ORIGINAL_ARTICLE
Optimal Intervention in the Foreign Exchange Market: The Case of Iran
In a managed floating exchange rate regime, one of the most important issues is the degree to which the monetary authorities intervene in the foreign exchange market. The appropriate level of intervention in the foreign exchange market can be discussed in a framework which emphasizes the trade-off between changes in the country’s level of international reserves and minimizes the country’s real exchange rate misalignment. In this paper we derived an optimal intervention rule for the period of post managed floating regime in Iran applying a dynamic programming approach. The derived rule indicates that, in the context of the Iranian economy, how the monetary authorities can manage the foreign exchange market with minimum possible cost.
https://ijes.shirazu.ac.ir/article_1559_3c09205f4dbaefddf18f3c73a77750f4.pdf
2014-03-21
1
22
10.22099/ijes.2014.1559
Foreign exchange market intervention
Foreign reserves management
Optimal rule
Dynamic programming
Zahra
Azizi
zazizi61@yahoo.com
1
Ph.D. Students in Shiraz Universityh
LEAD_AUTHOR
Ebrahim
Hadian
ehadian@rose.shirazu.ac.ir
2
Professor of Economics in Shiraz University
AUTHOR
Almekinders, G. (1996). The political economy of Central Bank intervention. Public Choice, July, 127-146.
1
Bereau, B., Lopez, A., & Mignon, V. (2008). Nonlinear Adjustment of the Real Exchange Rate Towards its Equilibrium Value: a Panel Smooth Transition Error Correction Modelling, Working Papers 2008-23, CEPII research center.
2
Boyer, R. S. (1978). Optimal foreign exchange market intervention. The Journal of Political Economy, 86(6), 1045-1055.
3
Brainard, W. C. (1967). Uncertainty and the effectiveness of policy. American Economic Revenue Papers and Proceedings, 57, 411-25.
4
Cadenillas, A., & Zapatero, F. (1999). Optimal Central Bank Intervention in the foreign exchange market. Journal of Economic Theory, 87, 218- 242.
5
Calvo, G. A., & Rienhart, C. M. (2002). Fear of floating. The Quarterly Journal of Economics, 117(2), 379-408.
6
Dee, P. S. (1983). Optimal Exchange Market Intervention. (Ph.D. Thesis), Canada, Vancouver, Simon Fraser University.
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Domac, I., Kyle, P. & Yevgeny, Y. (2001). Does the Exchange Rate Regime Affect Macroeconomic Performance? Evidence from Transition Economies. Policy Research Working Paper 26242.
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Edwards, S. (1988). Real and Monetary Determinants of Real Exchange Rate Behavior: Theory and Evidence from Developing Countries. Journal of Development Economics, 29, 311-341,
9
Frenkel, J. (2003). Experience of and Lessons From Exchange Rate Regimes in Emerging Economies. NBER WP 10032.
10
Friedman, M. (1953). The Case for Flexible Exchange Rates. in Friedman M. Essays in Positive Economics, Chicago: University of Chicago Press, 157-203.
11
Galati, G., & Melick, W. (2002). Central Bank Intervention and Market Expectations. BIS Papers, 10.
12
Garcia, L. G. (2002). Trading Rule Profitability and Official Intervention in Foreign Exchange Markets of Emerging Economies. Ph.D. Thesis, College of Business and Economics at West Virginia University.
13
Hassan, M. M. (2009). Essays on Central Bank Interventions in Advanced and Emerging Market Economies an Application to Japan and Turkey. Ph.D. Thesis, United States The City University of New York.
14
Horvath, R. (2007). Modelling Central Bank Intervention Activity under Inflation Targeting. Economics Bulletin, 6(29), 1-8.
15
Im, J-H. (2001). Optimal Currency Target Zones: How Wide Should Exchange Rate Bands Be? International Economic Journal, 15(1), 61 – 93.
