Abstract and Introduction of 'Illicit Financial Flows From Africa: Hidden Resource For Development

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  • 7/31/2019 Abstract and Introduction of 'Illicit Financial Flows From Africa: Hidden Resource For Development'

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    A PROGRAM OF THE CENTER FOR INTERNATIONAL POLICY

    Illicit Financial Flows from Africa:Hidden Resource for Development

    Prepared by Dev Kar and Devon Cartwright-Smith1

    ABSTRACT

    This paper presents an analysis o the volume and pattern o illicit nancial fows rom Arican countries over a

    39-year period rom 1970 to 2008. The paper makes a contribution given that existing research on long-term

    trends in the pattern o illicit fows rom Arican countries is rather scanty. The classication o Arican countries

    used in this paper diers rom that in the IMFs World Economic Outlook; here, Egypt and Libya (members o

    the Arican Union) are included under North Arica while the group o CFA Franc countries is distributed along

    a geographical basis. The paper presents estimates o illicit nancial fows rom Arica and its various regions and

    economic groupings during the 1970s, 1980s, 1990s, and the most recent nine-year period 2000-2008 or which

    data are available. We nd that illicit fows have not only grown on a decennial basis, cumulatively they have cometo ar exceed the continents outstanding external debt at the end o 2008. The statistical analysis o long-term trends

    brings out some interesting regional disparities in the pattern and growth o such fows. Utilizing the World Bank

    Residual model and the IMF Direction o Trade Statistics, illicit outfows rom Arica across the 39-year period

    are estimated at US$854 billion. The authors point out that data limitation signicantly understates the problem.

    Making various adjustments to the estimate suggests that the volume o illicit fows over the period 1970 to 2008

    may be closer to US$1.8 trillion. We argue that this staggering loss o capital seriously hampers Aricas eorts at

    poverty alleviation and economic development.

    1 Dev Kar, ormerly a Senior Economist at the International Monetary Fund (IMF), is Lead Economist atGlobal Financial Integrity (GFI) at the Center or International Policy, Washington DC, and Devon Cartwright-Smith is an Economist at GFI. The authors thank Raymond Baker and other sta at GFI or helpul comments.Thanks are also due to the sta o the IMFs Statistics Department or their assistance with balance o paymentsdata. Any errors that remain are the authors responsibility. The authors would welcome comments; citations shouldreer to a Working Paper o Global Financial Integrity, a Program o the Center or International Policy (CIP). Theviews expressed herein are those o the authors and do not necessarily refect those o CIP or its board.

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    6 | G L O B A L F I N A N C I A L I N T E G R I T Y

    I. Introduction

    The problem o illicit fows rom Arica deserves serious consideration. As Governor Ndungu (2007) o the

    Central Bank o Kenya noted in his keynote address at a policy seminar o Governors o Arican central banks:

    q

    The costs o this nancial hemorrhage have been signicant or Arican countries. In the shortrun, massive capital outfows and drainage o national savings have undermined growth by

    stifing private capital ormation. In the medium to long term, delayed investments in support

    o capital ormation and expansion have caused the tax base to remain narrow. Naturally and

    to the extent that capital fight may encourage external borrowing, debt service payments also

    increased and urther compromised public investment prospects. Furthermore, capital fight

    has had adverse welare and distributional consequences on the overwhelming majority o

    poor in numerous countries in that it heightened income inequality and jeopardized employment

    prospects. In the majority o countries in the sub-region, unemployment rates have remained

    exceedingly high in the absence o investment and industrial expansion.

    qA recent study produced by Global Financial Integrity (GFI) estimates illicit nancial fows out o all developing

    countries at $858 billion to $1.06 trillion a year. Among developing countries, Arica presents the most analytical

    diculties because countries with inadequate data account or nearly 37 percent o regional GDP.2 One thing

    is certain: while Arican countries have had to shoulder a heavy debt burden, a number o researchers such as

    Ndikumana and Boyce (2008), have shown that sustained illicit outfows have turned the continent into a net

    creditor to the rest o the world.

    Seminal research at GFI on the absorption o illicit unds (orthcoming) show that while some o the private

    assets held outside their countries by developing country nationals may be legitimate, the bulk o such unds are

    certainly not. This is because estimates o illicit capital outfows provided by economic models such as the WorldBank Residual model and the Trade Misinvoicing model (see Section II or a brie description) account or the bulk

    o deposits reported by banks to the Bank or International Settlements (BIS) and by oshore nancial centers.

