ORIGINAL_ARTICLE
The Investigating the Role of Institutional Quality on Development of Medical Tourism Industry in Iran: Gravitational Search Algorithm and Firefly Algorithm
On one hand, countries dependent on oil revenue have reached the conclusion that oil cannot be a reliable source of income and the oil dependent economy has become a major challenge for oil-exporting countries. On the other hand, in recent years tourism has become one of the most dynamic sectors of global economy and income from different capacities of the tourism industry is sought to replace the income from oil sales. Medical tourism is one of the important areas of the tourism industry. In this study, the effect of institutional indicators on medical tourism in Iran have been investigated using an optimization approach. The results of the study indicate that, Improvement in institutional quality index, gross fixed capital investment in public and private hospitals, gross fixed capital in tourism services, as well as an increase in the number of service providers to medical tourists, including general practitioners and specialists, and an decrease in real effective exchange rates in Iran has led to an increase in the attraction of medical tourists to the country.
https://ecoj.tabrizu.ac.ir/article_8223_d4aabda730a75ec5aecdce416bd74574.pdf
2019-01-21
1
30
Medical Tourism
Institutional Quality
Gravitational Search Algorithm
Firefly Algorithm
Nina
Mirani
nina_mirani2003@yahoo.com
1
Ph.D. Candidate in Economics, University of Tabriz
AUTHOR
Ahmad
Assadzadeh
assadzadeh@gmail.com
2
Associate Professor of Economics, University of Tabriz
LEAD_AUTHOR
حقیقی کفاش، مهدی، ضیایی، محمود و جعفری، قاسم (1384). اولویتبندی عوامل مربوط به توسعه گردشگری درمانی ایران. فصلنامه مطالعات مدیریت گردشگری، 4(11و12)، 23-40.
1
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2
دلگشایی، بهرام، جباری، علیرضا، فرزین، محمدرضا، شعربافچی زاده، نسرین و طبیبی، سیدجمالالدین (1391). وضعیت موجود گردشگری پزشکی: مطالعه موردی ایران. فصلنامه پایش، 11(2)، 171-179.
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5
گودرزی، مجید، تقوایی، مسعود و زنگیآبادی، علی (1392). توسعه گردشگری پزشکی داخلی در شهر شیراز. مطالعات مدیریت گردشگری، 11(4)، 485-496.
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Delgoshaie, Bhram, Jabbari, Alireza, Farzin, Mohammad Reza, Sherbafchizadeg, Nasrin & Tabibi, Seyed Jamalaldin (2012). Medical tourism in Iran: A case study. Payesh Journal, 11(2), 171-179 (In Persian).
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49
ORIGINAL_ARTICLE
Portfolio Optimization Using Three-Objective Particle Swarm Optimization
In optimizing the portfolio, the main issue is the optimal selection of assets that can be bought with a certain amount of money. Although risk minimizing and revenue maximizing on investment seems simple, but in practice several approaches have been proposed for an optimal portfolio. In 1950, Harry Marquitz introduced his model in which proposed the optimization of the asset basket as a quadratic programing model with the aim of minimizing the variance of the asset set, provided that the expected return equals a constant value. In this research, the problem of three-objective optimization (i.e., maximizing stock returns, minimizing its risk and the third objective function, namely minimizing the number of assets) has been studied. Accordingly, investors, with admission a small amount of risk and a similar amount of return, will choose a basket of less assets. For this purpose, at first, genetic algorithms and multi- Particle Swarm Optimization algorithm were used to estimate the two-objective model of minimum variance and maximum return for better algorithm identification. Then, with regard to the better performance of the algorithm, this algorithm was used to estimate the three-objective model for maximizing stock returns, minimizing risk, and minimizing the number of assets.
https://ecoj.tabrizu.ac.ir/article_8079_ea07a01c908401a7196c5034333ae957.pdf
2019-01-21
31
52
Portfoloio Optimization
Marquitz Model
MOPSO Algorithm
NSGA2 Algorithm
Asaad
Alahrezaee
alahrezaee1982@gmail.com
1
Ph.D. Candidate in Economics, Razi University
AUTHOR
Ali
Falahati
ali.falahatii96@gmail.com
2
Associate Professor of Economics, Razi University
LEAD_AUTHOR
Kiomars
Sohaili
qsoheily@yahoo.com
3
Associate Professor of Economics, Razi University
AUTHOR
اصغرپور، حسین، و رضازاده، علی (1394). تعیین سبد بهینه سهام با استفاده از روش ارزش در معرض خطر. فصلنامه نظریههای کاربردی اقتصاد،، 2(4)، 93-118.
1
راعی، رضا، و پویانفر، احمد (1390). مدیریت سرمایهگذاری پیشرفته. ﺗﻬﺮان. ﺳﺎزﻣﺎن ﻣﻄﺎﻟﻌﻪ و ﺗﺪوﻳﻦ ﻛﺘﺐ ﻋﻠﻮم اﻧﺴﺎﻧﻲ داﻧﺸﮕﺎهﻫﺎ (ﺳﻤﺖ).
2
راﻋﻲ، رﺿﺎ، و ﺗﻠﻨﮕﻲ، اﺣﻤﺪ (1383). ﻣﺪﻳﺮﻳﺖ ﺳﺮﻣﺎﻳﻪﮔﺬاری ﭘﻴﺸﺮﻓﺘﻪ. ﺗﻬﺮان: ﺳﺎزﻣﺎن ﻣﻄﺎﻟﻌﻪ و ﺗﺪوﻳﻦ ﻛﺘﺐ ﻋﻠﻮم اﻧﺴﺎﻧﻲ داﻧﺸﮕﺎهﻫﺎ (ﺳﻤﺖ)، 105-142.