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Ito, T. (2002). Is Foreign Exchange Intervention Effective? The Japanese Experiences in the 1990s. NBER Working Paper, No. 8914.
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Kearny, C., & McDonald, R. (1986). Intervention and sterilization under Floating Exchange Rates: the UK 1973-1983. European Economic Review, 30, 345-364.
18
Kenen, P. (2000). Fixed Versus Floating Exchange Rates. Cato Journal, 20(1), 109-113.
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Kercheval, A. N., & Moreno, J.F. (2009). Optimal Intervention in the Foreign Exchange Market When Interventions Affect Market Dynamics. Quantitative Finance Papers, No. 0909.1142.
20
Kim, S., & Sheen, J. (2002). The Determinants of Foreign Exchange Intervention by Central Banks: Evidence from Australia. Journal of International Money and Finance, 21(4), 619-649.
21
Kriljenko, J. I. C., Guimaraes, R., & Karacadag C. (2003). Official Intervention in Foreign Exchange Market: Element of Best Practice. IMF Working Paper, WP/03/152.
22
Miller M., & Zhang, L. (1996). Optimal Target Zones: How an Exchange Rate Mechanism Can Improve upon Discretion. Journal of Economic Dynamics and Control, 20, 1641-1660.
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Mundaca G., & Oksendal, B. (1998). Optimal Stochastic Intervention Control With Application to the Exchange Rate. Journal of Mathematical Economics, 29, 225-243.
25
Poirson, H. (2001). How Do Countries Choose Their Exchange Regime? IMF Working Paper, WP/01/46.
26
Pontines V., & Rajan, R. S. (2011). Foreign Exchange Market Intervention and Reserve Accumulation in Emerging Asia: Is There Evidence of Fear of Appreciation? Economics Letters , 111, 252–255.
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Poole, W. (1970). Optimal Choice of Monetary Policy Instruments in a Simple Stochastic Macro Model. Journal of Political Economy, 84, 197-216.
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Reinhart, C. M., & Rogoff, K. S. (2004). The Modern History of Exchange Rate Arrangements: A Reinterpretation. The Quarterly Journal of Economics, 119(1), 1-48.
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Sargent, T. L. (1987). Dynamic Macroeconomic Theory. Cambridge: Harvard University Press.
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Sarno, L., & Taylor, M. )2001(. Official Intervention in the Foreign-Exchange Market: Is It Effective and, if So, How Does It Work? Journal of Economic Literature, 39, 839-868.
31
Sohman, E. (1969). Flexible Exchange rates: Theory and Controversy, Chicago: University of Chicago Press.
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Tagaki, S. (1991). Foreign Exchange Market Intervention and Domestic Monetary Control in Japan, 1973-89. Japan and the World Economy, 147-180.
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Taylor, D. (1982). Official Intervention in the Foreign Exchange Market, or, Bet Against the Central Bank. Journal of Political Economy, 90, 356-368.
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35
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36
ORIGINAL_ARTICLE
The Impact of Oil and Gold Prices’ Shock on Tehran Stock Exchange: A Copula Approach
There are several researches that deal with the behavior of SEs and their relationships with different economical factors. These range from papers dealing with this subject through econometrical procedures to statistical methods known as copula. This article considers the impact of oil and gold price on Tehran Stock Exchange market (TSE). Oil and gold are two factors that are essential for the economy of Iran and their price are determined in the global market. The model used in this study is ARIMA-Copula. We used data from January 1998 to January 2011 as training data to find the appropriate model. The cross validation of model is measured by data from January 2011 to June 2011. We conclude that: (i) there is no significant direct relationship between gold price and the TSE index, but the TSE is indirectly influenced by gold price through other factors such as oil; and (ii) the TSE is not independent of the volatility in oil price and Clayton copula can describe such dependence structure between TSE and the oil price. Based on the property of Clayton copula, which has lower tail dependency, as the oil price drops, stock index falls. This means that decrease in oil price has an adverse effect on Iranian economy.
