Illicit financial flows have in the recent times been a source of worry to the Nigerian government. It is in that light that this study is motivated to examine the relationship between illicit financial flows and the growth of Nigerian economy. Ordinary Least Square Statistical tool was adopted, applying E-View version 9 software to run the analysis. The results show that illicit financial flows via illegal commercial activities have a negative nexus with economic growth in Nigeria with a correlation coefficient of -0.006832. It is equally revealed that with a correlation coefficient of -0.043301, a negative relationship exists between illicit financial flows caused by corruption and economic growth in Nigeria. A negative nexus is reported between illicit financial flows caused by international crime and economic growth in Nigeria as depicted with a correlation coefficient of -0.006675.
Keywords: Illicit financial flows, International crime, Illegal commercial activities, Corruption, Foreign direct investment, Financial economics.
JEL Classification: K42, P37, P45, P47.
DOI: 10.20448/811.4.1.13.24
Citation | Joseph, Fineboy Ikechi; Omodero, Cordelia Onyinyechi (2019). Illicit Financial Flows and the Growth of Nigerian Economy. International Journal of Economics and Financial Modelling, 4(1): 13-24.
Copyright: This work is licensed under a Creative Commons Attribution 3.0 License
Funding : This study received no specific financial support.
Competing Interests: The authors declare that they have no competing interests.
History : Received: 2 October 2019 / Revised: 8 November 2019 / Accepted: 11 December 2019 / Published: 2 January 2020 .
Publisher: Online Science Publishing
Highlights of this paper
|
Nigeria as a nation is endowed with one of the most valuable and widely demanded liquid natural resources, the black gold (crude oil). The exploration, drilling and production have been on for decades and because of high tech requirements of the oil sector, activities in this sector are dominated by Multinational Corporations owned by developed. Through the exportation and production of crude oil, Nigeria has earned hard currencies via foreign exchange earnings amounting to trillions of dollars in the past five decades. It should be recalled that as reported by Asagunla Temitope Michael (2018) in the past fifty years, the country’s oil subsector has grown phenomenally. Both production and exports have increased a great deal since commercial production in 1958. Take for instance, oil revenue increased from N166.6 million in 1970 to N 1,591,675.00 million and N 6, 530,430.00 million in 2000 and 2008. Oil revenue in 2012 was N 8025.971 billion and in 2013 and 2014 were N6809.231bn and N 5403.51bn respectively (NNPC Statistical Bulletin, 2014). Despite the huge amount that has been generated over the decades, the country still remains poor in almost all ramifications. Every sector is relatively sick ranging from education, electricity, manufacturing, agriculture, no security, poor to worn out medical equipment and facilities.
Corruption, fraud and other related crimes are responsible for mismanagement and misappropriation of the huge fund generated as has been widely reported by organizations and researchers. Transparency International (2019) revealed that ‘Joint Task Force (JTF) comprising personnel from the Nigerian Army, Air Force, Navy and Police, has been deployed in the Niger Delta region since the early 2000s. The JTF is tasked with tackling the militant threat in the region and protecting its oil from theft. However, there have been indications that some JTF members are complicit in, and often benefit from, precisely the pursuit they are mandated to eradicate: the illicit oil industry. Existing research suggests that members of the Nigerian armed forces have enabled and benefitted from the illegal trade in a number of ways. Often this benefit comes from providing “protection” – both ensuring military officials turn a blind eye to illegal activity and protecting oil thieves’ access to extraction points from rivals – in exchange for financial bribes’. It can be observed that the Nigerian army officials are corrupt and therefore compromise their core mandate.
However, there is another mysterious means through which Nigeria loses huge resources financially and otherwise that appears not popular among average Nigerians. It is through what is referred to as capital flight perpetrated by developed countries through their Multinational Corporations (MNCs). The impact of this is enormous. Capital flight is aided and abated by Nigeria corruption politician and foreigners who have the monopoly of the technology to tap these natural resources. The MNCs carry out these acts via tax evasion, tax avoidance, transfer pricing and involvement in banking secrecy. It appears that corruption and fraud among the political class have distracted attention from capital flight to the extent that majority of Nigerians, even among the scholars report less on the dangers it portends to the nation.