3
رجبی، مهسا و خالوزاده، حمید (1393). ﻣﻘﺎﻳﺴﺔ ﺑﻬﻴﻨﻪﺳﺎزی ﺳﺒﺪ ﺳﻬﺎم در ﺑﻮرس اوراق ﺑﻬﺎدار ﺗﻬﺮان ﺑﺎ ﺑﻬﺮهﻣﻨﺪی از اﻟﮕﻮرﻳﺘﻢﻫﺎی ﺑﻬﻴﻨﻪﺳﺎزی ﭼﻨﺪﻫﺪﻓﻪ ﺗﻜﺎﻣﻠﻲ. فصلنامه تحقیقات مالی، 16(2)، 253-270.
4
ﻋﺒﺪاﻟﻌﻠﻲزاده، ﺷﻬﻴﺮ، و ﻋﺸﻘﻲ، ﺳﻴﻤﻴﻦ (1382). ﻛﺎرﺑﺮد اﻟﮕﻮرﻳﺘﻢ ژﻧﺘﻴﻚ در اﻧﺘﺨﺎب ﻳﻚ ﻣﺠﻤﻮﻋﻪ داراﻳﻲ از ﺳﻬﺎم ﺑﻮرس اوراق ﺑﻬﺎدار. ﻓﺼﻠﻨﺎﻣﻪ ﭘﮋوﻫﺶﻫﺎی اﻗﺘﺼﺎدی، 5(17)، 175-192.
5
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6
نریمانی، احمد، و نریمانی، رضا (1392). مدیریت سبد دارایی با استفاده ازMATLAB و GAMS. تهران، انتشارات ناقوس.
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ﺗﻘﻮی ﻓﺮد، محمدتقی، و ﻣﻨﺼﻮری، ﻃﺎﻫﺎ و ﺧﻮشﻃﻴﻨﺖ، ﻣﺤﺴﻦ (1386). ارائه ﻳﻚ اﻟﮕﻮرﻳﺘﻢ ﻓﺮااﺑﺘﻜﺎری ﺟﻬﺖ انتخاب ﺳﺒﺪ ﺳﻬﺎم ﺑﺎ در ﻧﻈﺮ ﮔﺮﻓﺘﻦ ﻣﺤﺪودﻳﺖﻫﺎی ﻋﺪد ﺻﺤﻴﺢ. ﻓﺼﻠﻨﺎﻣﻪ ﭘﮋوﻫﺶﻫﺎی اﻗﺘﺼﺎدی، 7(4)، 49-69.
8
Abdolalizade, Sh., & Eshghi. K (2004). Portfolio optimization using Genetic Algoritm. Journal of Economic Research, 5(17), 175-192 (In Persian).
9
Asgharpor. H., & Rezazade. A, (2016). Determining the stock optimal portfolio using value at risk. Applied Theories of Economics, 3(4), 93-118 (In Persian).
10
Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: from natural to artificial systems, New York, Oxford University Press.
11
Celikyurt. U, & Ozekici. S (2007). Multiperiod portfolio optimization models in stochastic markets using the mean-variance approach. European Journal of Operational Research (179), 186–202.
12
Clerc, M. (2006). Particle swarm optimization.London, ISTE.
13
Chang, T., Meade, N., & Sharaiha, J. (2000). Heuristics for cardinality constrained portfolio optimization. Computers & Operations Research 27: 1271–1302.
14
Coello, C.A.C., & Lechuga, M.S. (2002). MOPSO, A Proposal for multiple objective particle swarm optimization. Congress on Evolutionary Computation (CEC’2002), Vol. 2, 1051–1056.
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Deb, K., Agrawal, S., Pratap, A., & Meyarivan, T. (2000). A fast elitist nondominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In proceedings of parallel problem solving from nature - PPSN VI, Springer 849–858.
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Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. John Wiley & Sons, Chichester, UK.
17
Engelbrecht, A. P. (2005). Fundamentals of computational swarm intelligence. Hoboken, NJ: Wiley
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Fernandez, A,. Gomez, S. (2007). Portfolio selection using neural networks. Computers & Operations Research (34), 1177–1191.
19
Fieldsend, E., & Singh, S. (2002). A Multi-objective algorithm based upon particle swarm optimisation, an Eefficient data structure and turbulence, proceedings of the 2002. Workshop on Computational Intelligence, Birmingham, UK 37–44.
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Fonseca, C.M., & Fleming, P.J. (1993). Genetic algorithms for 13- multiobjective optimization, formulation, discussion, and generalization. In Proceedings of the Fifth International Conference on Genetic Algorithms 355–365.
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Goldberg, D.E., & Richardson, J.J. (1987). Genetic algorithms with sharing for multimodal function optimization. Genetic Algorithms and Their Applications, Proceedings of the Second ICGA, Lawrence Erlbaum Associates, Hillsdale, NJ, 41–49.
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Haupt, R. L., & Haupt, S. E. (1998). Practical genetic algorithms. New York: Wiley.
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Horn, J., Nafpliotis, N., & Goldberg, D.E. (1994). A niched pareto genetic algorithm for multiobjective optimization. In Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, vol: 1, Piscataway, New Jersey. IEEE Service Center 82–87.
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Kennedy, J., & Eberhart. R.C. (1995). Particle swarm optimization. IEEE Int’l Conf. on Neural Networks, (4),1942–1948.
