دوره 9، شماره 33 - ( 7-1397 )                   سال9 شماره 33 صفحات 188-151 | برگشت به فهرست نسخه ها


XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

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-fa.html
برات‌زاده منیژه، هراتی جواد، لشکری محمد. بررسی عوامل مؤثر بر پول‌شویی مبتنی بر تجارت (TBML) در ایران: کاربرد الگوی جاذبه فرویدا. تحقیقات مدلسازی اقتصادی. 1397; 9 (33) :151-188

URL: http://jemr.khu.ac.ir/article-1-1482-fa.html


1- دانشگاه پیام نور مشهد
2- دانشگاه بجنورد ، j.herati@ub.ac.ir
چکیده:   (5712 مشاهده)
پول‌شویی عملی غیرقانونی است که درآمدهای ناشی از  فعالیت‌های خلاف قانون طی فرآیندی مشروعیت قانونی پیدا می‌کند.  پول‌شوئی مبتنی بر تجارت(TBML)   به عنوان یکی از جدیدترین و پیچیده‌ترین انواع پول‌شوئی دارای آثار زیانباری در همه عرصه‌های اقتصادی، اجتماعی و سیاسی جامعه است. هدف اصلی مطالعه حاضر بررسی عوامل مؤثر بر پول‌شویی مبتنی بر تجارت (TBML) در ایران با استفاده از الگوی جاذبه فرویدا است. برای این منظور با استفاده از یک الگوی داده‌های ترکیبی با اثرات تصادفی و داده‌های دوره 1999 تا 2012 به بررسی عوامل مؤثر بر پول‌شویی مبتنی بر تجارت ایران و برخی از شرکای تجاری آن پرداخته شده است. نتایج بیانگر آن است که بخش قابل توجهی از جریان پول¬شوئی مبتنی بر تجارت بین ایران و شرکای تجاری منتخب توسط عوامل بکار رفته در الگوی جاذبه فرویدا قابل توضیح است. براین اساس متغیرهای تولید ناخالص داخلی، حجم تجارت، متغیرهای جغرافیایی، فرهنگی و جمعیت و متغیرهای جذابیت دارای تاثیر معناداری بر حجم پول‌شوئی مبتنی بر تجارت ایران می¬باشند. بدین معنی با افزایش جریان تجارت، فرصت‌های پول‌شوئی از کانال تجارت که در آن پنهان است، نیز افزایش پیدا می‌کند. نتایج بدست آمده می‌تواند از نقطه نظر طراحی سیاست‌های مبارزه با پول‌شویی بویژه از کانال تجارت مورد توجه برنامه‌ریزان اقتصادی قرار گیرد.
متن کامل [PDF 1320 kb]   (2590 دریافت)    
نوع مطالعه: كاربردي | موضوع مقاله: تجارت و مالیه بین الملل
دریافت: 1396/10/19 | پذیرش: 1397/7/28 | انتشار: 1397/9/28

فهرست منابع
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]

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

ارسال پیام به نویسنده مسئول


بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به فصلنامه تحقیقات مدلسازی اقتصادی می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2024 CC BY-NC 4.0 | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb