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Maximum Likelihood Estimation

  • R. Kelley Pace
Reference work entry

Abstract

Maximum likelihood estimation has been the standard method employed for estimating spatial econometric models. This chapter introduces these methods, examines the specific case of a spatial error model, and provides an example based on a large data set. In addition, the chapter sets forth various solutions to the computational difficulties that arise for large data sets.

Keywords

Ordinary Little Square Information Matrix Spatial Weight Matrix Spatial Error Model Observe Information Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

I would like to thank Mark Mclean, James LeSage, and Shuang Zhu for their very helpful comments.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Finance, E.J. Ourso College of Business AdministrationLouisiana State UniversityBaton RougeUSA

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