Tax Evasion, Capital Flight and Growth of Developing Countries By AYANKENG GODSLOVE

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Tax Evasion, Capital Flight and Growth of Developing Countries (With the report of frequent tax evasion scandals in the world, Ayankeng Godlove N, University of Yaoundé II Soa explores, tax evasion in developing countries, the difference between financial fraud, which is illegal, and tax optimisation, which is a service to its customers and remains within the limits of the law; other authors’ perspectives of tax evasion, capital flight, the theories of Allingham and Sandmo models; and finally, my findings and conclusions)

By Ayankeng Godlove PhD Student & lecturer, Accounting, Management & Marketing University of Yaoundé II, Soa, Cameroon

ALL YOU SHOULD KNOW ABOUT TAX EVASION, CAPITAL FLIGHT, FINAINCIAL FRAUD AND GROWTH OF DEVELOPING COUNTRIES

Tax Evasion and Financial Fraud at a glance

This paper examines tax evasion, and emphasises the difference between financial fraud, which by definition is illegal, and tax optimisation, a service to its customers that remains within the limits of the law. In recent years, tax evasion has been on the forefront of the world’s debate. Over time, it has attracted supporters for the fight against the practice, which is widely considered as the illegal avoidance of taxes by individuals, corporations and trusts. In order to understand the concept better, this study describes tax evasion as the illegal evasion of taxes by individuals, corporations and trust and that, this activity goes to reduce states’ revenues which were meant for the provision of goods and services for the general public. Therefore, tax evasion happens when individuals, businesses or corporations fail to comply with their tax obligation. Tax evasion, can, therefore, be defined as a crime that adversely affects a nation’s economy and the tax morale of citizens by reducing the nation’s capacity to provide government services or manage its debt and by placing a disproportionate burden on those who pay their share [(Burman, 2003;Bajada and Schneider, 2005, pp 3-5; Kirchle 2007, p.24) as cited by Braithwaite, 2009, in crime and public policy, p.381]. The importance of tax concept cannot and should not be undermined, especially with its vital role in public financing. This is because taxes are part of government revenue, which contribute to the wellbeing of the economy. However, Corchon (1992) argues that the problem of tax evasion arises in an economy in which every taxpayer regards the output of the public sector as independent of its actions and the taxpayer can be audited by the public authority and fined, if found guilty. Thus, for a given activity, the choice is either to be on the legal side, or to become a member of the underground economy i.e. secret accounts in foreign countries, clandestine building, black markets, barter transactions, illegal gambling and prostitution, secret workshops: shoes, garments, leather, and furniture; street vendors, 'gypsy' cabs, rental of spare rooms. In all these situations the parties concerned have no incentive to provide information to the competent authorities concerned. This lack of incentive is particularly severe in the case where workers involved are receiving unemployment benefits. But it is worth noting that tax avoidance and evasion are prevalent in all countries and tax structures are undoubtedly skewed by this


