn to less productive sectors. However, Mishra (2007) notes that this may have further implications in the long run in the sense that if talent is driven away from the productive sector and returns are low, payoff to the corrupt bureaucrat will fall and thus we arrive at a multiple outcome poverty trap type scenario. Nevertheless, faced with either no growth and high corruption levels or low (but positive) growth and low corruption levels, Ehrlich and Lui (1999) argue that the final outcome will depend on the structural formation of corruption – an idea we will later revisit. Does this imply that levels of corruption should be encouraged? Not entirely, Acemoglu and Verdier simply argue that in developing countries the costs of eliminating corruption are too high and as such positive levels of corruption arise in equilibrium.
Olson (1993) further argues that specialised interests which manifest themselves as interest groups tend to decrease efficiency as the subsequent preferential treatment dissipates resources, inevitably leading to larger governmental organisations, increased bureaucracy stifling growth. Thus, the theory suggests several negative implications of corruption on long term economic growth.
I will now focus on the empirical investigations led by Mauro (1995), Wei (1999), Mo (2001) and Rock and Bonnett (2004) to see if it corroborates the aforementioned theory.
Following a neoclassical regression framework, Mauro (1995) studied the relationship between corruption and economic growth using the Business International (BI) corruption index, claiming to find that corruption lowered private investment thereby reducing economic growth even in sub-samples of countries where bureaucratic regulations were cumbersome. He argues that his results suggest corruption and bureaucratic efficiency are robustly negatively associated with investment over the period of 1960-85 for 70 countries, even when controlling for other determinants of investment, including the political stability index. Mauro's reasoning for proxying corruption as bureaucratic inefficiency can be supported by Djankov et al. (2002), showing that a greater number of procedures, official time, and official cost that a start-up firm must bear before it can operate legally is associated with higher levels of corruption (see also Kaufman and Wei 1999).
Wei (1999) understands Mauro's work to imply that if the Philippines reduced their corruption to be level with Singapore's, assuming ceteris paribus, their investment-GDP ratio would rise 6.6 percentage points. He goes further to suggest that the overall effect of corruption on economic growth is negative and that had China’s corruptions levels been lower, their FDI would have been significantly higher. Rock and Bonnett (2004) find somewhat similar results in that corruption slows growth and reduces investment in most developing countries but it is exacerbated in smaller developing countries. However, they also found that growth and corruption increased simultaneously in the larger East Asian newly industrialised economies over the time periods 1980-1996.
Mo (2001) has shown in his work that corruption reduces economic growth predominantly through human capital and political instability channels revealing that 1% rise in the corruption level decreases the growth rate by about 0.72%. However, it is also noted that Mo's growth framework is somewhat incomplete and given the multicollinearity present in his measurement of corruption it is near impossible to disentangle and observe the individual effects empirically, but in general there is still strength in his negative relationship between corruption and economic growth.
From the empirical evidence we can see that there is some general support of the theory but on a macroeconomic level it is slightly unclear of the strength of this relationship between economic growth and corruption and the channels through which the relationship is most prevalent.
The Asian Controversy
The recent rapid growth in Asia (especially in countries like China and India) despite relatively high levels of corruption (See Appendix A for further detail) presents further complications and I will now look at three possible explanatory hypotheses surrounding the paradoxical happenings as outlined by Gill and Kharas (2007).
Some critics argue that the paradox we have witnessed is a false one; Asia's perceived corruption levels are much higher than their true values. Mauro's (1995) statistical study suggests a positive correlation between investment and bureaucratic inefficiency rather than economic growth and corruption; bureaucratic inefficiency may simply relate to inefficient or slow governments as opposed to specifically corrupt ones. Some economists including Svensson (2005) have rerun the same regressions as Mauro but come to quite different conclusions showing no significant relationship between economic growth and corruption.
Wei (1999) supports the false hypothesis arguing that Asia is no exception to corruption's negative implications on growth; there are several channels through which corruption hinders economic development and there is no statistical evidence to support the notion that corruption in Asia is any less harmful than anywhere else in the world. Nonetheless, whilst it can be argued that growth would be significantly greater in the countries without corruption, the false growth hypothesis fails to explain Asian growth despite the high corruption measures.
Huntington (1968) argues that in the 'context of economic growth, the only thing worse than a society with rigid, over-centralised, dishonest bureaucracy, is one with a rigid, over-centralised, honest bureaucracy'. Commonly referred to as the 'Grease' hypothesis, Huntington (1968) and Leff (1964) suggest that corruption can increase the efficiency of an economy in overcoming bureaucratic rigidity and cumbersome rules and regulations. Particularly in developing countries where administration can be slow, inflexible and costly – corruption can be considered as a 'lubricant' to overcome these hindrances.
The cleavages among elite personnel and the potential for violence are said to be overcome through the distribution of the spoils of corruption as it allows minorities and opposition groups access to a closed system of rewards (David, Gould and Amaro-Reyes, 1983), contrary to the common view that corruption favours a particular class of people and creates inequality in opportunities (Mo, 2001). They are also said to promote political development through the facilitation of electoral politics as the proceeds of corruption create valuable political institutions. However, some might argue that the creation of political institutions can be done within the boundaries of the law and thus question the need to resort to illegal, corrupt practices.
