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Nonparametric prediction with spatial data

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

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Identification Number: 10.1017/S0266466622000226

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
Official URL: https://www.cambridge.org/core/journals/econometri...
Additional Information: © 2022 The Authors
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
Date Deposited: 07 Jun 2022 10:45
Last Modified: 18 Jul 2022 07:57
URI: http://eprints.lse.ac.uk/id/eprint/115292

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