ORIGINAL_ARTICLE
The Effect of Economic Growth on Energy Consumption in Iranian Economic Sectors
Energy as a consumer input is of particular importance in all sectors of the economy. This study aims to investigating the factors affecting on energy consumption in different sectors of the economy of the country (industry, mining, services and agriculture) using combined data during 1986-2016. To achieve this goal were used of panel cointegration analysis and to estimate short and long-run relationships from Dynamic Least Squares (DOLS) and Integrated Mean Groups (MG) test, respectively. The long-run estimation of the model states that there is a significant and positive relationship between capital and gross domestic product with energy consumption and a non-significant relationship between labor force and energy consumption. Also, the short-run relationship between all variables in the model was confirmed. The other results of the research showed that the elasticity of energy consumption in the economic sectors is positive and significant to labor force, capital and GDP in agriculture, industry and mining and services sectors.
https://ecoj.tabrizu.ac.ir/article_7748_9340b8e93ff1f90248b8567857dab1b0.pdf
2018-11-22
1
20
energy consumption
Economic growth
Labor Force
MG
DOLS
Aboalghasem
Mortazavi
samortazavi@modares.ac.ir
1
Assistant Professor of Agricultural Economics, Tarbiat Modares University
LEAD_AUTHOR
Mehdi
Elahi
elahi.mehdi2007@gmail.com
2
MA. Student of Agricultural Economics, Tarbiat Modares University
AUTHOR
Mohammad Ali
Assadi
a.asaadi68@yahoo.com
3
PH.D Student of Agricultural Economics, Tarbiat Modares University
AUTHOR
ابریشمی، حمید (1388). اقتصادسنجی کاربردی: رویکردهای نوین. انتشارات دانشگاه تهران. ص 348.
1
آرمن، سید عزیز، و زارع، روح اله (1388). مصرف انرژی در بخشهای مختلف و ارتباط آن با رشد اقتصادی در ایران: تحلیل علیت بر اساس روش تودا و یاماموتو. مطالعات اقتصاد انرژی، 6(21)، 92-67.
2
آقایی، مجید، قنبری، علی، عاقلی، لطفعلی، و صادقی، حسین (1391). بررسی رابطه بین مصرف انرژی و رشد اقتصادی در استانهای ایران با استفاده از مدل همانباشتگی و تصحیح خطای پانل چند متغیره، فصلنامه اقتصاد و الگوسازی، (9)3، 185-148.
3
شهبازی، کیومرث، اصغرپور، حسین، و محرم زاده، کریم (1391). تأثیر مصرف فرآوردههای نفتی بر رشد اقتصادی در استانهای کشور. فصلنامه مدلسازی اقتصادی، 6 (17): 44-25.
4
شهنازی، روح اله، هادیان، ابراهیم، و جرگانی، لطف اله (1396). بررسی رابطه علیت میان مصرف حامل های انرژی، رشد اقتصادی و دی اکسید کربن در بخش های اقتصاد ایران. پژوهش های رشد و توسعه اقتصادی، 7(28)، 70-51.
5
علویراد، عباس، و کانور، رویا ( 1393). تأثیر مصرف انرژی بر ارزشافزوده بخشهای اقتصادی کشاورزی، صنعت و خدمات در ایران: تحلیل مبتنی بر رویکرد پنل هم جمعی. تحقیقات اقتصاد کشاورزی، 6 (3)، 19-1.
6
محسنی زنوزی، جمال، و اصغری، رعنا (1396). بررسی تأثیر آستانهای مصرف انرژی بر رشد اقتصادی کشورهای عضو اوپک حاشیه خلیج فارس. فصلنامه اقتصاد انرژی، 14 (52)، 86-61.
7
وبسایت بانک مرکزی ایران، آمار و دادهها (www.cbi.ir)
8
وبسایت مرکز آمار ایران، داده ها و اطلاعات آماری (www.amar.org.ir)
9
وبسایت وزارت نیرو، ترازنامه سالهای مختلف (www.moe.gov.ir)
10
Abrishami, H. (2009). Applied econometrics: New approaches. University of Tehran Press, p 348 (In Persian).
11
Aghaei ,M., Ghanbari, A., Agheli, L., & Sadeghi, H.(2012). Investigating the relationship between energy consumption and economic growth in Iran’s provinces using cointegration and multivariate panel error correction model. Journal of Economics and Modeling, 3(9), 148-185 (In Persian).
12
Alavirad, A., & Kanoor, R. (2014). Effects of energy consumption on value added of various sectors of Iranian economy. Journal of Agricultural Economics Research, 6(23), 1-11 (In Persian).
13
Arman, S. A., & Zare, R. A. (2009). Energy consumption in different sectors and its relation to economic growth in Iran: Application of Toda-Yamamoto test. QuarterlyEnergyEconomics Review, 6(21), 67-92 (In Persian).
14
Asghari, R., & Mohseni Zonouzi, S. J. (2017). An investigation of the threshold effect of energy consumption on economic growth in OPEC members countries. Quarterly Energy Economics Review, 14 (52) :61-86 (In Persian).
15
Berndt, E. R., & Wood, D. O. (1975). Technology, prices, and the derived demand for energy. The review of Economics and Statistics, 259-268.
16
Central Bank of Iran (www.cbi.ir).
17
Chen, L. (2011). The effect of China's RMB exchange rate movement on its agricultural export: A case study of export to Japan. China Agricultural Economic Review, 3(1), 26-41.
18
Chontanawat, J., Hunt, L. C., & Pierse, R. (2006). Causality between energy consumption and GDP: evidence from 30 OECD and 78 non-OECD countries (No. 113). Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
19
Côté, A. (1994). Exchange rate volatility and trade. Bank of Canada Work. Pap, 94-5.
20
Engle, R. (2001). GARCH 101: The use of ARCH/GARCH models in applied econometrics. Journal of economic perspectives, 15(4), 157-168.
21
Ghali, K. H., & El-Sakka, M. I. (2004). Energy use and output growth in Canada: a multivariate cointegration analysis. Energy economics, 26(2), 225-238.
22
Ghali, K. H., & El-Sakka, M. I. (2004). Energy use and output growth in Canada: a multivariate cointegration analysis. Energy economics, 26(2), 225-238.
23
Granger, C. W., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of econometrics, 2(2), 111-120.
24
Kao, C., & Chiang, M. H. (2001). On the estimation and inference of a cointegrated regression in panel data. In Nonstationary panels, panel cointegration, and dynamic panels (pp. 179-222). Emerald Group Publishing Limited.
25
Kim, D. H., Lin, S. C., & Suen, Y. B. (2010). Dynamic effects of trade openness on financial development. Economic Modelling, 27(1), 254-261.
26
Lee, C. C., & Chang, C. P. (2008). Energy consumption and economic growth in Asian economies: a more comprehensive analysis using panel data. Resource and energy Economics, 30(1), 50-65.
27
Maji, I. K. (2015). Does clean energy contribute to economic growth? Evidence from Nigeria. Energy Reports, 1, 145-150.
28
Ministry of Energy (www.moe.gov.ir)
29
Mtembu, M. D., & Motlaleng, G. R. (2011). The effects of exchange rate volatility on Swaziland’s exports. Review of Economic and Business Studies, 167-185.
30
Nishimura, Y., & Hirayama, K. (2013). Does exchange rate volatility deter Japan-China trade? Evidence from pre-and post-exchange rate reform in China. Japan and the World Economy, 25, 90-101.
31
Ozturk, I. (2010). A literature survey on energy–growth nexus. Energy policy, 38(1), 340-349.
32
Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric theory, 20(3), 597-625.
33
Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of econometrics, 68(1), 79-113.
34
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634.
35
Shahbazi, K., Asgharpur, H., & Moharramzadeh, K. (2011). Impact of oil different products consumption on economic growth in Iran provinces. Quartery Journal of Economical Modeling, 6 (17), 25-44 (In Persian).
36
Shahnazi, R., Hadian, E., & Jargani, L. (2017). An investigation of energy consumption, economic growth and CO2 emission in the Iranian economic sectors. Quarterly Journal of Economic Growth and Development Research, 7(28), 51-70 (In Persian).
37
Statistical Center of Iran (www.amar.org.ir)
38
Stern, D. I. (1993). Energy and economic growth in the USA: a multivariate approach. Energy economics, 15(2), 137-150.
39
Tang, C. F., Tan, B. W., & Ozturk, I. (2016). Energy consumption and economic growth in Vietnam. Renewable and Sustainable Energy Reviews, 54, 1506-1514.
40
Wang, S., Li, Q., Fang, C., & Zhou, C. (2016). The relationship between economic growth, energy consumption, and CO2 emissions: Empirical evidence from China. Science of the Total Environment, 542, 360-371.
41
Zhixin, Z., & Xin, R. (2011). Causal relationships between energy consumption and economic growth. Energy Procedia, 5, 2065-2071.
42
ORIGINAL_ARTICLE
Study of Non-linear Relationship between Income Inequality and Economic Growth: A Case of Iran
The purpose of this paper is to investigate the effect economic growth to income inequality, both in linear and non-linear specification. Autoregressive distributed lag model (ARDL) approach has been used co-integration method for long run relationships and error correction model (ECM) for short run behavior. The paper has used annual time series data over the period of 1978 up to 2016. Empirically, our baseline estimation and sensitivity analyzes have indicated the inequality is negatively and significantly, associated with economic growth in long run. Our finding is contrast to the Kuznets inverted- U and support for the existence of Kuznets U as well as S- shaped curve in Iran. This paper opens up new direction for policy-making authorities to equalize income distribution and understanding the economic situation in the development process. This paper makes a unique contribution to the literature with reference to Iran, being a pioneer attempt that employs ARDL co-integration approach.
https://ecoj.tabrizu.ac.ir/article_7746_a8f02f08f819bc185a12d874389cac5c.pdf
2018-11-22
21
42
Economic growth
Income distribution
Kuznets curve
Sakineh
Ashrafi
sm.ashrafi90@gmail.com
1
Ph.D. Candidate in Economics, University of Tabriz
LEAD_AUTHOR
Davood
Behbudi
dbehbudi@tabrizu.ac.ir
2
Professor of Economics, University of Tabriz
AUTHOR
Farhad
Dejpasand
f_dejpasandi@sbu.ac.ir
3
Associate Professor of Economics, University of Shahid Beheshti
AUTHOR
حسین زاده، هدایت (1396). تأثیر رشد اقتصادی بر توزیع درآمد در کشورهای منطقه خاورمیانه و شمال آفریقا: رهیافت اقتصادسنجی فضایی. فصلنامه پژوهشها وسیاستهای اقتصادی، 82(2)، 233 - 260.
1
عظیمی، حسین (1373). نگاهی به مسئله فقر و محرومیت در ایران. انتشارات کمیته امداد امام خمینی، تهران.
2
مهرگان، نادر، و زمانی شیخانه، صابر (1392). بررسی اثر شهرنشینی بر توزیع درآمد در ایران با تأکید بر نظریه کوزنتس. فصلنامه برنامهریزی و بودجه، 18(3)، 3-19.
3
ناجی میدانی، علیاکبر (1374). بررسی آثار متقابل رشد اقتصادی و توزیع درآمد در ایران. پایان نامه کارشناسی ارشد، دانشگاه تربیت مدرس.
4
نیلی، مسعود (1376). اقتصاد ایران. مؤسسه عالی پژوهش در برنامهریزی و توسعه، تهران.
5
نیلی، مسعود، و فرحبخش، علی (1377). ارتباط رشداقتصادی و توزیع درآمد. مجله برنامه و بودجه، 3(10و 11)، 154-121.
6
Aghion, P. & Bolton, P. (1992). Distribution and growth in models of imperfect capital markets. European Economic Review, 36 (2-3), 603-611.
7
Aghion, P., Caroli, E., & Garsia-Penalosa, C. (1998). Inequality and economic growth. Growth, Inequality and Globalization: Theory, History and Policy, 5-102.
