IDEAS home Printed from https://ideas.repec.org/a/psc/journl/v8y2016i4p219-239.html
   My bibliography  Save this article

A Bayesian Approach to Matrix Balancing: Transformation of Industry-Level Data under NACE Revision

Author

Listed:
  • Jakub Boratyński

    (University of Łódź)

Abstract

We apply Bayesian inference to estimate transformation matrix that converts vector of industry outputs from NACE Rev. 1.1 to NACE Rev. 2 classification. In formal terms, the studied issue is a representative of the class of matrix balancing (updating, disaggregation) problems, often arising in the field of multi-sector economic modelling. These problems are characterised by availability of only partial, limited data and a strong role for prior assumptions, and are typically solved using bi-proportional balancing or cross-entropy minimisation methods. Building on Bayesian highest posterior density formulation for a similarly structured case, we extend the model with specification of prior information based on Dirichlet distribution, as well as employ MCMC sampling. The model features a specific likelihood, representing accounting restrictions in the form of an underdetermined system of equations. The primary contribution, compared to the alternative, widespread approaches, is in providing a clear account of uncertainty.

Suggested Citation

  • 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.
  • Handle: RePEc:psc:journl:v:8:y:2016:i:4:p:219-239
    as

    Download full text from publisher

    File URL: http://cejeme.org/publishedarticles/2016-27-06-636166240622656250-2539.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Randall Jackson & Alan Murray, 2004. "Alternative Input-Output Matrix Updating Formulations," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 135-148.
    2. Michael Lahr & Louis de Mesnard, 2004. "Biproportional Techniques in Input-Output Analysis: Table Updating and Structural Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 115-134.
    3. Manfred Lenzen & Blanca Gallego & Richard Wood, 2009. "Matrix Balancing Under Conflicting Information," Economic Systems Research, Taylor & Francis Journals, vol. 21(1), pages 23-44.
    4. Heckelei, Thomas & Mittelhammer, Ronald C. & Jansson, Torbjorn, 2008. "A Bayesian Alternative To Generalized Cross Entropy Solutions For Underdetermined Econometric Models," Discussion Papers 56973, University of Bonn, Institute for Food and Resource Economics.
    5. 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.
    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. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    8. Manfred Lenzen & Daniel D. Moran & Arne Geschke & Keiichiro Kanemoto, 2014. "A Non-Sign-Preserving Ras Variant," Economic Systems Research, Taylor & Francis Journals, vol. 26(2), pages 197-208, June.
    9. 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.
    10. 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.
    11. McDougall, Robert A., 1999. "Entropy Theory and RAS are Friends," Working papers 283439, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    12. Golan, Amos & Judge, George & Robinson, Sherman, 1994. "Recovering Information from Incomplete or Partial Multisectoral Economic Data," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 541-549, August.
    13. Jeffrey C. Peters & Thomas W. Hertel, 2016. "Matrix balancing with unknown total costs: preserving economic relationships in the electric power sector," Economic Systems Research, Taylor & Francis Journals, vol. 28(1), pages 1-20, March.
    14. McDougall, Robert, 1999. "Entropy Theory and RAS are Friends," GTAP Working Papers 300, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    3. Peters, Jeffrey C. & Hertel, Thomas W., 2016. "The database–modeling nexus in integrated assessment modeling of electric power generation," Energy Economics, Elsevier, vol. 56(C), pages 107-116.
    4. Andrea Bacilieri & Pablo Austudillo-Estevez, 2023. "Reconstructing firm-level input-output networks from partial information," Papers 2304.00081, arXiv.org.
    5. Tamas Revesz, 2023. "A not sign-preserving iteration algorithm for the ‘Improved Normalized Squared Differences’ matrix adjustment model," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 49-71, March.
    6. Casiano A. Manrique-de-Lara-Peñate & Dolores R. Santos-Peñate, 2017. "SAM updating using multi-objective optimization techniques," Papers in Regional Science, Wiley Blackwell, vol. 96(3), pages 647-667, August.
    7. Ramos Carvajal, Carmen & Fernández Vázquez, Esteban, 2002. "Temporal projection of an input-output tables series for the region of Asturias," ERSA conference papers ersa02p211, European Regional Science Association.
    8. Niemi, Janne, 2009. "Dynamic (GTAP) model and baseline for energy and environment issues," Conference papers 331856, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    9. M. Alejandro Cardenete & Ferran Sancho, 2002. "Sensitivity of Simulation Results to Competing SAM Updates," UFAE and IAE Working Papers 556.02, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    10. repec:rre:publsh:v:34:y:2004:i:1:p:37-56 is not listed on IDEAS
    11. Rich, Jeppe & Mulalic, Ismir, 2012. "Generating synthetic baseline populations from register data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 467-479.
    12. Chisari, Omar Osvaldo & Mastronardi, Leonardo Javier & Romero, Carlos Adrián, 2012. "Building an input-output Model for Buenos Aires City," MPRA Paper 40028, University Library of Munich, Germany.
    13. Casiano Peñate & Dolores Peñate, 2003. "New Nonlinear Approaches for the Adjustment and Updating of a SAM," Economic Change and Restructuring, Springer, vol. 36(3), pages 259-272, September.
    14. 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.
    15. Casiano Peñate & Dolores Peñate, 2004. "New Nonlinear Approaches for the Adjustment and Updating of a SAM," Economic Change and Restructuring, Springer, vol. 36(3), pages 259-272, September.
    16. Hamasaki, Hiroshi, 2004. "Japanese strategy on climate change to achieve the Kyoto Target with steady economic development -An investigation by using the dynamic version of GTAP-E model," Conference papers 331201, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    17. G. Ferrari & G. Garau & P. Lecca, 2009. "Constructing a Social Accounting Matrix for Sardinia," Working Paper CRENoS 200902, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    18. Haykel Hadj Salem, 2004. "The Macroeconomic Social Accounting Matrix of Tunisia in 1996," Computational Economics 0410001, University Library of Munich, Germany.
    19. 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.
    20. Szabó, Norbert, 2015. "Methods for regionalizing input-output tables," MPRA Paper 73947, University Library of Munich, Germany.
    21. Többen, Johannes & Schröder, Thomas, 2018. "A maximum entropy approach to the estimation of spatially and sectorally disaggregated electricity load curves," Applied Energy, Elsevier, vol. 225(C), pages 797-813.

    More about this item

    Keywords

    matrix balancing; Bayesian inference; NACE revision; transformation matrix; multi-sector modelling;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models

    Statistics

    Access and download statistics

    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:psc:journl:v:8:y:2016:i:4:p:219-239. 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: Damian Jelito (email available below). General contact details of provider: http://cejeme.org/ .

    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.