https://ijes.shirazu.ac.ir/article_1560_cb2ee08f98df3a119f4fde4322554bc2.pdf
2014-03-21
23
47
10.22099/ijes.2014.1560
Stock Exchange market (SE)
Oil
Gold
Copula
ARIMA processes
Amir
T. Payandeh Najafabadi
amirtpayandeh@sbu.ac.ir
1
Professor of Economics in Shahid Beheshti University
LEAD_AUTHOR
Marjan
Qazvini
2
Ph.D. Student in Allameh Tabatabai University
AUTHOR
Reza
Ofoghi
ofoghi@gmail.com
3
pH.D. Student in Allameh Tabatabai University
AUTHOR
Abbasian, E. A., Moradpour Ouladi, M., and Abbasioun, V. (2008). The impact of macroeconomic variables on the SE: Evidence from Tehran Stock Exchange. Iranian Economic Research, 36, 135-152.
1
Arouri, M. (2011). Does crude oil move SE in Europe? A sector investigation. Economic Modeling,28, 1716-1725.
2
Arouri, M., Lahiani, A., and Ngugen, D. (2011). Return and volatility transmission between world oil prices and SEs of the GCC countries. Economic Modeling, 28, 1815-1825.
3
Arouri, M. and Rault, C. (2010). Oil prices and SEs: What drives what in the Gulf Corporation Council Countries? ESIFO working paper No. 2934. Category 10: Energy and Climate Economics.
4
Basher, S. A. and Sadorsky, P. (2006). Oil price risk and emerging SEs. Global Finance Journal, 17, 224–251.
5
Bashiri, N. (2011). The study of relationship between stock exchange index and gold price in Iran and Armenia. 5, http//:www.armef.com/pdfs/Neda_Bashiri.pdf/.
6
Brockwell, P. J. and Davis, R. A. (2009). Time Series: Theory and methods. New York: Springer.
7
Cherubini U., Luciano E., and Vecchiato W. (2004). Copula methods in finance, England: Wiley.
8
Clayton, D. G. (1978). A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika, 65, 141–151.
9
Constantinos, K., Ektor, L., and Dimitrios, M. (2010). Oil price and SE linkages in a small and oil dependent economy: the case of Greece. The Journal of Applied Business Research,26, 55–63.
10
Denuit, M., Dhaene, J., Goovaerts, M., and Kaas, R. (2005). Actuarial theory for dependent risks, measures, orders and models, Wiley, England.
11
El-Sharif, I., Brown, D., Burton, B., Nixon, B., and Russel, A. (2005). Evidence on the nature and extent of the relationship between oil prices and equity values in the UK. Energy Economics, 27, 819–830.
12
Eslamlouian, K. and Zare, H. (2007). The impact of macro variables and alternative assets on stock price movement in Iran: An ARDL model. Iranian Economic Research,29, 17-46.
13
Farzanegan, M. R. and Markwardt, G. (2009). The effect of oil price shocks on the Iranian economy. Energy Economics,31, 134–151.
14
Foster, K. and Kharazi, A. (2008). Contrarian and momentum returns on Iran’s Tehran Stock Exchange, The Journal of International Financial Markets. Institutions and Money,18, 16–30.
15
Frees, E. W. and Valdez, E. A. (1998). Understanding relationships using copulas. North American Actuarial Journal, 1, 1–25.
16
Frees, E. W. and Wang, P. (2005). Credibility using copula. North American Actuarial Journal, 2, 31–48.
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Furstenberg, G. M. and Bang, N. J. (1989). International stock price movements: links and messages. Brookings Papers on Economic Activity, 1, 125–179.
18
Genest, C. and Favre, A. C. (2007). Everything you always wanted to know about copula but were afraid to ask. Journal of Hydrologic Engineering, 12, 347–368.
19
Genest, C. Rémillard, B. and Beaudoin, D. (2009). Goodness-of-fit tests for copulas: A review and a power study. Insurance: Mathematics and Economics,44, 199–213.
