IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v95y2016icp385-402.html
   My bibliography  Save this article

Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

Author

Listed:
  • Hiramatsu, Tomoru
  • Inoue, Hiroki
  • Kato, Yasuhiko

Abstract

In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.

Suggested Citation

  • Hiramatsu, Tomoru & Inoue, Hiroki & Kato, Yasuhiko, 2016. "Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 385-402.
    • Handle: RePEc:eee:transe:v:95:y:2016:i:c:p:385-402
    DOI: 10.1016/j.tre.2016.07.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136655451530226X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2016.07.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bui Trinh & Nguyen Viet Phong, 2013. "A Short Note on RAS Method," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 3(4), pages 1-12.
    2. Manfred Lenzen & Blanca Gallego & Richard Wood, 2009. "Matrix Balancing Under Conflicting Information," Economic Systems Research, Taylor & Francis Journals, vol. 21(1), pages 23-44.
    3. Theo Junius & Jan Oosterhaven, 2003. "The Solution of Updating or Regionalizing a Matrix with both Positive and Negative Entries," Economic Systems Research, Taylor & Francis Journals, vol. 15(1), pages 87-96, March.
    4. Erasmia Valma, 2014. "Estimation of Interregional Trade Coefficients and Multipliers in the Context of An Interregional Model," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 101-118.
    5. Donald Gilchrist & Larry V. ST Louis, 1999. "Completing Input-Output Tables using Partial Information, with an Application to Canadian Data," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 185-194.
    6. Yoshifumi Ishikawa & Toshihiko Miyagi, 2004. "The Construction of a 47-Region Inter-regional Input-Output Table, and Inter-regional Interdependence Analysis at Prefecture Level in Japan," ERSA conference papers ersa04p432, European Regional Science Association.
    7. Batten, D & Martellato, D, 1985. "Classical versus Modern Approaches to Interregional Input-Output Analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 19(3), pages 1-15, November.
    8. Huiwen Wang & Cheng Wang & Haitao Zheng & Haoyun Feng & Rong Guan & Wen Long, 2015. "Updating Input-Output Tables with Benchmark Table Series," Economic Systems Research, Taylor & Francis Journals, vol. 27(3), pages 287-305, September.
    9. Erik Dietzenbacher & Manfred Lenzen & Bart Los & Dabo Guan & Michael L. Lahr & Ferran Sancho & Sangwon Suh & Cuihong Yang, 2013. "Input--Output Analysis: The Next 25 Years," Economic Systems Research, Taylor & Francis Journals, vol. 25(4), pages 369-389, December.
    10. Satoshi Nakano & Kazuhiko Nishimura, 2013. "A nonsurvey multiregional input–output estimation allowing cross-hauling: partitioning two regions into three or more parts," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(3), pages 935-951, June.
    11. Caggiani, Leonardo & Ottomanelli, Michele & Dell’Orco, Mauro, 2014. "Handling uncertainty in Multi Regional Input-Output models by entropy maximization and fuzzy programming," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 159-172.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shaojian Qu & Hao Cai & Dandan Xu & Nabé Mohamed, 2021. "Uncertainty in the prediction and management of CO2 emissions: a robust minimum entropy approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2419-2438, July.
    2. Ana Luiza Fontenelle & Erik Nilsson & Ieda Geriberto Hidalgo & Cintia B. Uvo & Drielli Peyerl, 2022. "Temporal Understanding of the Water–Energy Nexus: A Literature Review," Energies, MDPI, vol. 15(8), pages 1-21, April.
    3. Tzu-Yu Lin & Sheng-Hsiung Chiu, 2018. "Sustainable Performance of Low-Carbon Energy Infrastructure Investment on Regional Development: Evidence from China," Sustainability, MDPI, vol. 10(12), pages 1-21, December.
    4. Zhuang, Mufan & Gao, Ziyan & Geng, Yong & Xiao, Shijiang, 2022. "Spatial distribution pattern of embodied natural resources use in China and its relationship with socioeconomic development: From an exergetic perspective," Resources Policy, Elsevier, vol. 79(C).
    5. Cristian Mardones & Darling Silva, 2023. "Evaluation of Non-survey Methods for the Construction of Regional Input–Output Matrices When There is Partial Historical Information," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1173-1205, March.
    6. Yushen Tian & Siqin Xiong & Xiaoming Ma, 2017. "Analysis of the Potential Impacts on China’s Industrial Structure in Energy Consumption," Sustainability, MDPI, vol. 9(12), pages 1-13, December.
    7. Cheng-Ta Yeh, 2020. "Binary-state line assignment optimization to maximize the reliability of an information network under time and budget constraints," Annals of Operations Research, Springer, vol. 287(1), pages 439-463, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Umed Temursho & Manuel Alejandro Cardenete & Krzysztof Wojtowicz & Luis Rey & Matthias Weitzel & Toon Vandyck & Bert Saveyn, 2020. "Projecting input-output tables for model baselines," JRC Research Reports JRC120513, Joint Research Centre.