2 reality. Because of this, standard models of taxation and their conclusions must reflect these realities. In recent times, reports on worldwide tax fraud and illicit global financial flows have been appearing more and more frequently and in spite of the attention which such revelations attract, the international community is still far from an effective system of control. Braithwaite 2009 cited (Burman, 2003; Bajada and Schneider, 2005; Kirchler, 2007) that, tax evasion is a crime that adversely affects a nation’s economy and the tax morale of the citizens by reducing the nation’s capacity to provide government services or manage its debts and by placing a disproportionate burden on those who pay their share. It can be inferred; therefore that tax evasion has political, as well as, economic significance especially when there is a high level of a threat to a society’s economic security, political stability and social capital. In addition, financial institutions all over the world have an important function in the fight against suspicious transactions, tax evasion and money-laundering practices, but most often; institutions in bordering countries fail in their duty to do so. By this failure, they – banks especially international banks, participate in the tax evasion and avoidance mechanism of individuals and multinational corporations. Many governments find it concerning the decline in tax revenue despite the increased international tax planning. According to some scholars, some governments’ frenzied attacks against offshore havens is due to greed and the fear of seeing their deep pockets depleted. Some other schools of thoughts believe that international crime or offshore money launderings not the problem. They believe that it is the increased use of offshore tax free companies and secretive offshore banking by the general populace that is a major headache for the avaricious high-tax regimes. Effects of financial crime According to Bokosi and Chikumba (2015) in their presentation to the African Civil Society, they illustrated that the global economic crisis revealed the risks African economies face on depending too much on debt financing, official development assistance and foreign direct investment. While the crisis shifted attention towards the need for greater domestic resource mobilisation, Sub-Saharan African countries still mobilise less than 17 percent of their gross domestic product in tax revenues. They found that this was due to illicit financial flows – money that is illegally earned illegally transferred or illegally utilized – and limited capacity for collecting revenues from multinational companies, particularly those engaged in natural-resource extraction. They claimed that the financial leakages amounted to official development assistance ofUS$528.9 billion over the decade ending in 2012, compared to US$348.2 billion in 2002. The illicit resource outflows reduce the total development resource base. This forces governments to plug the gap with higher taxes that disproportionately fall on the poorest in society, as well as austerity measures that constrain the provision of public goods and services. Beyond this, the illegality of illicit financial flows is damaging to the state, as these flows are aided by bribery and theft, which ultimately undermine governance institutions. According to Braithwaite (2005), although corporations and the public may be at odds with their “rightful” contributions to the tax system, the reality is that many companies do not pay any tax. Therefore, most member nations of the Organisation for Economic co-operation and Development countries (hereafter referred to as OECD), have seen a significant drop in the proportion of revenue collection through company tax. This is because of the global tax planning by large corporations. It can also be argued rightly that this is one of the reasons that international forums and major economies such as the G20, G8, European Union (EU), OECD and other international organisations advocating for more international cooperation and control in this area, have found it difficult to implement the related resolutions (Haldenwang & Kerkow, 2013). It can also be argued that because of enterprise, tax evasion and avoidance have gone a long way to distorting the revenue of the government, thereby causing the implementation of taxation to be complicated for states. Wherever and whenever authorities decide to levy taxes, individuals and firms try to avoid paying them. Though this problem has always been present, it becomes more


3 pressing in the face of globalization as this process extends the range of opportunities to circumvent

PERSPECTIVES OF OTHER WRITERS Some authors of studies and books on tax evasion and avoidance, and who expanded on the theories of Allingham and Sandmo model will be discussed in this section and they include: Clotfelter (1983), Dubin and Wilde (1988) Feinstein (1991). This section will also discuss other authors, such as, Braithwaite (2009), Johannesen and Zucman (2014), Coechon (1992), Slemrod (2004). They wrote on tax evasion and avoidance, and how it affects the revenue collection and the impact on governments’ activities. As already stated, tax evasion happens when individuals, businesses or corporations fail to comply with their tax obligation. Tax evasion, however, is a vast topic, a phenomenon that is complex and here to stay. But researches, such as Allingham and Sandmo are helping us to understand this phenomenon and how to develop further research. We have noticed that since Michael Allingham and Agnar Sandmo launched their modern analysis on tax evasion in 1972 there has been an explosion in this field of research. James Alm (2012) assesses the learnings about tax evasion that have been acquired since Michael Allingham and Agnar Sandmo launched the modern analysis of tax evasion in 1972. Alm focuses on three specific questions and the answers to these questions that have emerged over the years: • First, how do we measure the extent of evasion? • Second, how can we explain these patterns of behaviour? • Third, how can we use these insights to control evasion? There are still many unanswered questions that need further research such as: How much evasion really occurs nationally and locally? Do higher tax rates encourage/discourage compliance? How effective are penalty rates? What about audit rates and targeted, announced audit programs? What is the actual magnitude of any individual response? What are costs versus benefits of policies? What are distributional effects of evasion, and of policies to reduce evasion? On their own part, E. Kirchler, B. Maciejovsky, F. Schneider, (2001) looked at tax evasion from an economic point of view. They argued that legal considerations apart, tax avoidance, tax evasion and tax flight have similar effects, such as a reduction of revenue yields, which are based on the same desire to reduce the tax burden. The legal differences and moral concerns mean that individuals may perceive them as different and as unequally fair. The results indicate that everyday representations differ with respect to tax avoidance, tax evasion, and tax flight. While tax evasion was perceived negatively, tax flight was perceived neutrally, and tax avoidance was perceived positively. It could be shown that despite that tax avoidance, tax evasion, and tax flight lead to similar effects on revenue yields, taxpayers discriminate between them and evaluate them differently. Moreover, it could be shown that these evaluations depend, for instance, on personal affectedness, experience, profession, and knowledge. Luigi Alberto Franzoni (1999) offers an overview of the theoretical and empirical research on tax evasion, delineating the variety of factors affecting noncompliance and examining possible remedies. Particular emphasis is placed on the institutional and procedural rules governing the tax enforcement policy. It cannot be overstated that tax evasion is a complex phenomenon that cannot be eradicated by marginal changes in enforcement practice. The empirical evidence suggests that a stricter enforcement regime is likely to induce greater compliance - the key variable here is the probability of detection. Alex Cobham (2005) considers the effects of tax avoidance and evasion on the financing of development. He argues that although funding for new aid commitments is important, sustainable development requires developing states to approach fiscal independence, and that the annual revenue cost of tax leakages is well in excess of aid flows. Firstly, he surveys the structure of tax systems in rich and poor regions of the world and developments during the last three decades; then he sets out a simple model of all leakages, and uses existing work and new data to generate the first comprehensive estimate of the cost to developing countries in revenues foregone.


