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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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:	12 Dec 2024 03:02
URI:	http://eprints.lse.ac.uk/id/eprint/115292

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