Table 10.

Summary of analytical modeling.

Models and Assumption	Test	Result
Choosing Model Effect (Random or fixed)	Hausman test statistics	p-value>0.05, random effects are present
Model Assumptions 1. Autocorrelation Test	Serial correlation tests whether sequences are temporally related to each other.	p-value <0.05, serial correlations is existing so should be resolved.
2. Serial Correlation and Heteroskedasticity Correction	Arellano correction is applied to the model to solve autocorrelation and heteroskedasticity problems.	Arellano method can be used for coefficient estimation.
3. Cross-Sectional Dependence Test and Correction	The Pesaran CD test is used to test whether there is cross-section dependence	p-value is < 0.05. There is a stationarity.To resolve this problem, PCSE is used.
4. Panel Corrected Standard Errors (PCSE)	To correct stationary problem, the panel-corrected standard error method is used	p-value is < 0.05. The new coefficients of the model is determined.
Model After Assumption Corrections	$\mathit{p}\mathit{e}\mathit{r}\mathit{f}\mathit{o}\mathit{r}\mathit{m}\mathit{a}\mathit{n}\mathit{c}\mathit{e}\mathit{s}\mathit{c}\mathit{o}\mathit{r}\mathit{e}=\mathbf{50.45}+{\mathbf{3.41}*\mathit{h}\mathit{a}\mathit{p}\mathit{p}\mathit{i}\mathit{n}\mathit{e}\mathit{s}\mathit{s}\_\mathit{r}\mathit{a}\mathit{t}\mathit{e}}_{\mathit{i}\mathit{t}}$