Computing the Jacobian in spatial models: an applied survey
AbstractDespite attempts to get around the Jacobian in fitting spatial econometric models by using GMM and other approximations, it remains a central problem for maximum likelihood estimation. In principle, and for smaller data sets, the use of the eigenvalues of the spatial weights matrix provides a very rapid and satisfactory resolution. For somewhat larger problems, including those induced in spatial panel and dyadic (network) problems, solving the eigenproblem is not as attractive, and a number of alternatives have been proposed. This paper will survey chosen alternatives, and comment on their relative usefulness.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Department of Economics, Norwegian School of Economics in its series Discussion Paper Series in Economics with number 20/2010.
Length: 30 pages
Date of creation: 17 Aug 2010
Date of revision:
Contact details of provider:
Postal: NHH, Department of Economics, Helleveien 30, N-5045 Bergen, Norway
Phone: +47 55 959 277
Fax: 5595 9100
Web page: http://www.nhh.no/sam/
More information through EDIRC
Spatial autoregression; Maximum likelihood estimation; Jacobian computation; Econometric software.;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-05-30 (All new papers)
- NEP-ECM-2011-05-30 (Econometrics)
- NEP-URE-2011-05-30 (Urban & Real Estate Economics)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Millo, Giovanni, 2014. "Maximum likelihood estimation of spatially and serially correlated panels with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 914-933.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dagny Hanne Kristiansen).
If references are entirely missing, you can add them using this form.