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Improved asymptotic analysis of Gaussian QML estimators in spatial models

Object's details: Improved asymptotic analysis of Gaussian QML estimators in spatial models

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Provider:Repozytorium Uniwersytetu Łódzkiego

Description

Title:
Improved asymptotic analysis of Gaussian QML estimators in spatial models
Creator:
Olejnik, Jakub;
Olejnik, Alicja
Contributor:
Department of Mathematics and Computer Science University of Lodz;
Faculty of Economics and Sociology, University of Lodz
Description:
This paper presents a fundamentally improved statement on asymptotic behaviour of the well-known Gaussian QML estimator of parameters in high-order mixed regressive/autoregressive spatial model. We generalize the approach previously known in the econometric literature by considerably weakening assumptions on the spatial weight matrix, distribution of the residuals and the parameter space for the spatial autoregressive parameter. As an example application of our new asymptotic analysis we also give a statement on the large sample behaviour of a general fi xed effects design.
Object availability:
free access
Rights:
Uznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Polska;
http://creativecommons.org/licenses/by-nc-nd/3.0/pl
Date:
2017.12.28;
2017.12
Type:
Working Paper
Language:
English
Format:
application/pdf
Publisher:
Faculty of Economics and Sociology
Relation:
Lodz Economics Working Papers;9
Identifier: http://hdl.handle.net/11089/23762
Data provider:
Repozytorium Uniwersytetu Łódzkiego

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FBC TeNe Project

Project co-financed by European Funds under the Operational Program Digital Poland for 2014-2020 (project no. POPC.02.04.00-00-0012 / 20-00)

More information about the project can be found at: https://tene.fbc.pionier.net.pl

European Funds. Digital Poland

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Digital Libraries Federation

European Union - European Regional Development Fund

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