A Study of Factors Affecting Iran’s Trade Base Money Laundering (TBML): (Ferwerda Gravity Model Application)

Bratzadeh, Manizheh; Harati, Javad; Lashkari, Mohammad

doi:10.29252/jemr.9.33.151

Volume 9, Issue 33 (10-2018) jemr 2018, 9(33): 151-188 | Back to browse issues page

‎ 10.29252/jemr.9.33.151

‎ 20.1001.1.22286454.1397.9.33.1.5

Mendeley

Zotero

RefWorks

Bratzadeh M, Harati J, Lashkari M. A Study of Factors Affecting Iran’s Trade Base Money Laundering (TBML): (Ferwerda Gravity Model Application). jemr 2018; 9 (33) :151-188
URL: http://jemr.khu.ac.ir/article-1-1482-en.html

A Study of Factors Affecting Iran’s Trade Base Money Laundering (TBML): (Ferwerda Gravity Model Application)

Manizheh Bratzadeh¹

, Javad Harati ^*

², Mohammad Lashkari¹

1- Payame Noor University, Mashhad
2- University of Bojnord , j.herati@ub.ac.ir

Abstract: (5641 Views)

Money laundering is an illegal practice that legitimizes the income from illegal activities during a legitimate process.Trade-based money laundering (TBML) as one of the newest and most complicated types of money laundering has negative effects on economic, social and political aspect of a society.The most important objective of the present study is to investigate the effect of various factors on trade based money laundering in Iran using the Ferwerda Gravity model.For this purpose the effective factors on trade base money laundering between iran and some selected trade partners are investigated by the use of a random effect model during the period 1999-2012. The results indicate that a great significant part of the trade based money laundering flow between Iran and selected trade partners can be explained by the the Ferwerda Gravity model. Accordingly, gorss doimestic product(GDP), trade volume, geographical, cultural, population and attractiveness variables have a significant effect on the amount of trade based money laundering in Iran.This means that with the increase in trade flow, money laundering opportunities resulted from the trade channel, that is hidden in it, will also increase. These results can be used by policy makers for designing policies to combat money laundering particularly coming from trade channel.

Keywords: Trade Base Money Laundering, Ferwerda Gravity Model, Panel Data.

Full-Text [PDF 1320 kb] (2565 Downloads)

Type of Study: Applicable | Subject: تجارت و مالیه بین الملل
Received: 2018/01/9 | Accepted: 2018/10/20 | Published: 2018/12/19

References

1.  Akbari, N. & Moalemi, M. (2005). Economic Integration in Persian Gulf Countries: A Spatial Econometrics Approach. Iranian Journal of Economic Research, 7 (25), 109-126. (in Persian)

2.  Alexander, K. (2001). The International Anti-Money-Laundering Regime: The Role of the Financial Action Task Force. Journal of Money Laundering Control, 4 )3(, 231-248. [DOI:10.1108/eb027276]

3.  -Anderson, J. E. (1979). A Theoretical Foundation for the Gravity Equation. American Economic Review, 69, 106-16.

4.  Ant-Abedini, J. & Mesgari, I. (2012). Estimating Bilateral Export Potentials of the Economic Cooperation Organization (ECO) in Non-Oil Industries, Journal of Economic Modeling Research, 2 (7), 75-96. . (in Persian)

5.  Asia/Pacific APG Typology Report (2012) on Trade Based Money Laundering, pp. 1-93.

6.  -Bergstrand, J. H. (1985). The Gravity Equation in International Trade: Some Microeconomic Foundations and Empirical Evidence. Review of Economics and Statistics, 67, 471-81. [DOI:10.2307/1925976]

7.  Bhagwati, J. N. (1967). Fiscal Policies, the Faking of Foreign Trade Declarations and the Balance of Payment. Bulletin of the Oxford University Institute of Statistics, February.

8.  Central Bank of Iran. (2010). Money Laundering, International Measures and Anti-Money Laundering Strategies, Management of the Whole Regulation, Licenses and Money Laundering. Anti Money Laundering Office, Expert Group International, Maryam Keshtkar, 1-41. (in Persian)

9.  Deardorff, A. (1998). Determinants of Bilateral Trade: Does Gravity Work in a Neoclassical World? In: Frankel, J.A. (Ed.), the Regionalization of the World Economy. University of Chicago Press, Chicago (Chapter 1).