20
Grégoire, V., Genest, C., and Gendron, M. (2008). Using copulas to model price dependence in energy market. Energy Risk,5, 58–64.
21
Hammoudeh, S., and Aleisa, E. (2004). Dynamic relationships among GCC SEs and Nymex oil futures. Contemporary Economic Policy, 22, 250–269.
22
Hammoudeh, S., and Choi, K. (2006). Behaviour of GCC SEs and impacts of US oil and financial markets. Research in International Business and Finance, 20, 22–44.
23
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24
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26
IMF (2010). Islamic Republic of Iran: Selected Issues, IMF Country Report No. 10/76.
27
IMF (2011). Islamic Republic of Iran: Selected Issues, IMF Country Report No. 11/242
28
Jawadi F., Arouri M., and Bellalah M. (2010). Nonlinear linkages between oil and SEs
29
in developed and emerging countries. International Journal of Business, 15, 19–31.
30
Jondeau, E., and Rockinger, M. (2006). The Copula-GARCH model of conditional dependencies: An international SE application. Journal of International Money and Finance, 25, 827–853.
31
Keshavarz, H. G., and Manavi, S. H. (2009). SE and exchange rates interactions with respect to oil shocks. Iranian Economic Research, 37, 147-169.
32
Kilian, L., and Park, C. (2009). The impact of oil price shocks on the US SE. International Economic Review, 4, 1267–1287.
33
Kojadinovic, I., and Yan, J. (2010). Modeling multivariate distributions with continuous margins using the copula R package. Journal of Statistical Software, 9, 1–20.
34
Lehmann, E. L., and Romano, J. P. (2005). Testing statistical hypothesis, 3rd ed. Springer, New York, USA.
35
Lin, C., Fang, C., and Cheng, H. (2009). Relationship between oil price shocks and SE: An empirical analysis from the Greater China.
36
Malik, F., and Hammoudeh, S. (2007). Shock and volatility transmission in the oil, US and Gulf equity markets. International Review of Economics and Finance, 16, 357–368.
37
Mashayekh, S., Haji Moradkhani, H., and Jafari, M. (2011). Impact of macroeconomic variables on SE: The case of Iran. 2nd International conference on business and economic research (2nd ICBER 2011).
38
Masron, T. A., and Fereidouni, H.G. (2010). Performance and diversification benefits of housing investment. International Journal of Economics and Finance, 4, 7–11.
39
Melo Mendes, B. V., and Ai’ube, C. (2011). Copula based models for serial dependence. International Journal of Managerial Finance, 7, 68–82.
40
Mohanty, S., Nandha, M., and Bota, G. (2010). Oil shocks and stock returns: The case of the Central and Eastern European (CEE) oil and gas sectors. Emerging Markets Review, 11, 358–372.
41
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42
Nandha, M., and Hammoudeh, S. (2007). Systematic risk, and oil price and exchange rate sensitivities in Asia-Pacific SEs. Research in International Business and Finance,21, 326–341.
43
Nelsen, R. (2006). An introduction to copulas,2nd, Springer, New York.
44
Ning, C. (2010). Dependence structure between the equity market and the foreign exchange market- A copula approach. Journal of International Money and Finance, 29, 743–759.
45
Papachristou, D. (2004). Modelling dependencies. The Actuary, April, 24–27.
46
Park, J. W., and Ratti, R. A. (2007). Oil price shocks and SEs in the US and 13 European countries, Department of Economics, University of Missouri-Colombia, USA.
47
Pesaran, M. H., and Shin, Y. (1999). An autoregressive distributed lag modeling approach to cointegration analysis. (ed) S. Strom, Econometrics and Economic Theory in the 20th Century: The Ragner Frisch Centennial Symposium, chapter 11.Cambridge University Press, Cambridge.
