Forecasting Change of Iran's Trading Partners with an Emphasis on Continuing Sanctions in Horizon of Fifth Iranian Development Plan

Document Type : Original Article

Authors

1 Department of Agricultural Economics and Developments, Tehran, University, Daneshkadeh St, Karaj, Alborz, Iran.

2 Department of Agricultural Economics and Developments, Tehran, University.

Abstract

Expanding non-oil exports for diversifying export earnings is a common policy in developing countries with monoculture economics. However, in recent years, sanctions as the major obstacle of achieving the objectives lead to change of trading partners through affecting domestic and foreign policies. Therefore, the uncertainty of future trading partners due to the uncertain conditions of sanction highlights the necessity of forecasting the change trends of Iran's trading partners. This paper aimed to review and forecast share changing of Iran's major trading partners from 1996 until the end of the fifth development plans. Thus, first, the share of trading partners from agricultural export products as the part of non-oil exports during 1996-2012 was investigated using the data on non-oil exports of Iran Customs Administration. Then, the share of Iran's trading partners was forecasted during 2013-2015 by considering sanctions and using econometric techniques. Results of the forecasts showed that, in the non-sanction conditions, the share of western countries of Iran's non-oil exports would increase and, with continuing sanctions, exports would be limited to the neighbouring countries.

