ORIGINAL_ARTICLE
The Role of Household Participation in Financial Market in Effectiveness of Monetary Shock on Macroeconomic Dynamics in Iran
Using a sticky price dynamic stochastic general equilibrium (DSGE) model, this paper study how the presence of both Ricardian and non-Ricardian households in the economy might affect the effectiveness of the monetary policy on macroeconomic dynamics and the determinacy of equilibrium in Iran. If the household participation in the financial market is not sufficiently big, the slope of a dynamic IS curve becomes positive. In the case of an upward-sloping IS curve, the equilibrium is indeterminant. Based on the degree of financial development in Iran, we estimate the share of non-Ricardian households for two periods: 1990 to 1999 and 2000 to 2017. The results show that during the first period, the share of non-Ricardian household in Iranian economy was 54 percent and the slope of the IS curve was upward. Hence, the model did not have a stable equilibrium during 1990-1999. However, in the second period, with an increase in the level of financial development in Iran, the share of non-Ricardian household decreased to 38 percent. In this case, the dynamic IS curve sloped downward and the model had a stable unique equilibrium. The impulse response functions show that in the second period, a monetary shock has the expected effect on macroeconomic variables including output, inflation, employment, real wage and the growth rate of money base. Our results underscore the role of households' participation in the financial market in the effectiveness of the monetary policy on macroeconomic variables and the determinacy of equilibrium in a dynamic stochastic model.
https://ecoj.tabrizu.ac.ir/article_9359_87a25ae9efe5b9ddf63d7af043c61cdf.pdf
2019-11-22
1
22
Heterogeneous Households
Monetary Policy
Dynamic IS Curve
DSGE model
Iran
Raha
Gharraie
r.gharraie@shirazu.ac.ir
1
Ph.D. Candidate in Economics, Shiraz Universityz
AUTHOR
Karim
Eslamloueyan
keslamlo@rose.shirazu.ac.ir
2
Professor of Economics, Shiraz University
LEAD_AUTHOR
Ebrahim
Hadian
ehadian@rose.shirazu.ac.ir
3
Associate Professor of Economics, Shiraz University
AUTHOR
zahra
Dehghan
zdehghan@shirazu.ac.ir
4
Economics, Shiraz University, Shiraz,Iran.
AUTHOR
اسلاملوییان، ک. (1396). ملاحظاتی در اسلامیسازی منطق هیکسی: ثبات و سازگاری چارچوب IS-LM اسلامی. دو فصلنامه علمی پژوهشی اقتصاد اسلامی. (19). 7-40.
1
توکلیان، ح. و صارم، م. (1396). الگوهای DSGE در نرم افزار داینار، الگوسازی، حل و برآورد مبتنی بر اقتصاد ایران. پژوهشکده پولی و بانکی بانک مرکزی جمهوری اسلامی ایران.
2
خلاصه تحولات اقتصادی کشور. بانک مرکزی جمهوری اسلامی ایران، نشریات و پژوهشها. (www.cbi.ir).
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دمیری، ف.، اسلاملوییان، ک.، هادیان، ا. و اکبریان، ر. (1397). تاثیر تکانه نفتی بر تراز تجاری و متغیرهای کلان اقتصاد ایران با استفاده از یک مدل تعادل عمومی پویای تصادفی. فصلنامه علمی پژوهشی مطالعات اقتصادی کاربردی ایران. (23). 35-60.
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صمدی، ع. و اوجیمهر، س. (1394). بررسی پایداری و سکون تورم در ایران: مقایسه دو الگوی چسبندگی قیمت هایبرید و چسبندگی اطلاعات. فصلنامه تحقیقات مدلسازی اقتصادی. (5). 41-72.
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Damiri, F., Eslamloueyan, k., Hadian, A. & Akbarian. R. (1397). The effects of oil shock on trade balance and macroeconomic variables in Iran using a dynamic stochastic general equilibrium model. The quarterly journal of applied economics studies. 23. 35-60. (In Persian)
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Furlanetto, F., Seneca, M., (2012). Rule of thumb consumers, productivity and hours. The Scandinavian Journal of Economics, 114,658-679.
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Gali, J. , Lopez-Salido, D. and Valles, J. (2007). Understanding the effects of government spending on consumption. Journal of European Economic Association. 5 (1): 227-270.
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King, R., Plosser, C., and Rebelo. (1987). Production, growth and business cycles. Journal of Monetary Economics 21. 195-232.
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Lubik, T. and Schorfheide, F. (2003). Testing for indeterminacy: an application to U.S. monetary policy. Economic dynamic control. 28.273-285.
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McCallum, B. T. (1989). Monetary economics, theory and policy, New York: Macmillan.
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McCafferty, S. (1990)., Macroeconomic theory, New York: Harper and Row.
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Modigliani, F. (1944). Liquidity preference and the theory of interest and money. Econometrica, 12. 45-88.
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Motta, G. and Tirelli, P. (2015). Money targeting, heterogeneous agents and dynamic instability. Macroeconomic dynamics. 19, 288-310.
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Walsh, C. (2010). Monetary theory and policy. Massachusetts institute of technology. Fourth Edition.
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Walsh, C. (2017). Workers, capitalists, wages and employment. Prepared for federal bank of Richmond, Forthcoming.
31
ORIGINAL_ARTICLE
Assessing Resilience Index of Monetary and Financial Sector of Iran’s Economy
Economic resilience refers to the ability to deal with various economic shocks as well as the ability to recover from crises. In this regard, the monetary and financial sectors are among the most important sectors in Iran’s economy, which are affected by shocks such as sanctions. For this reason, their resilience to crises is very important. The purpose of this paper is to define and estimate Iran's monetary and financial sectors resilience index. Therefore, according to the existing resilience literature, and using the grounded theory (GT) approach, theoretical saturation was obtained with respect to the resilience components of the monetary and financial sectors. As far as their importance is concerned, the growth rate of government oil revenues, the fluctuation of the growth rate of liquidity, risk index, the ratio of bank debt to the central bank to the monetary base and the ratio of government debt to the banking system to liquidity were identified as indicators of resilience of the monetary and financial sectors; respectively. The time series of the resilience index of monetary and financial sectors were estimated for the period from 1976 to 2016. Based on the obtained index, with exogenous shocks, the vulnerability of this sector is high. In addition, based on the results, in order to increase the resilience of this sector, it is recommended to correcting the banking system and relationship the government as an effective institution with the monetary and banking structure of Iran's economy.
https://ecoj.tabrizu.ac.ir/article_9143_26c7af0bd603a00aa2dacfb989e3b34b.pdf
2019-11-22
23
48
Resilience
Vulnerability
Grounded theory
Bayesian model averaging
Monetary and Financial Sector
Hesameddin
Ghasemi
he_ghasemi@sbu.ac.ir
1
Ph.D. Candidate in Economics, University of Shahid beheshti
AUTHOR
Abbas
Arabmazar
ab_arabmazar@sbu.ac.ir
2
Associate Professor of Economics, University of Shahid Beheshti
LEAD_AUTHOR
ابونوری، اسماعیل، و لاجوردی، حسن (1395). برآورد شاخص آسیبپذیری و تابآوری اقتصادی به روش پارامتریکی: بررسی موردی کشورهای عضو اوپک. نظریههای کاربردی اقتصاد، 3(3)، 44–25.
