The bell regression is used, when the response variable is in the form of counts with over dispersion. The bell regression coefficients are generally estimated using the maximum likelihood estimator (MLE). It is known that the performance of the traditional MLE is very sensitive to multicollinearity. Therefore, we propose a Bell ridge regression (BRR) as a solution to the multicollinearity problems. For the assessment of BRR, we conduct a Monte Carlo simulation study to monitor the performance of the proposed estimator where the mean squared error (MSE) is considered as an evaluation criterion. Also, two real examples are included to show the superiority of the BRR estimator.

Recently, the Bell regression model (BRM) is proposed to model a count variable. The BRM is generally preferred over the Poisson regression model to overcome the restriction that the mean is equal to the variance. The BRM is usually estimated using the maximum likelihood estimator (MLE). It is a well-known phenomenon that the MLE is very sensitive to multicollinearity. We propose a Bell Liu regression (BLR) estimator to circumvent the problem of multicollinearity associated with the BRM. Moreover, some new Liu parameters are proposed for the BLR estimator. To evaluate the performance of the proposed estimators, we conduct a Monte Carlo simulation study where the mean squared error is considered as an evaluation criterion. In addition, a real application is also included to show the superiority of the proposed method.

The ridge regression estimator (RRE) is a widely used estimation method for the multiple linear regression model when the explanatory variables are correlated. The situation becomes problematic for the RRE when the data set contains outliers in the y-direction. The use of the RRE in the presence of outliers may have some adverse effects on parameter estimates. To address this issue, the robust ridge estimators based on M-estimator are available in the literature which are less sensitive to the presence of outliers. It is a well-known fact that the selection of ridge parameter k is very crucial while using the RRE and the same phenomenon may happen in the case of robust ridge estimators. This study proposes some robust ridge estimators for the ridge parameter k. The performance of proposed estimators is evaluated with the help of the Monte Carlo simulations and a real application where the mean squared error (MSE) is considered as a performance evaluation criterion. Results show a better performance of the proposed robust ridge estimators as compared to the RRE, least square and M-estimation methods. While for modified ridge M-estimator, different ridge parameters found to be better for different conditions.

The Almon technique is a widely used estimation procedure for the distributed lag model (DLM) to encounter the problems associated with direct application of the ordinary least squares method to this model. The Almon estimator may be sensitive to outliers in the y-direction. This study is aimed to propose a robust estimator for parameter vector of the DLM when data set is contaminated with outliers. Moreover, this study proposes the robust t-tests and confidence intervals for the lag coefficients. Performance of our proposed estimator is evaluated through the Monte Carlo simulations by comparing the estimated mean squared error while the performance of t-tests and confidence intervals is evaluated using the null rejection rates and coverage, respectively. The simulation results reveal an attractive performance of the proposed methods in the presence of outliers in the y-direction.

This study investigates the relationship between quality of work-life, perceived union effectiveness and job security with union commitment among bank employees in Malaysia. This study is motivated by the decline of union density worldwide in recent times. Indeed, the National Union of Bank Employees (NUBE) has experienced a huge decline of membership, which may weaken and challenge the union to perform efficiently. Hence, this study examined the influence of quality of work-life, perceived union effectiveness and job security on union commitment. Survey questionnaires were distributed using simple random sampling to all five branches of the NUBE in Malaysia. The primary data were collected from 350 respondents and analyzed using correlation and multiple regression analysis. The findings of the study indicated that quality of work-life and perceived union effectiveness have positive and significant influences on union commitment. On the other hand, job security showed no significant influence on union commitment. Thus, representatives or the leaders in NUBE should focus more on the job insecurity of member in banking sector and should encourage the younger generation to participate in the union activities. Membership declining dilemma can be resolved by giving priorities to important issue such as job security among banking employees.