Abstract

http://ssrn.com/abstract=2406216
 


 



Spatial Errors in Count Data Regressions


Marinho Bertanha


Stanford University - Department of Economics

Petra Moser


Stanford University - Department of Economics; National Bureau of Economic Research (NBER)

August 7, 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 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. In addition to the PCFE, this result also applies to the commonly used Logit model of panel data with fixed effects. 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: 36

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

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

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

Suggested Citation

Bertanha, Marinho and Moser, Petra, Spatial Errors in Count Data Regressions (August 7, 2014). Available at SSRN: http://ssrn.com/abstract=2406216 or http://dx.doi.org/10.2139/ssrn.2406216

Contact Information

Marinho Bertanha
Stanford University - Department of Economics ( email )
Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
Petra Moser (Contact Author)
Stanford University - Department of Economics ( email )
Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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