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Full-Text Articles in Social and Behavioral Sciences
Indirect Inference In Spatial Autoregression, Maria Kyriacou, Peter C. B. Phillips, Francesca Rossi
Indirect Inference In Spatial Autoregression, Maria Kyriacou, Peter C. B. Phillips, Francesca Rossi
Research Collection School Of Economics
Ordinary least-squares (OLS) is well known to produce an inconsistent estimator of the spatial parameter in pure spatial autoregression (SAR). In this paper, we explore the potential of indirect inference to correct the inconsistency of OLS. Under broad conditions, it is shown that indirect inference (II) based on OLS produces consistent and asymptotically normal estimates in pure SAR regression. The II estimator used here is robust to departures from normal disturbances and is computationally straightforward compared with quasi-maximum likelihood (QML). Monte Carlo experiments based on various specifications of the weight matrix show that: (a) the II estimator displays little bias …
Indirect Inference In Spatial Autoregression, Maria Kyriacou, Peter C. B. Phillips, Francesca Rossi
Indirect Inference In Spatial Autoregression, Maria Kyriacou, Peter C. B. Phillips, Francesca Rossi
Research Collection School Of Economics
Ordinary least-squares (OLS) is well known to produce an inconsistent estimator of the spatial parameter in pure spatial autoregression (SAR). In this paper, we explore the potential of indirect inference to correct the inconsistency of OLS. Under broad conditions, it is shown that indirect inference (II) based on OLS produces consistent and asymptotically normal estimates in pure SAR regression. The II estimator used here is robust to departures from normal disturbances and is computationally straightforward compared with quasi-maximum likelihood (QML). Monte Carlo experiments based on various specifications of the weight matrix show that: (a) the II estimator displays little bias …
In-Fill Asymptotic Theory For Structural Break Point In Autoregression: A Unified Theory, Liang Jiang, Xiaohu Wang, Jun Yu
In-Fill Asymptotic Theory For Structural Break Point In Autoregression: A Unified Theory, Liang Jiang, Xiaohu Wang, Jun Yu
Research Collection School Of Economics
This paper obtains the exact distribution of the maximum likelihood estimatorof structural break point in the OrnsteinñUhlenbeck process when a continuousrecord is available. The exact distribution is asymmetric, tri-modal, dependenton the initial condition. These three properties are also found in the önite sampledistribution of the least squares (LS) estimator of structural break point inautoregressive (AR) models. Motivated by these observations, the paper then developsan in-öll asymptotic theory for the LS estimator of structural break point inthe AR(1) coe¢ cient. The in-öll asymptotic distribution is also asymmetric, trimodal,dependent on the initial condition, and delivers excellent approximationsto the önite sample distribution. Unlike …