Pokaż uproszczony rekord

Improved asymptotic analysis of Gaussian QML estimators in spatial models

dc.contributor.authorOlejnik, Jakub
dc.contributor.authorOlejnik, Alicja
dc.date.accessioned2017-12-28T06:21:29Z
dc.date.available2017-12-28T06:21:29Z
dc.date.issued2017-12
dc.identifier.urihttp://hdl.handle.net/11089/23762
dc.description.abstractThis 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.pl_PL
dc.language.isoen_USpl_PL
dc.publisherFaculty of Economics and Sociologypl_PL
dc.relation.ispartofseriesLodz Economics Working Papers;9
dc.rightsUznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Polska*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/pl/*
dc.titleImproved asymptotic analysis of Gaussian QML estimators in spatial modelspl_PL
dc.typeWorking Paperpl_PL
dc.contributor.authorAffiliationDepartment of Mathematics and Computer Science University of Lodzpl_PL
dc.contributor.authorAffiliationFaculty of Economics and Sociology, University of Lodzpl_PL
dc.referencesAnselin, L. (1988). Spatial Econometrics: Methods and Models, Kluwer Academic, Dordrecht, doi:10.1007/978-94-015-7799-1.pl_PL
dc.referencesAnselin, L., Le Gallo, J. and Jayet, H. (2006). Spatial Panel Econometrics, in Matyas, L. and Sevestre, P. (eds.) The Econometrics of Panel Data, Fundamentals and Recent Developments in Theory and Practice, 3rd edition, Kluwer, Dodrecht, doi:10.1007/978-3- 540-75892-1.pl_PL
dc.referencesBadinger, H. and Egger, P. (2013). Estimation and testing of higher-order spatial autoregressive panel data error component models. Journal of Geographical Systems 15 (4) 453{489, doi:10.1007/s10109-012-0174-z.pl_PL
dc.referencesBaltagi, B. H. (2005). Econometric Analysis of Panel Data, Chichester West Sussex, England.pl_PL
dc.referencesBhansali, R. J., Giraitis, L. and Kokoszka, P. S. (2007). Convergence of quadratic forms with non-vanishing diagonal. Statistics and Probability Letters 77 726{734, doi:10.1016/j.spl.2006.11.007.pl_PL
dc.referencesBillingsley, P. (1995). Probability and Measure, 3nd ed. John Wiley & Sons, New York.pl_PL
dc.referencesBillingsley, P. (1999). Convergence of Probability Measures, 2nd ed. John Wiley & Sons, New York, doi:10.1002/9780470316962.pl_PL
dc.referencesCliff, A. D. and Ord, J. K. (1973). Spatial Autocorrelation, Pion, London.pl_PL
dc.referencesCressie, N. (1993). Statistics for Spatial Data, Wiley, New York.pl_PL
dc.referencesElhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Springer, Heidelberg, doi:10.1007/978-3-642-40340-8.pl_PL
dc.referencesElhorst, J. P., Lacombe, D. J. and Piras, G. (2014). On model speci cation and parameter space de nitions in higher order spatial econometric models. Regional Science and Urban Economics 42 211{220, doi:10.1016/j.regsciurbeco.2011.09.003.pl_PL
dc.referencesFeng, C., Wang, H., Han, Y., Xia, Y. and Tu, X. M. (2014). The Mean Value Theorem and Taylors Expansion in Statistics. The American Statistician 67 245{248, doi:10.1080/00031305.2013.844203.pl_PL
dc.referencesGupta, A. and Robinson, P. (2015). Inference on higher-order spatial autoregressive models with increasingly many parameters. Journal of Econometrics 186 19{31, doi:10.1016/j.jeconom.2014.12.008pl_PL
dc.referencesH ajek, P. and Johanis, M. (2014). Smooth Analysis in Banach Spaces, De Gruyter, Berlin.pl_PL
dc.referencesHall, P. and Hyde, C. C. (1980). Martingale Limit Theory and Its Application, Academic Press Inc., New York.pl_PL
dc.referencesHan, X., Hsieh C. and Lee, L. F. (2017). Estimation and Model Selection of Higher-order Spatial Autoregressive Model: An E cient Bayesian Approach. Regional Science and Urban Economics 63 97{120, doi:10.1016/j.regsciurbeco.2016.12.003.pl_PL
dc.referencesKelejian, H. H. and Prucha, I. R. (2001). On the Asymptotic Distribution of the Moran I Test Statistic with Applications. Journal of Econometrics 104 219{257 doi:10.1016/S0304- 4076(01)00064-1.pl_PL