1
استراوس، انسلم، و کوربین، جولیت (1395). مبانی پژوهش کیفی فنون و مراحل تولید نظریه زمینهای. مترجم: ابراهیم افشار، تهران: نشر نی، چاپ پنجم.
2
خوانساری، رسول، و قلیچ، وهاب (1394). اولویتبندی عوامل موثر بر تحقق سیاست های کلی اقتصاد مقاومتی در نظام بانکی با استفاده از روش تاپسیس فازی. دو فصلنامه علمی – پژوهشی تحقیقات مالی اسلامی، 5(1)، 118–89.
3
رضوی، سیدمصطفی، اکبری، مرتضی، جعفرزاده، مرتضی، و زالی، محمدرضا (1392). بازکاوی روش تحقیق آمیخته. تهران: انتشارات دانشگاه تهران، چاپ دوم.
4
غیاثوند، ابوالفضل، و عبدالشاه، فاطمه (1394). مفهوم و ارزیابی تابآوری اقتصادی ایران. فصلنامهپژوهشنامهاقتصادی، 15(4)، 187-161.
5
نادعلی، محمد (1395). سنجش میزان شکنندگی نظام بانکی در اقتصاد ایران. فصلنامه روند، 23 (4)، 172–145.
6
Abiad, A., Bluedorn, J., Guajardo, J., & P., Topalova (2015). The rising resilience of emerging market and developing economies. World Development, 72, 1–26.
7
Abounoori, E., & Lajevardi, H. (2016). Estimated the index of economic vulnerability and resilience using parametric method: The case of OPEC. Applied Theories of Economics, 3(3), 25-44 (In Persian).
8
Akter, S., & Mallick, B. (2013). The poverty–vulnerability–resilience nexus: Evidence from Bangladesh. Ecological Economics, 96, 114-124.
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Bakhtiari, S., & Sajjadieh, F. (2018). Theoretical and empirical analysis of economic resilience index. Iranian Journal of Economic Studies, 7(1), 41-53.
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Boorman, J., Fajgenbaum, J., Ferhani, H., Bhaskharan, M., Drew, A., & A.K., Harpaul (2013). The centennial resilience index: Measuring countries resilience to shock, Centennial Group. Global Journal of Emerging Market Economies, 5(2), 57 – 98.
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Briguglio, L., Cordina, G., Farrugia, N., & S., Vella (2006). Conceptualising and measuring economic resilience, In Briguglio, L., G.Cordina & E.J. kisanga. (eds) Building the Economic Resilience of Small States. Malta: Islands and Small States Institute and London: Commonwealth Secretariat, 265-287.
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Cordina, G. (2004). Economic vulnerability and economic growth: Some results from a neo-classical growth modelling approach. Journal of Economic Development, 29(2), 21-39.
18
Exner, A., Politti, E., Schriefl, E., Erker, S., Stangl, R., Baud, S., Warmuth, H., Matzenberger, J., Kranzl, L., Paulesich, R., Windhaber, M., Supper, S., & G., Stöglehner (2016). Measuring regional resilience towards fossil fuel supply constraints. Adaptability and vulnerability in socio-ecological transformations-the case of Austria. Energy Policy, 91, 128-137.
19
Fratzscher, M., Konig, P.J., & C., Lambert (2016). Credit provision and banking stability after the Great Financial Crisis: The role of bank regulation and the quality of governance. Journal of International Money and Finance, 66, 113-135.
20
Gallopin, G. (2006). Linkages between vulnerability, resilience, and adaptive capacity. Global Environmental Change, 16, 293–303.
21
Giannone, D., Lenza, M., & L., Reichlin (2011). Market freedom and the global recession. IMF Economic Review, 59(1), 111-135.
22
Ghiyasvand, A., & Abdoshah, F. (2015). The concept and measurement of economic Resilience. Journal of Economic Research, 15(4), 161-187 (In Persian).
23
Khansari, R., & Ghelich, W. (2015). Prioritizing the factors affecting implementation of general policies of resistance economy in Iranian banking system by Fuzzy Topsis Method. Islamic Finance Researches, 5(1), 89 – 118 (In Persian).
24
Markman, G., & Venzin, M. (2014). Resilience: Lessons from banks that have braved the economic crisis-and from those that have not. International Business Review, 23, 1096 - 1107.
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26
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27
Modica, M. & Reggiani, A. (2015). Spatial economic resilience: Overview and perspectives. Networks and Spatial Economics, 15, 211-233.
28
Nadali, M. (2016). Measuring the fragility index of banking system in Iran. Journal of Ravand, 23(4), 145 – 172 (In Persian).
29
Onder, S., Damar, B., & A.A., Hekimoglu (2016). Macro stress testing and an application on turkish banking sector. Procedia Economics and Finance, 38, 17-37.
30
Proag, V. (2014). The concept of vulnerability and resilience. Procedia Economics and Finance, 18, 369-376.
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32
Rose, A., & Krausmann, E. (2013). An economic framework for the development of a resilience index for business recovery. International Journal of Disaster Risk Reduction, 5, 73-83.
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Strauss, A., & Corbin, J. (2016). Basic of Qualitative Research: Techniques and Procedures for Grounded Theory. Translator: Afshar, Ebrahim, Tehran: Ney. (In Persian).
34
Vallascas, F., & Keasey, K. (2012). Bank resilience to systemic shocks and the stability of banking systems: Small is beautiful. Journal of International Money and Finance, 31, 1745-1776.
35
ORIGINAL_ARTICLE
The Impact of The Government Expenditures Shocks on the Current Account and Real Effective Exchange Rate in the Oil and Nonoil Developing Countries: Panel VAR Approach
The performance of the fiscal policy has always been one of the topics discussed in macroeconomics. The main purpose of this paper is to investigate the effect of government expenditures on the current account and the real effective exchange rate in two groups of oil and non-oil developing countries. In this regard, we used Panel VAR method and annual data during 2001-2015. Empirical findings show that the government expenditures shocks on the current account in the two groups of oil and non-oil countries is negative, leading to current account deficits, but in the long run, the current account deficit in oil countries is increasing and in non-oil countries is decreasing. The results also showed that the impact of government expenditures shocks on the real effective exchange rate in the two groups of oil and non-oil countries is different. So that the impact of government expenditures in non-oil countries in the short term will increase real effective exchange rate and in the mid and long term it will decrease, but in oil countries, the government expenditures shocks will increase the real effective exchange rate.
https://ecoj.tabrizu.ac.ir/article_8393_bfa60702dc61462e46be57b0c20e5035.pdf
2019-11-22
49
72
real effective exchange rate
current account
government expenditures
Panel-VAR
Ahmad
Sojodi
sujudi89@yahoo.com
1
Ph.D. Candidate in Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Ira
AUTHOR
Saeed
Daei-Karimzadeh
saeedkarimzade@yahoo.com
2
Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
LEAD_AUTHOR
امامی، کریم (1390)، تأثیر نااطمینانی مخارج جاری و عمرانی دولت بر سرمایه گذاری بخش خصوصی در اقتصاد ایران، فصلنامهمدلسازیاقتصادی، 5 (4).
