@ARTICLE{Boratyński_Jakub_A_2016,
 author={Boratyński, Jakub},
 number={No 4},
 journal={Central European Journal of Economic Modelling and Econometrics},
 pages={219-239},
 howpublished={online},
 year={2016},
 publisher={Oddział PAN w Łodzi},
 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.},
 type={Artykuły / Articles},
 title={A Bayesian Approach to Matrix Balancing: Transformation of Industry-Level Data under NACE Revision},
 URL={http://ochroma.man.poznan.pl/Content/103711/PDF-MASTER/mainFile.pdf},
 doi={10.24425/cejeme.2016.119197},
 keywords={matrix balancing, Bayesian inference, NACE revision, transformation matrix, multi-sector modelling},
}