Journal
MATHEMATICS
Volume 9, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/math9060622
Keywords
PLASEM; local linear estimation; GMM estimation; consistency; asymptotic normality; Monte Carlo simulation
Categories
Funding
- NSF of Fujian Province, PR China [2018J05002, 2020J01170]
- Fujian Normal University Innovation Team Foundation, PR China [IRTL1704]
- Scientific Research Foundation of Chongqing Technology and Business University, PR China [2056015]
- Science and Technology Research Program of Chongqing Municipal Education Commission, PR China [KJQN202000843]
Ask authors/readers for more resources
This article introduces a partially linear additive spatial error model (PLASEM) specification and its corresponding generalized method of moments (GMM), deriving consistency and asymptotic normality of estimators for cases with nonparametric terms. The finite sample performance of estimates is assessed through Monte Carlo simulations, and the proposed method is illustrated through the analysis of Boston housing data.
This article presents a partially linear additive spatial error model (PLASEM) specification and its corresponding generalized method of moments (GMM). It also derives consistency and asymptotic normality of estimators for the case with a single nonparametric term and an arbitrary number of nonparametric additive terms under some regular conditions. In addition, the finite sample performance for our estimates is assessed by Monte Carlo simulations. Lastly, the proposed method is illustrated by analyzing Boston housing data.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