1
زارع نقده، سمیه (1390)، بررسی تاثیر مخارج جاری و عمرانی دولت بر نرخ ارز حقیقی در ایران، پایان نامه کارشناسی ارشد، دانشگاه الزهرا.
2
مجدزاده طباطبایی، شراره، نعمت اللهی، فاطمه (1389)، تاثیر رشد مخارج دولتی بر رشد اقتصادی مطالعه موردی اقتصاد ایران، فصلنامه پژوهشها و سیاستهای اقتصادی، 17 (53) ، 44-25.
3
عظیمی، سید امیر، نوفرستی، محمد، (1394) بررسی رابطه بین کسری بودجه دولت وتراز تجاری در ایران درچارچوب یک الگوی اقتصادسنجی کلان ساختاری پویا، فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)، 15(2)، 156-137.
4
زوارئیان کچومنقالی، منصوره (1391)، مطالعه رابطه بین کسری بودجه دولت و حساب جاری در اقتصاد ایران در طی دوره 1385-1342، فصلنامه پژوهشهای بازرگانی، (62)، 221-193.
5
دلاوری، مجید، کریمیکیا، اسما (1387)، بررسی تاثیر سیاست مالی بر تراز تجاری ایران با تاکید بر مخارج دولتی، فصلنامه تحقیقات اقتصادی، 43(4)، 174-145.
6
طهماسبی، بهمن، جعفری صمیمی، احمد، امیری، حنیفه (1391)، تاثیر کسری بودجه بر نرخ ارز حقیقی در اقتصاد ایران، فصلنامه دانش حسابرسی، (49)، 50-25.
7
مهرآرا، محسن و مرادی، مهدی (1387)، بررسی تاثیرات کسری بودجه، نرخ ارز حقیقی و رابطه مبادله بر کسری حساب جاری کشورهای صادرکننده نفت عضو (OPEC)، فصلنامه پژوهشهای بازرگانی، (47)، 167-141.
8
Abrigo, M.R.M., & Love, I. (2016). Estimation of panel vector autoregression in stata: a package of programs, University of Hawai`i at Mānoa Department of Economics Working Paper Series . 16, 1-30
9
Beetsma, R., Giuliodori, M., & Klaassen, F. (2008). The Effects Of Public Spending Shocks On Trade Balances And Budget Deficits In The European Union. Journal of the European Economic Association, 6(2-3), 414-423.
10
Benetrix, AS, Lane, PR. (2009). The impact of fiscal shocks on the Irish economy, The economic and social review, 40, 407-434.
11
Bouakez, H, Eyquem, A. (2015). Government spending, monetary policy, and the real exchange rate, Journal of International Money and Finance, 56, 178-201.
12
Castro, F., Garrote, D. (2015), The effects of fiscal shocks on the exchange rate in the EMU and differences with the USA, Empirical Economics, 49, 1341-1365.
13
Cebi, C., Culha, AA. (2014). The effects of government spending shocks on the real exchange rate and trade balance in Turkey, Applied Economics, 46, 3151-3162.
14
Ilzetzki, E., Mendoza, E. G., & Végh, C. A. (2013). How big (small?) are fiscal multipliers? Journal of Monetary Economics, 60(2), 239-254.
15
Ilzetzki, E., Carmen, R., and Kenneth, R. (2009), Exchange rate arrangements entering the 21st century: Which anchor will hold?(mimeo, University of Maryland and Harvard University).
16
Kim, S. (2015). Country characteristics and the effects of government consumption shocks on the current account and real exchange rate. Journal of International Economics, 97(2), 436-447.
17
ORIGINAL_ARTICLE
A Comparative Study of the Efficiency of Ponzi Vs. No-Ponzi Economic System Based on Agent-Based Modeling
One of the main concerns of economic scholars and thinkers is to predict the behavior of individuals in an economic system. Although economists often use complex mathematical equations for economic analysis, in recent decades due to the weakness of forecasting analyses based on equations and inability of such equations to justify empirical events, economists have used modeling and simulation methods. In other words, they are looking for ways to justify complex phenomena in the economy as a complex system. In addition to applying complexity theory, this research attempts to introduce a research tool to scholars for the simulation of agent-based research. In this study, we will examine the efficiency of each system by developing an agent-based model based on a No-Ponzi economic system and comparing it with a Ponzi economic model. We will also examine the effects and consequences of some economic behaviors that are contrary to the ethics and teachings of Islam. Comparing the two models, the results indicate that the No-Ponzi model has a better human development index and more social welfare.
https://ecoj.tabrizu.ac.ir/article_9360_6d717328b4cf2fb9221e5afc5560b731.pdf
2019-11-22
73
102
Agent-based modeling
Islamic economics
Wealth distribution
Gini coefficient
Consumption؛ Saving؛ Wealth
Narges
Javidi Abdollahzadeh Aval
njavidi@tabrizu.ac.ir
1
PhD Student in Economics, University of Tabriz
AUTHOR
Ahmad
Assad Zadeh
assadzadeh@tabrizu.ac.ir
2
Associate Professor of Economics, University of Tabriz
LEAD_AUTHOR
Sedaghat
Shahmorad
shahmorad@tabrizu.ac.ir
3
Professor of Applied Mathematics, University of Tabriz
AUTHOR
جلایی، عبدالمجید، قاسمی، امین، و ستاری، امید. (1394). شبیهسازی تابع مصرف و پیشبینی میزان مصرف ایران تا افق 1404 با استفاده از الگوریتم ژنتیک و الگوریتم بهینهسازی انبوه ذرات. فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)، 2(15)، 27-47.
1
حر عاملی، محمدحسن (1364ش). وسائل الشیعه. شماره ۱۲ . تهران: انتشارات اسلامیه.
2
زراء نژاد، منصور، و منصوری، سیدامین (1395). برآورد تابع مصرف آندو-مودیگیلیانی با لحاظ انواع ثروت در ایران. فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)، 16(3)،131-153.
3
عطارزاده، سعید، جلیلیان، مهدی، و ساریخانی، عادل (1392). بازاریابی شبکه ای در فقه و حقوق کیفری ایران. ﻓﺼﻠﻨﺎﻣﻪ ﭘﮋوﻫﺶﻫﺎی ﻓﻘﻪ و ﺣﻘﻮق اﺳﻼﻣﯽ، 10(34)، 59-83.