10.  Ebrahi, S. & Sadeghnegad Naeeni, M. (2013). Criminal Analysis of Economic Crimes. Criminal Law Research, 2 (5), 147-174. (in Persian)

11.  FATF Annual Report (2003-04). Financial Action Task Force on Money Laundering, 1-26.

12.  - Financial Action Task Force. (2006). Trade Based Money Laundering, FATF Secretariat, 2rue André-Pascal, 75775 Paris Cedex 16, France Fax: +33 1 44 30 61 37 or www.fatf-gafi.org.

13.  FATF Repot. (2010). Money Laundering vulnerabilities of Free Trade Zones, 1-38.

14.  Ferwerda, J, Kattenberg, M, Chang, Unger, B, Loek Groot, J. & Bikker, A. (2013). Gravity Models of Trade-based Money Laundering. Applied Economics, 3170-3182, ISSN 0003-6846. [DOI:10.1080/00036846.2012.699190]

15.  -Gholami, A. (2006). Analysis of the Effects of Islamic Republic of Iran Trade Liberalization with Muslim Countries (Gravity Model Implications), Andisheh Sadeq Quarterly, Imam Sadiq University Research Center, 22, 30-45. (in Persian)

16.  Harati, J. Behrad Amin, M & Gahrazeh, S. (2015). A Study of the Factors Affecting Iran's Export (Gravity Model Application). Journal of Economic Modelling, 6(21), 29-46. (in Persian)

17.  Helpman, E. (1987). Imperfect Competition and International Trade: Evidence from Fourteen Industrialized Countries. Journal of the Japanese and International Economies, 1, 62-81 [DOI:10.1016/0889-1583(87)90027-X]

18.  Jalei, S, A. & Solemani, S. (2006). Economic Integration in Persian Gulf Countries; A Spatial Econometrics Approach, Iranian Journal of Economic Research, 7(25), 109-126. (in Persian)

19.  Kar, D. and LeBlanc, B. (2013). Illicit Financial Flows from Developing Countries 2002-2011, Washington, DC. [DOI:10.2139/ssrn.2335028]

20.  Karimi, Hesinjeh, H. (2006). Globalization, Economic Integrity and Commercial Potential: A Study of the Gravity Model in Iran's Business Analysis, Quarterly Journal OF New Economy & Commerce, 5, 118-143. (in Persian)

21.  Khodadeian, Chagani, Z. (2013). A Comparative Consideration of the Criminal Justice Systems of France & Iran in Confrontation with Economical Crimes, Journal of Legal Studies, 4 (2), 31-58. (in Persian)

22.  Lotfalipour, M. R., Shakeri, S. Z. & Bata, F. K. (2012). The Analysis of Economic Integration of Iran and Latin American Countries (An Application of Gravity Model), Economic Growth and Development Research, 1 (3), 73-98. (in Persian)

23.  Money Laundering Department. (2013). Post Bank of Iran, 7-116. (in Persian)

24.  Naheem, M. A. (2015). Trade Based Money Laundering: Towards a Working Definition for the Banking Sector. Journal of Money Laundring Control, 18 (4), 513-524. [DOI:10.1108/JMLC-01-2015-0002]

25.  Naheem, M. A. (2015). Money Laundering: A Primer for Banking Staff. International Journal of Disclosure and Governance advance online publication, 1-22. (in Persian)

26.  -Naheem, M, A. (20017). Trade Based Money Laundering: Exploring the Implications for International Banks, (Doctoral dissertation, University of Wolverhampton). (in Persian)

27.  Nasrolahi, Z. & Hakimi, N. (2016). Estimation of Money Laundering and its Impact on Consumption in Iranian Economy: Structural Model Approach Using Amos Graphics Software, Quarterly Journal of Quantitivr Economics, 12 (4), 135-157. (in Persian)

28.  Rahbar, F., Zalpour, G. & Mirzavand, F. (2003). Anti-money Laundering Study Design: Reviewing Money Laundering Rules in other Countries (2). Economic Survey Office, Reporting sequential number: 6693, Issue Code 410, 1-46. (in Persian)

29.  Sadeghi Amroabadi, B., Googerdchian, A. & Shahbazi, N. (2012). Empirical Analysis of Money Laundering Shocks on Economic Growth, Government Expenditure and Income Inequality in IRAN, 1 (1), 97-117. (in Persian)

30.  Schneider, F. (2006). Shadow Economies of 145 Countries All over the World: What Do We Really Know?" revised May 2006, available at http://www.econ.jku.at/ Schneider/ Shad Economy World145_2006.pdf.