The High-Level-Level Panel and Global Financial Integrity (GFI) in their study divided IFFs into three categories based on the source of the flow and that is captured in a study by Service Centre for Development Cooperation (2010) as follows: a. Corruption: This was the focus of a wide-range of talk during the 1990s, which accounts only for 3-5% of all these money/illicit outflows. b. International Crime: This includes drug and human trafficking, money laundering et cetera which accounts for about 30%.c. Illegal commercial capital flight via tax evasion by multinational companies is clearly of greatest significance. This accounts for about 64% of capital flight repatriation/illicit outflows. The financial figures that would be derived as the worth of illicit financial flows/capital flight for a period of the study would be divided according to the subdivision of illicit financial flows percentage wise. That is, illegal commercial capital flight/activities 64%; International Crime 30%; Corruption 3% - 5% (average 4%).
Therefore, this study would be critically examining the relationship between capital flight and economic growth in Nigeria, putting into consideration the three subdivisions of capital flight/illicit financial flows; thus filling a gap created in prior studies that have not looked at the relationship between the independent variables and dependent variable from this perspective. It is based on the classification of illicit financial flows by SCDC (2010) that the objectives and hypotheses of this study hinge.
Illicit outflows can be seen as illicit wealth that is earned, transferred or used in contravention of a country’s laws. It can be referred to as wealth whose origin is connected with illegal activity, such as corruption, the illicit manufacture of goods, other varying forms of crime; it includes concealing a company’s wealth from a country’s tax authorities. The definition is used here of illicit or illegal financial flows (or illegal capital flight) comes from the Global Financial Integrity studies, whose figures have been used by many different development policy organisations, including the World Bank. In practice, the majority of unrecorded financial flows break the laws of one country or another, which is why it is reasonable to speak of illegal capital flight.
SCDC (2010) as flows: a. Corruption: This was the focus of a wide-range of talk during the 1990s, which accounts only for 3-5% of all these money/illicit outflows. b. International Crime: This includes drug and human trafficking; money laundering et cetera which accounts for about 30%.c. Illegal commercial capital flight via tax evasion by multinational companies is clearly of greatest significance. This accounts for about 64% of capital flight repatriation/illicit outflows. Illegal commercial means that funds are transferred from a company to subsidiaries sited in a number of tax havens at exceedingly high or low prices. By investments in tax haven companies, the investors can conceal their true identity. For example, allowing them to enjoy the benefit from special treatment targeted to overseas investors. A similar process can be used for laundering money. For example, in the case of China it is estimated that as much as a quarter of capital illegally taken out of the country returns as foreign investments. China is famous as a country of origin of huge illicit financial flows. It is estimated that up to €80 billion of taxable income evaporates from China each year. Some multinational companies engaging in illegal capital flight are situated and do business in emerging economies. Unfortunately, about 80–90% of illegally taken capital leaves developing countries permanently through these MNCs that claim they attract development.
Also when foreign investors make extensive use of offshore companies, shell companies, and tax havens, they weaken disclosure standards and undermine the efforts of reformers in Africa to promote transparency. Such practices also facilitate tax evasion and, in some countries, corruption, draining Africa of revenues that should been deployed to fight poverty and vulnerability’ (Kofi Annan African Progress Report, 2013). MNCs are very selfish in their business dealings in developing nations such as Nigeria, taking a look at these developments. Some foreign companies operating in Nigeria are the conduit pipes for this act. Some of these foreign investors do business in those areas that require huge capital outlay and are also technology-driven. Take for instance; reported that the Airline Operators of Nigeria has called on the Federal Government to support domestic carriers, saying that foreign airlines had dominated the country’s airspace resulting in about $3bn capital flight, annually.