Keywords


Abbaschian, Abolfazl & Masoomeh Zirak (2012), Outlook of Non-oil Exports in the Fifth Development Plans, Bimonthly Economic journal of investigating issues and Economic Policy, Vol. 7, No.7 & 8, pp 47-66. (in Persian).
Akal, Mustafa (2004), Forecasting Turkey’s Tourism Revenues by ARMAX Model, Tourism Management, Vol. 25, No. 5, pp 565-580.
Bessler, David A. & A. Brant Jon (1979), Composite Forecasting of Livestock Prices: an Analysis of Combining Alternative Forecasting Method, Purdue University, USA.
Box, George E. P. & Gwilym M. Jenkins (1970), Time Series Analysis: Forecasting and Control, San Francisco, Holden-Day.
Brown, Robert Goodell (1959), Statistical Forecasting for Inventory Control, New York, McGraw-Hill.
Chi, Chen Wang (2011), A Comparison Study Between Fuzzy Time Series Model and ARIMA Model for Forecasting Taiwan Export, Expert Systems with Applications, Vol. 38, No. 8, pp 9296–9304.
Claveria, Oscar, Ernest Pons & Raul Ramos (2007), Business and Consumer Expectations and Macroeconomic Forecasts, The International Journal of Forecasting, Vol. 23, No. 1, pp 47-69.
Database of Chamber of Commerce, Industry, Mine and Trade of Tehran, www.tccim.ir.
Database of Iran Customs Administration, www.irica.gov.ir.
Dominick Salvatore (2008), International Economics, Maxwell Macmillan International Editions. Business and Economics, Published by Alpha Books, 695 pages.
Enders, Walter (2004), Applied Econometrics Time Series, 2nd edition, John Wiley& Sons, Inc.
Fathi, Yah'ya. & Reza pakdaman (2010), Position of Iran’s Partners in Diplomacy of Trade, Journal Quarterly Foreign Relations, Vol. 2, No. 3, pp 201-250. (in Persian).
Fomby, B. Thomas (1998), How to Model Multivariate Time Series Data?, Department of Economics, Southern Methodist University Dallas, USA.
Ghafoor, Abdul & Sarvet Hanif (2005), Analysis of the Trade Pattern of Pakistan: Past Trends and Future Prospects, Journal of Agriculture & Social Sciences, Vol. 1, No. 4, pp 346-349.
Gilanpour, Omid & Norooz Kohzadi (1997), Forecasting the Rice Prices in International Market by Using Autoregressive Integrated Moving Average, Journal of Agricultural Economic and Development, Vol. 1, No. 8, pp 189-201. (in Persian).
Gujarati, Damodar (1995), Basic Econometrics, 3rd edition, abrishami, hamid (translator), Tehran: Institute of Universities Publishing and Printing. (in Persian).
Haykin, Simon S. (1994), Neural Networks: A Comprehensive Foundation. Macmillan, New York.
Hong-Tzer, Yang, Huang Chao-Ming, Huang Ching-Lien (1995), Identification of ARMAX Model for Short Term Load Forecasting: an Evolutionary Programming Approach, Power Industry Computer Application Conference, Conference Proceedings IEEE, 325-330.
Hyndman, Rob. Koehler, B. Anne, Ord, J. Keith, & Ralph D. Synder (2008), Forecasting with Exponential Smoothing, Springer Series in Statistics, ISBN 978-3-540-71916-8.
Jantarakolica Tatre & Porjai Chalermsook (2012), Test Forecast Performance Using Leading Indicator: A Case Study of Thai Export, APEA 8th Annual Conferences, Nanyang Technological University Singapore.
Kargbo, Joseph M. (2007), Forecasting Agricultural Exports and Imports in South Africa, Applied Economics , Vol. 39, No. 16, pp 2069-2084.
Lim, Chiristine., Jennifer C. H. Min & Michael McAleer (2008), Modelling Income Effects on Long and Short Haul International Travel From Japan, Tourism Management, Vol. 29, No. 6, pp 1099-1109.
Maknickiene, Nijole & Algirdas Maknickas (2012), Application of Neural Network for Forecasting of Exchange Rates and Forex Trading, 7th International Scientific Conference “Business and Management”, Vilnius, LITHUANIA.
Management and Planning Organization of Iran (2003), Fourth Report of the National Economic Developments. (in Persian).
Management and Planning Organization of Iran, (2003), Third Report of the National Economic Developments. (In Persian).
Mohamed A. H. Milad, Irnawaty Binti Ibrahim Ross & Samiappan Marappan (2014), Modeling and Forecasting the Volumes of Malaysia’s Import, International Conference on Global Trends in Academic Research, Bali, Indonesia Global Illuminators, Kuala Lumpur, Malaysia.
Mojaverian, Mojtaba. & Afshin Amjadi (1999), Compared the Common Methods With Trigonometric Functions In Power of Forecasting Ttime Series in Agricultural Prices With Seasonal Effects: A Case Study Citrus, Journal of Agricultural Economics and Development, Vol. 1, No. 25, pp 43-64. (in Persian).
Moshiri, Saeed & Habib Morovat (2006), Forecasting Total Returns Index of Tehran’s Stocks by Using the Linear and Nonlinear Models, Iranian Journal of Trade Studies (IJTS(,Vol. 1, No. 41, pp 245-275. (in Persian).
Moshiri, Saeed (2001), Forecasting the Inflation of Iran by Using Structural Models, Time Series and Neural Networks, Economic Research, Vol. 1, No. 58, pp 147-184. (in Persian).
Nelson, Charles R. (1973), Applied Time Series Analysis, San Francisco, Holden-Day.
Noferesti, Mohammad (1999), Unit Roots and Cointegration in Econometrics, First Edition, Tehran, Institute of Rasa’s Cultural Services. (in Persian).
Rahmani, Mitra & Mohammad Reza abedin moghanaki (2008), Investigating the Possibility of Iran’s Developing Exports With Selected Trading Partners, Iranian Journal of Trade Studies (IJTS(, Vol. 46, No. 12, pp 145-177. (in Persian).
Ranjit Kumar, Paul, Panwar Sanjeev, Sarkar Susheel Kumar, Anil Kumar, K.N. Singh, Samir Farooqi, Choudhary Vipin Kumar (2013), Modelling and Forecasting of Meat Exports from India. Indian Journals. Vol. 26, No. 2, pp 249-256.
Sengupta Sushanta & Ruma Datta (2014), Identification of Demand Forecasting Model Considering Key Factors in the Context of Healthcare Products, International Journal of Application or Innovation in Engineering & Management (IJAIEM), Vol. 3, No. 3, pp 365-369.
Tayebi, Seyyed Komeil, Karim Azarbayejani & Leili Bayari (2009), Forecasting the Egg Prices in Iran: Comparison the ARCH Methods and Artificial Neural Networks, Journal of Agricultural Economics and Development, Vol. 1, No. 65, pp 73-96. (in Persian).
Williams, Billy (2001), Multivariate Vehicular Traffic Flow Prediction: Evaluation of ARIMAX Modeling, Journal of the Transportation Research Board, Vol. 1776, No. 1, pp 194-200.