دوره 11، شماره 40 - ( 4-1399 )
سال11 شماره 40 صفحات 122-99 |
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Maddah M, Sinaeyan M. The Empirical Analysis of Money Laundering Trend in Iran (by Using PLS-SEM Method ). jemr 2020; 11 (40) :99-122
URL: http://jemr.khu.ac.ir/article-1-2046-fa.html
URL: http://jemr.khu.ac.ir/article-1-2046-fa.html
مداح مجید، سینائیان مهلا. تحلیل تجربی روند پولشویی در ایران (رهیافت روش معادلات ساختاری مبتنی بر حداقل مربعات جزیی). تحقیقات مدلسازی اقتصادی. 1399; 11 (40) :99-122
مجید مداح* 
1، مهلا سینائیان2
1، مهلا سینائیان2
1- دانشگاه سمنان ، majid.maddah@semnan.ac.ir
2- دانشگاه سمنان
2- دانشگاه سمنان
چکیده: (4182 مشاهده)
پولشویی از طریق تضعیف اعتبار نهادهای مالی، اعتماد سرمایه¬گذاران به بازارهای مالی را کاهش می¬دهد و بی¬ثباتی سیاسی و انحراف در تخصیص منابع را تشدید می¬کند. در پولشویی منابع غیرقانونی به طور مخفیانه و دور از نظارت¬های رسمی وارد اقتصاد قانونی می¬شود که بر این اساس ماهیت پنهان دارد. این مقاله تلاش دارد تا با بررسی ابعاد مختلف پولشویی، تغییرات آن را در اقتصاد ایران در چارچوب ادبیات متغیرهای پنهان با استفاده از روش مدل¬سازی ساختاری با رویکرد حداقل مربعات جزیی (PLS-SEM) طی سال¬های 1360 تا 1396 به لحاظ تجربی بررسی کند. نتایج حاصل از مقاله نشان می¬دهد جرایم سرقت و قاچاق مواد مخدر اثر مثبت و معنی¬داری بر روند پولشویی دارند. همچنین شرایط اقتصادی می¬تواند انگیزه افراد را در ورود به فعالیت¬های غیر قانونی تحریک کند. علاوه بر آن رشد پولشویی همراه با کاهش تولید ناخالص داخلی و افزایش حجم پول نقد در جریان است که در نتیجه آن ثبات اقتصادی تضعیف می¬شود. طبق نتایج این تحقیق پولشویی در ایران روند صعودی دارد که در صورت رشد جرایم به ویژه قاچاق مواد مخدر، این روند ادامه خواهد یافت که بر بخش حقیقی اقتصاد اثر منفی دارد.
فهرست منابع
1. Aluko, A. & Bagheri, M. (2012). The impact of money laundering on economic and financial stability and on political development in developing countries. Journal of Money Laundering Control, 15(4), 442-457. [DOI:10.1108/13685201211266024]
2. Amroabadi Sadeghi, B., Googerdchian, A. & Shahbazi, N. (2012). Empirical analysis of money laundering shocks on economic growth, government expenditure and income inequality in IRAN. Strategic Research on Social Problems in Iran, 1(1), 97-111. (In Persian).
3. The Parliament of Islamic Republic of Iran, Anti-Money Laundering Amendment Act, 2019.1.23. (available at: https://rc.majlis.ir/fa/law/show/1107413). (In Persian).
4. Arab Mazar Yazdi, A. & Khodkari, L. (2007). Estimating dirty money in Iran. Journal of Economic Research, 27(7), 119-142. (In Persian).
5. Argentiero, A., Bagella, M. & Busato, F. (2008). Money laundering in a two-sector model: using theory for measurement. European Journal of Law and Economics, 26(3), 341-359. [DOI:10.1007/s10657-008-9074-6]
6. Blackburn, K., Neanidis, K. C. & Rana, M. P. (2017). A theory of organized crime, corruption and economic growth. Economic Theory Bulletin, 5(2), 227-245. [DOI:10.1007/s40505-017-0116-5]
7. Buchanan, B. (2004). Money laundering-a global obstacle. Research in International Business and Finance, 18(1), 115-127. [DOI:10.1016/j.ribaf.2004.02.001]
8. Buehn, A. & Schneider, F. (2013). A preliminary attempt to estimate the financial flows of transnational crime using the MIMIC method. In Research handbook on money laundering. Edward Elgar Publishing. [DOI:10.4337/9780857934000.00024]
9. Busato, F., Chiarini, B. & Di Maro, V. (2006). Using theory for measurement: an analysis of the underground economy. Aarhus University Department of Economics Working Paper. [DOI:10.2139/ssrn.1147615]
10. Chin, W., (1998).The partial least squares approach to structural equation modeling. In G.A. Marcoulides [Ed.]. Modern Methods for Business Research. Mahwah, NJ: Lawrence Erlbaum Associates, Publisher, 295-336.