48
Roch, O., and Alegra, A. (2006). Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish SE. Computational Statistics and Data Analysis, 51, 1312–1329.
49
Reboredo, J. (2011). How do crude oil prices co-move? A copula approach. Energy Economics, 33, 948-955.
50
Saeidi, P., and Amiri, A. (2009). Relation between macroeconomic variables and general index in Tehran Stock Exchange. Economic Modeling,(Iran), 2, 111-130.
51
Samadi, S., Shirani, Z., and Davarzadeh, M. (2007). Investigating the influence of world price of gold and oil on the Tehran Stock Exchange Index: modeling and forecasting. Quarterly Journal of Quantitative Economics,4, 25–51.
52
Wang, K., Chen, Y., and Huang, S. (2011). The dynamic dependence between the Chinese market and other international SEs: A time-varying copula approach. International Review of Economics and Finance,20, 654–664.
53
Zare, H., and Rezaei, Z. (2006). The effects of foreign exchange, gold coin and housing markets on Tehran SE: A vector error correction model. Research Bulletin of Isfahan University (Humanities),21, 99–112.
54
Zhang, Y., and Wei, Y. (2010). The crude oil market and the gold market: Evidence for cointegration, causality and price discovering. Resources Policy,35, 168–177.
55
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56
http://www.indexmundi.com/.
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http://www.tse.ir/.
58
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59
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60
ORIGINAL_ARTICLE
Wage Inequality in Developing Countries: An Examination of New Economic Geography Theory
The purpose of this study is to investigate the factors affecting the manufacturing industry wage among selected developing countries based on new economic geography theory. More specifically, we use a panel data model to study the spatial structure of wages in 136 countries for the period 1998-2007. The results indicate that this theory provides a good description of the spatial structure of wages. We find that the market size and the distance-weighted have positive relationships with wage. However, the price of non-tradable goods has a negative effect on the spatial structure of wages. The result shows that the conditions governing the labor market is more important in explaining wage inequalities than the characteristics of labor or labor productivity.
https://ijes.shirazu.ac.ir/article_1561_03cca5db0f0b6d772ecd27dd92ebd1f3.pdf
2014-03-21
49
67
10.22099/ijes.2014.1561
New Economic Geography
Spatial Structure of Wage
Centralization
Transport Costs
developing countries
Saeed
Rasekhi
srasekhi@umz.ac.ir
1
Professor of Economics in Mazandaran Universityh
LEAD_AUTHOR
Marzieh
Dindar Rostami
marzieh.dindar@gmail.com
2
Ph.D. Student in Mazandaran University
AUTHOR
Amiti, M. & Cameron, L. (2004). Economic geography and wages. CEPR Discussion Papers, No.4234.
1
Ashrafzadeh, H. & Mehregan, N. (2008). Econometrics of panel data. Tehran University, Tehran.
2
Betts, C. M. (2008). Real exchange rate movements and the relative price of non-traded goods. Staff papers, Federal Reserve Bank of Minneapolis Research Department, No. 1.
3
Bosker, M. (2008). The empirical relevance of geographical economics. Utrecht University.
4
Bosker, M., Brakman, S., Garretsen, H., & Schramm, M. (2010). The new economic geography of prefecture cities in China: The relevance of market access and labor mobility for agglomeration. Seminar participants at the Spatial Economics Research Centre, London.
5
Brakman, S., Garretsen, H., & Schramm, M. (2004). The spatial distribution of wages estimating the Helpman-Hanson model for Germany. Journal of Regional Science, 44(3): 437-466.
6
Brakman, S., Garretsen, H., & Schramm, M. (2006). Putting new economicgeography to the test: Freeness of trade and agglomeration in the EUregions. Cesifo Working Paper, No. 1566.
7
Brakman, S., Garretsen, H., Gorter, J., Horst, A., & Schramm, M. (2005). New economic geography; Empirics and regional policy. Netherlands Bureau for Economic Policy Analysis, CPB Special Publications, No. 56.