4 Joel Slemrod (2007) reviews what is known about the magnitude, nature, and determinants of tax evasion, with an emphasis on the U.S. income tax. Alm (1999), Andreoni, Erard, and Feinstein (1998), and Slemrod and Yitzhaki (2002) offer more comprehensive recent reviews of the literature. Slemrod then places this information into a conceptual and policy context. In conclusion, Slemrod found that the stark differences in compliance rates across taxable items that line up closely with detection rates suggest strongly that deterrence is a powerful factor in evasion decisions. The overall net noncompliance rate for all U.S. federal taxes and the individual income tax seems to stand at about 14 percent. No other country has as much information on tax evasion as does the United States. This makes it difficult to compare information from the U.S with other countries. Channels of lost revenues Luigi Alberto Franzoni (1999) uses empirical evidence to support his paper. E. Kirchler, B. Maciejovsky, F. Schneider, (2001) used Overall, 252 fiscal officers, business students, business lawyers, and entrepreneurs produced spontaneous associations to a scenario either describing tax avoidance, tax evasion, or tax flight, and evaluated them as positive, neutral or negative. James Alm (2012) focused on three specific questions. First, how do we measure the extent of evasion? Second, how can we explain these patterns of behaviour? Third, how can we use these insights to control evasion?

MY FINDINGS Pilot test for validation and reliability of instrument and data analysis Data analysis: Data analysis for this study involved two major steps: the data reduction process and the structural relationship analysis. The data reduction process aimed to reduce the number of variables and parameters in the research model to a manageable number in terms of the ratio between sample size and parameters estimated in the structural equation modelling (SEM). The structural relationship analysis was used to examine the simultaneous relationship between TQM and organizational performance. Data reduction process The data reduction process was conducted in order to reduce the constructs employed in this study into composite variables. Three (3) constructs (illicit hot money outflows, trade misinvoiving outflows and trade misinvoincing inflow) constituted illicit financial flow variables, and 4 constructs (gross domestic product, trade, foreign direct investment and official development assistance). These 3 constructs were subjected to validity and reliability tests before a single score could be calculated to represent each construct. Confirmatory Factor Analysis (CFA) using SPSS P20 was employed for examining construct validity of each scale by assessing how well the individual item measured the scale. During this process, 2 items of illicit financial flows and 4 items of economic growth were retained. The goodness of fit indices (GFI) of the 2 constructs reached the 0.9% criterion that is required in establishing the construct validity. The reliability analysis was conducted by calculating the Cronbach’s alpha for each scale. The result shows that the Cronbach’s alpha measure for the constructs did not exceed the threshold point of 0.7 suggested by Nunnally (1967), but were at least 57% and this is encouraging given that the constructs are still in the exploratory stage. The final results of construct validity and reliability tests of the constructs are reported in this work. Having met the requirement of construct validity and reliability, the composite measure of each construct can be measured by calculating their mean values (Hair et al., 1998)


