抄録
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.
| 本文言語 | English |
|---|---|
| ページ（範囲） | 148-160 |
| ページ数 | 13 |
| ジャーナル | Spatial Economic Analysis |
| 巻 | 16 |
| 号 | 2 |
| DOI | |
| 出版ステータス | Published - 2021 |
ASJC Scopus subject areas
- 地理、計画および開発
- 経済学、計量経済学および金融学（全般）
- 統計学、確率および不確実性
- 地球惑星科学（その他）