Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

New Mixed Method of CHARM-RAS for Generating Regional Input-Output Tables (RIOTs) of Gilan and Hormozgan Provinces, Iran


Affiliations
1 Allameh Tabataba'i University, Tehran, Iran, Islamic Republic of
2 Eco-College of Insurance, Allameh Tabataba'i University, Tehran, Iran, Islamic Republic of
3 Allameh Tabataba'i University, Iran, Islamic Republic of
     

   Subscribe/Renew Journal


The application of CHARM for the estimation of RIOTs needs two residuals: exports and value added. The first one seems to be plausible whereas the second one is not appropriate for those countries like Iran which have regional accounts. The comparison of the regional sectoral value added and the regional GDP figures of Gilan and Hormozgan provinces derived from the CHARM method with corresponding official figures reveal underestimation of 2.4 per cent for Gilan province and overestimation of 9.9 per cent for Hormozgan province. These deviations are more pronounced in regional sectoral value added of two provinces. These observations raise an important question: why one should overlook and/or unnecessarily adjust the official data? To solve this issue a new mixed CHARM-RAS method is proposed. The overall findings show that first of all, as compared to the CHARM method, the proposed mixed method guarantees the regional sectoral value added and GDP of two provinces provided by SCI. Secondly, the degree of accuracy between two methods reveals that the proposed method outperforms the CHARM method in all the statistical methods.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Bonfiglio, A. (2009), On the Parameterization of Techniques for Researching Regional Economic Structures, Economic Systems Research, 21(8): 791-794.

  • Flegg, A.T. and C.D. Webber (1996), Using Location Quotients to Estimate Regional Input-Output Coefficients and Multipliers, Local Economic Quarterly, 40: 58-86.

  • ---------- (1997), On the Appropriate Use of Location Quotients in Generating Regional Input-Output Tables: Reply, Regional Studies, 31(8): 795-805.

  • ---------- (1998), Industrial Location, Regional Specialization and Regional Input-Output Coefficients, Working Paper in Economics, No. 27, University of the West of England, Bristol.

  • ---------- (2000), Regional Size, Regional Specialization and the FLQ Formula, Regional Studies, 34(2): 563-569.

  • Flegg, A.T. and C.D. Webber and M.V. Elliot (1995b), On the Appropriate Use of Location Quotients in Generating Regional Input-Output Tables, Regional Studies, 29(6): 547-561.

  • Flegg, A.T. and T. Thomo (2016), Refining the Application of the FLQ Formula for Estimating Regional Input Coefficients: An Empirical Study for South Korean Regions, 24th International Input-Output Conference and 6th Edition of the International School of Input-Output Analysis, 4-8 July, Seoul, South Korea.

  • Flegg, A.T. and T. Tohmo (2013), Regional Input-Output Tables and the FLQ Formula: A Case Study of Finland, Regional Studies, 47(2): 703-721.

  • ---------- (2016), Estimating Regional Input Coefficients and Multipliers, the Use of FLQ is not a Gamble, Regional Studies, 50(2): 310-325.

  • Flegg, A.T., L.J. Mastronardi and C.A. Romero (2016), Evaluating the FLQ and AFLQ Formulae for Estimation Regional Input-Output Coefficients: Empirical Evidence for the Province of Cordoba, Argentina, Economic Systems Research, 28(1): 21-37.

  • Flegg, A.T., Y. Huang and T. Tohmo (2015), Using CHARM to Adjust for Cross-Hauling: The Case of the Province of Hubei, China, Economic System Research, 27(3): 391-413.

  • Harrigan, F., J.W. McGilvray and I.H. McNicoll (1981), The Estimation of Interregional Trade, Flows, Journal of Regional Sciences, 21(1): 65-77.

  • Hermannsson, T. (2016), Beyond Intermediates: The Role of Consumption and Commuting in the Construction of Local Input-Output Tables, Spatial Economic Analysis, 11(2): 1-25.

  • Isard, W. (1953), Regional Commodity Flows, The American Economic Review, 43(2): 167-180.

  • Jackson, R. (2014), Cross-Hauling Input-Output Tables: Comments on CHARM, Working Paper 2014, Regional Research Institute, West Virinia University.