4
فخرایی، عنایت اله، و منصوری، سیدامین (1388). برآورد میل نهایی به مصرف در گروههای درآمدی بر اساس فرضیه درآمد دائمی در ایران. ﻣﺠﻠﺔ داﻧﺶ و ﺗﻮﺳﻌﻪ، 16(29)، 21-39.
5
کاغذیان، سهیلا. نقدی، یزدان، و اکبرنژاد، لیلا (1389). رابطه پسانداز و ثروت در استانهای ایران. فصلنامه مدلسازی اقتصادی، 4(2)، 73-94.
6
کلینی، محمدبن یعقوب (1407ق). اصول کافی (5). قم: دارالحدیث.
7
متقی هندی، علاالدین علی (۱۴۲۴). کنزل العمال فی سنن الاقوال و الافعال. بیروت: دارالکتب العلمیه.
8
مجلسی، محمدباقر (۱۴۰۴). بحارالانوار. بیروت: موسسه الوفا.
9
Alatas, H., Nurhimawan, S., Asmat,F., Hardheinata, H. (2017). Dynamics of an agent-based opinion model with complete social connectivity network. Chaos, Solitons and Fractals, 101, 24-32.
10
Al-Suwailem, S. (2008). Islamic Economics in a complex world. Islamic Development Bank.
11
Al-Zoubi, H., Maghyere, A. (2008). Does issuing government debt needed as a Ponzi scheme in Islamic finance. Managerial Finance, 34(10). 726-738.
12
Artzrouni, M. (2009). The mathematics of Ponzi schemes. Math.SocialSci, 58 ,190–201.
13
Atarzadeh, S., Jalilian, M., Sarikhani, A. (2014). Net marketing in law and jurisprudence of Iran. Islamic law & jurisprudence research quarterly, 10(34), 59-84. (In Persian)
14
Baucus, M., Mitteness, C. (2016). Crowdfrauding: Avoiding Ponzi entrepreneurs when investing in new ventures. Bus.Horiz, 59(1), 37–50.
15
Bensaid, K., El Haloui, A.M., Naciri, N., Aboulaich, R., Tkiouat, M. (2017). Agent Based Modeling of Islamic Microfinance with Cooperative and Takaful System. International Journal of Applied Business and Economic Research, 15(5), 737-756.
16
Bhattacharya, U. (2003). The optimal design of Ponzi schemes in finite economies. Journal of Financial Intermediation, 12(1), 2-24.
17
Fakhrai, E.& Mansoori, A. (2010). Estimating marginal propensity to consume for income groups on the basis of relative permanent income hypothesis in Iran. Financial monetary economics, 16(29), 21-39 (In Persian).
18
Guerini, M., Moneta, A. (2017) A Method for Agent-Based Models Validation. Journal of Economic Dynamics and Control, 82, 125-141.
19
Hachaqmi, K., Tkiouat, M., (2016). Towards an Agent-Based Modeling of the Consumer Goods Market. Asian Journal of Applied Sciences, 4(2), 276-285 .
20
Jalaee, S., A., Ghasemi, A., Sattari, O. (2015). Simulating consumption function and Forecasting Iran's consumption until 1404 horizon using genetic and Particle SWARM optimization algorithm. The Economic Research, 15(2), 27-47 (In Persian).
21
Kaghazian, S., Naghdi, Y., Akbarnezhad, l., (2010). Relationship between saving and wealth (By emphasizing the housing values) in Iran Provinces. Economical Modeling, 4(12), 73-94 (In Persian).
22
Naciri, N., Tkiouat, M., (2016). Economic Agent Based Models: Review. International Journal of Applied Engineering Research, 11( 8), 5492-5502
23
Pascoa, A., Seghir, A. (2009). Harsh default penalties lead to Ponzi schemes. Games and Economics Behavior, 65, 270-286.
24
Sabzian, H., Aliahmadi, A., Azar, A., Mirzaee, M. (2018). Economic inequality and Islamic Charity: An exploratory agent-based modeling approach. Cornell university.
25
Tamegawa, K. (2013). How does the no Ponzi game condition work in an optimal consumption problem?. Economics & Finance Research, 1, 42-44.
26
Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: modeling natural, social, and engineered complex systems with netlogo: MIT Press.
27
Zarra Nezhad, M. &Mansouri, S., A. (2016). Estimating Ando-Modigliani consumption function regarding the kinds of wealth in Iran. The economic research, 16(3), 131-153 (In Persian).
28
Zhua, A., Fua, P., Zhangb, Q., Chena, Z. (2017). Ponzi scheme diffusion in complex networks. Phisyca, A, 479, 128-136.
29
ORIGINAL_ARTICLE
Analysis of Establishing a Coalition between Iran and Russia and Its Effect on Iran’s Bargaining Power in Europe’s Natural Gas Market: A Network Game Approach
According to the BP statistics, The Middle East with almost 40 percent of natural gas reserves is the richest region all over the world and Iran with more than 18 percent is the richest country. It means that Iran can become a great supplier in international natural gas markets. Transferring natural gas through the pipeline or transporting it in the liquefied form are the main options for natural gas trades in international markets. The geographical location of Iran in the Middle East makes it possible for Iran to export natural gas to Europe through the pipeline. In this trade two main issues should be considered. The pipeline should pass through Turkey and Russia as the main supplier has great bargaining power in the market. Trades in the natural gas market are restricted by the pipeline structure. So these markets can be considered a network and pipelines as the links of the network. Jackson (2005) introduced the link-based flexible networks method that can be used for the analysis of cooperative network games. In this paper, the effect of a coalition between Russia and Iran on the relative bargaining power of Iran, Russia, and Turkey have been studied. According to the results, Turkey, as the only available path to Europe, has considerable bargaining power and the coalition between Iran and Russia will have no effect on it. As Iran has no other choice to export natural gas to Europe through the pipeline, the coalition will have no effect on Iran’s bargaining power.
https://ecoj.tabrizu.ac.ir/article_9363_3db1d563a320164e908992bd72fad15a.pdf
2019-11-22
103
134
Natural gas
Iran
Russia
Turkey
Europe
Network Game
Alireza
Fayazi
fayazi@semnan.ac.ir
1
Economics Department, Faculty of Economics and management, Semnan University, Semnan, Iran
LEAD_AUTHOR
ْGhahraman
Abdoli
abdoli@ut.ac.ir
2
Associate Professor, Faculty of Economics, University of Tehran
AUTHOR
Esmaiel
Abounoori
e.abounoori@profs.semnan.ac.ir
3
Professor of Economics, Semnan University
AUTHOR
تکلیف، عاطفه (1391). امکانپذیری همکاری یا رقابت بین اعضای مجمع کشورهای صادرکننده گاز در صادرات گاز طبیعی از طریق خط لوله. اقتصاد محیطزیست و انرژی، 2(5)، 49-79.