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Kennedy, J., & Shi, Y. (2001). Swarm intelligence. San Francisco: Morgan Kaufmann Publishers.
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Konno, H., & Yamazaki, H. (1991). Mean-absolute deviation portfolio in optimization model and its application to Tokyo stock market. Management Science, (37) 519–531.
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Markowitz, H. (1952). Portfolio selection. Journal of Finance, 77-90
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Miettinen, K. (1999). Evolutionary algorithms in engineering and computer science: recent advances in genetic algorithms, evolution strategies, evolutionary programming, genetic programming, and industrial applications. Chichester; New York: Wiley.
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Mitchell, M. (1998). An introduction to genetic algorithms. Cambridge, Mass.: MIT Press.
30
Moshekhian, S., & Najafi, A. (2015). Portfolio optimization using multi-objective particle swarm optimization. Financial Engineering and Portfolio Management, 6(23), 133-147 (In Persian).
31
Narimani, A., & Narimani, R. (2014). Portfolio management by using MATLAB & GAMS, Naghos (In Persian).
32
Olsson, A. (2011). Particle swarm optimization: theory, techniques and applications. New York: Nova Science Publishers.
33
Otten, R., & Ginneken, L. (1989). The annealing algorithm. Boston: Kluwer Academic Publishers.
34
Parsopoulos, K., & Vrahatis, M.N. (2002). Particle swarm optimization method in multiobjective problems. Symposium on Applied Computing (SAC’2002) 603–607.
35
Raei, R., & Alibaigi, H. (2011). Portfolio optimization using particle swarm optimization method. Financial Research Journal, (29) 21-41 (In Persian).
36
Raie, R., & Poutanfar, A. (2012). Advanced investment management. The Organization for Researching and Composing Univercity Textbook in the Humanities, 175-192 (In Persian).
37
Raie, R., & Talangi, A. (2005). Advanced Investment Management. The Organization for Researching and Composing Univercity Textbook in the Humanities, 175-192 (In Persian).
38
Rajabi, M., & Khalozade, H. (2015). Optimal portfolio prediction in Tehran stock market using multi-objective evolutionary algorithms, NSGA-II and MOPSO. Financial Research Journal, 16(2), 253-270 (In Persian).
39
Sumathi, S., Hamsapriya, T., & Surekha, P. (2008). Evolutionary intelligence: an introduction to theory and applications with Matlab, Berlin: Springer.
40
Taghavifard, M., & Mansouri, T. (2008). A Meta-heuristic algorithm for portfolio selection problem under cardinality and bounding constraints. The Economic Research, 7(4), 49-69 (In Persian).
41
Venkataraman, P. (2002). Applied optimization with MATLAB programming. New York: Wiley.
42
Yin Peng, Y., & Jing Yu, W. (2006). A particle swarm optimization approach to the nonlinear resource allocation problem. Applied Mathematics and Computation, 183: 232–242.
43
Yan, W., & Shurong, L. (2007). Multi-period semi-variance portfolio selection: Model and numerical solution. Applied Mathematics and Computation, (194),128–134.
44
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45
ORIGINAL_ARTICLE
The Behavior of Monetary Policy during the Business Cycle in the Iran Using DSGE Model
The countercyclical monetary policy is a policy that economists recommend to decrease the economic fluctuations. The purpose of this study is to answer the question of how the monetary policy behavior in Iran's economy was and how it should be. To find the right answers, by using a Markov-Switching model, shown that behavior of monetary policy in the Iran during 1991 to 2015 was mainly procyclical. Then, a dynamic stochastic general equilibrium model, according to the structure of the economy, is considered. Then, optimal monetary policy has been calculated in terms of fiscal domination and institutional quality over a business cycle and calibrated using equilibrium parameters. The results show that the optimal monetary policy over the business cycle, monetary policy is counter-cyclical. The optimal monetary policy coefficient during the business cycle decreases with decreasing institutional quality and increased fiscal domination. Also, if the policymaker's goal is only to stabilize inflation, the optimal monetary policy is acyclic. In addition, when a completely independent monetary policy is assumed, the optimal policy coefficient takes the highest value compared to other assumed conditions.
https://ecoj.tabrizu.ac.ir/article_8401_e86ad242fe2baf30f31d51894d444557.pdf
2019-01-21
53
80
Monetary Policy
Business cycle
Markov-switching model
DSGE model
Alireza
Erfani
aerfani@semnan.ac.ir
1
Associate Professor of Economics, Semnan University
LEAD_AUTHOR
Neda
Kasaipour
kasaipour@yahoo.com
2
Ph.D. Student in Economics, Semnan University
AUTHOR
انواری، ابراهیم، و زراءنژاد، منصور (1394). نااطمینانی پارامتر و اثر آن بر سیاست پولی در اقتصاد ایران رهیافتی از مدل اقتصاد باز کینزینی جدید. پژوهشنامهیاقتصادکلان، 20، 154-134.
1
بیات، مرضیه، افشاری، زهرا، و توکلیان، حسین (1395). سیاست پولی و شاخص کل قیمت سهام در چارچوب یک مدل .DSGE فصلنامه پژوهشها و سیاستهای اقتصادی، 78، 206-178.