8
Alesina, A. & Perotti, R. (1994). The political economy of growth: a critical survey of the recent literature. World Bank Economic Review, 8 (3), 351-371.
9
Alesina, A. & Roderick, D. (1994). Distributed politics and economic growth. Quarterly Journal of Economics, 109 (2), 465-490.
10
Azimi, H. (1994). A look at the issue of poverty and deprivation in Iran. Tehran: Publication of the Imam Khomeini Relief Committee, (In Persian).
11
Baltagi, B.H. & Wu, P.X. (1999). Unequally spaced panel data regression with AR (1) disturbances. Econometric Theory,15 (6), 814-823.
12
Banerjee, A.V. & Newman, A.F. (1993). Occupational choice and the process of development. Journal of Political Economy, 101(2), 274-299.
13
Bengoa-Calvo, M. & Sanchez-Robles, B. (2005). Does equality reduce growth? Some empirical evidence. Applied Economics Letters, 12(8), 479-483.
14
Benhabib, J. & Rustichini, A. (1996). Social conflict and growth. Journal of Economic Growth, 1(1), 125-142.
15
Conceicao, P. & Galbraith, J. (2001). Towards a new Kuznets hypothesis: theory a evidence on growth and inequality. Boston: Cambridge University Press, 139- 167.
16
Datt, G. & Ravallion, M. (2011). Has Indias Economic Growth Become More Pro-Poor in the Wake of Economic Reforms? World Bank Economic Review, 25(2), 157-189.
17
Ferreira, F, Leite, P. & Ravallion, M. (2010). Poverty Reduction without Economic Growth? Explaining Brazils Poverty Dynamics, 1985- 2004. Journal of Development Economics, 93(1), 20-36.
18
Halter, D., Oechslin, M. & Zweimullwer, J. (2014). Inequality and Growth: The Neglected Time Dimension. Journal of Economic Growth, 19(1), 81-104.
19
Hosseinzade, H. (2017). An analysis of effects of economic growth on income distribution in countries of Middle East and North Africa area . Quartery Journal of Economic Research and Policies, 82(2), 233-260, (In Persian).
20
Knack, S. & Keefer, P. (2000). Polarization, politics and property rights: links between inequality and growth. Washington, DC: The World Bank.
21
Kuznets, S. (1955). Economic growth and income inequality. The American Economic Review, 45(1), 1-28.
22
Kuznets, S. (1963). Quantitative aspects of economic growth of nations: III, distribution of income by size. Economic Development and Cultural Change, 11(2), 1-80.
23
Lee, K., Pesaran, M. & R., Smith (2013). Growth and Convergence in Multi Country Empirical Stochastic Solow Model. Journal of Applied Econometrics, 12(4), 357-392.
24
Li, H., Squire, L. & Zou, H. (1998). Explaining international and intertemporal variations in income inequality. Economic Journal, 108(1), 26-43.
25
Lim, C. Y. & Sek, S. K. (2014). Exploring the Two-Way Relationship between Income Inequality and Growth, Journal of Advanced Management Science, 2(1), 33-37.
26
List, J.A. & Gallet, C.A. (1999). The Kuznets curve: what happens after the inverted U?. Review of Development Economics, 3(2), 200-206.
27
Masih, A., & Masih, R. (1997). On the temporal causal relationship between energy consumtion, real income, and prices: some new evidence from Asian-energy dependent NICs based on a multivariate cointegration/ vector error -correction approach. Journal of Policy Modeling, 19(4), 417-440.
28
Mehregan, N. & Zamani-Shabkhaneh, S. (2013). The impact of urbanization on income distribution with emphasis on the Kuznets’ theory. The Journal of Planning and Budgeting, 18(3), 3-19, (In Persian).
29
Naji Meydani, A. A. (1995). Study of the interaction of economic growth and income distribution in Iran. Master thesis, Tarbiat Modarres University, Tehran, (In Persian).
30
Narayan, P., & Smyth, R. (2004). Temporal causality and the dynamic of exports, human capital and real income in china. International journal of Applied Economics, 1(2), 24-45.
31
Nili, M. (1998). Iran Economy. Institute of Research in Planning and Development, Tehran, (In Persian).
32
Nili, M. & Farahbakhsh, A. (1999). Relationship between economic growth and income distribution. The Journal of Planning and Budgeting, 3(10, 11), 121-154, (In Persian).
33
OECD (2012). Poverty Reduction and Pro-Poor Growth. Paris, France: Organisation for Economic Cooperation and Development (OECD), 26-27.
34
Panniza, U. (2002). Income inequality and economic growth: evidence from American data. Journal of Economic Growth, 7(1), 25-41.
35
Partridge, M. (2005). Dose income distribution affect US state economic growth? Journal Regional science, 45(2). 363- 394.
36
Persson, T. & Tabellini, G. (1994). Is inequality harmful for growth? The American Economic Review, 84(3), 600-621.
37
Pesaran, M. H. & Shin, Y. (1999). An autoregressive distributed lag modeling approach to cointegration analysis. Econometrics and Economic Theory in the 20th Century (p. Ch. 11). The Ragnar Frisch Centennial Symposium.
38
Pesaran, M.H., Shin, Y. & Smith, R.J. (1996). Testing for the existence of a long-run relationship. Cambridge: Department of Applied Economics, University of Cambridge.
39
Pesaran, M. H. & Smith, R. (2014). Signs of Impact Effects in Time Series Regression Model . Economics Letters, 122( 2), 150- 153.
40
Raza, S. A. & Shah, N. (2017). Tourism growth and income inequality: does Kuznets Curve hypothesis exist in top tourist arrival countries. Journal Asia Pacific Journal of Tourism Research, 22 (8), 874-884.
41
Rubin, A. & Segal, D. (2015). The effects of economic growth on income inequality in the US. Journal of Macroeconomics, 45(C), 258-273.
42
Shibalee, M. & Partridge, M. D.(2009). Impact of economic growth on income inequality: a regional perspective. Selected Paper prepared for presentation at the Agricultural and Applied Economics, 1-12.
43
Sinha, N. (2004). Growth, inequality and structural adjustment: an empirical interpretation of the S-curve for Indian economy,. ASARC Working Paper16.
44
Tribble, R. (1996). The Kuznets-Lewis process within the context of RCAE and class in the US economy. International Advances in Economics Research, 2(2), 151-164.
45
ORIGINAL_ARTICLE
Investigating Iran and Saudi Arabia Behavior in OPEC Using the Markov Switching Model
After establishment of OPEC in 1960, a new era of competition was emerged between world’s two big oil producers, e.i., Iran and Saudi Arabia, and from then, OPEC’s internal changes and their reflections on the international atmosphere were affected by the intensive competitions arising between OPEC’s two outstanding members Thus, Iran and Saudi Arabia are recognized as two significant and forceful countries in OPEC organization. So, studying and analyzing the behaviors of these two countries in OPEC and global oil market is of great importance. This paper examines Iran-Saudi Arabia behavior in OPEC using monthly data between 1973:1-2015:12. To this end, estimations were initially developed using Griffin’s linear model, then they were conducted using Markov Switching’s method with fixed transition probability. Results of the fixed transition probability indicated that Iran-Saudi Arabia behavior was nonlinear and a collusion regime is applied for Iran’s behavior while a competitive regime is applied for Saudi Arabia’s one. In other words, during the research period, Iran’s behavior in OPEC has often been in complianc and competent with other members and based on the agreement, collusion and Cartel’s rules, yet Saudi Arabia’s behavior has been against Cartel’s rules and it was based on competition. Moreover, findings indicated that the length of remaining of Iran in the collusion regime was approximately 217 months and that in the competitive regime was approximately 13 months. Anyway, Saudi Arabia stayed approximately 40 and 68 months in the collusion regime and competitive one, respectively. As a result, in this research period, the probability of Iran’s staying in the Collusion regime is far more from its staying probability in the competitive regime. Yet, the probability of Saudi Arabia’s staying in the competitive regime is more than its staying in the collusion regime.
https://ecoj.tabrizu.ac.ir/article_7767_ecf3d35f3935ef2c8dbafdd4dc2382f3.pdf
2018-11-22
43
74
Iran
Saudi Arabia
OPEC
Collusion
Competitive
Markov regime-switching
Rouhollah
Nazari
rnazari2004@gmail.com
1
Ph.D Candidate in Economics, International Campus of Ferdowsi University of Mashhad
AUTHOR
Mehdi
Khodaparast Mashhadi
m_khodaparast@um.ac.ir
2
Associate Professor of Economics, Ferdowsi University of Mashhad, Mashhad
AUTHOR
Ahmad
Seifi
spring05@um.ac.ir
3
Associate Professor of Economics, Ferdowsi University Of Mashhad, Mashhad, Iran
LEAD_AUTHOR
استقامت، فاطمه (1383). اوپک (سازمان کشورهای صادرکننده نفت)، تهران، وزارت امور خارجه، دفتر مطالعات سیاسی و بینالمللی.
1
امامیمیبدی، علی، حقدوست، احساناله، و پاکدین، جواد (1389). آزمون پایداری رشد در مورد منابع تجدیدناپذیر (بازبینی مدل هتلینگ) مطالعه موردی نفت اوپک، پژوهشهای اقتصادی ایران، 42، 167-149.
2
تکلیف، عاطفه (1389)، استراتژی بلندمدت اوپک با توجه به تحولات بازار جهانی نفت، فصلنامه راهبرد، 57، 154-133.
3
جمشیدیرودباری، مستانه (1387). بررسی علل تطابق نیافتن مدلهای اقتصادی رفتار اوپک در بلندمدت از دیدگاه تحولات بازار نفت و ویژگیهای این سازمان، فصلنامه پژوهشها و سیاستهای اقتصادی، 47، 63-25.
4
جوکار، محمدصادق (1393). کاهش قیمت نفت و سناریوهای رفتاری عربستان سعودی، بولتن ماهانه تحولات بازارهای نفت و گاز، 86. 74-69.
5
روحانی، فواد (1354). تاریخ اوپک، برگردان منوچهر روحانی، تهران، شرکت سهامی کتابهای جیبی.
6
شکاری، مهری (1388). تأثیر ظرفیتهای مازاد تولید نفت بر روی رفتار تولیدات اوپک، مطالعات اقتصاد انرژی، 20، 86-57.
7
طائفیهمراه، نفیسه (1391). رقابت ایران و عربستان در اوپک و تأثیر آن بر سیاست خارجی ایران در دهه اخیر (2010-2000)، پایاننامه کارشناسی ارشد، دانشکده علوم سیاسی دانشگاه علامه طباطبایی.
8
عبدلی، قهرمان، و ماجد، وحید (1391). بررسی رفتار اوپک در قالب یک بازی همکارانه، فصلنامه تحقیقات مدلسازی اقتصادی، 7، 50-27.
9
عبدلی، قهرمان، و ناخدا، محمدجواد (1388). کاربرد نظریه فیرون در بررسی پایداری اوپک: با رویکرد نظریه بازیهای تکراری، مطالعات اقتصاد انرژی، 20، 56-33.
10
فرشادگهر، ناصر (1374). بررسی قدرت اوپک در بازار جهانی نفت، تهران، انتشارات دانشگاه امام حسین (ع).
11
فهیمیدوآب، رضا؛ صباحی، احمد؛ مهدویعادلی، محمدحسین، و سیفی، احمد (1393). بررسی نحوه تعیین قیمت نفت خام میان دو سازمان OPEC و OECD با استفاده از مدل تئوری بازیها و روش جوهانسون- جوسیلیوس، مطالعات اقتصاد انرژی ایران، (12)3، 90-60.
12
نادریان، محمدامین (1393). تحلیلی بر رفتار عربستان در بازار نفت. بولتن ماهانه تحولات بازارهای نفت و گاز، 89، 87-82.
13
Abdoli, G., & Nakhoda, M.J. (2009). An Application Of Fearon’s Theory To Consider OPEC’s Stability: Through a Repeated Game Approach, Quarterly Energy Economics Review, 6(20), 33-56 (In persion).