8
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9
De Haan, J. & Sturm, J.E. (2000). On the relationship between economic freedom and economic growth. European Journal of Political Economy, 16, 215-241.
10
Faina. A., Rodriguez, J., Gabriela, B.C., & Candamioan, L.V. (2010). Income disparities in Romanian regions: The role of market access. Working Paper, No. 5-0.
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Fallah, B. N., Partridge, M. D., & Olfert, M. R. (2011). New economic geography and US metropolitan wage inequality super. Journal of Economic Geography, 11(3): 865-895.
12
Fally, T., Paillacar, R., & Terra, C. (2010). Economic geography and wages in Brazil: Evidence from micro-data. Journal of Development Economics. 91, 155–168.
13
Farmanesh, A. (2009). Regional dimensions of economic development in Iran; A new economic geography approach. MPRA Paper, No. 13580, University of Maryland, College Park.
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Hanson, G. H. (2005). Market potential, increasing returns, and geographic concentration. Journal of International Economics, 67(1): 1-24.
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Helpman, E. (1998). The size of regions. In D. Pines, E. Sadka & I. Zilcha (Eds.). Topics in Public Economics: Theoretical and Applied Analysis,Cambridge, UK: Cambridge University Press.
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Henderson, V. (2003). The urbanization process and economic growth: the so-what question. Journal of Economic Growth, 8, 47-71.
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Hering, L., & Poncet, S. (2009). The impact of economic geography on wages: Disentangling the channels of influence. China Economic Review, 20, 1–14.
20
Hering, L., & Poncet, S. (2010). Market access and individual wages: Evidence from China. Journal the Review of Economics and Statistics, 92, 145-159.
21
International Labor Organization (ILO). Key Indicators of the Labor Market (KILM), Sixth edition, Employment-to-population ratio, retrieved from www.ilo.org.
22
Kazerooni, A. R., & Mohammadi, A. R. (2007). Examine the relationship between productivity and wages in the industrial sector in Iran. Iranian Journal of Economic Research, 9(31): 127-150.
23
Kiso, T. (2005). Does new economic geography explain the spatial distribution of wages in Japan? Mimeo, University of Tokyo.
24
Krugman, P. & Venables, A .J. (1995). Globalization and the inequality of nations. Quarterly Journal of Economics, 110, 857-880.
25
Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3): 483-499.
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Mion, G. (2004). Spatial externalities and empirical analysis: the case of Italy. Journal of Urban Economics, 56, 97–118.
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Ottaviano, G. I. P. & Puga, D. (1998). Agglomeration in the global economy: A survey of the new economic geography. The World Economy, 21(6): 707-731.
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Paredes, D. (2011). Can NEG explain the spatial distribution of wages of Chile? Discussion Papers, Series, No. 2.
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Pires, A. J .G. (2006). Estimating Krugman’s economic geography model for the Spanish regions. Spanish Economic Review, (8), 83–112.
30
Puga D. (1998). Urbanisation patterns: European versus less developed countries. Journal of Regional Science, 38, 231-252.
31
Puga, D. (1999). The Rise and fall of regional inequalities. European Economic Review, 43, 303-334.
32
Redding, S. J. (2010). The empirics of new economic geography. Journal of Regional Science, 50(1): 297-311.
33
Roberts, M., Deichmann, U., Fingleton, B., & Shi, T. (2010). On the road to prosperity? The economic geography of China's national expressway network. Working Paper, Series No. 5479.
