2021年4月
Spatial extension of generalized autoregressive conditional heteroskedasticity models
SPATIAL ECONOMIC ANALYSIS
- ,
- 巻
- 16
- 号
- 2
- 開始ページ
- 148
- 終了ページ
- 160
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1080/17421772.2020.1742929
- 出版者・発行元
- ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
This paper proposes an extension of generalized autoregressive conditional heteroskedasticity (GARCH) models for a time series to those for spatial data, which are called here spatial GARCH (S-GARCH) models. S-GARCH models are re-expressed as spatial autoregressive moving-average (SARMA) models and a two-step procedure based on quasi-likelihood functions is proposed to estimate the parameters. The consistency and asymptotic normality are proven for the two-step estimators. S-GARCH models are applied to simulated and land-price data in areas of Tokyo to demonstrate the empirical properties.
- リンク情報
- ID情報
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- DOI : 10.1080/17421772.2020.1742929
- ISSN : 1742-1772
- eISSN : 1742-1780
- Web of Science ID : WOS:000523758300001