Paul et al. (2015) noted that the high value of world-wide estimate of capital flight of $539 billion to $829 billion every year is worrisome and debilitates development intentions of the developing countries. The capital flight in countries represents a significant proportion of their gross domestic product (GDP). For instance, South Africa lost 9.2% of her GDP (US $ 13 billion) in 2000, China 10.2% of GDP (US $ 109 billion) in 1999; Chile 6.1% of GDP (US 4.7%) in 1998 and Indonesia 6.7% of GDP (US $14 billion) in 1997. In addition, between 1990 and 1995, Russia is estimated to have lost about $400 billion. Nigeria and other sub- Saharan African countries are estimated to have lost over 100% of their GDP ($230 billion) since 1970. It is inimical to the economic growth of Nigeria that such resources are lost to even richer and developed nations via capital/illicit flows.
They include tax haven practices by MNCs, tax evasion and avoidance, corruption, organized crime, fraud in international trade through mis-invoicing, illegal exploitation of natural resources and diversion of public fund from priorities. Other forms through which illicit outflows occur include illegal logging, fishing and mineral extraction. The consequence of these is the impoverishment of the citizenry and country at large.
They include political and economic security challenges around the world especially in developing countries. Poverty, economic retardation, poor standard of living and general underdevelopment in all ramifications have become the norm in developing world. IFFs reduce domestic resources and tax revenue needed to fund poverty-reducing programmes and infrastructure in developing countries. It goes further to erode resources thereby constraining poverty reduction and shared prosperity (World Bank, 2015) Nigeria has fallen victim of capital flight perpetrated by developed nations mostly through their agents, that is, multinational corporations. Though these multinational companies are welcome by their host developing countries with a view to speeding up development and increasing FDI, studies have shown that unknowingly to these developing countries, huge sum of capital/resources are illegally transferred to the countries of origin or parent companies of these MNCs abroad through their subsidiaries abroad in order to avoid/avert filling in their tax return to their host governments thereby robbing these developing nations of their resources through various tax havens practices and other illegal cross border practices. These developments have negatively affected the citizenry and economy of Nigeria.
GDP as Used in the Study: The make-up of GDP includes personal consumption expenditures plus business investment plus government spending plus (export minus imports). Economic growth looks the expansion of a country’s economy. It is most popularly measured by increasing gross domestic product, or GDP. This indicator estimates the value added in a country which is the total value of all goods and services produced in a country minus the value of the goods and services needed to produce them. It is common to divide this indicator by a country’s population to better gauge how productive and developed an economy is, that is, the GDP per capita.
Change in GDP (GDP Growth Rate) = | Final GDP –Initial GDP |
In recent times, Change in GDP has been found to be a reliable proxy for economic growth and therefore adopted in this study as the proxy for economic growth.
It is possible to have economic growth without economic development in the short or even medium term (Feldman et al., 2016). On the other hand, there could be an increase in GDP without any increase in standard of living of people in a state.
Foreign Direct Investment Explained: The internationally accepted definition of FDI is captured in the fifth edition of the IMF (1993). Foreign direct investment (FDI) is investment made to acquire a lasting interest in or effective control over an enterprises operating outside of the economy of the investor. With respect to this definition, FDI has three components: equity investment, reinvested earnings, and short term and long term inter-company loans between parents firms and foreign affiliates, that is, FDI flows consist of three components: FDI Flow=New equity+ Retained earnings+ Net Intra-corporate loans.
These elements of direct investment capital transactions are recorded on a directional basis (i.e. resident direct investment abroad and non-resident direct investment in the recording economy).The FDI net inflow records the net flow of non-resident direct investment in the recording economy, while the FDI net outflow records the net flow of resident direct investment abroad. FDI net inflows are the value of inward direct investment made by non-resident investors in the reporting economy, including intra-company loans, net of repatriation of capital and repayment of loans.
Similarly, FDI net outflows are the value of outward direct investment made by the resident of the reporting economy to external economies including re-invested earnings and intra-company loans, net of receipts from the repatriation of capital and repayment of loans.
As distinguished from other forms of international investment, FDI is made to create a lasting interest in or effective and efficient management control over a firm in another country.
There are different views on how capital flight /illicit cash outflows affect economic and social aspects of society or any nation especially developing nation. The theoretical overview or background is discussed hereunder.
