We propose a new class of models specifically tailored for spatiotemporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, that is, SARAR(1, 1), by exploiting the recent advancements in score-driven (SD) models typically used in time series econometrics. In particular, we allow for time-varying spatial autoregressive coefficients as well as time-varying regressor coefficients and cross-sectional standard deviations. We report an extensive Monte Carlo simulation study in order to investigate the finite-sample properties of the maximum likelihood estimator for the new class of models as well as its flexibility in explaining a misspecified dynamic spatial dependence process. The new proposed class of models is found to be economically preferred by rational investors through an application to portfolio optimization.

Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances / Leopoldo Catania; Anna Gloria Billé. - In: JOURNAL OF APPLIED ECONOMETRICS. - ISSN 0883-7252. - ELETTRONICO. - 32:6(2017), pp. 1178-1196. [10.1002/jae.2565]

Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances

Anna Gloria Billé
Secondo
2017

Abstract

We propose a new class of models specifically tailored for spatiotemporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, that is, SARAR(1, 1), by exploiting the recent advancements in score-driven (SD) models typically used in time series econometrics. In particular, we allow for time-varying spatial autoregressive coefficients as well as time-varying regressor coefficients and cross-sectional standard deviations. We report an extensive Monte Carlo simulation study in order to investigate the finite-sample properties of the maximum likelihood estimator for the new class of models as well as its flexibility in explaining a misspecified dynamic spatial dependence process. The new proposed class of models is found to be economically preferred by rational investors through an application to portfolio optimization.
2017
Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances / Leopoldo Catania; Anna Gloria Billé. - In: JOURNAL OF APPLIED ECONOMETRICS. - ISSN 0883-7252. - ELETTRONICO. - 32:6(2017), pp. 1178-1196. [10.1002/jae.2565]
Leopoldo Catania; Anna Gloria Billé
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/853794
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