Determining the Economic Sectors with Most Backward and Forward Linkages in Isfahan Province with an Emphasis on Adjustment of National Technology Coefficients in the CHARM Method

Document Type : Original Article

Authors

1 PhD Candidate in Economics, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran

2 Professor of Economics, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran

3 Associate Professor of Economics, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran

4 Associate Professor of Economics, Faculty of Social Sciences and Economic, Al-Zahra University, Tehran, Iran

10.29252/jem.2023.230485.1820

Abstract

Using regional input- output tables is a way to understand regional economy and sector policies. In Iran, due to the lack of regional data collection by national institutions, non-statistical methods for estimating regional input-output tables have been of interest. The CHARM method is one of the conventional methods of regionalization the national input-output tables in the conditions of simultaneous bilateral trade. But one of the problems of CHARM method is the assumption of equality of national and regional technology coefficients. With this assumption, the regional difference is practically ignored. This study is trying to prevent the underestimation of provincial value added by regionalizing the coefficients of national technology and to include regional differences in the analysis. Also, the sections with the most posterior and anterior links will be identified. The results show that the value added of Isfahan province and other provinces of the country are closer to reality in the adjusted state. Also, the industrial sector of Isfahan province has the most backward and forward linkages in the adjusted state.

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- Abutalebi, M., & Akbari, N. (2016). Factor-oriented analysis of spillover and feedback effects in input-output model of two regions (Isfahan province and other provinces of the country). PhD Thesis. Faculty of Administrative Sciences and Economics. University of Esfahan (In Persian).
- Abutalebi, M., & Akbari, N. (2017). Simulation of ordinal input-output pattern (Iran input-output table, 2019). The 5th conference on the use of data-output models in economic and social planning, Al-Zahra University (In Persian).
- Akbari, N., & Abutalebi, M. (2019). Regional input-output analysis. Country Management and Planning Organization (In Persian).
- Banouei, A. A., Ziyaee, Z., & Mohajeri, P. (2020). Quantitative Analysis of Spatial Dimensions of Regional Economic sectors Using New Mixed EFLQ-RAS Method. Regional Planning9(36), 31-48 (In Persian).
- Banoui, A., Ghasemi, R., Arab Mazar, A., & Mohajeri, P. (2016). Calculation of input-output table of Gilan province and its application in identifying competitive advantages. Gilan province budget program organization, first edition (In Persian).
- Banoui, A., Mohajeri, P., Sadeghi, N. & Sherkat, A. (2016). A new combined FLQ-RAS method for calculating the regional input-output table: Case study: Gilan province. Iranian Economic Research Quarterly, 22(17), 81-114 (In Persian).
- Bazazan, F., Banoui, A., & Karimi, M. (2006). More reflection on the new spatial contribution functions between the dimensions of space economy and the coefficients of regional input-output model: a case study of Tehran province. 9(31), 27-53 (In Persian).
- Cai, M. (2022). A calibrated gravity model of interregional trade.
Spatial Economic Analysis, 18(1), 89-107.
- Chen, Y., & Dai, W. (2022). Tracking Control of the Dynamic Input-Output Economic System Based on Data Fusion. Security and Communication Networks, 2022.
- Dashtban, M., Tofiqh, F., Zenouz, H., & Peikarjo, K. (2016). Spillover effects caused by the expansion of industries in Eitan, Tehran, on neighboring provinces (interregional input-output table approach). Financial Economics Quarterly, 12(42), 149-180 (In Persian).
- Davidson, S., Black, J., Connolly, K., & Spowage, M. (2022). Improving the Quality of Regional Economic Indicators in the UK: A Framework for the Production of Supply and Use and Input Output Tables for the Four Nations. ESCoE Discussion Paper Series.
- Dehghan, F., & Nasrallahi, Z. (2022). Ranking of economic activities in Yazd province using two input-output models and TOPSIS (with an emphasis on sustainable development). Quarterly Journal of Economics and Modeling, 13(2), 121-150 (In Persian).
- Diodato, D., Neffke, F., & O'Clery, N. (2018). Why do Industries Conglomerate? How Marshallian Externalities Differ by Industry and Have Evolved Over Time. Journal of Urban Economics, 106(C), 1-26.
- Faridzad, A., Banoui, A., & Shokri, E. (2022). Comparative study of the standard RAS method with the proposed method in the analysis of the economic effects caused by the gasoline price impulse. Quarterly Journal of Economics and Modeling, 12(3), 71-105 (In Persian).