5 Population, sample size and sampling method of the study Population of the study The study population is the aggregation of element from which the sample is actually selected. It is the aggregation or the totality of all members or units from which information could be obtained (Rubin and Babbie, 2001). Sample size and sampling method The research data was obtained from all the developing countries of the world. The focus of this study was limited to the information collected from the World Bank. Data collection method The researcher’s data collection methods were both primary and secondary. The sources of secondary information were mainly from the World Bank. The Extraction Process Of The Independent Variables And The Determination Of KMO Test. Extraction refers to the process of determining how many factors best explain the observed co variation matrix within the data set. The study found that all factors, except one, were positively correlated with each other at the significance level of �< 0.01. Total Variance Explained Component Initial Eigenvalues Total % of Variance 1 1.453 48.447 2 1.115 37.169 3 .432 14.384

Extraction Sums of Squared Loadings Cumulative % Total % of Variance Cumulative % 48.447 1.453 48.447 48.447 85.616 1.115 37.169 85.616 100.000

Extraction Method: Principal Component Analysis. KMO & Bartlett’s Test KMO & Bartlett’s Test of Sphericity is a measure of sampling adequacy that is recommended to check the ratio of the variable for the analysis being conducted. In most academic and business studies, KMO & Bartlett’s test play an important role for accepting the sample adequacy. While the KMO ranges from 0 to 1, an index of over 0.5 is widely accepted. There was a significant level at 0.000 which is less than 0.05, and in turn this denotes that the data is adequate. KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Approx. Chi-Square Bartlett's Test of Sphericity Df Sig.

.385 607.423 3 .000

Regional Analysis of the trend The table above shows that the highest cause of outflow is trade misinvoicing. The Asian region registered the highest amount by far in illicit outflows from 2003 to 2012.It was followed by developing Europe, Sub-Saharan Africa. This picture would be different if I look at the growth


6 rates of illicit financial flow per region. The MENA region registered the highest growth rate by far in illicit outflows from 2003 to 2012, at 24.2 percent per annum. It was followed by Sub-Saharan Africa at 13.2 percent, developing Europe at 9.8 percent, Asia at 9.5 percent, and the Western Hemisphere at 3.5 percent. The high rate of growth witnessed in the MENA can be attributed to the rise in oil prices that occurred over this time period.

Descriptive Statistics

IFF GDP TDE FDI ODA

Mean

Std. Deviation

N

13.100 340.280 18.3200 11.320 1.540

8.3271 234.5827 12.66420 8.1435 1.1589

5 5 5 5 5

Correlations IFF GDP TDE FDI ODA

IFF 1 .985** **

.970 .996** -.196

GDP

TDE

FDI

ODA

1 .966** -.202

1 -.269

1

1 .952** .979** -.259

The table above clarifies the correlation coefficients for each field, the average of the part and correlation coefficients denoted significance at (0.01, 0.05), which means a content reliability for what is being measured **. Correlation is significant at the 0.01 level (2-tailed). Determination of Cronbach’s Alpha: Cronbach's alpha can be written as a function of the number of test items and the average intercorrelation among the items. Reliability Statistics Cronbach's Alpha

.247

Cronbach's Alpha Based on Standardized Items

N of Items

.829

5

The table above gives the Cronbach’s alpha values for the variables in the research model. The standardized factor loadings were 0.829 greater than 0.591 thresholds. This means that construct validity of the measures were satisfied. Cronbach’s alpha values of the factors were high. This showed that all illicit financial flows and growth factors had acceptable reliabilities. It also indicates that the regression model predicts the outcome variable