There are five views on the possible effect of MNCs and FDI on the direction the world economy is going. These are termed ‘the Race to the Bottom’, ‘the Climb to the Top’, ‘Neo-liberal Convergence’, ‘Uneven Development’, and ‘Much Ado about Nothing’. The study settled with ‘the Race to the Bottom’ view. According to this view, capital will more and more be able to compensate workers, communities and nations off against one another, while it will threaten to run away once there is demand for tax and when the need for regulatory and wage concessions are not forthcoming. In this perspective, increased capital mobility benefits corporations, while workers and communities lose (Bluestone and Harrison, 1982; Barnet and Cavanagh, 1995; Greider, 1997) . For the purpose of this study we adopt ‘the race to the bottom’ view because it has relationship with the reason MNCs and foreign investors indulge in activities that encourage illegal capital leading to huge losses by their host communities and countries to their own advantage.
Orimolade and Olusola (2018) studied the nexus between capital flight and the growth of Nigerian economy and discovered that there is a long run negative nexus between GDP and all the capital flight variables as used in the study.
Rabah et al. (2014) in their own study on the relationship between natural resources and capital flight in the form of tax avoidance from multinational corporations, it noted spill over effects in terms of tax revenue mobilization and stock market development from the thin capitalization rule, a policy instrument aimed at limiting firm tax avoidance through setting limits on a firm’s foreign indebtedness. The study exploited the plausibly exogenous within-country variations of data on oil discoveries for a group of countries during the period 1970–2012. It was discovered that oil discoveries significantly boost both tax revenue mobilization and stock market development, but only when thin capitalizations rule is in place. The study therefore concluded that through, capital flight perpetrated by MNCs, tax evasion is entrenched in developing nations hence the loss of capital in such countries and this brings about erosion of domestic tax base.
Global Reporting Initiative (2006) in a study/report to determine the rate of capital flight in developing countries, discovered that capital flight with the intention to evade tax returns are of various forms such illegal commercial capital flight by MNCs amounting to 64%, international crime estimated at 30% and corruption between 3-5%. Some multinational companies engaging in illegal capital flight are domiciled and operating in emerging economies, but nevertheless, about 80–90 percent of illegally taken capital leaves developing countries permanently.
Issues related to the methodology of the study with emphasis laid on sources, the choice of the data collected, method of data analysis and model specification were addressed for the purpose of the paper. There is also discussion on the a-prior proposition or expectation of the model for the deep understanding of the readers.
The study is used ex post facto design. Data on illicit capital flows and GDP were obtained from the databases of Global Financial Integrity and UNCTAD, FDI/MNE database (www.unctad.org/fdistatistics) including published researched works by Global Financial Integrity, IMF, the World Bank (The World Development Indicators), Kar and Devon (2009). Others include OECD reports, textbooks and other materials in existence adopted in explaining the researched variables.
This study used the Ordinary Least Square analysis (OLS) to examine the nexus between illicit financial flows (independent variable) and economic growth in Nigeria proxied by Change in GDP (CGDP) (dependent variable). This study was designed to cover a period of 13 years (2005-2018). The results of the data analysis and hypothesis testing using E-views 9 Computation, 2017 presented reliable evidence upon which this study draws conclusions.
This study adopts a linear model written thus:
CGDP= f(IFFC, IFFINTC, IFFICA) (1)
By turning the Equation 1 into econometric model:
CGDP = β0 + β1IFFCt + β2IFFINTCt + IFFICAβ3t + μt (2)
Where
β0, β1, β2, β3 in Equation 2 are the parameters.
CGDP = Change in Gross Domestic Product.
IFFC = Illicit Financial Flows via Corruption.
IFFINTC = Illicit Financial Flows via International Crime.
IFFICA = Illicit Financial Flows via Illegal Commercial Activities.
μt =Stochastic disturbance.
