Gupta, Abhimanyu and Hidalgo, Javier (2022) 'Nonparametric prediction with spatial data.' Econometric Theory. pp. 1-39. ISSN 0266-4666

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Abstract

We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorization of the spectral density function. We provide theoretical results showing that the predictor has desirable asymptotic properties. Finite sample performance is assessed in a Monte Carlo study that also compares our algorithm to a rival nonparametric method based on the infinite AR representation of the dynamics of the data. Finally, we apply our methodology to predict house prices in Los Angeles.

Item Type:	Article
Uncontrolled Keywords:	Lattice data; unilateral models; canonical factorization; spectral density; nonparametric prediction
Divisions:	Faculty of Social Sciences Faculty of Social Sciences > Economics, Department of
SWORD Depositor:	Elements
Depositing User:	Elements
Date Deposited:	25 Mar 2022 10:52
Last Modified:	22 Jun 2022 12:58
URI:	http://repository.essex.ac.uk/id/eprint/32564

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