SEMIPARAMETRIC ESTIMATION of CENSORED SPATIAL AUTOREGRESSIVE MODELS

研究成果: Article

抜粋

This study considers the estimation of spatial autoregressive models with censored dependent variables, where the spatial autocorrelation exists within the uncensored latent dependent variables. The estimator proposed in this paper is semiparametric, in the sense that the error distribution is not parametrically specified and can be heteroskedastic. Under a median restriction, we show that the proposed estimator is consistent and asymptotically normally distributed. As an empirical illustration, we investigate the determinants of the risk of assault and other violent crimes including injury in the Tokyo metropolitan area.

元の言語English
ページ(範囲)48-85
ページ数38
ジャーナルEconometric Theory
36
発行部数1
DOI
出版物ステータスPublished - 2020 2 1

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

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