1
تکلیف، عاطفه (1392). ساختار مجمع کشورهای صادرکننده گاز: عدم تجانس اعضا و معیارهای رتبهبندی آنها در اثرگذاری بر بازار گاز. فصلنامه اقتصاد انرژی ایران، 2(8)، 45-67.
2
جعفرزاده، امیر، شاکری، عباس، مؤمنی، فرشاد، و عبدلی، قهرمان (1393). تحلیل همکاری میان ایران و ترکمنستان در صادرات گاز به اروپا از طریق خط لوله نوباکو: چارچوب نظریه بازی همکارانه. پژوهشنامه اقتصاد انرژی ایران، 3(12)، 117-144.
3
شهریار، بهنام (1388). تحلیل حساسیت بازار گاز طبیعی اروپای غربی با رویکرد نظریه بازی. مطالعات اقتصاد انرژی، 6(22)، 167-186.
4
شهریار، بهنام، صیاد زاده، علی، و خسروی، عبدالحمید (1387). بررسی مدلهای چانهزنی در صادرات گاز طبیعی ایران به اروپای غربی با رویکرد مدل VECM. پژوهشهای اقتصادی، 8(2)، 133-147.
5
عبدلی، قهرمان (1391). نظریه بازیها و کاربردهای آن (بازیهای اطلاعات ناقص، تکاملی و همکارانه). تهران: سمت.
6
عبدلی، قهرمان (1390). نظریه بازیها و کاربردهای آن (بازیهای ایستا و پویا با اطلاعات کامل). تهران: جهاد دانشگاهی.
7
گلستانی، شهرام، هاتفی مجومرد، مجید، و جلالی، امالبنین (1392). مدلهای رهبری قیمت و تبانی در کارتل گازی با استفاده از الگوریتم ژنتیک. اقتصاد محیطزیست و انرژی، 2(6)، 151-182.
8
منظور، داوود، و یوسفی، حسن (1393). ترانزیت گاز ایران به اروپا: رویکرد نظریه بازی. مطالعات اقتصاد انرژی، 10(43)، 21-45.
9
مهدوی عادلی، محمدحسین، فلاحی، محمدعلی، عبدلی، قهرمان، و دهنوی، جلال (1391). تدوین بازی همکارانه بین کشورهای عضو مجمع کشورهای صادرکننده گاز در زمینه صادرات گاز از طریق خط لوله. مطالعات اقتصاد انرژی، 9(35)، 1-21.
10
Abdoli, G. (2011). Game theory and its application . Tehran: Jahat.(In Persian).
11
Abdoli, G. (2013). Game theory and its application. Tehran: Samt (In Persian).
12
ACER. (2015). Gas infrastucture unit investment costs. Agency for Cooperation of Energy Regulators.
13
British Petroleum Company. (2017). BP statistical review of world energy. London: BP P.L.C.
14
Chaczykowski, M., Osiadacz, A., & Uilhoorn, F. (2011). Exergy-based analysis of gas transmission system with application to Yamal-Europe pipeline. Applied Enegy, 88(6), 2219-2230.
15
Cobanli, O. (2014). Central Asian gas in Eurasian power game. Energy Policy, 68, 348-370.
16
Gabriel, S., Rosendahl, K., Egging, R., Avetisyan, H., & Siddiqui, S. (2012). Cartelization in gas markets: Studying the potential for a “Gas OPEC”. Energy Economics, 34(1), 137–152.
17
Golestani, S., Hatefi majomard, M., & Jalali, O. (2014). Price leadership and collusion models in gas cartel with use of genetic algorithm. JIEE, 2(6), 151-182 (In Persian).
18
Holz, F., Brauers, H., Richter, P., & Roobeek, T. (2016). Shaking Dutch grounds won’t shatter the European gas market. Energy Economics, 64, 520-529.
19
Holz, F., von Hirschhausen, C., & Kemfert, C. (2008). A strategic model of European gas supply (GASMOD). Energy Economics, 30(3), 766-788.
20
Hubert, F., & Orlova, E. (2018). Network access and market power. Energy Economics, 76, 170-185.
21
Jackson, M. O. (2005). Allocation rules for network games. Games and Economic Behavior, 51, 128–154.
22
Jafarzadeh, A., Shakeri, A., Momeni, F., & Abdoli, G. (2014). Exploring cooperation between Iran and Turkmenistan for natural gas exporting via Nabucco pipeline: A co-operative game theory framework. JIEE, 3(12), 144-177 (In Persian).
23
Jansen, T., van Lier, A., van Witteloostuijn, A., & von Ochsse´e, T. (2012). A modified Cournot model of the natural gas market in the European Union: Mixed-motives delegation in a politicized environment. Energy Policy, 41, 280-285.
24
Mahdavi Adeli, M., Falahi, M., Abdoli, G., & Dehnavi, J. (2013). Presenting a cooperative game between the members of exporting countries forum for export of gas through pipeline: A game theory analysis. Quarterly Energy Economics Review, 9(35), 1-22 (In Persian).
25
Nagayama, D., & Horita, M. (2014). A network game analysis of strategic interactions in the international trade of Russian natural gas through Ukraine and Belarus. Energy Economics, 43, 89–101.
26
Shahreaar, B., Sayyadzadeh, A., & Khosravi, A. (2008). Bargaining models of the Iranian natural gas exports to western Europe: A VECM approach. ECOR, 8(2), 119-132 (In Persian).
27
Shariar, B. (2009). Sensitivity analysis of west European natural gas market: A game theory approach. Quarterly Energy Economics Review, 6(22), 167-186 (In Persian).
28
Taklif, A. (2012). The feasibility of competition or cooperation amongst GECF member countries in exporting natural gas via pipeline. jiee, 2(5), 49-79 (In Persian).
29
Taklif, A. (2014). The structural of gas exporting countries forum: heterogeneity of member countries and criteria for ranking them regarding their impacts on gas market. jiee, 2(8), 45-67 (In Persian).
30
Yousefi, H., & Manzoor, D. (2015). Iran’s gas transit to Europe: A game theoretic approch. QEER, 10(43), 21-45 (In Persian).
