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The RAS Approach in Updating Input-Output Matrices: An Instrumental Variable Interpretation and Analysis of Structural Change

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  • Mun-Heng Toh

Abstract

The main purposes of the paper are to reconsider the rationale of the RAS method, and to attempt to improve on its interpretation and usefulness. The substitution and fabrication factors in the RAS method are interpreted as statistical estimates obtained by the method of instrumental variables. This enables the computation of asymptotic standard errors for the factors and the relative precision of the predicted technical coefficients. Furthermore, an adjustment cost minimization model to describe how a sector determines its substitution and fabrication factors is presented. The solutions of the model provide another rationale for the RAS method, and the associated Lagrangian multipliers can be useful for assessing structural constraints and structural change.

Suggested Citation

  • Mun-Heng Toh, 1998. "The RAS Approach in Updating Input-Output Matrices: An Instrumental Variable Interpretation and Analysis of Structural Change," Economic Systems Research, Taylor & Francis Journals, vol. 10(1), pages 63-78.
  • Handle: RePEc:taf:ecsysr:v:10:y:1998:i:1:p:63-78
    DOI: 10.1080/09535319800000006
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    Cited by:

    1. Gu, Alun & Teng, Fei & Lv, Zhiqiang, 2016. "Exploring the nexus between water saving and energy conservation: Insights from industry sector during the 12th Five-Year Plan period in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 28-38.
    2. Bernadette Andreosso-O'Callaghan & Guoqiang Yue, 2000. "An Analysis of Structural Change in China using Biproportional Methods," Economic Systems Research, Taylor & Francis Journals, vol. 12(1), pages 99-111.
    3. Cai, Wenjia & Mu, Yaqian & Wang, Can & Chen, Jining, 2014. "Distributional employment impacts of renewable and new energy–A case study of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1155-1163.
    4. Amos Golan & Stephen Vogel, 2000. "Estimation of Non-Stationary Social Accounting Matrix Coefficients with Supply-Side Information," Economic Systems Research, Taylor & Francis Journals, vol. 12(4), pages 447-471.
    5. Ali Reza Jalili, 2000. "Comparison of Two Methods of Identifying Input-Output Coefficients for Exogenous Estimation," Economic Systems Research, Taylor & Francis Journals, vol. 12(1), pages 113-129.
    6. Sherman Robinson & Andrea Cattaneo & Moataz El-Said, 2001. "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods," Economic Systems Research, Taylor & Francis Journals, vol. 13(1), pages 47-64.
    7. Kuksa Ihor M. & Rudenko Marina Anatolievna, 2013. "Directions and Tasks of Development of the Strategy of Support of Innovation Development at Enterprises of the Agroindustrial Complex APK)," Business Inform, RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics, issue 10, pages 203-206.
    8. Xiangzheng Deng & Fan Zhang & Zhan Wang & Xing Li & Tao Zhang, 2014. "An Extended Input Output Table Compiled for Analyzing Water Demand and Consumption at County Level in China," Sustainability, MDPI, Open Access Journal, vol. 6(6), pages 1-20, May.
    9. Erik Dietzenbacher & Bart Los, 2000. "Structural Decomposition Analyses with Dependent Determinants," Economic Systems Research, Taylor & Francis Journals, vol. 12(4), pages 497-514.
    10. Zhang, Zhonghua & Zhao, Yuhuan & Su, Bin & Zhang, Yongfeng & Wang, Song & Liu, Ya & Li, Hao, 2017. "Embodied carbon in China’s foreign trade: An online SCI-E and SSCI based literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 492-510.
    11. Wang, Can & Zhang, Weishi & Cai, Wenjia & Xie, Xi, 2013. "Employment impacts of CDM projects in China's power sector," Energy Policy, Elsevier, vol. 59(C), pages 481-491.

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