scholarly journals The performance of count panel data estimators: a simulation study and application to patents in Arab countries

2021 ◽  
Keyword(s):  
Panel Data ◽  
Simulation Study ◽  
Arab Countries ◽  
Count Panel Data

Board diversity and corporate social responsibility in Jordan

2016 ◽  
Vol 14 (2) ◽  
pp. 279-298 ◽  
Author(s):  
Abdul Hadi Ibrahim ◽  
Mustafa Mohd Hanefah
Keyword(s):  
Corporate Social Responsibility ◽  
Data Analysis ◽  
Panel Data ◽  
Social Responsibility ◽  
Panel Data Analysis ◽  
Arab Countries ◽  
Board Diversity ◽  
Content Type ◽  
Csr Disclosure ◽  
Corporate Social

Purpose This study aims to investigate the impact of board diversity characteristics, namely, independence, gender, age and nationality of directors on the level of corporate social responsibility (CSR) disclosures. Design/methodology/approach Content analysis was used to determine CSR disclosure. This study used panel data analysis to investigate the influence of board diversity characteristics on CSR disclosures. Findings Panel data analysis show that the level of CSR disclosure has increased over the period of study. Results also reveal a positive and significant association between the level of CSR disclosure and board diversity variables. Research limitations/implications This study examined only companies listed on Amman Stock Exchange. Therefore, the generalisation of the results might be limited to the listed companies only. Practical implications Findings are relevant to policymakers, professional organisations and practitioners in Jordan and in other Arab countries. Social implications The role of women in the boardroom is important to ensure more CSR activities by the listed companies. Jordan being a Muslim country should take the initiative to introduce laws to increase the number of women to the board. Originality/value This study offers significant contributions to existing CSR literature in Jordan and in other Arab countries by introducing female directors. Findings are important to policymakers. They should implement quotas for women in the boardroom, and adopting such a policy will increase the participation of women in the decision-making process of the companies and reduce gender bias.

scholarly journals A Simple Approach to Fit the Beta-binomial Model

2005 ◽  
Vol 5 (3) ◽  
pp. 385-394 ◽  
Author(s):  
Paulo Guimarães
Keyword(s):  
Panel Data ◽  
Binomial Distribution ◽  
Regression Models ◽  
Multinomial Distribution ◽  
Simple Approach ◽  
Binomial Model ◽  
Multivariate Generalization ◽  
Count Panel Data

In this paper, I show how to estimate the parameters of the beta-binomial distribution and its multivariate generalization, the Dirichlet-multinomial distribution. This approach involves no additional programming, as it relies on an existing Stata command used for overdispersed count panel data. Including covariates to allow for regression models based in these distributions is straightforward.

MODELLING AND ESTIMATING INDIVIDUAL AND FIRM EFFECTS WITH COUNT PANEL DATA

2018 ◽  
Vol 48 (3) ◽  
pp. 1049-1078 ◽  
Author(s):  
Jean-François Angers ◽  
Denise Desjardins ◽  
Georges Dionne ◽  
François Guertin
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Parametric Model ◽  
Random Effects Model ◽  
Road Accidents ◽  
Fixed Effects Model ◽  
Insurance Pricing ◽  
Count Panel Data ◽  
Unobservable Factors

AbstractWe propose a new parametric model for the modelling and estimation of event distributions for individuals in different firms. The analysis uses panel data and takes into account individual and firm effects in a non-linear model. Non-observable factors are treated as random effects. In our application, the distribution of accidents is affected by observable and non-observable factors from vehicles, drivers and fleets of vehicles. Observable and unobservable factors are significant to explain road accidents, which mean that insurance pricing should take into account all these factors. A fixed effects model is also estimated to test the consistency of the random effects model.

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