14
Abdoli, G., & Majed, V. (2012). Analyzing OPEC members behavior: A cooperation game approach. Journal of Economic Modeling Research, 2(7), 27-50 (In persion).
15
Almoguera, P.A., Douglas, C.C., & Herrera, A.M. (2011). Testing for the cartel in OPEC: non-cooperative collusion or just non-cooperative?, Oxford Review of Economic Policy, 27(1), 144–168.
16
4. Al-Qahtani, A., Balistreri, E., & Dahl, C. (2008). Literature review on oil market modeling and OPEC's behavior. Working paper, Colorado School of Mines.
17
5. Al-Yousef, N. A. (1998). Modeling Saudi Arabia Behavior in the World Oil Market 1976-1996, Department of Economics, University of Surrey. SEEDS 93.
18
Chang, Y., Yi, J., Yan, W., Yang, X., Zhang, S., Gao, Y., & Wang, X. (2014). Oil supply between OPEC and non-OPEC based on game theory, International Journal of Systems Science, 45(10), 2127-2132.
19
Cremer, J., & Salehi-Isfahani, D. (1980). A Competitive Theory of the Oil Market: What Does OPEC Really Do?, Caress Working Paper, No. 80-4, mimeo., University of Pennsylvania.
20
Deschamps, Ph. J., (2008). Comparing Smooth Transition and Markov Switching Autoregressive Models of Us Unemployment. Journal of Applied Econometrics. 23, (4), 435 -462.
21
Dibooglu, S., & AlGudhea, S.N. (2007). All time cheaters versus cheaters in distress: An examination of cheating and oil prices in OPEC, Economic Systems, 31(3), 292-310.
22
Emami Meibodi, A., Haghdoost, E., & Pakdin, J. (2010). A Test for Growth Stability in Non-renewable Resources, The Case of OPEC, Iranian Economic Research, 14(42), 149-167 (In persion).
23
Esteghamat, F. (2004). The Organization of Oil Exporting Countries (OPEC), the Ministry of Foreign Affairs Publications, Tehran(In persion).
24
Ezzati, A. (1976). Future OPEC Price and Production Strategies as Affected by its Capacity to Absorb Oil Revenues, European Economic Review, August, 8, 107-38.
25
Fahimi Doab, R., Mahdavi Adeli, M.H., & Seifi, A. (2014). The survey on determination of crude oil price between OPEC and OECD organizations by using game theory model and Johansen-Juselius technique, Iranian Energy Economics, 3(12), 61-90 (In persion).
26
Farshad Gohar, N. (1995). International Oil Market and OPEC, Tehran, Imam Hosein University (In persion).
27
Fattouh, B., & Mahadeva, L. (2013). OPEC: What Difference Has It Made? The Annual Review of Resource Economics, 5, 427-43.
28
Franz, W. (2009). OPEC as a political and economical entity, European Journal of Political Economy, 25(4), 399-408.
29
Geroski, P. A., Ulph, A. M., & Ulph, D. T. (1987). A Model of the Crude Oil Market in which Market Conduct Varies, The Economic Journal, 97, 77-86.
30
Golombek, R., Irarrazabal, A.A., & Ma, L. (2014). OPEC’s market power: An empirical dominant firm model for the oil market, Norges Bank Research, Working Paper 3.
31
Green, E., & Porter, R. (1984). Non cooperative Collusion under Imperfect Price Information, Econometrica, 52, 87-100.
32
Griffin, J.M. (1985). OPEC Behavior: A Test of Alternative Hypotheses, American Economic Review, 75, 954-963.
33
Gülen, S.G. (1996). Is OPEC a Cartel? Evidence from Cointegration and Causality Tests, The Energy Journal, 17(2), 43-57.
34
Hamilton, J. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle, Econometrica, 57(2), 357-384.
35
Hammoudeh, S., & Madan, V. (1995). Expectation, Target Zones, and Oil Price Dynamics. Journal of Policy Modeling, 17(6), 597-613.
36
Hammoudeh, S. (1997). Oil Pricing Policies in a Target Zone Model, Research in Human Capital and Development, 11(B), 497-513.
37
Hnyilicza, E., & Pindyck, R. S. (1976). Pricing Policies for a Two-Part Exhaustible Resource Cartel: The Case of OPEC. European Economic Review, 8(2), 139-154.
38
Hochman, G., & Zilberman, D. (2015). The political economy of OPEC, Energy Economics, 48, 203–216.
39
Huppmann, D. (2013). Endogenous Shifts in OPEC Market Power- A Stackelberg Oligopoly with Fringe, Discussion Papers of DIW Berlin,http://ideas.repec.org/s/diw/diwwpp.html
40
Hyndman, K. (2008). Disagreement in Bargaining: An Empirical Analysis of OPEC, International Journal of Industrial Organization, 26(3), 811–828.
41
Jamshidi Rudbari, M. (2008). An Investigation into the Incompatibility of Economic Models of OPEC’s Behaviour in the Long-run from the Point of View of the Evolution in the Crude Oil Market and the Basic Features of This Organization. Journal of Economic Research and Policies, 3, 16 (47): 25-63 (In persion).
42
Johany, A. D. (1978). OPEC is Not a Cartel: A Property Rights Explanation of the Rise in Crude Oil Prices, unpublished doctoral dissertation, University of California-Santa Barbara.
43
Jokar, M.S. (2014). Reduction of oil prices and Saudi Arabia's behavioral scenarios, Monthly bulletin of oil and gas markets developments, 86, 69-74 (In persion).
44
Kaufmann, R.K., Bradford, A., Belanger, L.H., Mclaughlin, J.P., & Miki, Y. (2008). Determinants of OPEC Production: Implications for OPEC behavior, Energy Economics, 30(2), 333-351.
45
Kim, S., & Bhattacharya, R. (2009). Regional Housing Prices in the USA: An Empirical Investigation of Nonlinearity. Journal of Real Estate Finance and Economics, 38(4), 443 -460.
46
Lee, L-F & Porter, R.H. (1984). Switching Regression Models with Imperfect Sample Separation Information--With an Application on Cartel Stability, Econometrica, 52(2), 391-418.
47
Loderer, C. (1985). A Test of the OPEC Cartel Hypothesis: 1974-1983, Journal of Finance, 40(3), 991-1008.
48
Mabro, R. (1975). Can OPEC Hold the Line, in OPEC and the World Oil Market: The Genesis of the 1986 Price Crisis, Oxford Institute for Energy Studies.
49
MacAvoy, P. (1982). Crude Oil Prices as Determined by OPEC and Market Fundamentals. Ballinger Publishing Company, Cambridge, MA.
50
Mead, W.J. (1979). The Performance of Government Energy Regulations, American Economic Review Proceedings, 69, 352-56.
51
Mixon, J, W. (1982). Saudi Arabia, OPEC, and Price of Crude Oil, Resources and Energy, 4, 195-201.
52
Naderyan, M.A. (2014). An analysis of Saudi behavior in the oil market, Monthly bulletin of oil and gas markets developments, 89, 82-87 (In persion).
53
OPEC. (2015). Annual statistical Bulletin OPEC 2015.
54
OPEC. (2016). Annual statistical Bulletin OPEC 2016.
55
Porter, R.H. (1983). A Study of Cartel Stability: The Joint Executive Committee, 1880-1886, The Bell Journal of Economics, 14(2), 301-314.
56
Ramcharran, H, (2002), Oil Production Responses to Price Changes: An Empirical Application of the Competitive Model to OPEC and non-OPEC Countries, Energy Economics, 24(2), 97-106.
57
Rouhani, F. (1975). A History of OPEC, translate; Manouchehr Rohani, Pocket Books (In persion).
58
Salehi-Isfahani, D. (1987). Testing OPEC behavior: Further results, Department of Economics, Virginia Polytechnic Institute and state University working paper-87-01-02.
59
Shekari, M. (2009). The impact of excess production capacity on opec’s production behavior, Quarterly Energy Economics Review, 6(20), 57-86 (In persion).
60
Spilimbergo, A. (2001). Testing the Hypothesis of Collusive Behavior among OPEC Members, Energy Economics, 23, 339-353.
61
Suranovic S. M. (1993). Does a Target-capacity Utilization Rule Fulfill OPEC Economic Objectives?, Energy Economics, 15(2): 71-79.
62
Taefi Hamrah, N. (2012). The competition between Iran and Saudi Arabia in OPEC and its impact on Iran's foreign policy in the last decade (2000-2010), M.A. Thesis, Faculty of Political Science, Allameh Tabatabai University, Theran (In persion).
63
Taklif, A. (2010). OPEC's Long-Term Strategy with Regards to Developments in the International Oil Market, strategy-strategic research center of the Expediency Council, 19(57), 133-154. (In persion).
64
Tang, L., & Hammoudeh S. (2002). An Empirical Exploration of the World Oil Price Under the Target Zone Model, Energy Economics, 24(6), 577-596.
65
Word Bank. (2016). World Development Indicators (WDI), Washington, D.C,USA.
66
Yang, B. (2003). OPEC Behavior: New Evidence from A Market-Sharing Cartel Model, Unpublished Master Thesis.
67
Yang, B. (2004). OPEC Behavior, Thesis in Doctor of Philosophy. The Pennsylvania State University.
68
ORIGINAL_ARTICLE
Asymmetric Effects of Monetary Policy on Iran Housing Market: A Nonlinear MS-VAR Approach
Recent studies in housing market especially in the aftermath of 2007 financial crisis show that monetary policy has a main role in housing market and its impact can be asymmetric. In other words, the effect of monetary policy depends on the state of housing market and during bull and bear periods, the market can be differently affected by the monetary policy. As a result, the main objective of this paper is to investigate the asymmetric effects of monetary policy on Iran housing market using quarterly data during 1994-2017. To this end, we use the Markov Switching VAR model in which parameters change according to the phase of the housing cycle. The results suggest that monetary policy has asymmetric effects on housing market. Also, regime dependent Impulse Response Functions show that impact of monetary policy (with same sign and size) on housing market is larger in bear regime than in bull regime.
https://ecoj.tabrizu.ac.ir/article_8097_e0640b0af28f67dc04e87b4649dac5b6.pdf
2018-11-22
75
102
Monetary Policy
Housing Prices
Markov Switching
Farzad
Saghi
farsaghi@yahoo.com
1
Ph.D. Candidate in Economics, Department of Economics, Qazvin Branch, Islamic Azad University, Qazvin, Iran
AUTHOR
kambiz
Hozhabr Kiani
kianikh@yahoo.com
2
Professor of Economics, Faculty of Management and Economics, Islamic Azad University, Science and Research Branch, Tehran, Iran
LEAD_AUTHOR
Akbar
Mirzapour Babajan
akbar.mirzapour@gmail.com
3
Assistant Professor of Economics, Qazvin Branch, Islamic Azad University, Qazvin, Iran
AUTHOR
Beytollah
Akbari Moghaddam
akbari.beitollah@gmail.com
4
Assistant Professor of Economics, Qazvin Branch, Islamic Azad University, Qazvin, Iran
AUTHOR
ابوالحسنی، اصغر، ابراهیمی، ایلناز، پورکاظمی، محمدحسین، و بهرامینیا، ابراهیم (1395). اثر تکانههای پولی و تکانههای نفتی بر تولید و تورم بخش مسکن در اقتصاد ایران: رویکرد تعادل عمومی پویای تصادفی نیوکینزی. پژوهشهای رشد و توسعه اقتصادی، 7(25)، 113-132.
1
افشاری، زهرا، و همتی، مریم (1392). شناسایی عوامل موثر بر احتمال وقوع رونق و رکود در بازار مسکن. پژوهشهای اقتصادی، 18(55)، 17-46.
2
جعفری صمیمی، احمد، علمی، زهرا، و هادیزاده، آرش (1386). عوامل موثر بر تعیین رفتار شاخص قیمت مسکن در ایران. پژوهشهای اقتصادی ایران، 9(32)، 31-53.
