Hello, i like to incorporate a SUR (Seemingly Unrelated Regression) in a multilevel-model. My panel-dataset includes variables for 400 regions from 1990-2010. In case of SUR-models i found the following econometric requirement that time observations need to exceed unit observations, which is obviously not true in my dataset. Is it possible to avoid this requirement by using MCMC inference? I am given to understand that one advantage of MCMC estimation is due to the fact that the number of parameteres to be estimated can be larger than the observation number (because estimation does not rely on degree of freedoms). Can someone confirm my thoughts? In my case the discrepancy between time observations (20) and unit observations (400) is quite large. Is it possible to use a SUR_MCMC-model to handle this problem?
Thanks in advance Mit freundlichen GrüÃen Linus Holtermann Hamburgisches WeltWirtschaftsInstitut gemeinnützige GmbH (HWWI) Heimhuder StraÃe 71 20148 Hamburg Tel +49-(0)40-340576-336 Fax+49-(0)40-340576-776 Internet: [1]www.hwwi.org Email: [2]holterm...@hwwi.org AmtsgerichtHamburg HRB 94303 Geschäftsführer: Prof. Dr. Thomas Straubhaar, Gunnar Geyer Umsatzsteuer-ID: DE 241849425 References 1. http://www.hwwi.org/ 2. mailto:holterm...@hwwi.org ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
