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Influence of Governance Indicators on Illicit Financial Outflow from Developing Countries

Anselm Komla Abotsi (PhD)
Senior Lecturer in the Department of Economics Education, University of Education, Winneba.

Illicit financial flows (IFFs) are defined in the Global Financial Integrity (2012)  report as “funds that are illegally earned, transferred, or utilized and cover all unrecorded private financial outflows that drive the accumulation of foreign assets by residents in contravention of applicable laws and regulatory frameworks”. –

Issues on IFFs have become very important particularly with regards to the quantum and its impact on the economic development of developing countries (see Economic Development in Africa Report 2020). According to Blankenburg and Khan (2012), IFFs have a direct or indirect negative effect on economic growth in the country of origin. Calculations carried out by Global Financial Integrity show that the estimated IFFs from developing countries are approximately ten times the total amount provided as official development assistance (Kar and Freitas, 2012).

The consequence of these IFFs is the aggravation of the enormous socio-economic problems confronting developing countries since these activities constitute a drain on foreign exchange reserves and reduce tax revenue, which culminates in worsening poverty in these developing countries (see The Economy of Illicit Trade in West Africa (2018)). The report by Purje, Ylönen, and Nokelainen (2010) indicates that IFFs from developing countries have become a major development policy issue since this act deprives states of tax revenue and disrupts the vital development of the private sector, which is recognized in the literature as the engine of growth in developing countries (Abotsi, Dake and Agyepong, 2014), by distorting competition; this culminates in increased dependency on development assistance (Purje, et al.,  2010).

For governments and stakeholders to be able to fight this issue of illicit financial outflow, there is the need for comprehensive scrutiny of the quality of governance indicators that enhance the activities of these multinational companies. Therefore, this study seeks to explore the influence of cross‐country indicators of governance on IFFs from developing countries.

Literature review

Illicit financial flow is composed of three components, which include commercial transactions, tax evasion, and laundered commercial transactions; the criminal element and bribery; and finally, abuse of office by public officials (Mbeki, 2014).

Empirical studies in explaining IFFs are generally based on the portfolio choice (PC) model, which attributed the massive capital outflow from developing countries to expropriation and currency losses and a reaction to comparatively low-profit expectations (risks aversion) (Collier, Hoeffler and Pattillo, 2001). According to Herkenrath, (2014), the PC model does not fully explain IFFs that originate from economically successful industrialized countries as well as fast-growing emerging countries, since these flows mainly enhance tax evasion. The research shows that the factors of the PC model have only limited explanatory power Herkenrath, (2014) since the explained variance of their final empirical model is below 50 percent (Le and Zak, 2006). IFFs are postulated to be a consequence and a cause of development-inhibiting circumstances (Moore, 2001; Shaxson, 2010). A theoretical model of IFFs suggests a circular relationship between IFFs and development-inhibiting economic, political, and social conditions (Moore, 2001). The world governance indicators reflect the views of thousands of survey respondents and public, private, and NGO sector experts worldwide on governance. These indicators also present the empirical measures of governance and thus make it possible to find the influence of these indicators on illicit financial flow from developing countries using qualitative analysis.

Based on the literature, this study reckons a set of potential quality governance indicator variables that influence illicit financial outflow. These variables include governance effectiveness, regulatory quality, and control of corruption with foreign direct investment inflow as the control.

FDI Inflow

The pursuit to attract FDI inflow led to the proliferation of multinational companies or firms in developing countries. A major problem concerning illicit financial flow is how these multinational firms benefit from tax holidays and then sell out immediately before the expiry period of such concessions, only to re-emerge as a new firm with a new tax holiday period. Multinational companies can have hundreds of subsidiaries in different jurisdictions in which they have little or no activity. A common practice has been for the group to resort to declaring the most profit in the jurisdiction with the lowest taxes rather than where the profits were generated. It is the expectation that countries that receive more FDI inflows are more likely to experience more illicit financial outflow.

Governance Effectiveness and Regulatory Quality

The term ‘governance’ is broad and far-reaching, and the improvements to ‘virtually all aspects of the public sector’ is necessary to achieve ‘good governance’(Grindle, 2004). Good governance is referred to by the World Bank as ‘sound development management’ and is regarded as “central to creating and sustaining an environment that fosters strong and equitable development and it is an essential complement to sound economic policies” (World Bank, 1992). Therefore, the quality of a government’s policy formulation and implementation and the credibility of the commitment of governments to such policies (regulatory quality) are very important in achieving good governance. The international development agencies have identified ‘bad governance’ as a major obstacle to economic growth and improved welfare in poor countries (Moore, 2001). It is expected in this study that governance effectiveness and regulatory quality will explain variation in illicit financial outflow; however, the direction of influence of these variables on illicit financial outflow must be determined empirically.

Control of corruption

Corruption epitomizes the illicit use of the willingness to pay as a decision-making criterion; therefore, in most cases, multinational companies make payments to public officials in return for a benefit (Abotsi, 2016). A report by OECD (2014) states that ‘high levels of corruption combined with weak institutions, and sometimes illegitimate regimes are drivers for such illicit financial outflows. Elsewhere, research findings also show a significant link between corruption and capital flight (Le and Rishi, 2006). Corruption is therefore expected to have a positive influence on illicit financial outflow in this study.

Methodology

The study on the governance indicators that influence illicit financial outflow is based on secondary data (panel) derived from the Global Financial Integrity, World Development Indicators, and Worldwide Governance Indicators. The total number of developing countries included in the analysis is 139, and 1562 observations are included. This study uses the multilevel approach in exploring the factors, that influence illicit financial outflow from developing countries.

The following multilevel model (equation 1) is proposed, where the selected variables are expected to influence illicit financial outflow. This model was developed by the author with data from Global Financial Integrity, World Development Indicators, and Worldwide Governance Indicators.

Empirical Results of the Mixed Model Estimation

It is prudent in a mixed model to determine whether there is sufficient variance represented at a higher level to warrant the mixed approach. The intraclass correlation coefficient found in this study shows that approximately 13.2% of the total variance in illicit financial outflows can be attributed to differences between the geographical regions (i.e., level 2); this is more than the minimum of 10% expected for further modelling. The FDI inflows predictor variable is designated as having a random slope; therefore, the slope parameter can have a variance (random coefficient models). This designation will allow FDI inflows to have a different effect on illicit financial outflows across different regions.


Furthermore, a likelihood ratio test is deployed to test for the random intercept model and the random coefficient model. The null hypothesis is that there is no significant difference between the two models. Since the result of the likelihood ratio test show that LR chi2 is equal to 166.75 with a probability of 0.00000, the null hypothesis is rejected with the conclusion that there is a statistically significant difference between the models. This finding shows that the random coefficients model provides a better fit (it has the lowest log-likelihood). It can be concluded that the random variance of the FDI inflows slope is different from zero.

The results show that FDI net inflows, control of corruption, regulatory quality, and government effectiveness significantly influence illicit financial flow at 1%. The results show that FDI net inflows and government effectiveness variables have a positive influence on illicit financial flow; however, control of corruption and regulatory quality variables have a negative effect.

The results depict that, on average, countries that receive more foreign direct investment inflow experience more illicit financial outflow from their countries. Also, the finding means that the exhibition of high governance effectiveness by developing countries is necessary but not sufficient in fighting illicit financial outflow. Furthermore, results also indicate that, on average, countries that exhibit high regulatory quality experience less illicit financial flow from their countries. This result means that the ability of governments to formulate and implement sound policies and regulations is paramount in the fight against illicit financial outflow. Finally, on average, developing countries that are more corrupt experience more illicit financial flow from their countries.