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35
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36
ORIGINAL_ARTICLE
The Optimal Share of Property Rights Protection Expenditure in Total Government Spending: The Case of Iran
Abstract The main purpose of this paper is to obtain the optimal amount of expenses of government relating to the protection of property rights (PPRs). To achieve these purposes we have introduced concept of social intelligence with respect to PPRs and then developed different growth model from existing literature. In the second step the optimal share of government spending on the PPRs is calculated. The theoretical results show inverse relationship between budget deficits and government spending in the PPRs. In other words, with increasing amount of government deficit, government reduced spending of PPRs. The results of calibration for Iranian economy show that, the growth rate of spending to PPRs should be equal to 31 percent for having sustainable economic growth rate of 6 percent.
https://ijes.shirazu.ac.ir/article_1562_774a0716467b6740cd1771462e697615.pdf
2014-03-21
69
94
10.22099/ijes.2014.1562
Augmented endogenous growth model
Property rights
Calibration
Iran
Ali Hussein
Samadi
asamadi@rose.shirazu.ac.ir
1
Professor of Economics in Shiraz University
LEAD_AUTHOR
Ali Hussein
Ostadzad
aostadzad@yahoo.com
2
Ph.D Student in Shiraz University
AUTHOR
Abdoli, Ghahraman (2009). An estimation of discount rate for Iran. Journal of Economic Research, 9.3, 135-186
1
Anderson, J. E., & Bandiera, O. (2005). Private enforcement and social efficiency. Journal of Development Economics, 77, 341-366.
2
Baier, S. L., & Glomm, G. (2001). Long run growth and welfare effects of public policies with distortionry taxation. Journal of Economic Dynamics & Control, 25, 2007-2042.
3
Central Bank of Islamic Republic of Iran, Economic report, multiple years.
4
Chang, W. -Y. (1999), Government spending, endogenous labor, and capital accumulation. Journal of Economic Dynamics & Control, 23, 1225-1242.
5
Dincer, O. C., & Ellis, C.J. (2005). Predation, protection, and accumulation: Endogenous property rights in an overlapping generations (OLG) growth model. International Tax and Public Finance, 12, 435-455.
6
Gonzales, F. M. (2007). Effective property rights, conflict and growth. Journal of Economic Theory, [In press].
7
Gradstein, M. (2004). Governance and growth. Journal of Development Economics, 73, 505-518.
8
Grossman, H. I., & Kim, M. (1996). Predation and accumulation. Journal of Economic Growth, Vol.1, pp. 333-350.
9
Iran’s center of statistics, Iran’s annuals of statistics, multiple years
10
Lindner I., & Strulik, H. (2004). Why not Africa? – Growth and welfare effects of secure property rights. Public Choice, Vol.120, No.1/2, pp.143-167.
11
Mino, K. (2006). Voracity vs. scale effect in a growing economy without secure property rights. Economic Letters, Vol.93, pp.278-284.
12
Palda, F. (1999). Property rights vs. redistribution: which path to national wealth? Public Choice, Vol.101, pp.129-145.
13
Rennani, M., Dallali Isfahan, L., & Samadi, A.H. (2008). Property rights and economic growth: An endogenous growth model. Tahgheghat- Eghtesadi, Vol 43, No. 85, pp. 175-206
14
Samadi, A. H., & Oujimehr, S. (2012). Evaluation of nature and equivalency of fiscal policy in IRAN (1979-2007). Biquarterly Journal of Economic Essay, Vol.6, No. 16, pp. 49-76.
15
Svensson, J. (1998). Investment, property rights and political instability: theory and evidence. European Economic Review, 42, 1317-1341.
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Sylwester, K. (2001). A Model of institutional formation within a rent seeking environment. Journal of Economic Behavior & Organization, 44, 169-176.
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Teng, J. (2000). Endogenous authoritarian property rights. Journal of Public Economics, 77, 81-95.
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Tornell, A., & Velasco, A. (1992). The Tragedy of commons and economic growth: why does capital flow from poor to rich countries? Journal of Political Economy, 100, 6, 1208-1231.
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Tornell, A., & Lane, P. R. (1999). The voracity effect. The American Economic Review, 89, 1, 22-46.
20
Turnovsky, S. J. (2000). Fiscal policy, elastic labor supply, and endogenous growth. Journal of Monetary Economics, 45, 185-210.