2
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46
ORIGINAL_ARTICLE
Investigating the Effects of Institutional-Structural Quality on Iran's Non-oil Exports: Time-Varying Models
Considering the importance of non-oil exports in state development plans, the present paper examined the nonlinear effects of real exchange rate, the value added of the industry and mining sector, non-oil export, and the institutional-structural quality on Iran non-oil exports. The results from the factor-augmented vector autoregressive (FAVAR) and time-varying parameters (TVP) methods on seasonal data of 1997-2015 timespan showed the symmetrical, positive effects of the institutional-structural quality and the state non-oil exports on the increase in the non-oil exports, rising in the course of time. In addition, the final effect of the real exchange rate on the state non-oil exports depends on the depression and prosperity conditions in the economy and can be asymmetrically positive or negative. Finally, the value added growth in the state industry and mining sector had a positive effect on the non-oil exports in the entire timespan studied; the only difference was that these symmetrical effects were stronger during periods of economic prosperity.
https://ecoj.tabrizu.ac.ir/article_8172_ee0a991f66556a162d473f59640e19c2.pdf
2019-01-21
81
106
Non-oil exports
institutional-structural quality
time-varying models
Zahed
Moradi
moradi_zahed@yahoo.com
1
Ph.D. Candidate in Economics, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
Abbas
Memarnejad
ab_memar@yahoo.com
2
Assistant Professor of Economics, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
LEAD_AUTHOR
Seyed Shamseddin
Hosseini
sh-hoseini@srbiau.ac.ir
3
Assistant Professor of Economics, Faculty of Economics, Allameh Tabataba'i University, Tehran, Iran
AUTHOR
Kambiz
Hojabr Kiani
k-kiani@srbiau.ac.ir
4
Professor of Economics, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
پیرایی، خسرو، تاسان، مونا، و دانشنیا، محمد (1394). تأثیر سرمایهگذاری مستقیم خارجی نرخ ارز حقیقی و آزادسازی اقتصادی بر صادرات غیرنفتی ایران (همراه با آزمون علیت تودا یاماموتو). فصلنامه تحقیقات اقتصادی، 1، 98-75.
1
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2
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46
ORIGINAL_ARTICLE
Estimating the Value of Statistical Life in Road Safety Improvement: The Case Study of Tabriz
With respect to the rapid development of the road transport industry, improving safety and valuing accidents have become an essential issue in public policy. Over the past few decades, studies based on the estimation of valuing statistical life have played a unique role in the cost-benefit estimations of investment in the transport sector. In this regard, this study has been conducted using the stated choice method and the mixed logit model to examine the willingness to pay and the value of statistical life among the Tabriz drivers. The research data were collected through a questionnaire from 300 people who travel daily in the city for various reasons. The statistical value of life and injury for Tabriz city was 18663384 and 135005 Tomans respectively. According to the results, investing in road safety improvement projects is necessary to reduce casualties and injuries.
https://ecoj.tabrizu.ac.ir/article_8389_51e45b5188566055c8a913b9ee778526.pdf
2019-01-21
107
142
Willingness to pay
Choice experiment
Value of statistical life
Amineh
Naderi
naderi.ameneh@yahoo.com
1
Ph.D. Candidate in Economics, Razi University, Kermanshah, Iran
AUTHOR
Shahram
Fatahi
sh_fatahi@yahoo.com
2
Associate Professor of Economics, Razi University, Kermanshah, Iran
LEAD_AUTHOR
Somaye
Azami
sazam_econ@yahoo.com
3
Associate Professor of Economics, Razi University, Kermanshah, Iran
AUTHOR
Mina
Golestani
mgolestani8958@gmail.com
4
Assistant professor of Pharmacoeconomics and Pharmaceutical Administration, Road Traffic Injury Research Center, Tabriz University of Medical Sciences
AUTHOR
آیتی، اسماعیل، و واحدی، جواد رضا (1386). ایجاد مدل شاخص ایمنی ترافیکی در محل پلها در راههای ایران. نشریه دانشکده مهندسی، 37(1)، 135-152.
1
حاجی زاده، ابراهیم، و اصغری، محمد (1390). روشها و تحلیلهای آماری با نگاه به روش تحقیق در علوم زیستی و بهداشتی. انتشارات جهاد دانشگاهی تهران.
2
عیسیزاده، سعید، جلیلی کامجو، پرویز، مددی، سعید، و محمودی نیا، داود (1390). ارزشگذاری کالاهای غیر بازاری مبتنی بر رویکرد ترجیحات بیان شده. مجله اقتصادی منابع طبیعی،1، 21-36.
3
عینی، الهه، سوری، حمید، گنجعلی، مجتبی، و باغفلکی، تابان (1393). برآورد هزینه سوانح ترافیکی در ایران با استفاده از روش تمایل به پرداخت. مجله ارتقای ایمنی و پیشگیری از مصدومیتها، 2(3)، 215-225.
4
جعفری، علی محمد، صالح، ایرج یزدانی، سعید، و حسینی، سید صفدر (1392). تحلیل پیامدهای اقتصادی زیست محیطی بالا بردن سد اکباتان همدان. اقتصاد کشاورزی، 7(2)، 69-92.
5
Mohamed, H. (2015). Estimation of socio-economic cost of road accidents in Saudi Arabia: Willingness to pay approach. Advances in Management and Applied Economics, 5(3), 43-61.
6
Ainy, E., Soori, H., Ganjali M., & Baghfalaki, T. (2014). Road traffic injury cost estimation by willingness to pay method. Safety Promotion and Injury Prevention, 2(3), 215-225 (In Persian).
7
Anderson, H., & Treich, N. (2011). The value of statistical life. Transport Economics, 1-36.
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Antonion, C. (2014). A stated preference study of the willingness to pay to reduce traffic risk in urban vs rural roads. EUR.Transp.Res.Rev, 6, 31-42.
