# Poisson and NB results

i did a regression with poisson model, and since the dependant variable is overdispersed (0.13) , i have also tried negative binomial. The problem is that my explanatory variable "repeated partner" is highly significant under poisson and not at all under NB. What should i do?

Dependent Variable: PATENT
Method: ML/QML - Poisson Count (Quadratic hill climbing) Date: 05/19/15 Time: 17:50
Included observations: 54 after adjustments Convergence achieved after 8 iterations Covariance matrix computed using second derivatives

Variable        Coefficient Std. Error  z-Statistic Prob.
LAG4_REPEATED   0.006209    0.000972    6.384682    0.0000


Dependent Variable: PATENT
Method: ML - Negative Binomial Count (Quadratic hill climbing) Date: 05/19/15 Time: 17:54
Included observations: 54 after adjustments Convergence achieved after 8 iterations Covariance matrix computed using second derivatives

Variable        Coefficient Std. Error  z-Statistic Prob.
LAG4_REPEATED   0.005510    0.004541    1.213525    0.2249


This is what appears to happen for your data: The coefficient of LAG4_REPEATED is at least similar, roundabout 0.006. But the standard error in the Poisson model is much smaller (0.00097) than in the NB model (0.0045). Typically, this means that the significance in the Poisson model is spurious and only due to the misspecified dispersion.