$0.00
D. M. Lambert
University of Tennessee, Knoxville, TN, USA
Series: Mathematics Research Developments
BISAC: MAT000000
This book reformulates the instrumental variable (IV) approach of estimating of the spatial lag autoregressive (SAR) model in the maximum empirical likelihood (MEL) framework, a nonparametric approach to estimate linear and nonlinear regression models. A Monte Carlo analysis compares the precision of the estimators under different levels of heteroskedasticity, lag autocorrelation, and sample size. Results suggest there are no gains in precision from the MEL estimator, and that the SAR-IV estimator is more precise as heteroskedasticity increases. (Imprint: Nova)
Table of Contents
ABSTRACT
1. INTRODUCTION
2. GENERALIZED METHOD OF MOMENT ESTIMATION OF THE SAR(1) MODEL
3. MAXIMUM EMPIRICAL LIKELIHOOD ESTIMATION OF THE SAR(1) PROCESS MODEL
4. MONTE CARLO EXPERIMENTS
5. MONTE CARLO RESULTS
CONCLUSIONS
REFERENCES
INDEX
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