Arbeitspapier
Efficient estimation of the semiparametric spatial autoregressive model
Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing non stochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the case of distribution of unknown, nonparametric, form, where series non parametric estimates of the score function are employed inadaptive estimates of parameters of interest. These estimates are as efficient as ones based on a correct form, in particular they are more effcient than pseudo-Gaussian maximum likelihood estimates at non-Gaussian distributions. Two different adaptive estimates are considered.One entails astringent condition on the spatial weight matrix,and is suitable only when observations have substantially many neighbours. The other adaptive estimate relaxes this requirement, at the expense of alternative conditions and possible computational expense. A Monte Carlo study of finite sample performance is included.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP08/06
- Klassifikation
-
Wirtschaft
Estimation: General
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
- Thema
-
Spatial autoregression , Efficient estimation , Adaptive estimation , Simultaneity bias
Nichtparametrisches Verfahren
Schätzung
Regression
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Robinson, Peter M.
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2006
- DOI
-
doi:10.1920/wp.cem.2006.0806
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Robinson, Peter M.
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2006
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