Year |
Illicit financial flows total figure (Amount=N= Millions of Naira) |
Illicit financial flows via corruption (3-5%)=3+5=8/2= 4%) ,i.e., 4% of total figure on yearly basis in Naira |
Illicit financial flows via international crime (30% )- 30% % of total figure on yearly basis in Naira |
Illicit financial flows via illegal commercial activities (64%, )- 64% of total figure on yearly basis in Naira |
GDP in billions of Naira =N= |
Change in GDP/GDP growth rate(Billions of Naira) |
2005 |
2,359,204.00 |
94,368.16 |
28,310.45 |
18,118.69 |
15,041,279,317.06 |
18,927,683,895.90 |
2006 |
2,363,003.40 |
94,520.14 |
28,356.04 |
18,147.87 |
18,927,683,896.69 |
20,390,273,640.03 |
2007 |
2,100,262.50 |
84,010.50 |
25,203.15 |
16,130.02 |
20,390,273,640.96 |
24,499,624,755.18 |
2008 |
2,692,353.75 |
107,694.15 |
32,308.25 |
20,677.28 |
24,499,624,756.01 |
26,778,048,170.47 |
2009 |
4,167,724.00 |
166,708.96 |
50,012.69 |
32,008.12 |
26,778,048,171.38 |
55,916,654,006.58 |
2010 |
2,480,370.21 |
99,214.81 |
29,764.44 |
19,049.24 |
55,916,654,007.06 |
65,086,401,454.70 |
2011 |
1,551,664.20 |
62,066.57 |
18,619.97 |
11,916.78 |
65,086,401,455.56 |
72,966,687,539.08 |
2012 |
791,158.41 |
31,646.34 |
9,493.90 |
6,076.10 |
72,966,687,539.97 |
81,161,261,694.28 |
2013 |
4,213,569.68 |
168,542.79 |
50,562.84 |
32,360.22 |
81,161,261,695.18 |
104,888,053,984.20 |
2014 |
2,414,367.00 |
96,574.68 |
28,972.40 |
18,542.34 |
104,888,053,984.97 |
120,026,005,144.94 |
2015 |
4,277,174.50 |
171,086.98 |
51,326.09 |
32,848.70 |
120,026,005,145.81 |
177,844,870,511.80 |
2016 |
8,350,060.50 |
334,002.42 |
100,200.73 |
64,128.46 |
177,844,870,512.47 |
163,084,489,763.29 |
2017 |
10,464,174.00 |
418,566.96 |
125,570.09 |
80,364.86 |
163,084,489,764.38 |
122,367,154,843.51 |
2018 |
9,051,480.00 |
362,059.20 |
108,617.76 |
69,515.37 |
122,367,154,844.84 |
1,068,978,488,732.23 |
Total |
57,276,566.15 |
2,291,062.65 |
687,318.79 |
439,884.03 |
1,068,978,488,732.34 |
2,122,915,698,136.00 |
Source: Global financial integrity (GFI).
It is important to state here that the total figure on illicit financial flows is apportioned based on the study by High-Level-Level Panel and Global Financial Integrity (GFI) as captured in the study by SCDC (2010) which classified illicit financial flows into three namely (a) Illicit Financial Flows via Corruption: It is estimated that this accounts for 3%-5% of all illicit outflows. b. Illicit Financial Flows via International Crime: This includes drug and human trafficking; money laundering et cetera which accounts for about 30%.c. Illicit Financial Flows through Illegal commercial such as tax evasion by multinational companies is clearly of greatest significance. The percentage contribution of the identified classes of illicit financial are applied in generating the data for dependent variable from the total figure of Illicit Financial Flows as depicted in the Table 1.
