Title: Corruption, economic growth and sustainable development - a conditional quantile analysis

Authors: Conceição Castro; Carlos Pinho

Addresses: CEOS.PP, ISCAP, Polytechnic of Porto, CEPESE, Porto Accounting and Business School, Rua Jaime Lopes Amorim, 4465-004 S. Mamede de Infesta, Portugal ' GOVCOPP Research Centre, DEGEIT – University of Aveiro, Aveiro, Portugal

Abstract: Corruption strangles not only economic growth and but also sustainable development, which comprises the economic, social, and environmental dimensions of development. This paper aims to analyse the effects of corruption on economic growth and sustainable development, measured by the adjusted net savings. Using a quantile regression approach, this paper develops a panel data model allowing the analysis of different potential effects in the relationships corruption - economic growth and corruption - sustainable development. This is done along different points of the conditional growth and sustainable development distributions in a sample of 134 countries during the period 2000-2018. The results suggest that corruption decreases GDP per capita and sustainable development despite its levels. But the magnitude of the effects of corruption increases as one moves from the higher to the lower tail of the conditional distribution of GDP per capita or sustainable development. Consequently, lower-performing countries could benefit more from reducing corruption. Controlling corruption can thus be seen as an effective way to promote growth and sustainable development.

Keywords: corruption; economic growth; sustainable development; conditional quantile analysis; adjusted net savings.

DOI: 10.1504/IJSD.2021.122714

International Journal of Sustainable Development, 2021 Vol.24 No.3/4, pp.220 - 244

Accepted: 03 Dec 2021
Published online: 06 May 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article