3
شهبازی، کیومرث، و کلانتری، زهرا (1391). اثرات شوک های سیاست های پولی و مالی بر متغیرهای بازار مسکن در ایران: رهیافت SVAR. پژوهشها و سیاستهای اقتصادی، 20(61)، 77-104.
4
عسگری، حشمتالله، و الماسی، اسحاق (1390). بررسی عوامل موثر بر قیمت مسکن در مناطق شهری کشور به روش دادههای تابلویی (طی سالهای 1370 تا 1385). پژوهشنامه اقتصادی، 11(41)، 201-224.
5
موسوی، میرحسین، و درودیان، حسین (1394). تحلیل عوامل موثر بر قیمت مسکن در شهر تهران. 9(31)، 103-127.
6
نظری، محسن، و فرزانگان، الهام (1389). سیاست پولی و حباب مسکن در تهران. تحقیقات اقتصادی، 45(93)، 229-249
7
Abolhasani, A., Ebrahimi, I., Pourkazemi, M. H., & Bahraminia, E. (2016). The effect of oil shocks and monetary shocks on production and inflation in the housing sector of the Iranian economy: New Keynesian dynamic stochastic general equilibrium approach. Quarterly Journal of Economic Growth and Development Research, 25(7), 113-132 (In Persian).
8
Afshari, Z., & Hemmati, M. (2013). Determinants of the probability of Boom-Bust cycles in the housing market. Economic Research, 55(18), 17-46 (In Persian).
9
Asgari, H., & Almasi, E. (2011). Factors affecting the price of housing in urban areas using panel data (during the 1370 to 1385). Economics Research, 41(11), 201-224 (In Persian).
10
Astveit, K. A., & Anundsen, A. K. (2016). Asymmetric effects of monetary policy in regional housing markets. Norges Bank working paper, No. 25/2017.
11
Azad Chowdhury, R., & Maclennan, D. (2014). Regional house price cycles in the UK, 1978-2012: a Markov switching VAR. Journal of European Real Estate Research, 7(3), 345-366.
12
Bernanke, B. S., & Gertler, M. (1995). Inside the black box: the credit channel of monetary policy transmission. Journal of Economic perspectives, 9(4), 27-48.
13
Ehrmann, M., Ellison, M., & Valla, N. (2003). Regime-dependent impulse response functions in a Markov-switching vector autoregression model. Economics Letters, 78(3), 295-299.
14
Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
15
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica: Journal of the Econometric Society, 357-384.
16
Hansen, B. E., & Seo, B. (2002). Testing for two-regime threshold cointegration in vector error-correction models. Journal of econometrics, 110(2), 293-318.
17
Jafari, S. A., Elmi, Z., & Hadizadeh, A. (2007). Affecting factors on house price index, Economic Research, 32(9), 31-53 (In Persian).
18
Krolzig, H. M. (1997). Markov-switching vector autoregression. Lecture Notes in Economic and Mathematical Systems.
19
Meltzer, A. H. (1995). Monetary, credit and (other) transmission processes: a monetarist perspective. Journal of economic perspectives, 9(4), 49-72.
20
Mousavi, M., & Doroodian, H. (2015). Analyzing the determinants of housing prices in Tehran city. Quarterly Journal of Economical Modeling, 31(9), 103-127 (In Persian).
21
Nazari, M., & Farzanegan, E. (2011). Monetary policy and housing price bubbles in Tehran. Journal of Economic Research, 45(4), 255-280 (In Persian).
22
Nelson, E. (2003). The future of monetary aggregates in monetary policy analysis. Journal of Monetary Economics, 50(5), 1029-1059.
23
Phiri, A. (2016). Asymmetric pass-through effects from monetary policy to housing prices in South Africa. MPRA Paper, No. 70258.
24
Shahbazi, K., & Kalantari, Z. (2012). The effects of fiscal and monetary policies shocks on housing market variables in Iran: a SVAR approach. Journal of Economic Research and Policies, 61(20), 77-104 (In Persian).
25
Simo-Kengne, B. D., Balcilar, M., Gupta, R., Reid, M., & Aye, G. C. (2013). Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-Switching Vector Autoregressive model. Economic Modelling, 32, 161-171.
26
Sims, C. A. (1980). Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 48(1),1-48.
27
Taylor, J. B. (2007). Housing and monetary policy. NBER working paper, No. 13682.
28
Tsai, I. C. (2013). The asymmetric impacts of monetary policy on housing prices: A viewpoint of housing price rigidity. Economic Modelling, 31, 405-413.
29
ORIGINAL_ARTICLE
Assessment of the Efficiency of FLQ and AFLQ Methods in the Regionalization of National Input-Output Tables in Iran’s Economy
This article seeks to compare the accuracy of the Flegg’s Location Quotients (FLQ) and Augmented Flegg’s Location Quotient (AFLQ) methods in the regionalization of the national input-output table. The study of the evolution of location quotient approaches shows that although all the empirical evidence confirms the superiority of Flegg’s location quotient and its augmented methods in comparison to location quotient approaches, there is no single theory about the success of these two methods compared to each other. Therefore, the input-output table is provided for 31 provinces of the country, using the value added and output statistics of the provinces, updated national input-output table provided by Statistical Center of Iran in 2011, and the FLQ and AFLQ methods. To compare the performance of the FLQ method with the AFLQ method, five statistical indicators of estimating deviation are used. The results of the research show that in the regionalization of the national input-output table in Iran’s economy, the FLQ method is more accurate than the AFLQ in many statistical indicators, especially Tiel’s index.
https://ecoj.tabrizu.ac.ir/article_7962_9524380b95a34d3999518a845d6dff4b.pdf
2018-11-22
103
136
Flegg’s location quotient
Augmented Flegg’s location quotient
National input-output table
Regional input-output table
Theil’s index
Hossein
Aliasgharpour
hossein.aliasgharpour@gmail.com
1
Ph.D. Candidate in Economics, Faculty of Economics, University of Mazandaran
AUTHOR
Nooraddin
Sharify
nsharify@umz.ac.ir
2
Associate Professor of Economics, University of Mazandaran
LEAD_AUTHOR
بانوئی، علیاصغر، و بزازان، فاطمه (1385). نقش و اهمیت ابعاد اقتصاد فضا در محاسبه جداول
1
داده- ستانده منطقهای: پدیده فراموششده در ایران. فصلنامه پژوهشهای اقتصادی ایران، 8(27)، 114-89.
2
بانوئی، علیاصغر، بزازان، فاطمه، و کرمی، مهدی (1385). بررسی کمی رابطه بین ابعاد اقتصاد فضا و ضرایب داده-ستانده 28 استان کشور. فصلنامه پژوهشهای اقتصادی ایران، 8(29)،
3
بانوئی، علیاصغر، بزازان، فاطمه، و کرمی، مهدی (1386). تأمل بیشتری در خصوص توابع سهم مکانی نوین بین ابعاد اقتصاد فضا و ضرایب داده-ستانده منطقهای: مطالعه موردی استان تهران. فصلنامه پژوهشهای اقتصادی ایران، 9(31)، 27-53.
4
بانوئی، علیاصغر (1391). ارزیابی شقوق مختلف نحوه منظور کردن واردات و روشهای تفکیک آن با تاکید بر جدول متقارن سال 1380. مجله علمی-پژوهشی سیاستگذاری اقتصادی، 4(8)، 73-31.
5
نصرالهی، زهرا، و زارعی، مهران (1396). معرفی و ارزیابی روش سهم مکانی خاص صنعتی فلگ (SFLQ) در منطقهایسازی جداول داده-ستانده ملی (مطالعه موردی: استان یزد 1390). دو فصلنامه پژوهشهای اقتصاد و توسعه منطقهای، 20(13)، 112-140.
6
Banouei, A. (2012). Evaluation of the different treatments and methods of separating imports with emphasis on 1381 IOT of Iran. The Journal of Economic Policy, 4(8), 31-74 (In Persian).
7
Banouei, A., & Bazzazan, F. (2006). The importance of spatial economic dimensions in construction of regional input-output table: Neglected phenomena in Iran. Iranian Journal of Economic Research, 8(27), 89-114 (In Persian).
8
Banouei, A., Bazzazan, F., & Karami, M. (2007a). Relationship between spatial economic dimensions and input-output coefficients in Iranian provinces. Iranian Journal of Economic Research, 8(29), 143-170 (In Persian).
9
Banouei, A., Bazzazan, F., & Karami, M. (2007b). The modern location quotient function, spatial dimension, and regional input-output coefficients: The case of Tehran province. Iranian Journal of Economic Research, 9(31), 27-53 (In Persian).
10
Bonfiglio, A., & Chelli, F. (2008). Assessing the behaviour of non-survey methods for constructing regional input-output tables through a Monte Carlo simulation. Economic Systems Research, 20(3), 243-258.
11
Flegg, A. T., & Webber, C. D. (2000). Regional size, regional specialization and the FLQ formula. Regional Studies, 34, 563-569.
12
Flegg, A. T., & Tohmo, T. (2013). Regional input–output tables and the FLQ formula: A case study of Finland. Regional Studies, 47(5), 703-721.
13
Flegg, A. T., & Tohmo, T. (2016).Estimating regional input coefficients and multipliers: The use of the FLQ is not a gamble. Regional Studies, 50(2), 310-325.
14
Flegg, A. T., & Webber, C. D. (1997). On the appropriate use of location quotients in generating regional input‐output tables: Reply. Regional studies, 31(8), 795-805.
15
Flegg, A. T., Mastronardi, L. J., & Romero, C. A. (2016). Evaluating the FLQ and AFLQ formulae for estimating regional input coefficients: Empirical evidence for the province of Cordoba, Argentina. Economic Systems Research, 28(1), 21-37.
16
Flegg, A. T., Webber, C. D., & Elliott, M. V. (1995). On the appropriate use of location quotients in generating regional input–output tables. Regional Studies, 29(6), 547-561.
17
Ghosh, A. (1958). Input-output approach in an allocation system. Economica, 25, 58–64.
18
Harris, R. I., & Liu, A. (1998). Input‐Output modelling of the urban and regional economy: The importance of external trade, Regional Studies, 32(9), 851-862.
19
Klijs, J., Peerlings, J., Steijaert, T., & Heijman, W. (2016). Regionalising input-output tables: Comparison of four location quotient methods, in impact assessment in tourism economics. Springer International Publishing, 43-65.
20
Kowalewski, J. (2015). Regionalization of national input-output tables: Empirical evidence on the use of the FLQ formula. Regional Studies,49(2), 240-250.
21
Kronenberg, T. (2009). Construction of regional input-output tables using nonsurvey methods: The Role of cross-hauling. International Regional Science Review, 32(1), 40-64.
22
Lihtonen, O., & Tykkylainen, M. (2014). Estimating regional input coefficients and multipliers: Is the choice of a non-survey technique a gamble?. Regional Studies, 48 (2), 382-399.
23
McCann, P., & Dewhurst, J. H. (1998). Regional size, industrial location and input-output expenditure coefficient. Regional Studies, 32(5), 435-444.
24
Miller, R. E., & Lahr, M. L. (2001). A taxonomy of extractions. Contributions to Economic Analysis, 249, 407-441.
25
Miller, R. E., & Blair, P. D. (2009). Input-output analysis: foundations and extensions. Cambridge University Press, Cambridge.
26
Morrison, W., & Smith, P. (1974). Nonsurvey input-output techniques at the small area level: an Evaluation. Journal of Regional Science, 14, 1-14.
27
Nasrollahi, Z., & Zarei, M. (2017). Introduction and evaluation of industry-specific FLQ method to regionalization of national input-output tables: A Case study of Yazd province in 2011. Journal of Economy and Regional Development, 24 (13), 112-140 (In Persian).
28
Polenske, K. R. (1995). Leontief’s spatial economic analysis. Structural Change and Economic Dynamics, 6, 309-318.