    2. Jakub Boratyński, 2016. "A Bayesian Approach to Matrix Balancing: Transformation of Industry-Level Data under NACE Revision," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(4), pages 219-239, December.
    3. Juan Manuel Valderas‐Jaramillo & José Manuel Rueda‐Cantuche, 2021. "The multidimensional nD‐GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1599-1624, December.
    4. L. Oosterhout & E. Koks & P. Beukering & S. Schep & T. Tiggeloven & S. Manen & M. Knaap & C. Duinmeijer & S. L. Buijs, 2023. "An Integrated Assessment of Climate Change Impacts and Implications on Bonaire," Economics of Disasters and Climate Change, Springer, vol. 7(2), pages 147-178, July.
    5. Barbara Hutniczak, 2022. "Efficient updating of regional supply and use tables with the national-level statistics," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 11(1), pages 1-11, December.
    6. Andre Fernandes Tomon Avelino, 2017. "Disaggregating input–output tables in time: the temporal input–output framework," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 313-334, July.
    7. Edward F. Baranov & Igor A. Kim & Dmitri I. Piontkovski & Elena A. Staritsyna, 2015. "Constructing Retrospective Time Series of Russian Input-Output Accounts Based on the Nace/Cpa Classifications," HSE Working papers WP BRP 108/EC/2015, National Research University Higher School of Economics.
    8. Ferreira, João-Pedro & Marques, João Lourenço & Moreno Pires, Sara & Iha, Katsunori & Galli, Alessandro, 2023. "Supporting national-level policies for sustainable consumption in Portugal: A socio-economic Ecological Footprint analysis," Ecological Economics, Elsevier, vol. 205(C).
    9. Xinxin Xu & Sheng Ma & Ziqiang Zeng, 2019. "Complex network analysis of bilateral international investment under de-globalization: Structural properties and evolution," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-16, April.
    10. Arne Geschke & Julien Ugon & Manfred Lenzen & Keiichiro Kanemoto & Daniel Dean Moran, 2019. "Balancing and reconciling large multi-regional input–output databases using parallel optimisation and high-performance computing," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-24, December.
    11. Zheng, Haitao & Fang, Qi & Wang, Cheng & Jiang, Yunyun & Ren, Ruoen, 2018. "Updating China's input-output tables series using MTT method and its comparison," Economic Modelling, Elsevier, vol. 74(C), pages 186-193.
    12. Coleman, Charles, 2016. "A SAS® Macro for the Generalized RAS Algorithm," MPRA Paper 77651, University Library of Munich, Germany, revised 19 Mar 2017.
    13. M. Alejandro Cardenete & M. Carmen Delgado & Patricia D. Fuentes & M. Carmen Lima & Alfredo J. Mainar & Jose M. Rueda-Cantuche & Sébastien Mary & Fabien Santini & Sergio Gomez y Paloma, 2015. "Rural-urban social accounting matrixes for modelling the impact of rural development policies in the EU," JRC Research Reports JRC94394, Joint Research Centre.
    14. Jaime Nieto & Pedro B. Moyano & Diego Moyano & Luis Javier Miguel, 2023. "Is energy intensity a driver of structural change? Empirical evidence from the global economy," Journal of Industrial Ecology, Yale University, vol. 27(1), pages 283-296, February.
    15. Malik, Arunima & Lenzen, Manfred & Ely, Rômulo Neves & Dietzenbacher, Erik, 2014. "Simulating the impact of new industries on the economy: The case of biorefining in Australia," Ecological Economics, Elsevier, vol. 107(C), pages 84-93.
    16. Thomas Wiedmann, 2017. "An input–output virtual laboratory in practice – survey of uptake, usage and applications of the first operational IELab," Economic Systems Research, Taylor & Francis Journals, vol. 29(2), pages 296-312, April.
    17. Dr. Srinita & SE & MSc1., 2017. "Economic and Consumption Distribution and Business Strategy Toward Improvement of Agricultural Industry," European Research Studies Journal, European Research Studies Journal, vol. 0(4A), pages 175-193.
    18. Daniel Moran & Richard Wood, 2014. "Convergence Between The Eora, Wiod, Exiobase, And Openeu'S Consumption-Based Carbon Accounts," Economic Systems Research, Taylor & Francis Journals, vol. 26(3), pages 245-261, September.
    19. Juan C. Surís-Regueiro & José L. Santiago, 2016. "An Input-Output methodological proposal to quantifying socio economic impacts linked to supply shocks," Working Papers 1603, Universidade de Vigo, Departamento de Economía Aplicada.
    20. He, Peijun & Ng, Tsan Sheng & Su, Bin, 2019. "Energy-economic resilience with multi-region input–output linear programming models," Energy Economics, Elsevier, vol. 84(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:95:y:2016:i:c:p:385-402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.