Estimating the Number of Patents in the World Using Count Panel Data Models

Youssef, Ahmed H. and Abonazel, Mohamed R. and Ahmed, Elsayed G. (2020): Estimating the Number of Patents in the World Using Count Panel Data Models. Published in: Asian Journal of Probability and Statistics , Vol. 6, No. 4 (19 March 2020): pp. 24-33.

Abstract

In this paper, we review some estimators of count regression (Poisson and negative binomial) models in panel data modeling. These estimators based on the type of the panel data model (the model with fixed or random effects). Moreover, we study and compare the performance of these estimators based on a real dataset application. In our application, we study the effect of some economic variables on the number of patents for seventeen high-income countries in the world over the period from 2005 to 2016. The results indicate that the negative binomial model with fixed effects is the better and suitable for data, and the important (statistically significant) variables that effect on the number of patents in high-income countries are research and development (R&D) expenditures and gross domestic product (GDP) per capita.

• Item Type: MPRA Paper
• Language: English
• Keywords: Conditional maximum likelihood estimation; fixed effects model; Hausman test; negative binomial regression; Poisson regression; random effects model.
• Subjects: B - History of Economic Thought, Methodology, and Heterodox Approaches > B2 - History of Economic Thought since 1925 > B23 - Econometrics ; Quantitative and Mathematical Studies; C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling

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