29
Richardson, H. W. (1985). Input-output and economic base multipliers: Looking backward and forward. Journal of Regional Science, 25, 607-661.
30
Round, J. I. (1978a). On estimating trade flows in interregional input-output models. Journal of Regional Science and Urban Economics, 8, 284-302.
31
Round, J. I. (1978b). An interregional input‐output approach to the evaluation of non-survey methods. Journal of Regional Science, 18(2), 179-194.
32
Round, J. I. (1983). Non-survey techniques: A critical review of the theory and evidence. International Regional Science Review, 8(3), 189-212.
33
Schaffer, W., & Chu, K. (1969). Nonservey techniques for constructing regional interindustry models. Paper and Proceeding of the Regional Science Association, 23, 83-101.
34
Sengupta, A. (1987). Input-output allocation model for India: A note. anvesak, 7(2), 103-107.
35
Tamesue, K., & Tsutsumi, M. (2014). Assessing the estimation accuracy of LQ methods for regionalization of input coefficients: A case study in Japan, 22nd International Input-Output Conference & 4th Edition of the International School of I-O Analysis, Lisbon, Portugal.
36
Tohmo, T. (2004). New development in the use of location quotients to estimate regional input-output coefficients and multipliers. Regional Studies, 38, 43-54.
37
ORIGINAL_ARTICLE
The Study of Relationship between Resource Abundance – Governance - Economic Growth with Emphasis on the Role of Information and Communication Technology
The role and influence of the natural resources abundance on economic growth is considered as a puzzle in the economy. In order to investigate this issue, quality of governance role and the diffusion of information and communication technology as a facilitator of good governance settling have been considered and due to studying topic data for 31 oil-rich countries (proxy for natural resources index), from 1980 to 2015, and dynamic common correlated effects method is used. The results of the study show that the role of natural resources in economic growth depends on the quality of governance in countries. Natural resources in high-quality governance nations have become an important and essential factor for economic growth, but in countries with poor governance, natural resources have deterred economic growth. It means natural resources abundance causes economic activities boosts while there is good governance, and with low quality of governance, natural resources abundance will slow down economic growth. Also, according to the results, it could be said that diffusion of ICT causes resource abundance to improve economic growth in the group of countries that the level of information and communication technology is low. This is because of market transparency, increase public awareness through access to more information and more government accountability towards people.
https://ecoj.tabrizu.ac.ir/article_7447_9750c14894d7fede2ad9b80b7de212e0.pdf
2018-11-22
137
164
Economic growth
Natural resources
Governance
Information and communication Technology
Dynamic panel data method (DCCE)
Zahra
Jalili
jalili_zahra@ymail.com
1
Ph.D Candidate in Economics, University of Tabriz
AUTHOR
Mohammadreza
Salmani Bishak
mrsalmani_2005@yahoo.com
2
Assistant Proessor of Economics, University of Tabriz
LEAD_AUTHOR
بهبودی، داوود، اصغرپور، حسین، و محمدلو، نویده (1391). نقش کیفیت نهادی بر رابطه وفور منابع طبیعی و رشد اقتصادی: مورد اقتصادهای نفتی. فصلنامه پژوهشها و سیاستهای اقتصادی، 20(62)، 116-95.
1
پورکاظمی محمدی، سید مهدی (1390). بررسیتاثیرحکمرانیخوببررشداقتصادیوتوسعهانسانیکشورهای دارایمنابعطبیعیفراوان. پایاننامه کارشناسی ارشد، دانشکده اقتصاد و مدیریت، دانشگاه تربیت مدرس.
2
شاهآبادی، ابوالفضل، و صادقی، حامد (1394). وفور منابع طبیعی و تولید ناخالص داخلی سرانه در کشورهای نفتی با تأکید بر آزادی اقتصادی. فصلنامه پژوهشهای رشد و توسعه اقتصادی (علمی ـ پژوهشی)، 5(20)، 98-79.
3
عبادی، جعفر، و نیکونسبتی، علی (1391). منابع طبیعی، نهادها، رشد اقتصادی. فصلنامه علمی ـ پژوهشی برنامهریزی و بودجه، 17(4)، 144-127.
4
غیاثوند، ابوالفضل، و صبوری، فاطمه (1390). رابطه حکمرانی منابع و رشد اقتصادی در کشورهای دارای منابع معدنی. فصلنامه اقتصاد مالی مالی (اقتصاد مالی و توسعه)، 5(16)، 134-113.
5
کمالیزاده، محمد (1393). تأثیر جهانی شدن بر کارکرد توزیعی دولت رانتیر. دو فصلنامه علمی ـ پژوهشی پژوهش سیاست نظری، 16، 19-1.
6
گلخندان، ابوالقاسم (1394). جهانی شدن و اندازه دولت: آزمون فرضیه رودریک. فصلنامه سیاستهای راهبردی و کلان، 3(10)، 62-39.
7
متفکرآزاد، محمدعلی، و ممیپور، سیاب (1393). تحلیل اقتصادی ـ سیاسی موانع تأثیرگذاری وفور منابع طبیعی بر رشد اقتصادی. فصلنامه علمی ـ پژوهشی نظریههای کاربردی اقتصاد، 1(1)، 124-97.
8
مهرآرا، محسن، و کیخا، علیرضا (1387). نهادها، نفت و رشد اقتصادی در کشورهای متکی به نفت طی دوره 2005- 1975: روش پانل همانباشتگی. فصلنامه اقتصاد مقداری (فصلنامه بررسیهای اقتصادی)، 5(4)،79-55.
9
یاوری، کاظم، و سلمانی، بهزاد (1384). رشداقتصادیدرکشورهایدارایمنابعطبیعی: موردکشورهایصادرکنندهنفت. فصلنامه پژوهشنامه بازرگانی، 9(37)، 24-1.
10
Aidt, T., Dutta, J., & Sena, V. (2008). Governance regimes, corruption and growth: Theory and evidence. Journal of Comparative Economics, 36(2), 195-220.
11
Alexeev, M., & Conrad, R. (2009). The elusive curse of oil. The Review of Economics and Statistics, 91(3), 586-598.
12
Al Mamun, M., Sohag, K., & Hassan, M. K. (2017). Governance, resources and growth. Economic Modelling, 63, 238-261.
13
Arcand, J. L., Berkes, E., & Panizza, U. (2013). Finance and economic development in a model with credit rationing. The Social Value of the Financial Sector: Too Big to Fail or Just Too Big?, 29, 67-80.
14
Arezki, R., & Van der Ploeg, R. (2007). Can the natural resource curse be turned into a blessing? The role of trade policies and institutions. IMF, Working Papers, 1-34.
15
Auty, R. (1994). The Resource Curse Thesis: Minerals in Bolivian Development, 1970-90. Singapore Journal of Tropical Geography, 15(2), 95-111.
16
Avgerou, C. (2003). The link between ICT and economic growth in the discourse of development. Organizational information systems in the context of globalization (pp. 373-386). Springer, Boston, MA.
17
Behboudi, D., Asgharpour, H., & Mohammadlou, N. (2012). The role of institutional quality on relationship between resource abundance and economic growth in oil economies. Quarterly Journal of Economic Reaserch and Policies, 20(62), 95-116. (In Persion).
18
Bhattacharyya, S., & Hodler, R. (2010). Natural resources, democracy and corruption. European Economic Review, 54, 608-621.
19
Bulte, E. H., Damania, R., & Deacon, R. T. (2005). Resource intensity, institutions, and development. World development, 33(7), 1029-1044.
20
Cardona, M., Kretschmer, T., & Strobel, T. (2013). ICT and productivity: conclusions from the empirical literature. Information Economics and Policy, 25(3), 109-125.
21
Cavalcanti, T. V. D. V., Mohaddes, K., & Raissi, M. (2011a). Growth, development and natural resources: New evidence using a heterogeneous panel analysis. The Quarterly Review of Economics and Finance, 51(4), 305-318.
22
Cavalcanti, T. V. D. V., Mohaddes, K., & Raissi, M. (2011b). Does oil abundance harm growth?. Applied Economics Letters, 18(12), 1181-1184.
23
Chudik, A., & Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188, 393-420.
24
Chudik, A., Mohaddes, K., Pesaran, M. H., & Raissi, M. (2016). Long-run effects in large heterogeneous panel data models with cross-sectionally correlated errors. In Essays in Honor of man Ullah (pp. 85-135). Emerald Group Publishing Limited.
25
Das, A., Khan, S., & Chowdhury, M. (2016). Effects of ICT development on economic growth in emerging Asian countries. In ICTs in Developing Countries (pp. 141-159). Palgrave Macmillan UK.
26
Demetriades, P., & Hook Law, S. (2006). Finance, institutions and economic development. International journal of finance & economics, 11(3), 245-260.
27
Ebadi, J., & Nikoonesbati, A. (2013). Natural Resources, Institutions, Economic Development. Journal of Planning and Budgeting, 17(4), 127-144. (In Persian).
28
Ghiasvand, A., & Saboori, F. (2011). The relationship between resources, governance and economic growth in countries with abundance natural resources. Quarterly Journal of Management System (Financial Economics and Development), 5(16), 113-134 (In Persian).
29
Golkhandan, A. (2015). Globalization and government size: Rodrik hypothesis testing. Quarterly Journal of the Macro and Strategic Policies, 3(10), 39-62 (In Persian).
30
Gurgul, H., & Lach, Ł. (2014). Globalization and economic growth: Evidence from two decades of transition in CEE. Economic Modelling, 36, 99-107.
31
Gylfason, T. (2001). Natural resources, education, and economic development. European Economic Review, 45(4), 847-859.
32
Hsiao, C. (2003). Analysis of panel data. Cambridge university press.
33
Iimi, A., & Ojima, Y. (2005). Natural resources, economic growth and good governance: An empirical note. JBIC, Working paper (No.21).
34
Ionescu, L. (2013). The impact that e-government can have on reducing corruption and enhancing transparency. Economics, Management, and Financial Markets, 8(2), 210-215.
35
Jorgenson, D. W., & Vu, K. M. (2016). The ICT revolution, world economic growth, and policy issues. Telecommunications Policy, 40(5), 383-397.
36
Kamalizadeh, M. (2015). The impact of globalization on distributional function of renter' state. Semi-Annually Research in Theoretical Politics, 16, 1-19 (In Persian).
37
Kolstad, I. (2009). The resource curse: Which institution matter?. Applied Economics, 16, 439-442.
38
Lio, M. C., Liu, M. C., & Ou, Y. P. (2011). Can the internet reduce corruption? A cross-country study based on dynamic panel data models. Government Information Quarterly, 28(1), 47-53.
39
Loayza, N. V., & Ranciere, R. (2006). Financial development, financial fragility, and growth. Journal of Money, Credit and Banking, 1051-1076.
40
Mehlum, H., Moene, K., and Torvik, R. (2006). Institutions and the Resource Curse. The Economic Journal, 116(508), 1–20.
41
Mehrara, M., & Keykha, A. (2009). Institutional quality, economic growth and oil revenues in oil dependent countries during the period 1975-2005: A panel cointegration approach. Quarterly Journal of Quantitative Economics (Quarterly Journal of Economics Review), 5(4), 55-79 (In Persian).
42
Mohaddes, K., & Pesaran, M. H. (2013). One Hundred Years of Oil Income and the Iranian Economy: A Curse or a Blessing?. Faculty of Economics, University of Cambridge, Working Paper, No. 1302.
43
Montinola, G. R., & Jackman, R. W. (2002). Sources of corruption: A cross-country study. British Journal of Political Science, 32(1), 147-170.
44
Morelli, M., & Rohner, D. (2015). Resource Concentration and Civil Wars. Journal of Development Economics, 117, 32–47.
45
Motafakker Azad, M. A., & Mamipour, S. (2014). Economical - Political analysis of barriers of natural resources abundance effect on economic growth. Applied Theories Economics, 1(1), 97-124 (In Persian).
46
Neal, T. (2015). Estimating heterogeneous coefficients in panel data models with endogenous regressors and common factors. Working Paper.