dc.referencesLee, L. F. (2004). Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models. Econometrica 72 (6) 1899{1925, doi: 10.1111/j.1468- 0262.2004.00558.x.pl_PL
dc.referencesLee, L. F. (2007). GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. Journal of Econometrics 137 489{514, doi:10.1016/j.jeconom.2005.10.004.pl_PL
dc.referencesLee, L. F. and Liu, J. (2010). E cient GMM estimation of high order spatial autoregressive models with autoregressive disturbances. Econometric Theory 26 187{230, doi:10.1017/S0266466609090653.pl_PL
dc.referencesLee, L. F., Liu, J. and Lin, X. (2010). Speci cation and estimation of social interaction models with network structures. The Econometrics Journal 13 145{176, doi:10.1111/j.1368- 423X.2010.00310.x.pl_PL
dc.referencesLee, L. F. and Yu, J. (2010a). Estimation of spatial autoregressive panel data models with fi xed effects Journal of Econometrics 154 165-185, doi:10.1016/j.jeconom.2009.08.001.pl_PL
dc.referencesLee, L. F. and Yu, J. (2010b). A spatial dynamic panel data model with both time and individual fixed effects Econometric Theory 26 564-597, doi:10.1017/S0266466609100099.pl_PL
dc.referencesLee, L. F. and Yu, J. (2013). Near Unit Root in the Spatial Autoregressive Model. Spatial Economic Analysis 8 314-351, doi:10.1080/17421772.2012.760134pl_PL
dc.referencesLee, L. F. and Yu, J. (2014). E cient GMM estimation of spatial dynamic panel data models with fi xed effects. Journal of Econometrics 180 174-197, doi:10.1016/j.jeconom.2014.03.003.pl_PL
dc.referencesLe Sage, J. and Pace, R. K. (2009). Introduction to spatial econometrics, CRC Press, Taylor & Francis Group, Boca Raton.pl_PL
dc.referencesLi, K. (2017). Fixed-effects dynamic spatial panel data models and impulse response analysis. Journal of Econometrics 198 102-121, doi:10.1016/j.jeconom.2017.02.001.pl_PL
dc.referencesLiu S. F. and Yang Z. (2015). Modi ed QML estimation of spatial autoregressive models with unknown heteroskedasticity and nonnormality. Regional Science and Urban Economics, 52 50-70, doi:10.1016/j.regsciurbeco.2015.02.003.pl_PL
dc.referencesOlejnik, A. and Olejnik, J. (2017). An alternative to Partial Regression in Maximum Likelihood Estimation of Spatial Autoregressive Panel Data Model. Statistical Review, in press.pl_PL
dc.referencesPaelinck, J. and Klaassen, L. (1979). Spatial Econometrics, Saxon House, Farnborough.pl_PL
dc.referencesPotscher, M. B. and Prucha, I. R. (1997). Dynamic Nonlinear Econometric Models: Asymptotic Theory, Springer-Verlag, Berlin Heidelberg.pl_PL
dc.referencesQu, X. and Lee, L. F. (2017). QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices. Journal of Econometrics, 197 173-201, doi:10.1016/j.jeconom.2016.11.004.pl_PL
dc.referencesShi, W. and Lee, L. F. (2017). Spatial dynamic panel data models with interactive fixed effects. Journal of Econometrics, 197 323-347, doi:10.1016/j.jeconom.2016.12.001.pl_PL
dc.referencesTakesaki, M. (1979). Theory of operator algebras I, Springer-Verlag, New York.pl_PL
dc.referencesYu, J., de Jong, R. and Lee, L. F. (2008). Quasi-Maximum Likelihood Estimators For Spatial Dynamic Panel Data With Fixed E ects When Both n and T Are Large. Journal of Econometrics 146 118-134, doi:10.1016/j.jeconom.2008.08.002.pl_PL
dc.referencesPruss, A. R. (1998). A bounded N-tuplewise independent and identically distributed counterexample to the CLT. Probability Theory and Related Fields 111 323-332, doi:10.1007/s004400050170.pl_PL


Pliki tej pozycji

Thumbnail
Nazwa:
LEWP_9_2017.pdf
Rozmiar:
551.7KB
Format:
PDF
Oglądaj/Otwórz
Thumbnail
Nazwa:
license_rdf
Rozmiar:
1.203KB
Format:
application/rdf+xml
Oglądaj/Otwórz

Pozycja umieszczona jest w następujących kolekcjach

Pokaż uproszczony rekord

Uznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Polska
Poza zaznaczonymi wyjątkami, licencja tej pozycji opisana jest jako Uznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Polska