7 significantly well. Looking at the "Regression" row and going to the Sig. column we see that, p< 0.006, which is less than 0.05, and indicates that, overall, the model applied can statistically significantly predict the outcome variable. ANOVA with Cochran's Test Sum of Squares Between People 55165.086 Between Items 434254.730 Within People Residual 166140.570 Total 600395.300 Total 655560.386

df

Mean Square Cochran's Q

4 4 16 20 24

13791.272 108563.683 10383.786 30019.765 27315.016

14.466

Sig

.006

Testing the significance of the models Model one: Economic growth (YEG) and illicit financial flows Determination of the model Summary: Model Summary Model

R

R Square

Adjusted R Square

1

.995a

.991

.987

Std. Error of the Estimate 30.1892

a. Predictors: (Constant), GER, HMN This table provides the R, R2, adjusted R2, and the standard error of the estimate, which can be used to determine how well a regression model fits the data: The "R" column represents the value of R, which is the multiple correlation coefficient and it is considered to be a measure of the quality of the prediction of the dependent variable and in this case of illicit financial flows, a value of 0.995 indicates a good level of prediction. The "R Square" column represents the R2 value (also called the coefficient of determination), which is the proportion of variance in the dependent variable that can be explained by the independent variables (technically, it is the proportion of variation accounted for by the regression model). This therefore means that our value of 0.991 of the independent variables explains 99.5% of the variability of our dependent variable which is the gross domestic variable. ANOVAa Model

Sum of Squares

Regression 4491370.105 1 Residual 92916.511 Total 4584286.616 a. Dependent Variable: GDP b. Predictors: (Constant), GER, HMN

df

Mean Square

F

Sig.

2 89 91

2245685.052 1048.719

2141.360

.000b

Statistical significance The F-ratio in the ANOVA table above tests whether the overall regression model is a good fit for the data. The table shows that the independent variables statistically significantly predict the dependent variable,


8 F (2.5) = 259.115, p=0.000< .0005. This shows that the regression model is a good fit of the data. Thus the means are significantly different and we decide that the effects are real. Connecting the dots – Where is the highest capital flight and what are the policy implication? In this study, I analysed the impact of capital flight on the GDP growth in the developing countries and countries in transition. For this purpose, we used a recently computed data on estimates of capital flight that was performed by the members of the Global Financial Integrity Project. I found that capital flight does negatively affect the economic growth and the significance of the estimate comes at a question. This impact has a country-individual origin, which motivated us to use fixed effect estimation procedure. However, after controlling for years, I find that the effect of capital flight is significant. In conclusion, the dynamic of Capital Flight to GDP ratio, we see that MENA region has higher level of Capital Flight. This was also constantly growing during the period under study. It is also important to note, that in the last year of analysis, Capital Flight to GDP ratio also greatly increased for Europe and Western Hemisphere. It is also seen that Asia exhibits the most evident link between capital flight and GDP per capita growth


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REFERENCES N. johannessen and G. Zucman, (2014), “The end of Bank secrecy?An evaluation of the G20 tax haven crackdown,” American economic journal, Economic policy, 2014. Braithwaite, (2009), “Chapter 15: Tax evasion,” The Oxford handbook of crime and public policy, edited by Michael. M. Gillman and M. Kejak, (2005), “Accounting for corruption: the effect of tax evasion and inflation on growth,” Preliminary Version J. Slemood and S. Yitzhaki, (2002), “Tax avoidance, evasion and administration,” Handbook of Public Economics, Volume 3, by A. J. Auerbach and M. Feldstein. R. Gordon and A. Morriss, (2014), “Moving money: international financial flows, taxes, and money laundering,” 37 Hastings international and comparative law review 1. L. Corchon, (1992), “Tax evasion and the Underground economy,” European Journal of Political Economy, October 1992, Vol.8, No 3, p445 – 454. Cowell, F.A., 1985, The economics of tax evasion; a survey, Bulletin of Economic Research 37, 163-193. Howard Stein (May 1999), “Globalization, Adjustment and the Structural Transformation of African Economies: The Role of International Financial Institution,” CSGR Working paper No32/99 Enrique G. M and Vincenzo Q, (March 25, 2009), “Financial Globalization, Financial Crises and Contagion” J. Rajotte, (May, 2013), “Tax evasion and the use of tax havens,” Report of the Standing Committee on Finance, 41st Parliament, first session, House of Commons, Canada.


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