- Farsi, F., & Afshari, Z. (2018). Applying the modified FLQ-RAS method in calculating the input-output table of Fars province. Al-Zahra's economic progress policy quarterly. 7(1), 209-233 (In Persian).
- Faturay, F., Sai Gargeya V., Venkata, Lenzen, M., & Singh, S  (2020). Using a new USA multi-region input output (MRIO) model for assessing economic and energy impacts of wind energy expansion in USA. Applied Energy, 261(C).
- Fujimoto, T. (2019). Appropriate assumption on cross-hauling national input–output table regionalization. Spatial Economic Analysis, 14, 106-128.
- Hermannsson, K. (2016). Beyond intermediates: The role of consumption and commuting in the construction of local input–output tables. Spatial Economic Analysis, 11, 315-339.
- Holy, V. & Safr, K. (2022). Disaggregating input–output tables by the multidimensional RAS method: a case study of the Czech Republic. Economic Systems Research, 35, 95-117.
- Homayonifar, M., Khodaparast, M., Lotfalipour, M. & Tarhami, F. (2015). Comparing the results of regional input-output table estimation with CHARM AFLQ methods (case study: Bushehr province). Economic Research and Policy Quarterly, 24(77) 115-138 (In Persian).
- Iran Statistics Center, national static data report for 2015.
- Jahn, M., Flegg, A. T., & Tohmo, T. (2020). Testing and implementing a new approach to estimating interregional output multipliers using input–output data for South Korean regions. Spatial Economic Analysis, 15(2), 165-185.
- Karimi, M., Mohajeri, P., & Banoui, A. (2017). Identification of superior statistics and their impact on the statistical validity of regional input-output tables with the new combined CHARM-RAS method. Journal of applied Economic Studies of Iran, 26, 169-195 (In Persian).
- Kronenberg, G.T. (2012). Regional Input-Output Models and the Treatment of Imports in the European Systems of Accounts. Review of Regional Research, 32(2), 175-191.
- Kronenberg, T. (2009). How Can Regionalization Methods Deal with Cross Hauling? International Input-Output Conference.
- Lamonica, G. R., Recchioni, M. C., Chelli, F. M., & Salvati, L. (2019). The efficiency of the cross-entropy method when estimating the technical coefficients of input–output tables. Spatial Economic Analysis, 15, 62-91.
- Lotfipour, M., Ashena, M., & Tarhami, T. (1400). Relative advantage of the economic sectors of oil-rich regions using the regional input-output table: a case study of West Karun region. Development Strategy Magazine, 67, 128-100 (In Persian).
- Management and Planning Organization of Isfahan Province, 1400.
- Miller, E., & Blair, D. (2009). Input-output analysis: foundations and extensions. Cambridge University Press.
- Nur Afandi, M., Tri Anomsari, E., & Novira, A. (2020). Sustainable Development Goals (SDGs) Perspective in Regional Development Planning and Implementation. Proceedings of the 2nd International Conference on Administration Science 2020 (ICAS 2020), Advances in Social Science, Education and Humanities Research.
- Dehghan, F., & Nasrollahi, Z. (2022). Ranking of Economic Activities in Yazd Province Using Input - Output and TOPSIS Models (With Emphasis on Water Intensive). Journal of Economics and Modeling, 13(2), 121-145 (In Persian).
- Omidi, N., Qavami, H., Houshmand, M., & Salimifar, M. (1400). Regional input-output table (RIOTs) with FLQ method using statistical vector of added value (case study of North Khorasan province). Economy and economic development, doi: 10.22067/erd.2022.68834.1013 (In Persian).
- Oosterhaven, J. (2022). From Regional IO Tables to Interregional SU Models. Rethinking Input-Output Analysis. edition 2, chapter 0, pages 35-56, Springer.
- Reissl, S., Caiani, A., Lamperti, F., Ferraresi, T., & Ghezzi. L. (2022). A regional input-output model of the Covid-19 crisis in Italy: Decomposing demand and supply factors. LEM Papers Series 2022/04.
- Sabbagh Kermani, M. (2012). Regional economy (theories and models). Side Publications.
- Sadeghi Shabanehi, M. (2014). Data modeling. Imam Sadegh University Press, Tehran.
- Shadabfar, E., Bezazan, F., & Banoui, A. (2019). Preparation of multi-region input-output table based on CHARM method. Economic research paper, 20(79), 226-260 (In Persian).
- Tofiqh, F. (2015). Material input-output table. Iranian Economic Research Quarterly, 21(68), 1-56 (In Persian).
- WEST, G.R. (1990). Regional Trade Estimation: A Hybrid Approach. International Regional Science Review, 13(1-2), 103-118.
- Ye, Q., Bruckner, M., Wang, R., Schyns, J., Zhuo., Yang, L., Su, H., & Krol, M. (2022). A hybrid multi-regional input-output model of China: Integrating the physical agricultural biomass and food system into the monetary supply chain. Resources, Conservation and Recycling, 177, 105981.
- Zeinalzadeh, R., Yaqhoubi, A., Khodaparast, A, & Homayoni Far, M. (1400). Investigating the growth rate of Fava sector in the 6th plan and its effect on the output growth of other economic activities (input-output analysis approach with ideal planning model). Regional Planning Scientific Quarterly, 11(44), 115-135 (In Persian).