Hypotheses testing as depicted in the Table 2:
Year |
Illicit financial flows via corruption (3-5%)=3+5=8/2= 4%) in Naira |
Change in GDP/GDP growth rate(Billions of Naira) |
2005 |
94,368.16 |
18,927,683,895.90 |
2006 |
94,520.14 |
20,390,273,640.03 |
2007 |
84,010.50 |
24,499,624,755.18 |
2008 |
107,694.15 |
26,778,048,170.47 |
2009 |
166,708.96 |
55,916,654,006.58 |
2010 |
99,214.81 |
65,086,401,454.70 |
2011 |
62,066.57 |
72,966,687,539.08 |
2012 |
31,646.34 |
81,161,261,694.28 |
2013 |
168,542.79 |
104,888,053,984.20 |
2014 |
96,574.68 |
120,026,005,144.94 |
2015 |
171,086.98 |
177,844,870,511.80 |
2016 |
334,002.42 |
163,084,489,763.29 |
2017 |
418,566.96 |
122,367,154,843.51 |
2018 |
362,059.20 |
1,068,978,488,732.23 |
Total |
2,291,062.65 |
2,122,915,698,136.00 |
The results of Analysis of HO1 as shown in the Table 3:
Dependent variable: GDP |
||||
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
Illicit financial flow |
-0.00683 |
0.005037 |
-1.356362 |
0.1365 |
Constant |
0.790675 |
0.225697 |
3.503255 |
0.0006 |
R-squared |
0.743159 |
Mean dependent var |
0.851852 |
|
Adjusted R-squared |
0.651693 |
S.D. dependent var |
0.356570 |
|
S.E. of regression |
0.356872 |
Akaike info criterion |
0.827577 |
|
Sum squared resid |
16.30173 |
Schwarz criterion |
0.978221 |
|
Log likelihood |
-48.8615 |
Hannan-Quinn criter. |
0.888795 |
|
F-statistic |
9.962258 |
Durbin-Watson stat |
1.864725 |
|
Prob(F-statistic) |
0.003569 |
The results shows that the coefficient of illicit financial flow (X1) is -0.006832 which shows that a percentage increase in illicit financial flow via illegal commercial activities will lead to -0.006832 decrease in economic growth in Nigeria; which means a negative nexus exists between illicit financial flows and economic growth in Nigeria. This implies that excess illicit flows of cash in the country will affect economic growths which in turn drastically decrease the GDP of the country.
The R2 coefficient explained the percentage by which the independent variable(s) explained the dependent variable. R2 which is = 0.743159. Durbin- Watson stat measures the existent of auto- correlation in the model. Durbin- Watson stat was 1.864725 which is close to 2, meaning that there is evidence of face auto- correlation.
Year |
Illicit financial flows via international crime (30% )-in Naira |
Change in GDP/GDP growth rate(Billions of Naira) |
|
2005 |
28,310.45 |
18,927,683,895.90 |
|
2006 |
28,356.04 |
20,390,273,640.03 |
|
2007 |
25,203.15 |
24,499,624,755.18 |
|
2008 |
32,308.25 |
26,778,048,170.47 |
|
2009 |
50,012.69 |
55,916,654,006.58 |
|
2010 |
29,764.44 |
65,086,401,454.70 |
|
2011 |
18,619.97 |
72,966,687,539.08 |
|
2012 |
9,493.90 |
81,161,261,694.28 |
|
2013 |
50,562.84 |
104,888,053,984.20 |
|
2014 |
28,972.40 |
120,026,005,144.94 |
|
2015 |
51,326.09 |
177,844,870,511.80 |
|
2016 |
100,200.73 |
163,084,489,763.29 |
|
2017 |
125,570.09 |
122,367,154,843.51 |
|
2018 |
108,617.76 |
1,068,978,488,732.23 |
|
Total |
687,318.79 |
2,122,915,698,136.00 |
The results of Analysis of HO2 as shown in the Table 5:
Dependent variable: GDP |
||||
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
Illicit financial flow |
-0.043301 |
0.015621 |
-2.77197 |
0.0135 |
Constant |
0.790475 |
0.225478 |
3.503475 |
0.0001 |
R-squared |
0.748452 |
Mean dependent var |
0.851852 |
|
Adjusted R-squared |
0.678593 |
S.D. dependent var |
0.356570 |
|
S.E. of regression |
0.356872 |
Akaike info criterion |
0.827577 |
|
Sum squared resid |
16.30173 |
Schwarz criterion |
0.978221 |
|
Log likelihood |
-48.86148 |
Hannan-Quinn criter. |
0.888795 |
|
F-statistic |
9.987592 |
Durbin-Watson stat |
1.788725 |
|
Prob(F-statistic) |
0.004782 |
The coefficient of illicit financial flow (X2) is -0.043301 which shows that a percentage increase in illicit financial flows caused by Corruption will lead to -0.043301 decrease in economic growth in Nigeria. This implies that when there is increase in corruption based on illicit financial flow will lead to decrease in GDP in Nigeria.
