Arbeitspapier
Quasi Maximum Likelihood Estimation of Spatial Models with Heterogeneous Coefficients
This paper considers spatial autoregressive panel data models and extends their analysis to the case where the spatial coefficients differ across the spatial units. It derives conditions under which the spatial coefficients are identified and develops a quasi maximum likelihood (QML) estimation procedure. Under certain regularity conditions, it is shown that the QML estimators of individual spatial coefficients are consistent and asymptotically normally distributed when both the time and cross section dimensions of the panel are large. It derives the asymptotic covariance matrix of the QML estimators allowing for the possibility of non-Gaussian error processes. Small sample properties of the proposed estimators are investigated by Monte Carlo simulations for Gaussian and non-Gaussian errors, and with spatial weight matrices of differing degree of sparseness. The simulation results are in line with the paper’s key theoretical findings and show that the QML estimators have satisfactory small sample properties for panels with moderate time dimensions and irrespective of the number of cross section units in the panel, under certain sparsity conditions on the spatial weight matrix.
- Language
-
Englisch
- Bibliographic citation
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Series: CESifo Working Paper ; No. 5428
- Classification
-
Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
- Subject
-
spatial panel data models
heterogeneous spatial lag
coefficients
identification
quasi maximum likelihood (QML) estimators
non-Gaussian errors
- Event
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Geistige Schöpfung
- (who)
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Aquaro, Michele
Bailey, Natalia
Pesaran, M. Hashem
- Event
-
Veröffentlichung
- (who)
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Center for Economic Studies and ifo Institute (CESifo)
- (where)
-
Munich
- (when)
-
2015
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Aquaro, Michele
- Bailey, Natalia
- Pesaran, M. Hashem
- Center for Economic Studies and ifo Institute (CESifo)
Time of origin
- 2015
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