47
North, D. (1990). Institutions, institutional change, and economic performance. Cambridge University Press, Cambridge, MA.
48
Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. In: Cambridge Working Papers in Economics No. 435. University of Cambridge, and CESifo Working Paper Series No. 1229.
49
Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74, 967-1012.
50
Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22(2), 265-312.
51
Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogenous panels. Journal of Econometrics, 68, 79-113.
52
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634.
53
Pour Kazemi MOhammadi, M. S. (2012). Investigating the effect of good governance on economic growth and human development in rich natural resources countries. M.A. Thesis, Economic and management faculty, Tarbiat Modares University (In Persian).
54
Sachs, J. D., & Warner, A. M. (1995). Natural resource abundance and economic growth. NBER, working paper.
55
Sachs, J. D., & Warner, A. M. (2001). The curse of natural resources. European Economic Review, 45(4), 827-838.
56
Salahuddin, M., & Alam, K. (2016). Information and communication technology, electricity consumption and economic growth in OECD countries: A panel data analysis. International Journal of Electrical Power & Energy Systems, 76, 185-193.
57
Samargandi, N., Fidrmuc, J., & Ghosh, S. (2015). Is the relationship between financial development and economic growth monotonic? Evidence from a sample of middle-income countries. World Development, 68, 66-81.
58
Shahabadi, A., & Sadeghi, H. (2015). Natural resource abundance and GDP per capita in oil countries, with emphasis on the economic freedom. Quarterly Journal of Economic Growth and Development Research, 5(20), 79-98 (In Persian).
59
Smith, B. (2015). The resource curse exorcised: Evidence from a panel of countries. Journal of Development Economics, 116, 57-73.
60
Van der Ploeg, F. (2011). Natural resources: Curse or blessing?. Journal of Economic Literature, 49(2), 366–420.
61
Williams, A. (2011). Shining a light on the resource curse: An empirical analysis of the relationship between natural resources, transparency, and economic growth. World Development, 39(4), 490-505.
62
Yavari, K., & Salmani, B. (2005). Economic growth in countries with natural resource: Oil exporting countries. Quarterly Iranian Journal of Trade Studies (IJTS), 9(37). 1-24 (In Persian).
63
ORIGINAL_ARTICLE
Pattern of Time Allocation of Home Production in Iran’s Rural and Urban Areas
The main purpose of this paper is to present a pattern of time allocation of the Iranian head of households’ housework for rural and urban areas, in 2015 using the data of Statistical Centre of Iran. In this research, the theory of allocation of time (household production) of Gary Becker has been used, and the effect of the households’ socio-economic characteristics (including age of head of household, size of household, area of household's lodging, education and income of head of household) on the time spending for home production with household budget and time constraints has been studied. The results indicate that male and female who are head of household in rural areas spent more hours for home production compare to urban areas. Also, the male in urban and rural areas, compare to the female, devoted less hours to housework.
https://ecoj.tabrizu.ac.ir/article_7865_a7994f0654ebb435b742364461d114c0.pdf
2018-11-22
165
184
Household economics
Housework
Theory of allocation of time
Head of household
Yeganeh
Mousavi Jahromi
mosavi@pnu.ac.ir
1
Professor of Economics, Payame Noor University of Tehran
LEAD_AUTHOR
Mohammad Sadegh
Alipour
msalipour@hotmail.com
2
Assistant Professor of Economics, Research Center of Statistical Center of Iran
AUTHOR
Farhad
Khodadad Kashi
khodadad@pnu.ac.ir
3
Professor of Economics, Payame Noor University of Tehran
AUTHOR
Hamide
Torabi
torabi2280@yahoo.com
4
Ph.D. Candidates in Economics, Payame Noor University of Tehran
AUTHOR
رضایی، سولماز (1388). برآورد ارزش اقتصادی کار خانگی زنان روستایی (مطالعهی موردی روستاهای استان گیلان). پایان نامه کارشناسی ارشد، دانشگاه تهران.
1
عرب مازار، عباس، علیپور، محمدصادق، و یاسر زارع نیاکوکی (1393). تحلیل عوامل اجتماعی – اقتصادی موثر بر اشتغال زنان در ایران. فصلنامه علمی پژوهشی اقتصاد و الگوسازی 5، 91- 75.
2
3. قاضی طباطبایی، محمود، مسکوب، محمود، و نادر مهری (1394). برآورد ارزش اقتصادی کار بدون مزد خانگی سالمندان در ایران و سهم آن در تولید ناخالص ملی. نامه انجمن جمعیتشناسی ایران 8، 79- 96.
3
میرجلیلی، فاطمه (1386). بررسی ارزش اقتصادی کار خانگی زنان و شیوههای حمایت از آن. مرکز پژوهشهای مجلس.
4
مرکز آمار ایران(www.amar.org.ir).
5
Arab Mazar, Abbas, Alipour, Mohammad Sadegh, Yaser Zare Niyakouki (2014). Analysis of socio-economic factors affecting women's work in Iran. Journal of Economics and Modeling 5,75-91.
6
Becker Gary S. (1965). A Theory of the Allocation of time, The Economic Journal 75, 493 – 517.
7
Francavilla, F.,G.C.Giannelli G., Grotkowska and M.W.Socha. (2011). Use of time and value of unpaid family care work: a comparison between Italy and Poland, Discussion paper series, The Institute for the study of labor(IZA).NO.157.
8
Ghazi Tabatabaiee, Mahmoud, Maskoub, Mahmoud, Nader Mehri. (2015). Estimating the economic value of unpaid elderly work in Iran and its contribution in GNP. Iranian Society Community 8:16,79-96(In Persion).
9
Goldschmidt-Clermont, L. (1999). Households' non-SNA production: Labour time, value of labour and of product, and contribution to extended private consumption, Review of Income and Wealth, Vol. 45, No. 4, pp 519-529.
10
Graham, John W. and . Green, Carole A .(1984). Estimating the Parameters of a Household Production Function With Joint Producs. The Review of Economics and Statistics, 66 (2), 277-282.
11
Gronau, Reuben .(1977). Leisure, Home Production and Work – The Theory of Allocation of Time Revisited, Journaul of Political Economy 85, 1099-1123.
12
Hawrylyshyn, O. (1976). The Value of Household Dervices: A Survey of Empirical Estimates. Review of Income and Wealth, 22, 101-131.
13
Kulshreshtha A.C and Gulab Singh. (1999). Valuation of Non-Market Household Production. Central Statistical Organisation, New Delhi.
14
Landefeld, J.S., and McCulla, S.H. (2000). Accounting for Nonmarket Household Production within a National Accounts Framework. Review of Income and Wealth, pp 289-307.
15
Mirjalili Fatemeh. (2007). Evaluating the economic value of women's household work and ways to support it, Researches Center of the parliament(In Persion).
16
Rezaiee Solmaz .(2009). Estimating the economic value of rural women's household work (case study of villages in Guilan province, Master's Thesis, Tehran university (In Persion).
17
Sharp D.C., Ciscel D.H. & Heath. (1998). Back to Becker: Valuing Women`s Economic Contribution From Housework with Household Production Functions. Journal of Forensic Economics. 11(3). P. 215-235.
18
Statistical Center of Iran (www.amar.org.ir)
19
ORIGINAL_ARTICLE
The Effect of the Tax Mix on Income Distribution in Iran: An Autoregressive Distributed Lag (ARDL) Approach
The main objective of this study is to investigate the effect of changes in the tax mix on income distribution in Iran using data for the period 1361-1395. To this end, an empirical model is proposed to analyze the effects of substitution of different taxes, including income tax, corporate tax, wealth tax, goods and services tax, and import tax, on income inequality (as measured by the Gini coefficient). The results of the cointegration analysis based on the autoregressive distributed lag (ARDL) approach show that (1) the substitution of income tax for corporate tax, wealth tax, or goods and services tax leads to a reduction in income inequality, (2) the substitution of corporate tax for wealth tax reduces income inequality, (3) the substitution of goods and services tax for wealth tax reduces income inequality, whereas the substitution of this type of tax for corporate tax has no statistically significant effect on income inequality, and (4) the substitution of import tax for income tax, corporate tax, wealth tax, or goods and services tax improves income distribution. These results provide a useful guide for policy makers to achieve an optimal mix of taxes aimed at reducing income inequality.
https://ecoj.tabrizu.ac.ir/article_7952_c243ce8c8c390cf319785895bdedfd8c.pdf
2018-11-22
185
212
Gini coefficient
Tax mix
Iran
Mahboobeh
Farahati
m.farahati@yahoo.com
1
Assistant Professor of Economic, Semnan University
LEAD_AUTHOR
ابونوری، اسمعیل (1376). اثر شاخصهای اقتصاد کلان بر توزیع درآمد در ایران. مجله تحقیقات اقتصادی، 32(2)، 1- 31.
1
ابونوری، اسمعیل، و اسناوندی، اسماعیل (1384). برآورد و ارزیابی سازگاری شاخصهای نابرابری اقتصادی با استفاده از ریزدادهها در ایران. مجله تحقیقات اقتصادی، 40(4)، 171-209.
2
ابونوری، اسمعیل، و خوشکار، آرش (1385). اثر شاخصهای اقتصادکلان بر توزیع درآمد در ایران: مطالعه بین استانی. مجله تحقیقات اقتصادی، 41(6)، 65-95.
3
احمدی، علی محمد، و مهرگان، نادر (1384). تاثیر سیاست های تعدیل اقتصادی بر توزیع درآمد در ایران. تحقیقات اقتصادی، 40(3)، 209-232.
4
اسداله زاده بالی، میررستم (1387). اثربخشی مالیات بر نابرابری توزیع درآمد در ایران. پژوهشنامه مالیات، 16(1)، 73-92.
5
امین رشتی، نارسیس، و رفعت میلانی، مژگان (1389). بررسی اثر مالیات بر ارزش افزوده بر توزیع درآمد در کشورهای منتخب. پژوهشنامه مالیات، 19(11)، 63-84.
6
بانک مرکزی جمهوری اسلامی ایران، خلاصه تحولات اقتصادی کشور، سالهای مختلف.
7
جعفری صمیمی، احمد (1391). اقتصاد بخش عمومی (1). انتشارات سمت، چاپ دوازدهم، تهران، ایران.
8
دادگر، یداله، و غفاری، علی اکبر (1387). بررسی اثر مالیات حقوق بر توزیع درآمد در ایران. پژوهشهای اقتصادی (رشد و توسعه پایدار). 8(3)، 73-97.
9
رهبر، فرهاد، و سرگلزایی، مصطفی (1389). بررسی آثار سیاست های مالی بر رشد اقتصادی و فقر طی دوره 1363-1386. تحقیقات اقتصادی، 46(3)، 89-110.
10
زمانی، جواد (1382). تجزیه و تحلیل آثار مالیاتها بر نابرابری اقتصادی در ایران. پایان نامه کارشناسی ارشد، دانشگاهمازندران.
11
سیفی پور، رویا و رضایی، محمد قاسم (1390). بررسی عوامل موثر بر توزیع درآمد در اقتصاد ایران با تاکید بر مالیات ها. پژهشنامه مالیات، 19(10)، 121-142.
12
صباحی، احمد، دهقان شبانی، زهرا، و شهنازی، روح اله (1389). تاثیر بهره وری نیروی کار بر توزیع درآمد (مطالعه موردی در کشورهای منتخب). دانش و توسعه، 17(31)، 115-138.
13
صمدی، سعید، زاهد مهر، امین، و فرامرزی، ایوب (1387). بررسی اثر سیاست های مالی دولت بر توزیع درآمد و رشد اقتصادی در ایران. فصلنامه پژوهش های بازرگانی،13(49)، 99-119.
14
عبداله میلانی، مهنوش، پروین, سهیلا، و سیدی، کوثر (1396). ساختار تصاعدی مالیات بر درآمد و اثر آن بر نابرابری درآمد در استانهای کشور. پژوهشنامه اقتصادی، 17(66)، 1-22.