Empirically the 'Grease' hypothesis does not hold and many economists disagree with Huntington's arguments. Myrdal (1968) argues a very valid point in that, if bureaucrats were aware of the power they hold, they'd be presented with opportunities to increase rigidity and red tape in order to receive greater pay-offs consequently increasing corruption and the administrative process. Kaufman and Wei (1999) also find evidence to support this; they observe that bribes and measures of official harassment are positively correlated across a study done over two thousand firms. Their evidence suggests that the corrupt official tailors each bribe according to the firm's 'ability to pay' and as such the bribery process is severely lengthened creating further inefficiencies.
Wedeman (2002) argues that the economic growth and development relationship in East Asia is unique in the sense that the system of kickbacks and illicit political contributions give ruling parties a direct political interest in actualising the ideologies that many espoused; a mutually beneficial 'developmental alliance' has been created between politicians and businessmen. He differentiates between two different types of corruption; predatory (anarchic) low-level of corruption whilst present is not dominant but in Asia there is a greater tendency towards high-level transactive corruption i.e. exchanging public resources for political contributions. Thus, whilst one might expect the corrupt bureaucrat to demand bribes for his/her private gain, in Asia corruption results in the distribution of public resources to the private sector thus facilitating economic expansion. The stable pattern of these corrupt activities create a stable economic environment therefore countering our usual negative externalities of corruption: instability and distrust.
The view that the level of uncertainty surrounding corruption can have an impact on long term economic growth has been explored by Schliefer and Vishny (1993) (who alluded to Olsen's work on stationary and roving bandits) with reference to South Korea; more organised corruption can reduce uncertainty and thus stimulate growth. In South Korea, whilst corruption was pervasive, the person paying the bribe was guaranteed to secure the good that was being paid for and would not need to pay bribes in future. In Olsen's work (1993) these corrupt bureaucrats would be referred to as 'stationary bandits' because they monopolise theft in their domain limitting what they steal with the view that in the long run they will be able to extract more if they give their subjects the public goods they need to invest and produce additional income and wealth. The difference between the Asian and African growth levels might be understood in this way because in many African countries not only do numerous bureaucrats need to be bribed, but the bribe does not guarantee that another bribe will not be demanded by some other bureaucrat; in Olsen's theory these bureaucrats would be considered 'roving bandits'. As a result, Schliefer and Vishny conclude that the structure of governmental institutions and the political process are also determinants on the effect of corruption on long term economic growth.
Conclusion and Policy Implications for the Developing World
As we have seen, the relationship between economic growth and corruption remains tenuous; the theory suggests a negative correlation between both variables yet empirically we have found some controversial results regarding the strength of this relationship. The surrounding explanatory hypotheses do aid our understanding of the Asian growth but the effects of corruption are multiple and vary by type, location, and extent (Klitgaard 1988) consequently blurring the implications for policy making.
Throughout this essay we have looked at the impact of corruption on long term growth but it might be that in the short run we see some positive effects. This can greatly impact the ability of policy makers when attempting to stimulate economic development as it suggests eradication of corruption may not always yield the expected economic outcomes (Rock and Bonnett, 2004). Whilst corruption is harmful, it is not the single most detrimental factor to economic growth, contrary to what the World Bank might suggest. As we have seen, the damages of corruption are exacerbated by poor institutions, poor political structures and the size of the developing country, however when structured and monopolised via the 'stationary bandit' analogy, corruption could play a central role in sustaining a pro-capitalist, pro-growth economy, as was the case under the Suharto government in Indonesia (Rock, 2002).
Nevertheless, understanding this multi-faceted relationship is far from black and white and it is difficult to make sense of highly aggregate measures of corruption and its link with growth (Mishra (pers.comm) 2012). Whilst more sophisticated measures have been developed in the past decade (Rose-Ackerman, 2004), the nature of corruption which thrives on secrecy, coupled with the use of technology, poses increasing threats to long term growth and thus becomes a more elusive problem to policy makers when trying to decide on effective long term strategies.
As is shown in the graphs below, corruption levels in Asia are varied and whilst there is a general consensus that corruption is higher in most Asian countries than elsewhere in the world, the CPI for those countries is broadly in line with what their GDP per capita would predict; richer countries have lower corruption indices. However, outliers such as Singapore shows lower than expected per capita income given their low corruption rates, and China's control of corruption rate equating Mongolia's despite China's income per capita being over three times that of Mongolia's suggests that corruption is not entirely determined by income levels (Gill and Kharas, 2007).
Comparing the CPI and the GDP growth in China and Bangladesh for example we can see that CPI behaves similar to a constant whilst growth fluctuates over time. This might be because perceptions of corruption take time to evolve unlike growth rates which are fluctuating significantly, but nevertheless it may question the causal relationship between both variables (Mishra, 2007).
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