Likelihood-based inference for regular functions with fractional polynomial approximations

Geweke, J; Petrella, L

Likelihood-based inference for regular functions with fractional polynomial approximations

Geweke, J Petrella, L

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Publication Type:: Journal Article
Citation:: Journal of Econometrics, 2014, 183 (1), pp. 22 - 30
Issue Date:: 2014-11-01

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Field	Value	Language
dc.contributor.author	Geweke, J	en_US
dc.contributor.author	Petrella, L	en_US
dc.date.issued	2014-11-01	en_US
dc.identifier.citation	Journal of Econometrics, 2014, 183 (1), pp. 22 - 30	en_US
dc.identifier.issn	0304-4076	en_US
dc.identifier.uri	http://hdl.handle.net/10453/117762
dc.description.abstract	© 2014 Elsevier B.V. All rights reserved. This paper shows that regular fractional polynomials can approximate regular cost, production and utility functions and their first two derivatives on closed compact subsets of the strictly positive orthant of Euclidean space arbitrarily well. These functions therefore can provide reliable approximations to demand functions and other economically relevant characteristics of tastes and technology. Using canonical cost function data, it shows that full Bayesian inference for these approximations can be implemented using standard Markov chain Monte Carlo methods.	en_US
dc.relation.ispartof	Journal of Econometrics	en_US
dc.relation.isbasedon	10.1016/j.jeconom.2014.06.007	en_US
dc.subject.classification	Econometrics	en_US
dc.title	Likelihood-based inference for regular functions with fractional polynomial approximations	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	183	en_US
utslib.for	140301 Cross-Sectional Analysis	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Economics Discipline
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	183	en_US

Abstract:

© 2014 Elsevier B.V. All rights reserved. This paper shows that regular fractional polynomials can approximate regular cost, production and utility functions and their first two derivatives on closed compact subsets of the strictly positive orthant of Euclidean space arbitrarily well. These functions therefore can provide reliable approximations to demand functions and other economically relevant characteristics of tastes and technology. Using canonical cost function data, it shows that full Bayesian inference for these approximations can be implemented using standard Markov chain Monte Carlo methods.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/117762