11. Davari, A. & Rezazadeh. A. (2016). Structural equation modeling with PLS. Iranian Student Book Agency Press. (In Persian)
12. Dell'Anno, R. (2019). Corruption around the world: an analysis by partial least squares-structural equation modeling. Public Choice, 1-24.
13. Ebrahimi, S. & Ahangari. A. (2013). Estimated the index of crime in Iran using the fuzzy approach. Quarterly Journal of Quantitative Economics, 10(3), 139-163. (In Persian).
14. Feiz Bakhsh, R., Ghorbanzadeh, H. & Akbar Shahi, M. (2016). Money-laundering and its relation to organized crimes (drug trafficking). The Professional drug Studies, 8 (2829), 65-84. (In Persian).
15. Falahati, A., Nazari, S. & Poshtehkeshi, M. (2020). Institutional quality, natural resource rent, and shadow economy. Journal of Economic Modeling Research, 10 (39), 149-185 (In Persian).
16. Hair, J. F., Ringle, C. M. & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139-151. [DOI:10.2753/MTP1069-6679190202]
17. Henseler, J. & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565-580. [DOI:10.1007/s00180-012-0317-1]
18. Khajavi, M., Rezaei, E. & Khodaveisi, H. (2010). Estimating dirty money and examining its consequences in the Iranian economy: an application of the Bounds test approach. Quarterly Journal of Quantitative Economics, 7(4), 81-99. (In Persian).
19. Kumar, V. A. (2012). Money laundering: concept, significance and its impact. European Journal of Business and Management, 4(2).
20. Loayza, N., Villa, E. & Misas, M. (2019). Illicit activity and money laundering from an economic growth perspective: a model and an application to Colombia. Journal of Economic Behavior & Organization, 159, 442-487. [DOI:10.1016/j.jebo.2017.10.002]
21. Maddah, M. & Noe Iran, F. (2013). Estimating the value of informal economy in Iran based on environmental variables: The Kalman Filter approach. Journal of Economic Modeling Research, 3 (10):1-19 (In Persian).
22. Maddah, M. & Farahati, M. (2019). The empirical analysis of the direct effect of unemployment on the shadow economy in Iran (money demand approach). Journal of Economic Research, 54(2), 419-441. (In Persian).
23. Mohammed, S. A. S. A. (2020). Money laundering in selected emerging economies: is there a role for banks?. Journal of Money Laundering Control.
24. Poursalimi, M., Keikha, M. & Salmani, K. (2016). Innovating a modern model for estimating the amount of money laundering in Iran (the application of numerical and inverse problem methods in economy). Financial Monetary Economics, 23(11), 215-238. (In Persian).
25. Quintano, C. & Mazzocchi, P. (2018). Behind the GDP: some remarks on the shadow economy in mediterranean countries. European Journal of Law and Economics, 45(1), 147-173. [DOI:10.1007/s10657-014-9434-3]
26. Quirk, P. J. (1996). Macroeconomic implications of money laundering. Washington, Fondo Monetario Internacional, WP, 96, 66. [DOI:10.5089/9781451962123.001]
27. Reganati, F. & Oliva, M. (2018). Determinants of money laundering: evidence from Italian regions. Journal of Money Laundering Control. [DOI:10.1108/JMLC-09-2017-0052]
28. Riccardi, M. & Levi, M. (2018). Cash, crime and anti-money laundering. In The Palgrave Handbook of Criminal and Terrorism Financing Law (pp. 135-163). Palgrave Macmillan, Cham. [DOI:10.1007/978-3-319-64498-1_7]
29. Sahraian, M. (2003). Parts of money laundering findings in Iran. Majlis & Rahbord, 37, 337-368. (In Persian).
30. Schneider, F. (2008). Money laundering and financial means of organized crime: some preliminary empirical findings. Paolo Baffi Centre Research Paper, (2008-17). [DOI:10.2139/ssrn.1136149]
31. Schneider, F. (2010). Turnover of organized crime and money laundering: some preliminary empirical findings. Public choice, 144(3-4), 473-486. [DOI:10.1007/s11127-010-9676-8]
32. Taremi, M. H. (2009). Money laundering and its relationship with bribery. Pegah Hozeh, 262. (In Persian).
33. Walker, J. (1999). How big is global money laundering? Journal of Money Laundering Control. [DOI:10.1108/eb027208]
34. Yearwood, D. L. & Koinis, G. (2011). Revisiting property crime and economic conditions: an exploratory study to identify predictive indicators beyond unemployment rates. The Social Science Journal, 48(1), 145-158. [DOI:10.1016/j.soscij.2010.07.015]
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