31
ORIGINAL_ARTICLE
An Introduction to Agent Based Modeling and Agent Based Computational Economics; A Simple Model for Markets Where Consumers are Imperfectly Informed
This paper introduces Agent Based Modeling (ABM) approach in social sciences especially in economics. By comparing the restrictions of mainstream economic models to those of agent based models we explain the benefits and capacities of using agent based modeling in economics named Agent based Computational Economics (ACE). Due to this restrictions and over simplifying assumptions in traditional models, sometimes economic policy makers cannot trust the results of these models because those assumptions caused them to be far from reality especially in case of abnormality and non-equilibrium. ACE is one of the so many efforts of economist to reduce this gap between economic models and economic realities. We enumerate some of the economic issues such as non-equilibrium, heterogeneity, learning and bounded rationality, nonlinearity, local interaction, network structure, complexity, aggregation failure and holism, and we explain the capacities of ACE to face with each of these issues. Finally we present a simple agent based model to deal with Markets Where Consumers are imperfectly informed about products quality
https://ecoj.tabrizu.ac.ir/article_8918_035c8d682d97c6ab1ba2aa8bed813975.pdf
2019-11-22
135
164
Agent Based Modelling (ABM)
Agent Based Computational Economics (ACE)
Simulation
complexity
Mohsen
Karimi
andanikarimi@gmail.com
1
Associate Professor of Economics, Allameh Tabataba’i University
AUTHOR
Teymoor
Mohammadi
mohammadi@atu.ac.ir
2
Associate Professor of Economics, Allameh Tabataba’i University
LEAD_AUTHOR
Arthur, W. B. (2006). Chapter 32 Out-of-Equilibrium Economics and Agent-Based Modeling. Handbook of Computational Economics. 2:1551-1564.
1
Axtell, R. (2003). Economics as Distributed Computation. Meeting the Challenge of Social Problems via Agent-Based Simulation: Post-Proceedings of the Second International Workshop on Agent-Based Approaches in Economic and Social Complex Systems. Springer Japan: 3-23.
2
Bedau, M. A. (2002). weak emergence. Principia, 6(1): 5
3
Blume, L. E. and S. N. Durlauf (2005). The Economy As an Evolving Complex System, III: Current Perspectives and Future Directions, Oxford University Press.
4
Epstein, J. M. (2006). Remarks on the foundations of agent-based generative social science. Handbook of computational economics, 2: 1585-1604.
5
Gode, D. K. and S. Sunder (1993). Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality. Journal of Political Economy 101(1): 119-137.
6
Gourieroux, C. and A. Monfort (1997). Simulation-based Econometric Methods, Oxford University Press.
7
Hofstadter, D. R. (1979). Godel, Escher, Bach: An Eternal Golden Braid, Basic Books, Inc.
8
Holland, J. H. (1995). Hidden order: how adaptation builds complexity, Addison Wesley Longman Publishing Co., Inc.
9
Kirman, A. P. (1992). Whom or What Does the Representative Individual Represent? The Journal of Economic Perspectives, 6(2): 117-136.
10
Page, S. E. (2012). Aggregation in agent-based models of economies. The Knowledge Engineering Review, 27(2): 151-162.
11
Richiardi, M., R. Leombruni, N. J. Saam and M. Sonnessa (2006). A Common Protocol for Agent-Based Social Simulation. Journal of Artificial Societies and Social Simulation, 9(1)..
12
Richiardi, M. G. (2012). Agent-based computational economics: a short introduction. The Knowledge Engineering, 27(2): 137-149.
13
Richiardi, M. G. (2017). The Future of Agent-Based Modeling. Eastern Economic Journal, 43(2): 271-287.
14
Smallwood, D. E. and J. Conlisk (1979). Product Quality in Markets Where Consumers are Imperfectly Informed. The Quarterly Journal of Economics, 93(1): 1-23.
15
Tesfatsion, L. J., K. L. (eds) (2006). Handbook of Computational Economics, Elsevier.
16
ORIGINAL_ARTICLE
Optimal Allocation of Zayanderood River AmongChaharmahal&Bakhtiary, Yazd and Isfahan Provinces
Water of Zayandehrood River is used as rival in the agriculture, industry and domestic sectors of Chaharmahal & Bakhtiari, Isfahan and Yazd provinces. In this study we answer to this question: How water resources must be optimally allocated among these sectors? In this regards game theory, a nonlinear programming model and demand functions in 2013 were used to maximize the consumers’ surplus in domestic sector of all provinces, agricultural sector of Isfahan and Chaharmaha l& Bakhtiari and the industry sector of Isfahan province. The different forms of cooperation as triple and dual form of coalitions were investigated and the existence of core was checked. The results showed that in the cooperative scenario among the different sectors of the three provinces, the consumer surplus will increase 2.95% compare to the non-cooperation scenario. In the cooperative scenario the consumer surplus will be increased respectively 6.1% and 0.09% in the Isfahan and Yazd provinces, whereas decreased 24.49% in Chaharmahal & Bakhtiary province. However, this consumer surplus reduction can be compensated from increased surplus in two other provinces. If the allocation forms in the Shapley structure in triple coalition among the players, the allocation will be located in the core and the automatic mechanism will be created that finally forms the Triple coalition
https://ecoj.tabrizu.ac.ir/article_9425_703798874f5b3b48d6a3f58bc396bd3a.pdf
2019-11-22
165
188
game theory
Efficient allocation
Shaply value
Surplus
Zayanderood
Gholam Hossain
Kiani
gh.kiani@ase.ui.ac.ir
1
Assistant Professor of Economics, University of Isfahan
LEAD_AUTHOR
Rahman
Khosh Akhlagh
rahmankh@yahoo.com
2
Professor of Economics, University of Isfahan
AUTHOR
Mohammad Mahdi
Kamal
mm.perfection@yahoo.com
3
Ph.D. Candidate in Economics, University of Isfahan
AUTHOR
استانداری اصفهان (1394). طرح آمایش سرزمین، گزارش فرابخش آب. استانداری اصفهان.
1
پورزند، فرناز، و زیبایی، منصور (1390). کاربرد نظریه بازیها در تعیین میزان برداشت بهینه از سفرههای آبهای زیرزمینی دشت فیروزآباد. اقتصاد کشاورزی و توسعه، 4(20)، 24-1.
2
حاجیان، ناصر، و حاجیان، پوریا (1392) پایگاه داده های زاینده رود. پژوهشگاه شاخص پژوه، اصفهان.
3
خوشاخلاق، رحمان (1378). اقتصاد منابع طبیعی. جهاد دانشگاهی.
4
شرقی عبدالعلی، و کیانی غلامحسین (1389). سالنامه آماری آب کشور 87-1386، وزارت نیرو.
5
مرکز آمار ایران (1392). سالنامه اماری کشور، ایران.
6
صالحی، فرزانه، دانشور، محمود، شاه نوشی, ناصر، و ژاله رجبی، میترا (1389). کاربرد نظریه بازیها در تعیین میزان برداشت بهینه از منابع آب زیرزمینی دشت تایباد. اقتصاد کشاورزی و توسعه، 3(15)، 65–89.
7
صبوحی، محمود، و مجرد، عصمت (1389). کاربرد نظریه بازیها در مدیریت منابع آبهای زیرزمینی حوزه آبریز اترک. اقتصاد و توسعه کشاورزی، 24(1)، 1–12.
