ESC
Clarivate

 
Source: Journal Citation ReportsTM from ClarivateTM 2022

Entrepreneurship and Sustainability Issues Open access
Journal Impact FactorTM (2022) 1.7
Journal Citation IndicatorTM (2022) 0.42
Received: 2020-03-10  |  Accepted: 2020-06-30  |  Published: 2020-09-30

Title

Investigating the relation of GDP per capita and corruption index


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


JEL classifications

D73 , N10 , C10


URI

http://jssidoi.org/jesi/article/652


DOI


Pages

780-794


This is an open access issue and all published articles are licensed under a
Creative Commons Attribution 4.0 International License

Authors

Moiseev, Nikita
Plekhanov Russian University of Economics, Moscow, Russian Federation http://www.rea.ru
Articles by this author in: CrossRef |  Google Scholar

Mikhaylov, Alexey
Financial University under the Government of the Russian Federation, Moscow, Russian Federation http://www.fa.ru
Articles by this author in: CrossRef |  Google Scholar

Varyash, Igor
Financial Research Institute of the Ministry of Finance of the Russian Federation, Moscow, Russian Federation https://nifi.ru
Articles by this author in: CrossRef |  Google Scholar

Saqib, Abdul
University of Science, Malaysia, George Town, Malaysia https://www.usm.my
Articles by this author in: CrossRef |  Google Scholar

Journal title

Entrepreneurship and Sustainability Issues

Volume

8


Number

1


Issue date

September 2020


Issue DOI


ISSN

ISSN 2345-0282 (online)


Publisher

VšĮ Entrepreneurship and Sustainability Center, Vilnius, Lithuania

Cited

Google Scholar

Article views & downloads

HTML views: 3038  |  PDF downloads: 4411

References