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11
Bahamonde, F., Kunert, U., & Link, H. (2015). The value of statistical life in road safety context: A review current literature. Article in Transport Reviews, 1-27.
12
Bamsal, P., Daziano, RA., & Achtnicht, M. (2018). Extending the mixed logit model for combination of random and fixed parameters. Journal of Choice Modeling, 27, 88-96.
13
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20
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22
Hensher, DA., Rose, JM., Ortuzar, JD., & Rizzi, L. (2009). Estimating the willingness to pay and value of risk reduction for car occupants in the road environment. Institute of Transport and Logistics Studies. Working Paper, 1-22.
23
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24
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26
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27
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43
ORIGINAL_ARTICLE
An Appraisal of Downside and Upside Risk Spillovers of Exchange Rates, Crude Oil and Gold Prices on Tehran Stock Exchange
In this Paper, we examined the upside and downside Risk spillovers between exchanges rates, crude oil, gold, and stock prices in Iranian financial markets. Due to special characteristics of financial data, we used copula methods to assess correlation between returns of the markets and using VaR and CoVaR approaches we examined the risk spillovers between markets. Our data spans from 2006-07-19 to 2017-03-21. Results show that the correlations between the exchange rates and the stock prices, as well as the oil prices and the exchange rates were symmetric but the correlations between the gold prices and the stock prices as well as the crude oil prices and stock market were asymmetric and strong in the upper tails. CoVaR analysis shows that risk spillover effects between the stock and gold prices are stronger than the other variables. The relationship between exchange rates and oil prices against stock prices are considered to be mostly between returns but there are some risk spillovers too. In most cases upper risk spillovers are stronger than lower ones.
https://ecoj.tabrizu.ac.ir/article_8476_26e3ff45ed6c98be94fedb8ddcea68ba.pdf
2019-01-21
143
172
Financial Markets
Spillover Effects
VaR
CoVaR
Copulae
Mohammad Mehdi
Barghi Osguei
m.barghi@tabrizu.ac.ir
1
Associated Professor of Economics, University of Tabriz
LEAD_AUTHOR
Reza
Saghafi Kelvanag
r.saghafi@tabrizu.ac.ir
2
Ph.D. in Economics, University of Tabriz
AUTHOR
تقوی، مهدی؛ بیابانی، شاعر؛ (1382)، اثرات تغییر نرخ ارز بازار آزاد و جریان نقد آتی بر ارزش سهام شرکتهای سهامی عام پذیرفته شده در بورس اوراق بهادار تهران، مجلۀ پژوهشنامه اقتصادی، 3، 3-4، 13-38.
1
دوراندیش، علی؛ شریعت، احسان؛ ارزنده، نادر؛ (1393)؛ بررسی اثرات سرریز نوسانات نرخ ارز بر شرکتهای صنعت کشاورزی در بورس تهران؛ مجله اقتصاد کشاورزی و توسعه؛ 28 (2)؛ 177-184.
2
حیدری، حسن؛ بشیری، سحر؛ (1391)، بررسی رابطه بین نااطمینانی نرخ واقعی ارز و شاخص قیمت سهام در بورس اوراق بهادار تهران: مشاهداتی بر پایه مدل VAR-GARCH، تحقیقات مدلسازی اقتصادی، 3، 71-92.
3
جهانگیری، خلیل؛ حکمتی فرید، صمد؛ (1393)، مطالعه آثار سرریز تلاطم بازارهای سهام، طلا، نفت و ارز، تحقیقات حسابداری و حسابرسی، 56، 159-192.
4
شهبازی، کیومرث؛ رضایی، ابراهیم؛ صالحی، یاور؛ (1392)، تاثیر شوکهای قیمت نفت بر بازدهی سهام در بورس اوراق بهادار تهران: رهیافت SVAR، فصلنامۀ علمی پژوهشی دانش مالی تحلیل اوراق بهادار، 6، 18، 125-136.
5
،محمدرضا؛ نیکبخت، فاطمه؛ (1389)، بررسی تاثیر بی ثباتی نرخ واقعی ارز بر شاخص سود نقدی و قیمت بورس اوراق بهادار تهران، فصلنامۀ بورس اوراق بهادار تهران، 3، 11، 43-59.
6
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29
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30
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31
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35
Najjarzadeh, R, & Aghaei, M. & Rezaeepour, M. (2009). The Impact of Price and Exchange Rate Fluctuations on Stock Price Index in Tehran Stock Market: Using a Vector Auto-Regression Method. Journal of Economic Research, 1(9), 147-175 (In Persian).
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43
Reboredo, J.C., (2013). Is gold a safe haven or a hedge for the US dollar? Implications for risk management. Journal of Banking and Finance 37, 2665-2676.
44
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45
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Shahbazi, K. & Rezaei, E. & Salehi, Y. (2013). The Impact of Oil Price Shocks on the Stock Returns of Tehran Stock Exchange (TSE). Financial Knowledge of Securities Analysis, 6(18), 125-136 (In Persian).