    The purpose o this paper is not to explain the actors that drive illicit nancial fows or to carry out a series o

    econometric tests seeking to determine their signicance. There is a wealth o existing research on these subjects.

    Rather, we analyze the long-term evolution o illicit fows rom the continent and its various regional and economic

    groupings. Thereby, we shed light on how such fows have aected particular groups o countries in terms o the size

    o regional economies, populations, and infows o ocial development assistance. Such an exercise has not been

    carried out or Arican countries. In presenting this discussion o long-term trends in regional illicit fows, we also

    point out certain common pitalls in data interpretation.

    2 See, Illicit Financial Flows from Developing Countries: 2002-2006, Dev Kar and Devon Cartwright-Smith,Global Financial Integrity, December 2008, Washington DC.

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    The paper is organized as ollows. Section II presents a brie description o the two main economic models

    used to estimate illicit fowsthe World Bank Residual model and the Trade Misinvoicing model based on the

    IMFs Direction o Trade Statistics. We then explain the methodology and the rationale underlying the treatment

    o estimates with reerence to the traditional method used in past studies. Section III presents a discussion o the

    long-term evolution o illicit fows starting with the 1970s through the 1980s, 1990s, and the 9-year period 2000-

    2008. Then we draw out certain dominant regional patterns, ranking countries in terms o the volume o outfows

    and comparing the results to a recent study by Ndikumana and Boyce (2008). Section IV presents a method to

    correct or data inadequacies and gaps which understate illicit fows rom developing countries. Note that we do notaccount or illicit fows generated due to smuggling, violations o intellectual property rights, trade in narcotics and

    other contraband goods, human tracking, sex trade, and other illegal activities as they are outside the scope o this

    study. Section V discusses the development impact o illicit fows. Finally, Section VI presents the main conclusions

    o the paper.

    II. Models of Illicit Financial Flows

    Illicit money is money that is illegally earned, transerred, or utilized. I it breaks laws in its origin, movement, oruse it merits the label.

    Flight capital takes two orms. The legal component stays on the books o the entity or individual making the

    outward transer. The illegal component is intended to disappear rom records in the country rom which it comes.

    By ar the greatest part o unrecorded fows are indeed illicit, violating the national criminal and civil codes, tax laws,

    customs regulations, VAT assessments, exchange control requirements, or banking regulations o the countries out

    o which the unrecorded/illicit fows occur.

    There are two main channels through which illicit capital, unrecorded in ocial statistics, can leave a country.

    The World Bank Residual model captures the rst channel through which illicit capital leaves a country through

    its external accounts. The second type o illicit fows, generated through the mispricing o trade transactions, iscaptured by the Trade Misinvoicing model which uses IMF Direction o Trade Statistics.

    Specically, the World Bank Residual model compares a countrys source o unds with its recorded use o unds.

    Sources o undsthe countries infows o capitalinclude increases in net external indebtedness o the public

    sector and the net infow o oreign direct investment. The net external indebtedness is derived by calculating

    the change in the stock o external debt which was obtained rom the World Banks Global Development Finance

    database. Use o unds includes nancing the current account decit and additions to central bank reserves. Both

    these data series along with data on oreign direct investment were obtained rom the IMF Balance o Payments

    database. According to the model, whenever a countrys source o unds exceeds its recorded use o unds, the

    residual comprises unaccounted-or, and hence illicit, capital outfows.

    Trade misinvoicing has long been recognized as a major conduit or illicit nancial fows. By overpricing importsand underpricing exports on customs documents, residents can illegally transer money abroad. To estimate trade

    misinvoicing, a developing countrys exports to the world are compared to what the world reports as having imported

    rom that country, ater adjusting or insurance and reight. Additionally, a countrys imports rom the world are

    compared to what the world reports as having exported to that country. Discrepancies in partner-country trade data,

    ater adjusting or insurance and reight, indicate misinvoicing. However, note that this method only captures illicit

    transer o und abroad through customs re-invoicing; IMF Direction o Trade Statistics cannot capture mispricing

    that is conducted on the same customs invoice (or which we make an adjustment in Section IV).