Investigating the relation of GDP per capita and corruption index

Nikita Moiseev (), Alexey Mikhaylov, Igor Varyash () and Abdul Saqib
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Nikita Moiseev: Plekhanov Russian University of Economics, Russian Federation
Igor Varyash: Financial Research Institute of the Ministry of Finance of the Russian Federation, Russian Federation
Abdul Saqib: University of Science, Malaysia, Malaysia

Entrepreneurship and Sustainability Issues, 2020, vol. 8, issue 1, 780-794

Abstract: The paper is devoted to modelling the corruption perception index in panel data framework. As corruption index is bounded from below and above, traditional econometric multiple regression will produce a bad quality model. In order to correct that, we propose a mathematical framework for modelling bounded variables implementing a logistic function. It is shown that corruption is best explained by GDP per capita and all other major macroeconomic indicators cannot add any statistically significant improvement to the models’ accuracy. Thus, we assume, that society wealthiness facilitates the reduction of corruption acts. Indeed, if some individual lives in a society that does not experiences almost any shortage of resources of whatever kind, the less interested this person is in getting wealthier by applying some corruption schemes. These methods are rather popular in less wealthy countries, where temptation to engage into corruption is higher, since it can drastically increase individual’s utility function. Therefore, in this research we assert, that the growth of wealth in a society makes corruption recede and not the other way around (reducing corruption helps increase GDP per capita). However, the most counterintuitive finding of this research is the fact, that GDP per capita, adjusted by purchasing power parity, produces the model of a worse quality then just using plain GDP per capita. This fact can be tentatively explained by the flaws in the methodology of calculating these adjustments, since the basket of goods varies drastically across the countries.

Keywords: corruption; GDP per capita; purchasing power parity; macroeconomic indicators; modelling bounded variables; logistic curve; probability distribution (search for similar items in EconPapers)
JEL-codes: C10 D73 N10 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:ssi:jouesi:v:8:y:2020:i:1:p:780-794

DOI: 10.9770/jesi.2020.8.1(52)

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