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

• Autorzy: Jakub Boratyński
• Języki publikacji: EN

Abstrakty

EN

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. (original abstract)

Słowa kluczowe

EN

Bayesian inference; Statistical Classification of Economic Activities in the European Community (NACE); Input-output tables; Macroeconomic modelling of economy; Statistical classification

PL

Wnioskowanie bayesowskie; Europejska Klasyfikacja Działalności (EKD); Tablice przepływów międzygałęziowych; Modelowanie makroekonomiczne gospodarki; Klasyfikacja statystyczna

• Czasopismo: Central European Journal of Economic Modelling and Econometrics (CEJEME)
• Rocznik: 2016
• Tom: 8
• Numer: nr 4
• Strony: 219--239

Twórcy

autor

Jakub Boratyński

• University of Łódź, Poland

Bibliografia

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Identyfikatory

DOI

DOI: 10.24425/cejeme.2016.119197