31.  -Schneider, F. (2008). Money Laundering and Financial Means of Organized Crime: Some Preliminary Empirical Findings, Global Business and Economics Review, 10, 309-330. [DOI:10.1504/GBER.2008.019986]

32.  Soudijn, M .R. J. (2014). A Critical Approach to Trade-based Money Laundering. Journal of Money Laundering Control, 17(2), 230-242. [DOI:10.1108/JMLC-01-2013-0001]

33.  SWIFT Annual Report. (2004). SWEFT NET now the benefits really begin, 1-47.

34.  SWIFT Annual Review. (2011-12). Eexcellence Communities Innovation, 1-40.

35.  Strategic Research Center (2008). Types of Money Laundering and its Effects on the Economy, Scientific Committee on Justice and Economic Welfare, Report Code, 8-87-3-04, 1-34. (in Persian)

36.  Taebi, K. & Azarbaejani, K. (2001). A Study of the Trade Potential between Iran and Ukraine: An Application of Gravity Equatity Model. Iranian Journal of Trade Studies, 21, 61-82. (in Persian)

37.  Tanzi, V. (1997). Macroeconomic Implications of Money Laundering, in Responding to Money Laundering. International Perspectives, 91-104. Amsterdam: Harwood Academic Publishers.

38.  - Tashkini, A. & Sori, A. R (2013). Analyzing the Factors Affecting Iran Services Sector Intra-industry Trade with Regional Blocks. Journal of Economic Modeling Researc, 3 (10), 153-177. (in Persian)

39.  Thanasegaran, H. & Shanmugan, B. (2007). International Trade-Based Money Laundering: The Malasian Prespective. Journal of Money Laundering Control, 10 (4), 429-437. [DOI:10.1108/13685200710830916]

40.  Tinbergen, J. (1962). Shaping the World Economy: Suggestions for an International Economic Policy, Twentieth Century Fund, New York.

41.  Unger, Brigitte. )2007(. The Scale and Impact of Money Laundering. Cheltenham, UK: Edward Elgar [DOI:10.4337/9781781007624]

42.  Unger, B, Siegel, J, Ferwerda, J. Rusuioic, M, Wokke, K, de Kruijf. & W, Rawlings, G. (2006). The Amounts and The Effects of Money Laundering, Report for the ministry of Finance, Utrecht School of Economics, Vredenburg 138, 3511 BG Utrecht, Nederland, b. unger econ.uu.nl, (0031- (0) 30-253-9890).

43.  Unger, B. (2007). The Scale and Impacts of Money Laundering, Edward Elgar, Cheltenham, UK. [DOI:10.4337/9781781007624]

44.  Unger, B, & Den Hertog, J. (2012). Water Always Finds its Way: Identifying New Forms of Money Laundering, Crime Law Soc Change, 57, 287-304. [DOI:10.1007/s10611-011-9352-z]

45.  Walker, J. (1995). Estimates of the Extent of Money Laundering in and Throughout Australia, Report for the Australian Financial Intelligence Unit AUSTRAC.

46.  Walker, J. (1999). How Big is Global Money Laundering? Journal of Money Laundering Control, 3, 25-37. [DOI:10.1108/eb027208]

47.  Walker, J. & Unger, B. (2009). Measuring Global Money Laundering: The Walker Gravity Model. Review of Law and Economics, 5, 821-53. [DOI:10.2202/1555-5879.1418]

48.  Walker, J. (2007). How Big is Global Money Launderin. Journal of Money Laundering Control, 3(1), 25-37. [DOI:10.1108/eb027208]

49.  Walker, J. & Unger, B. (2009). Measuring Global Money Laundering: The Walker Gravity Model. Centre for Transnational Crime Prevention, University of Wollongong, NSW 2522, Australia; Brigitte Unger: Utrecht University School of Economics, BL Utrecht, The Netherlands, 821-853. [DOI:10.2202/1555-5879.1418]

50.  Yavari, K. and Ashrafzadeh, H. R. (2005). Economic Integration in Developing Countries, Application of Gravity Model with Panel Data Using GMM and Cointegration, Iranian Journal of Trade Studied, 36, 1-28. (in Persian)

51.  Zdanowicz, J.S (2009b), Trade-based Money Laundering and Terrorist Financing. Review of Law and Economics, 5, 855-878. [DOI:10.2202/1555-5879.1419]