The R2 coefficient explained the percentage by which the independent variable(s) explained the dependent variable. R2 which is = 0.748452. Durbin- Watson stat measures the existent of auto- correlation in the model. Durbin- Watson stat was 1.788725 which is close to 2, meaning that there is evidence of face auto- correlation.
Year |
Illicit financial flows via illegal commercial activities (64%, )- in Naira |
Change in GDP/GDP growth rate(Billions of Naira) |
|||
2005 |
18,118.69 |
18,927,683,895.90 |
|||
2006 |
18,147.87 |
20,390,273,640.03 |
|||
2007 |
16,130.02 |
24,499,624,755.18 |
|||
2008 |
20,677.28 |
26,778,048,170.47 |
|||
2009 |
32,008.12 |
55,916,654,006.58 |
|||
2010 |
19,049.24 |
65,086,401,454.70 |
|||
2011 |
11,916.78 |
72,966,687,539.08 |
|||
2012 |
6,076.10 |
81,161,261,694.28 |
|||
2013 |
32,360.22 |
104,888,053,984.20 |
|||
2014 |
18,542.34 |
120,026,005,144.94 |
|||
2015 |
32,848.70 |
177,844,870,511.80 |
|||
2016 |
64,128.46 |
163,084,489,763.29 |
|||
2017 |
80,364.86 |
122,367,154,843.51 |
|||
2018 |
69,515.37 |
1,068,978,488,732.23 |
|||
Total |
439,884.03 |
2,122,915,698,136.00 |
The results of Analysis of HO3 as shown in the Table 7:
Dependent variable: GDP |
||||
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
Illicit financial flow |
-0.006675 |
0.007642 |
-0.873462 |
0.5431 |
Constant |
0.789512 |
0.225477 |
3.5047800 |
0.0000 |
R-squared |
-0.678523 |
Mean dependent var |
0.851852 |
|
Adjusted R-squared |
0.356872 |
S.D. dependent var |
0.356570 |
|
S.E. of regression |
17.32147 |
Akaike info criterion |
0.827577 |
|
Sum squared resid |
-48.86148 |
Schwarz criterion |
0.978221 |
|
Log likelihood |
9.962258 |
Hannan-Quinn criter. |
0.888795 |
|
F-statistic |
0.004782 |
Durbin-Watson stat |
1.781452 |
|
Prob(F-statistic) |
0.789512 |
The coefficient of illicit financial flows caused by international crime (X3) is -0.006675 shows that a percentage increase of illicit financial flows caused by international crime will lead to -0.006675 decrease in economic growth in Nigeria. This implies that the more the increase in financial international crime will lead to decrease in economic growth in Nigeria.The R2 coefficient explained the percentage by which the independent variable(s) explained the dependent variable. R2 which is = 0.789512. Durbin- Watson stat measures the existent of auto- correlation in the model. Durbin- Watson stat was 1.781452 which is close to 2, meaning that there is evidence of face auto- correlation.
Given the results obtained above from the models which is in line with the stated specific objectives; the findings from the first specific objective from where the second hypothesis is derived showed that the coefficient of illicit financial flow (X1) is -0.006832 which shows that a percentage increase in illicit financial flow via illegal commercial activities will lead to -0.006832 decrease in economic growth in Nigeria. This implies that excess illicit flows of resources in the country will affect economic growths which in turn drastically decrease the GDP of the country. This is in line with the works of Orimolade and Olusola (2018) which establishes that there exist a negative relationship between GDP and capital flight.
The findings from the second objective which formed the second hypothesis shows that the coefficient of illicit financial flow (X1) is -0.043301 which shows that a percentage increase in illicit financial flows caused by Corruption will lead to -0.043301 decrease in economic growth in Nigeria. This shows a negative relationship and it implies that when there is increase in corruption based on illicit financial flow will lead to decrease in GDP in Nigeria. This is in line with the findings in Arezki et al. (2014) which found evidence that capital flight decreases tax revenue and stock market development. As regards the third specific objective from where the third hypothesis is derived, the results show that the coefficient of illicit financial flows caused by international crime (X1) is -0.006675; which means that a percentage increase of illicit financial flows caused by international crime will lead to -0.006675 decrease in economic growth in Nigeria. This implies that the more the increase in financial international crime will lead to decrease in economic growth in Nigeria. This is also in line with the works of Orimolade and Olusola (2018) which establishes that there exist a negative relationship between GDP and capital flight.