  • Kowalewski, J. (2015), Regionalization of National Input-Output Tables: Empirical Evidence on the Use of the FLQ Formula, Regional Studies, 40: 240-250.

  • Kronenberg, G.T. (2009), Construction of Regional Input-Output Tables Using Non-Survey Methods: The Role of Cross-Hauling, International Regional Science Review, 32(1): 40-64.

  • ---------- (2012), Regional Input-Output Models and the Treatment of Imports in the European Systems of Accounts, Review of Regional Research, 32(1): 40-64.

  • Lahr, M. (2001), A Strategy for Producing Hybrid Regional Input-Output Tables, in M. L. Lahr and E. Dietzenbacher (Eds.), Input-Output Analysis: Frontiers and Extension, Palgrave, Great Britain, pp. 211-244.

  • Lehtonen, O. and M. Tykkylainen (2014), Estimating Regional Input Coefficients and Multipliers: Is the Choice of a Non-Survey Technique a Gamble?, Regional Studies, 43(2): 382-392.

  • Management and Plan Organization of Gilan Province (2006), Input-Output Table of Gilan Province, Application and Analysis, Rasht, Gilan (in Persian).

  • Management and Plan Organization of Hormozgan Province (2007), Input-Output Table of Hormozgan Province, Bandar-Abbas, Iran (in Persian).

  • National and Regional Accounts of Iran, Tehran, Iran (in Persian).

  • Richardson, H.W. (1985), Input-Output and Economic Base Multipliers: Looking Backward and Forward, Journal of Regional Science, 25(4): 607-661.

  • Statistical Centre of Iran (2003).

  • ---------- (2012), The 2011 National Census of Population and Housing, Tehran, Iran (in Persian).

  • Statistical Centre of Iran (2013), Guidance for Estimation and Evaluation of the Regional Accounts for the Year 2011, Tehran, Iran (in Persian).

  • Tobben, J. and T. Kronenberg, (2015), Construction of Multi-Regional Input-Output Tables Using CHARM Methods, Economic Systems Research, 27(4): 487-507.

  • Tohmo, T. (2004), New Developments in the Use of Location Quotients to Estimate Regional Input-Output Coefficients and Multipliers, Regional Studies, 38(2): 43-54.


Abstract Views: 583

PDF Views: 4




  • New Mixed Method of CHARM-RAS for Generating Regional Input-Output Tables (RIOTs) of Gilan and Hormozgan Provinces, Iran

Abstract Views: 583  |  PDF Views: 4

Authors

A. A. Banouei
Allameh Tabataba'i University, Tehran, Iran, Islamic Republic of
P. Mohajeri
Allameh Tabataba'i University, Tehran, Iran, Islamic Republic of
J. Banouei
Eco-College of Insurance, Allameh Tabataba'i University, Tehran, Iran, Islamic Republic of
Z. Ziyaei
Allameh Tabataba'i University, Iran, Islamic Republic of
S. Tavassoli
Allameh Tabataba'i University, Iran, Islamic Republic of
Z. Eghtesadi
Allameh Tabataba'i University, Iran, Islamic Republic of
S. Sadeghi
Allameh Tabataba'i University, Iran, Islamic Republic of

Abstract


The application of CHARM for the estimation of RIOTs needs two residuals: exports and value added. The first one seems to be plausible whereas the second one is not appropriate for those countries like Iran which have regional accounts. The comparison of the regional sectoral value added and the regional GDP figures of Gilan and Hormozgan provinces derived from the CHARM method with corresponding official figures reveal underestimation of 2.4 per cent for Gilan province and overestimation of 9.9 per cent for Hormozgan province. These deviations are more pronounced in regional sectoral value added of two provinces. These observations raise an important question: why one should overlook and/or unnecessarily adjust the official data? To solve this issue a new mixed CHARM-RAS method is proposed. The overall findings show that first of all, as compared to the CHARM method, the proposed mixed method guarantees the regional sectoral value added and GDP of two provinces provided by SCI. Secondly, the degree of accuracy between two methods reveals that the proposed method outperforms the CHARM method in all the statistical methods.

References





DOI: https://doi.org/10.21648/arthavij%2F2017%2Fv59%2Fi4%2F170799