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53
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55
ORIGINAL_ARTICLE
Estimating the Rebound Effect of Electricity Consumption in Iran: Threshold Level Approach
The literature on energy economics suggests a rebound effect of improving energy efficiency. Given the fact that existing rebound effect causes the electricity saving (due to the improvement of the efficiency of consumer electric appliances in the residential sector) be less than expected, the present paper based on the time series data of 1357-1395, uses linear and threshold models to estimate the direct rebound effect of residential electricity consumption in different scenarios. The results of linear model show that the direct rebound effect of residential electricity consumption in Iran during the period 1357-1395 is on average 81%. The results of the other model (threshold model), taking into account the two variables of Gross domestic product (GDP) per capita and cooling degree days (CDD) as threshold variables, show that decrease in GDP per capita and increase in cooling degree days will increase the direct rebound effect of residential electricity consumption.
https://ecoj.tabrizu.ac.ir/article_8102_bc13ff874774b18872e6503280608cc5.pdf
2019-01-21
173
196
Energy Economics
Electricity Consumption
Rebound Effect
Threshold Model
Musa
Khoshkalam Khosroshahi
musa_khosroshahi@yahoo.com
1
Assistant Professor of Economics, Alzahra University
LEAD_AUTHOR
Rohollah
Mahdavi
r_mahdavi@yahoo.com
2
Ph.D. in Economics, Allameh Tabataba'i University
AUTHOR
اسماعیلنیا، علیاصغر، و اختیاری، سارا (1391). بررسی میزان اثرات بازگشتی بهبود راندمان خودروها بر مصرف سوخت. مطالعات اقتصاد انرژی، 9(34)، 185-213.
1
اماموردی، قدرتاله، کریمی، مجتبی، و صادقی، هلن (1396). بررسی آستانهای و نامتقارن نسبت اهرمی بر سودآوری شرکتهای فعال در بورس اوراق بهادار تهران. فصلنامه اقتصاد مالی، 11(39)، 57-81.
2
وبسایت بانک مرکزی ایران، آمار و دادهها (www.cbi.ir)
3
ترازنامه انرژی (1394). وزارت نیرو.
4
منظور، داود، آقابابائی، محمد ابراهیم، و حقیقی، ایمان (1389). تحلیل اثرات بازگشتی ناشی از بهبود کارائی در مصارف برق در ایران: الگوی تعادل عمومی محاسبهپذیر. فصلنامه مطالعات اقتصاد انرژی، 8(28)، 1-23.
5
دلانگیزان، سهراب، خانزادی، آزاد، و حیدریان، مریم (1396). برآورد و تحلیل اثرات بازگشتی مستقیم ناشی از بهبود کارایی مصرف سوخت در بخش حملونقل جادهای ایران. فصلنامه مطالعات اقتصادی کاربردی ایران، 6(21)، 149-182.
6
خوشکلام خسروشاهی، موسی، جهانگرد، اسفندیار، و عابدیان، مریم (1394). بهبود کارائی مصرف بنزین و اثرات بازگشتی ناشی از آن در فعالیتهای مختلف اقتصادی. فصلنامه مطالعات اقتصاد انرژی، 12(44)، 37-63.
7
خوشکلام خسروشاهی، موسی (1396). بررسی آثار اقتصادی بکارگیری سیاستهای غیرقیمتی در مصرف حاملهای انرژی. تحقیقات مدلسازی اقتصادی، 8(29)، 37-72.
8
سالم، علی اصغر، و اکابری، مهدی (1396). برآورد اثر بازگشتی مستقیم بهبود کارایی مصرف برق در بخش خانگی مناطق شهری ایران. اقتصاد انرژی ایران، 6(22)، 45-74.
9
Allan, G., Hanley, N., McGregor, P., Swales, K., and Turner, K. (2007). The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom. Energy Economics, 29, 779-798.
10
Ang, B., Goh, T., and Liu, X. (1992). Residential electricity demand in Singapore. Energy, 17, 37-46.
11
Belaid, F., Bakaloglou, S., and Roubaud, D. (2018). Direct rebound effect of residential gas demand: Empirical evidence from France. Energy Policy, 115, 23–31.
12
Berkhout, P., Muskens, J., and Velthuijsen, J. (2000). Defining the Rebound Effect. Energy Policy, 28, 425-432.
13
Bessec, M, and Fouquau, J. (2008). The non-linear link between electricity consumption and temperature in Europe: a threshold panel approach. Energy Economics, 30, 2705-2721.
14
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15
Delangizan, S., Khanzadi, A., and Heidarian, M. (2017). Estimation and Analysis of Direct Rebound Effects Caused by Improving Fuel Consumption Efficiency in Iran's Road Transportation Sector. Quarterly Journal of Applied Economic Studies of Iran, 6(21), 149-182 (In Persian).
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Dimitropoulos, J., and Sorrell, S. (2006). The rebound effect: microeconomic definitions, extensions and limitations. In Proceedings of the 29th IAEE International Conference, Potsdam, Germany.
17
Duncan, R. (2015). A Threshold Model of the US Current Account. Economic Modeling, 48, 270-280.
18
Esmailnia, A., and Ekhtyari, S. (2012). Investigating the Rebound Effects of Improving Vehicle Efficiency on Fuel Consumption. Quarterly Journal of Energy Economics, 9(34), 185-213 (In Persian).
19
Emamverdi, G., Karimi, M., and Sadeghi, H. (2017). Threshold and asymmetric analysis of leverage ratio on profitability of active companies in Tehran Stock Exchange. Financial Economics, 39, 57-81 (In Persian).
20
Energy Balance (2015). Ministry of Power (In Persian).
21
Hansen, B. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of Econometrics, 93, 345-368.
22
http://www.tavanir.org.ir/
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http://sdwebx.worldbank.org/climateportal/index.cfm
24
Khoshkalam Khosroshahi, M., Jahangard, E., and Abedian, M. (2015). Improving the efficiency of gasoline consumption and its Rebound effects in various economic activities. Quarterly Journal of Energy Economics, 12(44), 37-63 (In Persian).