8
عبدلی، قهرمان (1395). نظریه بازیها و کاربردهای آن. تهران، انتشارات جهاد دانشگاهی.
9
کمال، محمد مهدی (1394). تخصیص بهینه آب زایندهرود بین استانهای چهارمحال بختیاری، اصفهان و یزد بهوسیله نظریه بازیها. پایان نامه کارشناسیارشد، دانشگاه اصفهان.
10
کیانی، غلامحسین (1395). نقش بازار در تخصیص بهینه منابع آب و عوامل موثر بر کارائی بازار آب. آب و توسعه پایدار، 3(1)، 93-102.
11
Abdoli, G. (2016). Descriptive solution manual and applicable problems in game theory. JahadDaneshgahi Press (In Persian).
12
Ahmadi, A., & Moreno, R. S. (2013). Game theory applications in a water distribution problem. Journal of Water Resource and Protection, 5(01), 91.
13
Dinar, A., Rosegrant, M. W., & Meinzen-Dick, R. (1997). Water allocation mechanisms, principles and examples. The World Bank.
14
Hajian, N., & Hajian, P. (2013). The database of Zayandehroud. ShakhesPajouh Institution. Isfahan (In Persian).
15
Kamal, M. M. (2015). Optimal allocation of Zayandehroud water among Chaharmahal & Bakhtiari, Isfahan and Yazd provinces using game theory. Msc. Thesis, University of Isfahan (In Persian).
16
Khoosh Akhlagh, R. (1998). Natural resources economics. JahadDaneshgahi Press (In Persian).
17
Kiani, G. H. (2016). The role of market in optimal water resources allocation and efficacious factors influencing the efficiency of water markets. Journal of Water and Sustainable Development, 3 (1), 93-102 (In Persian).
18
Madani, K. (2010). Game theory and water resources. Journal of Hydrology, 381(3-4), 225-238.
19
Podimata, M. V., &Yannopoulos, P. C. (2015). Evolution of game theory application in irrigation systems. Agriculture and Agricultural Science Procedia, 4, 271-281.
20
Pourzand, F., &Zibaei M. (2012). Application of game theory for the optimal groundwater extraction in Firozabad plain Agricultural Economics, 5(4), 1-24 (In Persian).
21
Provincial Government of Isfahan, (2015). Land use planning project (In Persian).
22
Salehi, F., Daneshvar, M., Shahnoushi, N. & JalehRajabi M. (2010). Application of game theory in determination of optimal groundwater extraction in Taybad Plain. Agricultural Economicst, 3 (15), 65-89 (In Persian).
23
Sedghamiz, A., Nikoo, M. R., Heidarpour, M., & Sadegh, M. (2018). Developing a non-cooperative optimization model for water and crop area allocation based on leader-follower game. Journal of Hydrology, 567, 51-59.
24
Sharghi A., & Kiani G. H. (2010). Iran water statistical yearbook. Ministry of Energy (In Persian).
25
Sobuhi M., & Mojarad, E. (2010).Application of game theory for groundwater resources management of Atrak, Agricultural Economics & Development, 24(1), 1-12 (In Persian).
26
Statistical Center of Iran (2013). Statistical yearbook, Iran (In Persian).
27
Wang, L., Fang, L., & Hipel, K. W. (2008). Basin-wide cooperative water resources allocation. European Journal of Operational Research, 190(3), 798-817.
28
Wei, S., Yang, H., Abbaspour, K., Mousavi, J., & Gnauck, A. (2010). Game theory based models to analyze water conflicts in the Middle Route of the South-to-North Water Transfer Project in China. Water research, 44(8), 2499-2516.
29
World Health Organization (2015). Technical Notes On Drinking-Water. Sanitation And Hygiene In Emergencies: Planning for Excreta Disposal in Emergencies.
30
Zeng, Y., Li, J., Cai, Y., Tan, Q., & Dai, C. (2019). A hybrid game theory and mathematical programming model for solving trans-boundary water conflicts. Journal of Hydrology, 570, 666-681.
31
ORIGINAL_ARTICLE
Investigating the Effect of Housing Prices on Non-Performing Loans in Banking System of Iran
Emersion of Non-performing Loan is one of the effects monetary activities of credit institutions. A phenomenon that has a negative impact on the Bank Resources and Uses. Housing price changes is one of the most important factors affecting on NPL. The boom and Recession of the housing sector, can be effective on the repayment ability of the received loans. In this study, using the model (tajik et al, 2015), it is attempting to examine the effect of housing prices on non-performing loans in the banking sector. For this purpose, a dynamic panel model was used for a sample of 15 banks during the period of 2005-2016 using generalized moments method. The results of this study shows that the growth rate of housing price changes and the growth rate of gross domestic product without oil has a negative and significant effect, and unemployment rate has a positive effect on the ratio of NPL. Also the analysis of inter banking factors shows that the ratio of Non-performing Loan has a positive and significant relation with the ratio of loan to assets, the ratio of cost to income and bank size. There was no meaningful relation between the ratio of given loans to the building and housing sector to the total loans and the NPL.
https://ecoj.tabrizu.ac.ir/article_9467_80e19fdb000b5f3b24d6e9b87cfae219.pdf
2019-11-22
189
214
House prices
Non-Performing Loan
generalized moments method
Aliakbar
Gholizadeh
a.gholizadeh@basu.ac.ir
1
Associate Professor of Economics, University of Buali Sina
AUTHOR
Siavash
Golzarian Pour
s.golzarian@ibi.ac.ir
2
Assistant Professor of Economics, Iran Banking Institute
LEAD_AUTHOR
fariba
Shakouri
shakoory68@gmail.com
3
MA in Banking
AUTHOR
حیدری، هادی، و زواریان، زهرا (1390). بررسی اثر شاخصهای کلان اقتصادی بر مطالبات معوق بانکها. فصلنامهپولواقتصاد، 4، 219-191.
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4
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محمدزاده، امیر محمد، عطائی، محمد، و سلیمی، حسین (1392). شناسایی و الویت بندی موانع وصول مطالبات معوق بانکی با استفاده از مدل ترکیبی دیمتل شبکه ای و ویکور. فصلنامهمدیریتتوسعهوتحول، 16، 26-15.
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8
واعظ، محمد، امیری، هادی، و حیدری، مهدی (1390). تاثیر چرخههای تجاری بر نرخ نکول تسهیلات بانکی ایران طی دوره 1388-1379 و تعیین سبد بهینه تسهیلات برای کل نظام بانکی. فصلنامه پول و اقتصاد، 7، 76-41.
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20
Gholizadeh, A. and Bakhtiyaripour, S. (2010). The effect of credits on housing prices in Iran. Journal of Applied Economics Studies, 3, 159-179. (In Persian).
21
Gholizadeh, A. and Shalyari, F. (2017). The Investigation of macroeconomic variables effect on credit risk Iranian banking system. mieaoi. 17 (20), 183-200. (In Persian).