21
ORIGINAL_ARTICLE
Welfare Impacts of Imposing a Tariff on Rice in Iran vs an Export Tax in Thailand: A Game Theory Approach
In this study, the social welfare impacts of the interaction of Iranian rice import policies and Thai export policies are analyzed using a game theoretic approach in conjunction with econometric supply and demand models. The joint impacts of increasing the world price of rice, resulting from the export policies in Thailand along with changes in tariff rates in Iran, on social welfare are analyzed in the two countries. Because Iran is a small country in terms of the volume of world rice trade its policies do not influence Thai social welfare. Results of this study show that in order to maximize its own social welfare, the government should impose a modest tariff rate of approximately 3%. This is much less than the actual tariff rate applied in recent years, e.g. 19% in 2007.
https://ijes.shirazu.ac.ir/article_1563_02b927c62a27a064807786482acc8f3e.pdf
2014-03-21
95
106
10.22099/ijes.2014.1563
Game Theory
Social Welfare
Tariff Rate
Rice Imports
Iran and Thailand
Azar
Sheikhzeinoddin
azeinoddin@yahoo.com
1
Ph.D Student in Shiraz University
LEAD_AUTHOR
Mohammad
Bakhshoodeh
bakhshoodeh@hotmail.com
2
Professor of Agricultural Economics in shiraz University
AUTHOR
David
Blandford
dblandford@psu.edu
3
Professor of Economics in Penn State University
AUTHOR
Beghin, J. C., & Bureau, J. C. (2001). Measurement of sanitary, phytosanitary and technical barriers to trade, A consultants report Prepared for the Food, Agriculture and Fisheries Directorate, OECD.
1
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2
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3
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Food and Agricultural Policy Research Institute, http://www.fapri. iastate.edu.
5
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6
International Rice Research Institute, http://beta.irri.org.
7
Lee, D. S., & Kennedy, P. L. (2002). A Game Theoretic Analysis of U.S. Rice Export Policy: The case of Japan and Korea, Presented at the annual meeting of the American Agricultural Economics Association, Long Beach, California, July 28-31.
8
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9
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10
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11
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12
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14
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15
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16
ORIGINAL_ARTICLE
Calibration of Fair Social Discount Rate in Utilizing Iran Oil Resources: An Islamic View Point
There is a long tradition in economics about the question of whether intergenerational discounting is fair or not. Ramsey (1928) was the first economist that criticized the discounting and mentioned that the just rate of discounting is zero. In this paper it was tried to calculate the just rate of discounting for Iran with respect to Islamic thoughts. According to Islam, intergenerational justice had been regarded when oil revenue was totally invested in other kinds of capital. So, we tried to calculate the social discount rate for Iran in current situations and after imposing the Islamic condition of intergenerational justice an overlapping generations’ model was used. Finally, our calculation showed that the value of social discount rate is 0.04 before imposing the intergenerational justice condition and -0.014 after it. Then, it was explained that in current economic situations of Iran, the best social discount rate which can satisfy the intergenerational justice, was an amount between zero and minus one.
https://ijes.shirazu.ac.ir/article_1564_7a00524c86d3b1a83a68b6b5d35a24df.pdf
2014-03-23
107
124
10.22099/ijes.2014.1564
Intergenerational Justice
Discounting
Social Discount Rate
Overlapping Generations Model
Mohammad Hadi
Zahedivafa
zahedi@isu.ac.ir
1
Professor of Imam Sadiq University
LEAD_AUTHOR
Mahdi
Sadeghi Shahdani
sadeghi@yahoo.com
2
Ph.D student of Imam Sadiq University
AUTHOR
Abolghasem
Tohidinia
atohidinia@gmail.com
3
Professor of Imam Sadiq University
AUTHOR
Altig, D., Auerbach, A., Kotlikoff, L., Smetters, K., & Walliser, J. (2001). Simulating fundamental tax reform in the United States. American Economic Review, 91(3): 574-595.
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