25
Khoshkalam Khosroshahi, M. (2017). Investigating Economic Effects of Application of Non-Price Policies on the Consumption of Energy Carriers. Quarterly Journal of Economic Modeling Research, 8(29), 37-72 (In Persian).
26
Lam, J. (1998). Climatic and economic influences on residential electricity consumption. Energy Conversion and Management, 39, 623-629.
27
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28
Lu, Y., Liu, Y., and Zhou, M. (2016). Rebound effect of improved energy efficiency for different energy types: A general equilibrium analysis for China. CAMA Working Paper 38/2016.
29
Manzoor, D., Aghababaie, E., and Hagigi, I. (2010). Analysis of the Rebound Effects Caused by Improving Efficiency in Electricity Consumption in Iran: A Computable General Balance Model. Quarterly Journal of Energy Economics, 8(28), 1-23 (In Persian).
30
Salem, A., and Akaberi, M. (2017). Estimating the direct rebound effect of improving the efficiency of power consumption in the residential sector of the urban areas of Iran. Journal of Energy Economics of Iran, 6(22), 45-74 (In Persian).
31
Saunders, H. (1992). The Khazzoom-Brookes postulate and neoclassical growth. The Energy Journal, 13(4), 131.
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Sorrell, S. (2007). UKERC review of evidence for the rebound effect.
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Sorrell, S., Dimitropoulos, J., and Sommerville, M. (2009). Empirical estimates of the direct rebound effect: A review. Energy Policy, 37, 1356-1371.
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Thomas, B., and Azevedo, I. (2013). Estimating direct and indirect rebound effects for U.S. households with input–output analysis. Part 2: Simulation. Ecological Economics, 86, 188-198.
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Wangpattarapong, K., Maneewan, S., Ketjoy, N., and Rakwichian, W. (2008). The impacts of climatic and economic factors on residential electricity consumption of Bangkok Metropolis. Energy Buildings, 40, 1419-1425.
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Zhang, M., Song, Y., Li, P., and Li, H. (2016). Study on affecting factors of residential energy consumption in urban and rural Jiangsu. Renewable and Sustainable Energy Reviews, 53, 330-337.
39
ORIGINAL_ARTICLE
The Relationship of Public Spending With Terrorism and Crime in the Countries of the MENA Region:
P-VAR Approach
According to statistics and evidence from the World Terrorist Database on the Terrorism Situation in the World and in the Mine Region, since 2004, the incidence of terrorist acts in the world and in this region has risen sharply. Governments try to increase the level of social security in the country by increasing their public expenditures, thereby reducing the crime and the terrorist acts. The purpose of this study was to investigate the dynamic relationship between public expenditures with crime and terrorism in MENA countries from 2003 to 2016 using the P-VAR approach. The results of the estimated model show that the existence of crime and terrorism has a positive dynamic effect on the general expenditures of the MENA countries. Also, the results of the analysis of variance decomposition indicate that the response to public expenditures varies by level of criminal activity and terrorism, so that criminal activity against terrorist activities has a greater contribution to the variance in these costs. In order to examine the dynamics of the model variables, IRF indicate that the shock caused by public expenditures has had a decreasing effect on crime, but the effects of this shock on terrorist attacks are meaningless, and this issue of inappropriate public spending In order to reduce the number of terrorist attacks in the countries of the MENA countries.
https://ecoj.tabrizu.ac.ir/article_8120_9eaddf56e1e5e54c780486b2f24f01fc.pdf
2019-01-21
197
220
Crime
Terrorist attack
Public expenditures
Panel vector autoregressive approach (P-VAR)
MENA countries
Mahnaz
Saeedikiya
mahnaz1420@gmail.com
1
Ph.D. Candidate in Economics, University of Sistan and Baluchestan
AUTHOR
Nazar
Dahmardeh
nazar@hamoon.usb.ac.ir
2
Professor of Economics, University of Sistan and Baluchestan
LEAD_AUTHOR
Gholamreza
Keshavarz Hadad
g.k.haddad@sharif.edu
3
Associate Professor of Economics, University of Sistan and Baluchestan
AUTHOR
Marzieh
Esfandiari
m.esfandiari@eco.usb.ac.ir
4
Assistant Professor of Economics, University of Sistan and Baluchestan
AUTHOR
بابایی، محمدعلی، و انصاری، اسماعیل (1391). تحلیل هزینههای جرم. حقوق تحلیلی، 8(2)، 98-79.
1
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2
سلمانی، بهزاد، پناهی، حسین، و جمشیدی، عذرا (1393). بررسی اثر شوکهای تروریسم بر جذب سرمایهگذاری مستقیم خارجی در کشورهای منطقه منا. پژوهشهای اقتصاد و توسعه منطقهای، 8(21)، 204-180.
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فرهمند، شکوفه، صفاری، بابک، و موسوی، وجیهه (1396). تحلیل فضایی تأثیر عوامل اقتصادی-اجتماعی بر وقوع جرائم در استانهای ایران با تأکید بر مهاجرت. تحقیقات اقتصادی، 1(52)، 138-117.
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لطفی، عزت اله، و فیض پور، محمدعلی (1393). رشد صنعتی و جرم (شواهدی از استانهای کشور طی برنامههای سوم و چهارم توسعه). فصلنامه مجلس و راهبرد، 21(80)، 60-39.
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محمدنسل، غلامرضا (1389). فرایند پیشگیری از جرم. فصلنامهحقوق، 40(1)، 334-317.
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Arin, K. P., Lorz, O., Reich, O. F., & Spagnolo, N. (2011). Exploring the dynamics between terrorism and anti-terror spending: Theory and UK-evidence. Journal of Economic Behavior & Organization, 77(2), 189-202.
