Gupta, Abhimanyu and Hidalgo, Javier (2022) Nonparametric prediction with spatial data. Econometric Theory. ISSN 0266-4666
![]() |
Text (nonparametric-prediction-with-spatial-data)
- Published Version
Available under License Creative Commons Attribution. Download (451kB) |
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: | 10 Aug 2024 03:48 |
URI: | http://eprints.lse.ac.uk/id/eprint/115292 |
Actions (login required)
![]() |
View Item |