15
کردبچه، محمد (1375). بررسی درآمدهای مالیاتی در ایران. مجله برنامه و بودجه، 1(5)، 29-51.
16
کمیجانی، اکبر، و فهیم یحیایی، فریبا (1370). تحلیلی بر ترکیب مالیاتها و برآورد ظرفیت مالیاتی ایران. مجله اقتصاد و مدیریت، 3(1)، 67-86.
17
مهرآرا، محسن، و اصفهانی، پوریا (1394). بررسی رابطه بین توزیع درآمد و ساختار مالیاتی کشورهای منتخب. پژوهشنامه مالیات، 23(28)، 228-209.
18
ناصری گلعذاری، رسول (1374). نقش مالیات در توزیع درآمد، مطالعه تجربی در خصوص ایران 1350-1370. پایان نامه کارشناسی ارشد، دانشگاهمازندران.
19
Abdollah Milani, M., Parvin, S., & Seyedi, K. (2017). Progressive income tax structure and its effect on income inequality in Iranian provinces. Economics Research, 17(66), 1-22 (In Persian).
20
Abounoori, E. (1998). The effects of macroeconomic indicators on the income distribution in Iran. Journal of Economic Research (Tahghighat-E-Eghtesadi), 2(32), 1-31 (In Persian).
21
Abounoori, E., & Khoshkar, A. (2006). Effect of macroeconomic indicators on distribution of income in Iran: A Cross- Province Study. Journal of Economic Research (Tahghighat-E-Eghtesadi), 41(6), 65-95 (In Persian).
22
Abounoori, E., & Snavandi, E. (2006). Estimation and evaluation of consistency of economic inequality indices using microdata in Iran. Journal of Economic Research (Tahghighat-E-Eghtesadi), 40(4), 171-209 (In Persian).
23
Ahmadi, A., & Mehregan, N. (2006). Variations of income distribution and the economic adjustment in Iranian economy. Journal of Economic Research (Tahghighat-E-Eghtesadi), 40(3), 206-232 (In Persian).
24
Alavuotunki, K., Haapanen, M., & Pirttilä, J. (2018). The effects of the value-added tax on revenue and inequality. The Journal of Development Studies, 1-19.
25
Aminrashti, N., & Raf'atmilani, N. (2012). The effect of the value added taxation (VAT) on income distribution in selected countries. Journal of Tax Research, 19(11), 63-84 (In Persian).
26
Asadollahzadeh Bali, M. (2008). The impacts of taxes on inequality and income distribution in Iran. Journal of Tax Research, 16(1), 73-92 (In Persian).
27
Atkinson, A.B. (1977). Optimal taxation and the direct versus indirect tax controversy. Canadian Journal of Economics, 10(4), 590-606.
28
Atkinson, A.B., & Stiglitz, J.E. (1976). The design of tax structure: Direct versus indirect taxation. Journal of Public Economics, 6, 55–75.
29
Bird, R.M., & Zolt, E.M. (2005). Redistribution via Taxation: The limited role of the personal income tax in developing countries. UCLA Law Review, 52(6), 1627-95.
30
Borge, L. E., & Rattsø, J. (2004). Income distribution and tax structure: Microeconomic test of the Meltzer-Richard hypothesis. European Economic Review, 48, 805-526.
31
Central Bank of the Islamic Republic of Iran (CBI), Economic report & Balance Sheet. https://www.cbi.ir/category/EconomicReport_en.aspx
32
Chu, K., Davoodi, H., & Gupta, S. (2000). Income distribution and tax and government social spending policies in developing countries. Working Paper, Fiscal affairs Department, InternationalMonetary Fund (IMF). Available at: https://www. imf.org/external/pubs/ft/wp/2000/wp0062.pdf.
33
Cremer, H., Pestieau, P., & Rochet, J.C. (2001). Direct versus indirect taxation: The design of the tax structure revisited. International Economic Review, 42, 781–99.
34
Dadgar, Y., & ghafari, A A. (2008). The analysis of the impact of income tax on income distribution in Iran. The Economic Research, 8(3), 73-97 (In Persian).
35
Damuri, Y. R., & Perdana, A. A. (2003). The impact of fiscal policy on income distribution and poverty: A computable general equilibrium approach for Indonesia. Economics Working Paper No. WPE068, Center for Strategic and International Studies, Jakarta, Indonesia.
36
Engel, E. M., Galetovic, A., & Raddatz, C. E. (1999). Taxes and income distribution in Chile: Some unpleasant redistributive arithmetic. Journal of Development Economics, 59(1), 155-192.
37
García-Peñalosa, C., & Turnovsky, S.J. (2011). Taxation and income distribution dynamics in a neoclassical growth model. Journal of Money, Credit and Banking, 43, 1543–77.
38
Harberger, A.C. (1962). The incidence of corporation income tax. Journal of Political Economy, 70, 215–40.
39
Ilaboya, O. J., & Ohonba, N. (2013). Direct versus indirect taxation and income inequality. European Journal of Accounting Auditing and Finance Research, 1(1), 1-15.
40
Iosifidi, M., & Mylonidis, N. (2017). Relative effective taxation and income inequality: Evidence from OECD countries. Journal of European Social Policy, 27(1), 57-76.
41
Jafari Samimi, A. (2013). Public sector economics (1). Samt Publication Co. 12th edition, Tehran, Iran (In Persian).
42
Jha, S.k. (1999). Fiscal policy, income distribution and growth. Asian Development Bank Economic & Development Resource Center (EDRC), Report Series, no, 67.
43
Komijani, A., & Fahim Yahyaei, F. (1991). Analysis of the composition of taxes and tax capacity of Iran. Journal of Economics and Management, 3(1), 67-86 (In Persian).
44
26. Kordbacheh, M. (1996). Tax revenues in Iran. The Journal of Planning and Budgeting, 1(5), 29-51 (In Persian).
45
Martínez-Vázquez, J., Vulovic, V., & Moreno-Dodson, B. (2012). The impact of tax and expenditure policies on income distribution: evidence from a large panel of countries. Hacienda Publica Espanola, 200(1): 95- 130.
46
28. Mehran, F. (1975). Tax and income distribution of tax burdens in Iran. ILO working paper, WEP 2-23/ WP 33.
47
Mehrara, M., & Esfahani, P. (2016). The relationship between income distribution and tax structure in the selected Countries. Journal of Tax Research, 23(28), 209-228 (In Persian).
48
Musgrave, R.A. (1959). Theory of Public Finance. New York: McGraw-Hill Book Co.
49
Narayan, P. K., & Smyth, R. (2006). What determines migration flows from low‐income to high‐income countries? An empirical investigation of fiji–Us migration 1972–2001. Contemporary Economic Policy, 24(2), 332-342.
50
Naseri Golozari, R. (1996). The role of tax in income distribution: An empirical study for Iran 1972-1992. Master’s thesis, University of Mazandaran, Mazandaran, Iran (In Persian).
51
Obaretin, O., Akhor, S. O., & Oseghale, O. E. (2017). Taxation an effective tool for income re-distribution in Nigeria. Mediterranean Journal of Social Sciences, 8(4), 187-196.
52
Palme, M. (1996). Income distribution effects of the Swedish 1991 tax reform: An analysis of a microsimulation using generalized Kakwani decomposition. Journal of Policy Modeling, 18(4), 419-443.
53
Pesaran, M. H., Shin, Y., & Smith R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
54
Rahbar, F., & Sargolzai, M. (2012). Effects of fiscal policy on economy growth and poverty during the period 1386-1363 in Iran. Journal of Economic Research (Tahghighat-E-Eghtesadi), 46(3), 89-110 (In Persian).
55
Sabahi, A., Dehghan Shabani, Z., & Shahnazi, R. (2011). The Impact of labor force productivity on income (distribution for selected countries). Knowledge and Development, 17(31), 115-138 (In Persian).
56
Samadi, S., Zahed Mehr, A., & Faramarzi, A. (2009). The Impacts of fiscal policy on income distribution and economic growth in Iran. Iranian Journal of Trade Studies (IJTS), 13(49), 99-119 (In Persian).
57
Seifeepour, R., & Rezaee, M. (2011). An analysis of the effective factors on income distribution in Iran with the emphasis on taxes. Journal of Tax Research, 19(10), 121-142 (In Persian).
58
Weller, C. E. (2007). The benefits of progressive taxation in economic development. Reviewof Radical Political Economics, 39(3), 368-376.
59
Zamani, J. (2011). An analysis of the effects of taxes on economic inequality in Iran. Master’s thesis, University of Mazandaran, Mazandaran, Iran (In Persian).
60
ORIGINAL_ARTICLE
Calibration of Precautionary Saving Models for Iran Economy
The main question of this paper is that which interest rate value assures existence and optimality of equilibrium, in an environment that we have only precautionary demand for money and assets. This environment has two properties: heterogeneous agents and incomplete markets. In this environment, agents hold precautionary savings (in form of a single asset such as fiat currency, credit, and capital) for self-insurancing themselves against idiosyncratic income fluctuations. Bewley models are formed in this environment. In this paper, we calibrate this model for Iran economy and show that when agents have access to the fiat currency or credit, these results are true. The main question of this paper is that which interest rate value assures existence and optimality of equilibrium, in an environment that we have only precautionary demand for money and assets. This environment has two properties: heterogeneous agents and incomplete markets. In this environment, agents hold precautionary savings (in form of a single asset such as fiat currency, credit, and capital) for self-insurancing themselves against idiosyncratic income fluctuations. Bewley models are formed in this environment. In this paper, we calibrate this model for Iran economy and show that when agents have access to the fiat currency or credit, these results are true.
https://ecoj.tabrizu.ac.ir/article_7961_8f73d7c5d1405c56fa96f4200939d1ee.pdf
2018-11-22
213
238
Interest rate
Monetary equilibrium
Self-insurancing
Bewley models
Seyyed Aqil
Hoseiny
aqil.hoseiny@yu.ac.ir
1
Assistant Professor of Economics, Yasouj University
LEAD_AUTHOR
Mohammad
Vaez Barzani
vaez@polt.ui.ac.ir
2
Associate Professor of Economics University of Isfahan
AUTHOR
Rasoul
Bakhshi Dastjerdi
r.bakhshi@ase.ui.ac.ir
3
Associate Professor of Economics University of Isfahan
AUTHOR
Afshin
Parvardeh
a.parvardeh@sci.ui.ac.ir
4
Associate Professor of Statistics, University of Isfahan
AUTHOR
حسینی، سید عقیل (۱۳۹۲). تحلیل اثرات نرخ بهره پولی مثبت بر بهینگی و پایداری با تأکید بر مدلهای پسانداز احتیاطی. پایاننامه دکتری علوم اقتصادی. دانشکده علوم اداری و اقتصاد، دانشگاه اصفهان.
1
شاهمرادی، اصغر، و کاوند، حسین و ندری، کامران (1389). برآورد نرخ بهره تعادلی در اقتصاد ایران، مجله تحقیقات اقتصادی، (۱)90، ۱۹-۴۱.
2
عباسینژاد، حسین، و شاهمرادی، اصغر و کاوند، حسین (1388). برآورد یک مدل ادوار تجاری برای اقتصاد ایران با استفاده از رهیافت کالمن و حداکثر راستنمایی. مجله تحقیقات اقتصادی ایران، (۴)۴۴، ۱۸۵-۲۱۴.
3
دینمحمدی، مصطفی (1387). ارائه الگویی برای تخصیص بهینه منابع گاز طبیعی ایران. پایاننامه دکتری علوم اقتصادی. دانشکده علوم اداری و اقتصاد، دانشگاه اصفهان.
4
وبسایت بانک مرکزی ایران، آمار و دادهها (www.cbi.ir).
5
Abbasinejad, H., Shahmoradi, A., & Kavand, H. (2009). Estimation of a real business cycle model for the iran's economy: Applying kalman filtering approach and maximum likelihood method. Journal of Economic Research, 44 (4), 185-214 (In Persian).