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21
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Lis, P. (2018). The impact of armed conflict and terrorism on foreign aid: A sector-level analysis. World Development, 110, 283-294.
24
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25
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26
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27
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32
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33
ORIGINAL_ARTICLE
Estimation of Household Educational Expenditure Model Using Censored Data
In recent decades, due to the growing importance of the role of human capital in economic models, the importance of the issue of education has risen in economics literatures. This paper aims to investigate the determinants of educational costs in micro level (household) in Iran. The determinants affecting educational costs are categorized at four levels: household characteristics, child characteristics, head characteristics and mother characteristics. The effect of these categories is estimated thorough a censored Tobit model for Iran household survey in 2016. This model has been chosen so that zero cost in some cases can be reported. The result shows that urban residency and having girl Childs (versus boy) are context factors that increase expenditure on education. Moreover, as men have traditionally been the head of families in Iran and their income has been higher than women’s, the gender of the head of the household is another important factor influencing the educational costs of the family. Finally, the analysis of the characteristics of the mother and of the head of the family shows that transition of the financial capital to children takes place mainly thorough the head of the family (stronger effect of the head’s income compared with the mother’s income) while the transition of the human capital to children takes place mainly thorough the mother of the family (stronger effect of mother’s education compared with the head’s education).
https://ecoj.tabrizu.ac.ir/article_8222_d2968ecf2b6925ef7b02f200a43e821e.pdf
2019-01-21
221
246
Censored data
Household budget
educational cost
Mahdi
Keramatfar
mkeramatfar@gmail.com
1
Ph.D. Candidate in Economics, Tarbiat Modares University
AUTHOR
Bahram
Sahabi
sahabi_b@modares.ac.ir
2
Associate Professor of Economics, Tarbiat Modares University
LEAD_AUTHOR
Abbas
Asari
asari_a@modares.ac.ir
3
Associate Professor of Economics, Tarbiat Modares University
AUTHOR
Ezzat allah
Abbasian
a.abbasian@basu.ac.ir
4
Associate Professor of Economics, University of Tehran
AUTHOR
ابراهیمی پورفائز، سهند، کریمی موغاری، زهرا، و محمدی، تیمور (1396). درونزایی در برآورد مدل کار کودک با دادههای سانسورشده؛ با بکارگیری مدل توبیت با متغیر ابزاری. فصلنامه نظریههای کاربردی اقتصاد، 4(3)، 34-1.
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2
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64
ORIGINAL_ARTICLE
Capital Bank, liquidity Risk and Credit in Iran's Banks
The present study investigates the effect of capital on liquidity and credit risks in the banking industry of Iran using a GMM system. Eviews9 and stata12 software have been used to carry out this research. The research findings show that there is a significant and significant correlation between bank capital and risk in the banking industry of Iran, so that by increasing the capital of a bank by as much as one percent, the liquidity risk on the basis of various indexes can decrease from 0/1% to 0/4% Find out. In the case of credit risk, the increase in bank capital leads to a reduction in credit risk from 5/7 to 6/8 percent. Based on the findings of this research and tests, the ethical hazard theory in the banking industry is confirmed. And the charter theory regarding the banking system of Iran is not approved. In this study, the size of the bank shows a direct and significant relationship with liquidity risk, so that a unit of increase in the bank's size index has increased the risk of liquidity from 0/003 to 0/008. There is also a meaningful relationship between the variables of economics and the risk of liquidity and credit. The results of the research also suggest that risk management in banks depends not only on internal banking factors, but also on macroeconomic factors.
https://ecoj.tabrizu.ac.ir/article_8098_f2522c9e4d4a0333dcb8f8421bf8f9b2.pdf
2019-01-21
247
270
Bank capital
Moral hazard theory
Charter value theory
SGMM
Amir Ali
Farhang
s_farhang@pnu.ac.ir
1
Assistant Professor of Economics, Payame Noor University
LEAD_AUTHOR
Abolghasem
Asna Ashari
esnaashari2000@gmail.com
2
Associate Professor of Economics, Payame Noor University
AUTHOR
Asghar
Abolhasani Hastiani
abolhasani2000@yahoo.com
3
Associate Professor of Economics, Payame Noor University
AUTHOR
Mohammad Reza
Ranjbar Fallah
rfallah@pnu.ac.ir
4
Assistant Professor of Economics, Payame Noor University
AUTHOR
Jahangir
Biabani
jbiabani2000@yahoo.com
5
Associate Professor of Economics, Payame Noor University
AUTHOR
اجلافی، مجید (1392). بررسی رابطه بین تمرکز و ثبات مالی بانکها در ایران، پایان نامه کارشناسی ارشد، موسسه آموزش عالی علوم بانکی، تهران، ایران.
1
بانک مرکزی جمهوری اسلامی ایران، حسابهای ملی ایران و گزارش اقتصادی و ترازنامه بانک مرکزی، سالهای مختلف.
2
خوش سیما، رضا، و شهیکی تاش، محمدنبی (2013). تأثیر ریسک های اعتباری، عملیاتی و نقدینگی بر کارایی نظام بانکی ایران. فصلنامه برنامهریزی و بودجه، 17(4)، 69-95.
3
خوشنود، زهرا، و اسفندیاری، مرضیه (1395). تحلیل سازوکار تعدیل نسبت کفایت سرمایه در گذر از سلامت بانکی به ثبات مالی. فصلنامه پژوهش های پولی - بانکی، سال هشتم، شماره ۲۵.
4
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