Corruption has been at the center of extensive research since the turn of the 21st century. Early corruption research can be traced back to the late 60s and before. A simple definition of corruption involves individuals who are public officials that are abusing their public office for private gain. However, some views extend that definition. Kaufmann (2015) sees corruption from a larger perspective "involving a network of politicians, organizations, companies, and private individuals colluding to benefit from access to power, public resources, and policy-making at the expense of the public good" The later form can affect the rule of law and regulations, and hence is referred to sometimes using the term State capture. Such forms of illegal activities may require widening the definition of the term corruption itself. Svensson (2005) regards corruption as a result and an indicator of the power of the political institutions of a country in addition to its economic standing, dominant culture and rule of law status and asserts that the definition of corruption itself is not definite.
Several indexes are used to measure corruption. An early measure was constructed by Political Risk Services Group, the publishers of the International Country Risk Guide. As part of a country's risk assessment, the guide tries to focus on actual and potential corruption where nepotism and political ties to businesses may take place. Their measure is a way to alert potential foreign investors of dangers that can form challenges to the government of a certain nation when corruption is exposed causing widespread discontent. Such backlash can overthrow a government and be of cost for foreign investors. Hence, the measure is designed in such a way that ties corruption to potential political instability.
A most widely used measure of corruption is the one published by Transparency International; the Corruption Perception Index. The measure utilizes data from 11 different organizations and 12 data sources and aims to evaluate the perception of corruption. The different data sources include country rankings in different aspects from the African Development Bank Governance Ratings, Bertelsmann Foundation Sustainable Governance Indicators, Bertelsmann Foundation Transformation Index, Economist Intelligence Unit Country Risk Ratings, Freedom House Nations in Transit, Global Insight Country Risk Ratings, IMD World Competitiveness Yearbook, Political and Economic Risk Consultancy Asian Intelligence, Political Risk Services International Country Risk Guide, World Bank Country Policy and Institutional Assessment, World Economic Forum Executive Opinion Survey and the World Justice Project Rule of Law Index.
Corruption is often perceived as a developing nation's phenomena and seen as an obstacle to development. It is viewed as a major hindering factor in attracting foreign direct investment and in drafting proper development polices. However, the inquiry into whether corruption is a cause or an effect is one that frequently engages researches. Is corruption a result of poverty or a cause of it has been a major question of economic research. In addition, research has been focused on many different correlations that can be made; how corruption relates to openness and trade, income inequalities, political institutions, the degree of urbanization and many other factors. In addition, much research investigates the most effective way to decrease corruption, comparing country experiences and correlating corruption to proxies of the rule of law and efficient institutions. This paper aims to shed some light on recent trends in corruption literature, the techniques and data used and the latest findings in this area.
Early corruption research can be traced back to the 1960's and 1970's. Work by Becker and Stigler (1974) focused on the relationship between the government official and the public. The research was trying to understand the roots of having corrupt government officials and suggest remedies. One straightforward solution suggested by Becker and Stigler was to introduce efficient wages. This line of research was further enhanced by work introduced by Banfield (1975) and Rose-Ackerman (1975) where they further investigate this principal agent problem. Shleifer & Vishny (1993) focused on consequences of corruption on resource allocation and economic development. Utilizing a model of demand and supply for government goods, where the marginal cost to the seller of the government good can be its legal price or taxation, or a bribe, Shleifer and Vishny argued that corruption hinders economic development through two channels; the weak grip of the government opens the door for a multitude of government institutions to enforce bribes on private individuals such as those seeking investment licenses, in the light of such weakness, bribe value can significantly increase to the point that it can stop the flow of vital growth needed capital from foreign direct investment. The later reason can explain why foreign investment didn't flow to certain countries in the transforming economies and in Africa. The second reason given by the authors is the distortions entailed by the secrecy of corruption which can divert resources from highly publicized and much needed projects in healthcare and education to less desired ones where eyes are less focused on and bribery can thrive.
Mauro (1995) carried out what may very well be the first empirical study that tries to link corruption to economic growth. Mauro utilized a newly assembled set of indices on red tape, corruption and government efficiency that was based on surveys to a multitude of international businesses operating in 70 countries covering the period between 1980 and 1983.
Mauro's dataset made available proxies for ranking institutional efficiency consisting of indexes of political stability, institutional change, social change, the possibility of opposition takeover, stability of labor, and terrorism among other factors. Moreover, he also constructed a bureaucratic efficiency index consisting of the efficiency of the judiciary system, the degree of red tape, in addition to the degree of perceived corruption. Mauro ran series of regressions and correlations of those variables to ethno-linguistic fractionalization, per capita GDP growth, investment to GDP ratio, primary education, secondary education, population growth, government expenditure to GDP, revolutions and coups, assassinations and other variables.
Mauro's utilization of the subjective indices of bureaucratic honesty and efficiency yielded what may be the first empirical evidence on the effects of corruption on economic growth. Mauro's findings indicated a negative and significant correlation between corruption and investment, and corruption and growth. The extent of Mauro's analysis allowed him to make quantified predictions. Based on his results, he predicted that if Bangladesh could increase its bureaucratic integrity and efficiency to the level of that of Uruguay which according to his calculation, corresponded to a one standard deviation increase in the subjective bureaucratic efficiency index, then its investment rate could rise by around five percentage points, and its annual GDP growth rate would also increase by more than half a percentage point. In addition, Mauro's findings also indicate that corrupt and unstable governments tend to spend less on education; a finding that is in line and is consistent with Shleifer and Vishny (1993) deduction that corruption...