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Mohammadzadeh, A, Ataei, M and Salimi, H. (2014). Identification and prioritization of barriers to collecting deferred bank claims using the Diethyl Network and Vicoure. Quarterly Journal of Development Evolution Managements, 16, 15-26. (In Persian).
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Moscone, F., Tosetti, E and Canepa, A. (2014). Real estate market and financial stability in US metropolitan areas: A dynamic model with spatial effects. Regional Science and Urban Economics, 49, 129–146.
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Pan, H and Wang, C. (2013). House prices, bank instability, and economic growth: evidence from the threshold model. Journal of Banking & Finance, 37 (5), 1720-1732.
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37
ORIGINAL_ARTICLE
Investigating the Mutual Relation between Entrepreneurship in Manufacturing Sector, Economic Growth and Employment in Iran Using SUR and SVAR Methods
The present study investigates the relation between entrepreneurship in Manufacturing sector, economic growth and employment rate in the Iranian economy, using the vector Auto-regressive model, using the Seemingly Unrelated Regression method and short-run Structural Vector Auto-Regressive model. According to the dependence of the Iranian economy on oil exports, sanctions and fluctuations in oil price in recent years have reduced economic growth in Iran. Entrepreneurship in the industry according to the young population of Iran, can lead to increase capacity in manufacturing sector, which in turn can have a positive impact on increasing non-oil exports and reduce the dependence of the Iranian economy on oil revenue. After estimating the model using annual data from 1959 to 2016, the results show that entrepreneurship in industrial sector has a positive effect on economic growth with six periods of lag and employment rate with five periods of lag in Iranian economy. Therefore, entrepreneurship can have a positive effect on employment and economic growth if new businesses are created for sequential periods and not closed for at least six years. Employment rate has a positive effect on entrepreneurship in the industrial sector and economic growth with two periods of lag. The results for the short-run SVAR pattern reflect the positive effect of economic growth on employment. Therefore, increasing economic growth can have a positive effect on employment rate in the current term
https://ecoj.tabrizu.ac.ir/article_9422_f25dc799264951dd5e583810ee893502.pdf
2019-11-22
215
240
Entrepreneurship
new company formation
Economic growth
Employment
VAR model
Masoumeh
Motallebi
masoumehmotallebi@yahoo.com
1
Ph.D in Economics, Lorestan University
AUTHOR
Mohammad
Alaizadeh
alizadeh.m@lu.ac.ir
2
Associate Professor of Economics, Lorestan University
LEAD_AUTHOR
Mohsen
Nazari Farsani
mohsen.nazari.f70@gmail.com
3
Ph.D Candidate in Economics, Allameh Tabataba’i University
AUTHOR
بهشتی، محمدباقر، خیرآور، حسن، و قزوینیان، محمد حسن (1388). بررسی رابطه علی بین کارآفرینی و بیکاری در بخش صنعت ایران (1385-1364). مدیریت بهرهوری، 3(11)، 157-183.
1
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2
شیرینبخش، شمساللّه، و صلویتبار، شیرین (1395). پژوهشهای اقتصادسنجی با Eviews 8 & 9. تهران: انتشارات نورعلم.
3
صباحی، احمد، ناجیمیدانی، علیاکبر، و سلیمانی، الهه (1392). بررسی اثر کارآفرینی بر رشد اقتصادی در کشورهای منتخب. فصلنامه علمی پژوهشی پژوهشهای رشد و توسعه اقتصادی، 3(11)، 9-18.
4
کمیجانی، اکبر، سهیلی احمدی، حبیب، و قربانی، پوریا (1391). نگاهی به نقش عوامل مؤثر اقتصاد کلان در ترکیب انگیزشی کارآفرینان. فصلنامه علمی پژوهشی برنامهریزی و بودجه، 17(1)، 49-72.
5
مهربانی، فاطمه، عبداللهی، فرشته، و بصیرت، مهدی (1395). اثر فضای کسبوکار بر رشد اقتصادی ایران، کشورهای MENA و OECD با استفاده از روش گشتاور تعمیمیافته. فصلنامه سیاستهای راهبردی و کلان، 4(13)، 65-96.
6
مودتی، مهدیه، ترابی، نقی، معمارنژاد، عباس، و محمودزاده، محمود (1397). عوامل نهادی رسمی و غیررسمی، کارآفرینی فرصتگرا و رشد اقتصادی به روش گشتاور تعیمیافته. نشریه توسعه کارآفرینی، 11(3)، 521-539.
7
Acs, Z.J., & Armington, C. (2004). Employment growth and entrepreneurial activities incities. Regional studies, 38, 911-927.
8
Acs Z.j., Audretsch, D. B., Braunerhjelm p., & Carlsson, B. (2004). The knowledge filter and entrepreneurship in endogenous growth. Discussion paper on Entrepreneurship, Growth and Public Policy Nr 0805, Max Planck Institute, Jena.
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12
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13
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14
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21
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24
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27
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28
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29
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30
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31
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33
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37
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38
ORIGINAL_ARTICLE
Identifying the Factors Affecting the Recession in Iran: Monte Carlo Simulation and Metropolis-Hastings (MH) Algorithm
Changes in macroeconomic indices and variables such as the decline in GDP, the decline in oil exports, and the exchange rate fluctuation indicate a period of recession in the Iranian economy. In this paper, the Monte Carlo Markov Chain (MCMC) and the MH algorithm are used to identify the factors that contributed to this recession during the years 0-1. The studies show that the results of MH algorithm confirm the model estimation results using Monte Carlo Markov chain approach and at 95% confidence level, the coefficients of the variables are statistically significant and reliable. Therefore, the most influential variables on the recession were estimated by Monte Carlo approach, exchange rate changes, crude oil prices, and government corruption. The results also show that the Bayes factor matrix for all estimation models is well-reasoned. The later probabilities of regimes and the final exponential ratio show that the change points in the sixth pattern (with variables: exchange rates, crude oil prices, government corruption and productivity) are different from the rest of the models presented, so regime change occurs in this model
https://ecoj.tabrizu.ac.ir/article_9562_acf8622386ab7c1e2c5a4afa8d8be396.pdf
2019-11-22
241
272
MH Algorithm
Monte Carlo Markov Chain
Recession
Bayes Factors
Ramiar
Refaei
ramiar_refaie@yahoo.com
1
Ph.D Student in Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
LEAD_AUTHOR
Morteza
Sameti
msameti@gmail.com
2
Professor of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
AUTHOR
Sara
Ghobadi
s_ghobadi@hotmail.com
3
Assistant Professor of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
AUTHOR
افشاری، زهرا، محمودی، نوشین، و بوستانی، رضا (1392). ارزیابی الگوی رشد نئوکلاسیک در تبیین چرخه های تجاری ایران. مطالعات اقتصادی کاربردی ایران، 3 (9)، 189-204.
1
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2
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3
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