alphanumeric journal
The Journal of Operations Research, Statistics, Econometrics and Management Information Systems
An Application of the Generalized Poisson Model for Over Dispersion Data on The Number of Strikes Between 1984 and 2017
Abstract
Poisson regression analysis is widely used in many studies including count data. Poisson regression analysis is based on the assumption of equal mean and variance. However, this assumption is quite difficult in regression models. In cases where the assumption is not provided, over dispersion or under dispersion occurs. Over dispersion in data occurs when the variance of the dependent variable is greater than the average. This results in lower estimates than the standard errors. The generalized Poisson regression model is one of the methods used in case of over dispersion. This model is a generalization of Poisson regression. In this study, Poisson regression and generalized Poisson regression methods were used in the modelling of count data for determinants of strikes between 1984 and 2017. According to empirical results, while all explanatory variables of the Poisson regression model were significant, the unemployment rate was found to be insignificant for the generalized Poisson regression model. This result was evaluated considering the structure of the data.
Keywords: Count Data, Generalized Poisson Model, Over Dispersion, Strike Numbers
Jel Classification: C46
Suggested citation
(). An Application of the Generalized Poisson Model for Over Dispersion Data on The Number of Strikes Between 1984 and 2017. Alphanumeric Journal, 8(2), 249-260. http://dx.doi.org/10.17093/alphanumeric.670611
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2020.08.02.STAT.02
alphanumeric journal
Pages 249-260
Received: Jan. 6, 2020
Accepted: Sept. 22, 2020
Published: Dec. 31, 2020
2020 Durmuş, B., İşçi Güneri, Ö.
This is an Open Access article, licensed under Creative Commons Attribution-NonCommercial 4.0 International License.
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