Abstract

http://ssrn.com/abstract=2406216
 


 



Spatial Errors in Count Data Regressions


Marinho Bertanha


Catholic University of Louvain (UCL) - Center for Operations Research and Econometrics (CORE)

Petra Moser


Leonard N. Stern School of Business - Department of Economics; National Bureau of Economic Research (NBER)

December 4, 2014


Abstract:     
Count data regressions are an important tool for empirical analyses ranging from analyses of patent counts to measures of health and unemployment. Along with negative binomial, Poisson panel regressions are a preferred method of analysis because the Poisson conditional fixed effects maximum likelihood estimator (PCFE) and its sandwich variance estimator are consistent even if the data are not Poisson-distributed, or if the data are correlated over time. Analyses of counts may however also be affected by correlation in the cross-section. For example, patent counts or publications may increase across related research fields in response to common shocks. This paper shows that the PCFE and its sandwich variance estimator are consistent in the presence of such dependence in the cross-section - as long as spatial dependence is time-invariant. We develop a test for time-invariant spatial dependence and provide code in STATA and MATLAB to implement the test.

Number of Pages in PDF File: 38

Keywords: Count-data, Poisson panel models, spatial correlation, patents, citations

JEL Classification: C10, C12, C23, O31, O33


Open PDF in Browser Download This Paper

Date posted: March 12, 2014 ; Last revised: December 5, 2014

Suggested Citation

Bertanha, Marinho and Moser, Petra, Spatial Errors in Count Data Regressions (December 4, 2014). Available at SSRN: http://ssrn.com/abstract=2406216 or http://dx.doi.org/10.2139/ssrn.2406216

Contact Information

Marinho Bertanha
Catholic University of Louvain (UCL) - Center for Operations Research and Econometrics (CORE) ( email )
Voie du Roman Pays, 34
Louvain-la-Neuve, 1348
Belgium
Petra Moser (Contact Author)
Leonard N. Stern School of Business - Department of Economics ( email )
269 Mercer Street
New York, NY 10003
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Feedback to SSRN


Paper statistics
Abstract Views: 1,005
Downloads: 239
Download Rank: 92,245
Paper comments
No comments have been made on this paper

© 2016 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollobot1 in 0.219 seconds