Based on the findings of this study, conclusions can be drawn as follow:
Rising illicit financial flows via illegal commercial activities in Nigeria affect economic growths because it decreases the GDP of the country. Increase in illicit financial flows caused by corruption will lead to decrease in GDP in Nigeria. Increase in illicit financial flows via international crime will lead to decrease in economic growth in Nigeria. The study therefore recommends that the government should set a strong independent body that cannot be influenced by the government, government officials (serving and retired), rich multinational corporations with sole responsibility to tackle the menace of illicit financial flows in the country. Implementable policies and laws should be formulated and enacted by the government to nip in the bud this monster that has impoverished the economy and the society by extension.
Arezki, R., G.R. Graziosi and L.W. Senbet, 2014. Centre for international governance innovation Africa portal.
Asagunla Temitope Michael, 2018. Oil revenue and output growth in Nigeria. International Journal of Economics and Business Management, 4(6): 65-74.
Barnet, R.J. and J. Cavanagh, 1995. Global dreams: Imperial corporations and the new world order. Publisher: Simon and Schuster.
Bluestone, B. and B. Harrison, 1982. The deindustrialization of America. New York: Basic Books.
Feldman, M., T. Hadjimichael, L. Lanahan and T. Kemeny, 2016. The logic of economic development: A definition and model for investment. Environment and Planning C: Government and Policy, 34(1): 5-21.Available at: 10.1177/0263774x15614653.
Global Reporting Initiative, 2006. GRI Guidelines, economic indicator protocol, EC1, version 3.0, sivu 5.
Greider, W., 1997. Why the global economy needs worker rights. Journal of Labour and Society, 1(1): 32-44.Available at: https://doi.org/10.1111/j.1743-4580.1997.tb00005.x.
IMF, 1993. IMF’s data on FDI and Balance of Payments Manual 1993.
Kar, D. and C.-S. Devon, 2009. Illicit financial flows from developing countries 2002–2006. Global Financial Integrity. Available from www.gfip.org/storage/gfip/documents/executive - final version 05-14-09.pdf [Accessed August 2009].
Kofi Annan African Progress Report, 2013. Equity in extractives: Stewarding Africa's natural resources for all. A Report Presented in Africa Progress Panel held in Cape Town, South Africa on May 10, 2013.
NNPC Statistical Bulletin, 2014. 10-year crude production. 2014 Annual Statistical Bulletin. NNPC ASB 2014 1st Edition.
Orimolade, E.M. and A.E. Olusola, 2018. Capital flight and the growth of Nigerian economy: An autoregressive distributed lag (ARDL) modeling. IIARD International Journal of Economics and Business Management, 4(2): 1-15.
Paul, C., E. Kalu, C. Joseph and O. Hyacinth, 2015. The impact of capital flight on economic development: Nigeria in focus. British Journal of Economics, Management and Trade, 10(3): 1-13.Available at: https://doi.org/10.9734/bjemt/2015/20122.
Rabah, A., R.G. Gregoire and W.S. Lemma, 2014. African economic research. Consortium and University of Maryland (Senbet), CERDI-CNRS and FERDI (Rota-Graziosi).
Service Centre for Development Cooperation, 2010. Illegal Capital Flight from Developing Countries, Series. pp: 101.
Transparency International, 2019. Military involvement in oil theft in the Niger Delta. Available from https://ti-defence.org/publications/military-involvement-in-oil-theft-in-the-niger-delta/.
World Bank, 2015. The World Bank Group’s Response to Illicit Financial Flows: A Stocktaking, 2015.
Online Science Publishing is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use of the content. Any queries should be directed to the corresponding author of the article. |