6
Acemoglu, D., & Jensen, M. K. (2015). Robust comparative statics in large dynamic economies. Journal of Political Economy, 123(3), 587-640.
7
Açıkgöz, Ö. T. (2018). On the existence and uniqueness of stationary equilibrium in Bewley economies with production. Journal of Economic Theory, 173, 18-55.
8
Aiyagari, S. R. (1994). Uninsured idiosyncratic risk and aggregate saving. The Quarterly Journal of Economics, 109(3), 659-684.
9
Bailey, M. J. (1956). The welfare cost of inflationary finance. Journal of political Economy, 64(2), 93-110.
10
Benhabib, J., Bisin, A., & Zhu, S. (2015). The wealth distribution in Bewley economies with capital income risk. Journal of Economic Theory, 159, 489-515.
11
Bewley, T. (1980). The optimum quantity of money. Models of monetary economies, 169-210.
12
Bewley, T. (1983). A difficulty with the optimum quantity of money. Econometrica: Journal of the Econometric Society, 1485-1504.
13
Bewley, T. F. (2009). General equilibrium, overlapping generations models, and optimal growth theory. Harvard University Press.
14
Central Bank of Iran (www.cbi.ir).
15
Chamberlain, G., & Wilson, C. A. (2000). Optimal intertemporal consumption under uncertainty. Review of Economic dynamics, 3(3), 365-395.
16
Debreu, G. (1959). Theory of value: An axiomatic analysis of economic equilibrium. Yale University Press.
17
Dinmohammadi, M. (2008). Model for optimal allocation of natural gas resources of iran, ph.d dissertation. Administrative Sciences &Economics, University of Isfahan (In Persian).
18
Friedman, M. (1957). The permanent income hypothesis. In A theory of the consumption function (pp. 20-37). Princeton University Press.
19
Gong, G., & Semmler, W. (2004). Stochastic dynamic macroeconomics: Theory, numerics and empirical evidence. Center for Empirical Macroeconomics, book manuscript, Bielefeld University.
20
Grandmont, J. M., & Laroque, G. (1973). Money in the pure consumption loan model. Journal of Economic Theory, 6(4), 382-395.
21
Hoseiny, S. A. (2013). Analysis of the positive money interest rate effects on the optimality and sustainability (by an emphasis on the precautionary saving models). Ph.d Dissertation in Monetary Economics, Supervisors: Dr Rahim Dallali Esfahani- Dr Mohammad Vaez Barzani. Administrative Sciences &Economics, University of Isfahan (In Persian).
22
Huggett, M. (1993). The risk-free rate in heterogeneous-agent incomplete-insurance economies. Journal of economic Dynamics and Control, 17(5-6), 953-969.
23
İmrohoroğlu, A. (1992). The welfare cost of inflation under imperfect insurance. Journal of Economic Dynamics and Control, 16(1), 79-91.
24
Kaplan, G., Moll, B., & Violante, G. L. (2018). Monetary policy according to HANK. American Economic Review, 108(3), 697-743.
25
Kirkby, R. (2018). Bewley–Huggett–Aiyagari models: computation, simulation, and uniqueness of general equilibrium. Macroeconomic Dynamics, 1-40.
26
Krusell, P., & Smith, Jr, A. A. (1998). Income and wealth heterogeneity in the macroeconomy. Journal of political Economy, 106(5), 867-896.
27
Krusell, P., M., T., & Smith, A. A. (2011). Asset prices in a Huggett economy. Journal of Economic Theory, 146(3), 812.
28
Lucas, Jr., R. E. & Prescott E. C., Stokey, N. (1989). Recursive methods in economic dynamics. Cambridge, MA: Harvard University Press.
29
Sargent, T. J. & Ljungqvist, L. (2013). Recursive macroeconomic theory (Third Ed.). MIT Press.
30
Shahmoradi, A., Kavand, H. & Nadri, K. (2010). Estimation of equilibrium interest rate in iran economy. Journal of Economic Research, 90 (In Persian).
31
ORIGINAL_ARTICLE
The Study of the Most Effective Factors Explaining Economic Growth in OIC Countries: Bayesian Panel Likelihood Ppproach
The defects of growth models and the methods of examining relevant empirical evidence, as well as the multiplicity of sources and factors of economic growth, have led to uncertainty about the accuracy of the model specification and impeded consensus among researchers about the key determinants of economic growth. The purpose of this paper is to determine the most important growth factors in OIC member states. For this purpose, a sample of these countries has been selected during period 1975 - 2015 and using the Bayesian Maximum Likelihood Approach (BML) in the context of panel data, among the many factors that can affect growth, endogenously and through various exams in many repetitions, the factors that have the greatest impact are selected and introduced as the robust factors. According to the results, saving rates (SR), foreign direct investment (FDI), investment (ISH), total factors productivity (TFP), and research and development expenditures (R & D) have had the greatest impact on economic growth in these countries. The results could be used to build appropriate patterns for explaining economic growth issues in OIC member states and better management of the economic growth process.
https://ecoj.tabrizu.ac.ir/article_7685_3579f7b2dcf97aa807c035644bc1c751.pdf
2018-11-22
239
263
Maximum Bayesian Trust
Economic growth
R&D
Productivity
Foreign direct investment
Organization of Islamic Cooperation
Ali
Besharat
indolandi@yahoo.com
1
Ph.D. Candidate in Economics, University of Tabriz
AUTHOR
Reza
Ranjpour
reza.ranjpour@gmail.com
2
Associate Professor of Economics, University of Tabriz
LEAD_AUTHOR
Seyed Kamal
Sadeghi
sadeghiseyedkamal@gmail.com
3
Associate Professor of Economics, University of Tabriz
AUTHOR
بهمنی، مجتبی، حسنخانی، معصومه، و شکیبایی، علیرضا (1395). بررسی تاثیر سرریز تکنولوژی ناشی از سرمایهگذاری مستقیم خارجی بر بهرهوری نیروی کار در صنایع کارخانهایی ایران، فصلنامه پژوهشهای اقتصاد صنعتی ایران، 1(2)، 115-92.
1
جلال آبادی، اسداله، و بهرامی، جاوید (1389). عوامل تعیینکننده رشد اقتصادی در گروه کشورهای مختلف (رویکردی نو به عوامل تعیین کننده رشد اقتصادی). اقتصاد مقداری، 7(1)، 51-23.
2
مهرآرا, محسن، و رضایی برگشادی، صادق. (1395). بررسی عوامل مؤثر بر رشد اقتصادی ایران مبتنی بر رویکرد متوسطگیری بیزین (BMA) و حداقل مربعات متوسط وزنی (WALS). فصلنامه علمی-پژوهشی، پژوهشهای رشد و توسعه اقتصادی, 6(23), 114-89.
3
Acemoglu, D., & Restrepo, P. (2016). The race between machine and man: Implications of technology for growth, factor shares and employment. (No. w22252). National Bureau of Economic Research.
4
Aghion, P. & Howitt, P. (1992). A model of growth through creative destruction. Econometrica 60(2), 323-351.
5
Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies, 58(2), 277-297.
6
Baccaro, L., & Pontusson, J. (2016). Rethinking comparative political economy: the growth model perspective. Politics & Society, 44(2), 175-207.
7
Bahmani, M, Hasankhani, M & Shakibaee, A (2016).
8
The effect of technology spillovers from foreign direct investment on labor productivity in manufacturing in Iran. Quarterly Journal of Industrial Economics Researches, 1(2), 92-115 (In Persian)
9
Barro, R. J. (2003). Determinants of economic growth in a panel of countries. Annals of economics and finance, 4, 231-274.
10
Doppelhofer, G., Miller, R. I., & Sala-i-Martin, X. (2000). Determinants of long-term growth: A Bayesian averaging of classical estimates (BACE) approach. (No. w7750). National Bureau of Economic Research
11
Draper, D. (1995). Assessment and propagation of model uncertainty. Journal of the Royal Statistical Societ: Series B (Methodological), 45-97.
12
Durlauf, S. N., Kourt ellos, A., & Tan, C. M. (2008). Are any growth theories robust? The Economic Journal, 118(527), 329-346.
13
Easterly, William, (1993). How much do distortions affect growth? Journal of Economic Growth, 1, 363–389.
14
Fernandez, C., Ley, E., & Steel, M. F. (2001). Benchmark priors for Bayesian model averaging. Journal of Econometrics, 100(2), 381-427.
15
Ghosh, J. K., & Samanta, T. (2001). Model selection–an overview. Current Science, 1135-1144.
16
Grossman, G. M., & Helpman, E. (1991). Quality ladders in the theory of growth. The Review of Economic Studies, 58(1), 43-61.
17
Jalalabadi, A., & Bahrami, J. (2010). Factors determining economic growth in various groups of countries (A new approach to determining factors of economic growth). Quantitative Economics, 7(1), 23-51 (In Persian)
18
Jeffreys, H. (1961). Theory of Probability. 3rd edn, Oxford: The Clarendon Prs.
19
Koop, G., (2003). Bayesian econometric, New York, John Wiley and Sons.
20
Kormendi, R. C., & Meguire, P. G. (1985). Macroeconomic determinants of growth: cross-country evidence. Journal of Monetary economics, 16(2), 141-163.
21
Leamer, E. E. (1983). Let's take the con out of econometrics. The American Economic Review, 73(1), 31-43.
22
Leon-Gonzalez, R., & Vinayagathasan, T. (2015). Robust determinants of growth in Asian developing economies: A Bayesian panel data model averaging approach. Journal of Asian Economics, 36, 34-46.
23
Levine, R., & Renelt, D. (1992). A sensitivity analysis of cross-country growth regressions. The American economic review, 942-963.
24
Lucas, R. E. (1998). On the mechanics of economic development. Econometric Society Monographs, 29, 61-70.
25
Magnus, J. R., Powell, O., & Prüfer, P. (2010). A comparison of two model averaging techniques with an application to growth empirics. Journal of Econometrics, 154(2), 139-153.
26
Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. The quarterly journal of economics, 107(2), 407-437.
27
Mehrara, M., & Rezaei Bargshadi, S, (2016). The determinants of Economic growth in Iran based on Bayesian model averaging and weighted averaging least square. Quarterly Journal of Research on Economic Growth and Development, 6 (23), 114-89. (In Persian).
28
Moral-Benito, E. (2012). Determinants of economic growth: a Bayesian panel data approach. Review of Economics and Statistics, 94(2), 566-579.
29
Nafziger, E. Wayne. (2012). Economic Development. Fifth edition published by Cambridge University Press.
30
Nickell, S. (1981). Biases in dynamic models with Fixed Effects. Econometrica, 49(6), 1417-1426.
31
Raftery, A. E. (1996b). Approximate Bayes factors and accounting for model uncertainty in generalised linear models. Biometrika, 83(2), 251-266.
32
Ramsey, F. P. (1928). A mathematical theory of saving. The economic journal, 38(152), 543-559.
33
Rodrik, D., Subramanian, A. & Trebbi, F. (2004). Institutions rule: The primacy of institutions over geography and integration in economic development. Journal of Economic Growth, 9, 131–165.
34
Romer, D. (2016). Advanced macroeconomics. Mc raw -hill companies.
35
Sachs, J. D., & Warner, A. M. (1997). Fundamental sources of long-run growth. The American economic review, 87(2), 184-188.
36
Sala-i-Martin, X., Doppelhoffer, G., & Miller, R. (2001). Cross-sectional growth regressions: Robustness and Bayesian model averaging. Columbia University. Mimeographed.
37
Solow, R. M. (1956). A contribution to the theory of economic growth. The quarterly journal of economics, 70(1), 65-94.
38
Todaro, M., & Smith, S. (2003). Development economics. Pearson education.
39
Zellner, A. (1986). On assessing prior distributions and Bayesian regression analysis with g-prior distributions. Bayesian inference and decision techniques: Essays in Honor of Bruno De Finetti, 6, 233-243.
40