The effect of corruption on FDI:a parametric and non-parametric analysis


This paper analyses the effect of corruption on Multinational Enterprises' (MNEs) incentives to undertake FDI in a particular country. We contribute to the existing literature by modelling the relationship between corruption and FDI using both parametric and non-parametric methods. We report that the impact of corruption on FDI stock is different for the different quantiles of the FDI stock distribution. This is a characteristic that could not be captured in previous studies which used only parametric methods. After controlling for the location selection process of MNEs and other host country characteristics, the result from both parametric and non-parametric analyses offer some support for the ‘helping-hand’ role of corruption.

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Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences > Aston Business School
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Europen journal of political economy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published Barassi, M & Zhou, Y, 'The effect of corruption on FDI: a parametric and non-parametric analysis' Europen journal of political economy, vol. 28, no. 3 (2012) DOI
Uncontrolled Keywords: corruption,FDI,non-parametric,parametric,MNEs' location choice,Economics and Econometrics,Political Science and International Relations
Publication ISSN: 1873-5703
Last Modified: 21 Jun 2024 07:08
Date Deposited: 11 Mar 2019 18:26
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2012-09
Authors: Barassi, Marco
Zhou, Ying



Version: Accepted Version

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