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Article
Publication date: 20 January 2020

Anas Al Qudah, Azzouz Zouaoui and Mostafa E. Aboelsoud

This study aims to better understand the phenomenon of corruption in Tunisia in relation to its impact on economic development. The period of study is 1995 to 2014. The…

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Abstract

Purpose

This study aims to better understand the phenomenon of corruption in Tunisia in relation to its impact on economic development. The period of study is 1995 to 2014. The auto-regressive distributed lag (ARDL) model is adopted to examine the existence of a long-term relationship between the above-mentioned variables and also the direct and indirect consequences of corruption on economic development in Tunisia.

Design/methodology/approach

The study uses a modern econometric technique to estimating the long-term relationship (e.g. the co-integration) between corruption and economic development; using this technique also allows us to investigate the impact of corruption on economic growth.

Findings

The empirical results show that corruption has a negative effect on per capita gross domestic product (GDP) in Tunisia for the period under review. This effect is described as a direct effect of corruption in the long term; specifically, declines are observed in per capita GDP, over the long run, by almost 1 per cent, following a 1 per cent increase in the level of corruption. The results also show that corruption has indirect effects via transmission channels, such as investment in physical capital, which is positively significant in the presence of corruption. The same observation is made at the level of government expenditure during the previous year, while for those of the current year, the coefficient becomes negative but not significant. With respect to human capital, the impact of corruption on education expenditures is insignificant.

Originality/value

The paper begins with an overview of previous literature in this area. Given the nature of corruption and the differences in the meanings attributed to it, from one country to another and from one culture to another, the paper moves on to study the impact of corruption in Tunisia as a case study for one country with one socio-cultural environment. The authors then propose several methods and possible solutions, which could be implemented to deal with this problem.

Details

Journal of Money Laundering Control, vol. 23 no. 1
Type: Research Article
ISSN: 1368-5201

Keywords

Article
Publication date: 13 May 2021

Azzouz Zouaoui, Mounira Ben Arab and Ahmad Mohammed Alamri

This paper aims to investigate the economic, political or sociocultural determinants of corruption in Tunisia.

Abstract

Purpose

This paper aims to investigate the economic, political or sociocultural determinants of corruption in Tunisia.

Design/methodology/approach

To better understand the main determinants of corruption in Tunisia. This study uses The Bayesian Model Averaging (BMA) model, which allows us to include a large number of explanatory variables and for a shorter period.

Findings

The results show that economic freedom is the most important variable of corruption in Tunisia. In second place comes the subsidies granted by the government, which is one of the best shelters of corruption in Tunisia through their use for purposes different from those already allocated to them. Third, this paper finds the high unemployment rate, which, in turn, is getting worse even nowadays. The other three factors considered as causal but of lesser importance are public expenditures, the human development index (HDI) and education. Education, the HDI and the unemployment rate are all socio-economic factors that promote corruption.

Originality/value

The realization of this study will lead to triple net contributions. The first is to introduce explicitly and simultaneously political, social and economic determinants of corruption in developing countries. Second, unlike previous studies based on the simple and generalized regression model, the present research uses another novel and highly developed estimation method. More precisely, this study uses the BMA model, on the set of annual data for a period of 1998–2018. The third contribution of this research resides in the choice of the sample.

Details

Journal of Financial Crime, vol. 29 no. 1
Type: Research Article
ISSN: 1359-0790

Keywords

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