Econometrics

Multicollinearity Multicollinearity is one of the common problems in spatial regression analysis. Sometimes some or all of the explanatory variable are highly correlated in the sample data, which means that it is difficult to tell which of them is influencing the dependent variable (Barrow, 2009, p. 306). Hence, to check whether the independent variables are correlated with each other, a correlation matrix for the three indicators was measured using excel. The correlation matrix in table 2…

Reliability Table 4.5 Reliability Test Variable Cronbach’s Alpha N of Items Remark Brand Awareness 0.825 5 Reliable Brand Association 0.757 3 Reliable Perceived Quality 0.763 4 Reliable Brand Loyalty 0.890 5 Reliable After validity test, this is the result of the reliability test. The requirement to be reliable is the Cronbach’s Alpha must be more than 0.7. As seen from the table 4.5 the Cronbach’s Alpha of every variables are more than 0.7 which are remarked as reliable. To be explained, the…

This paper will study the relationship between a country’s perceived amount of corruption, and how that affects the wages of its domestic workers. The premise behind this paper is that a country that is perceived as being dishonest and corrupt would have lower wages. Corruption in government is seemingly always present in our world. This paper will try to determine if there is a correlation between a country’s perceived corruption and the monthly disposable income its workers earn with…

Variance Decomposition Analysis The variance decomposition analysis has applied to quantify the extent up to which the selected indices one influenced by each other. We can also examine the short run dynamic relationship by variance decomposition. While impulse response functions trace the effects of a shock to one endogenous variable in the VAR, variance decomposition separates the variation in an endogenous variable in to the component shocks to the VAR. Thus, the variance decomposition…

FastCat Compensation Case Phase 2: External Competitiveness Presented to Oliver Stoutner, M.B.A. HR Practicum I: Compensation and Benefits MGT 4250-01 Presented By Morgan Tullis Kimberly Bowers Ashlie Hawes Travis Stone Rachel Kipling Step 1: Recommend Strategy for Competitiveness When determining a compensation strategy for FastCat, we decided the best option would be to have a job-based structure. The reason for this is that we want to focus on our internal pay structure and measure them…

Regression-Discontinuity Design. A powerful, alternative design for causal inference that is underutilized in the health and intervention sciences is the regression discontinuity (RD) design (Thistlewaite & Campbell, 1960). In its simplest form, the RD design involves the use of a screening measure of some form that is continuous and given to all persons. A cut point or criterion is set, which determines whether individuals are assigned to an intervention condition or a comparison condition. The…

4. Empirical results In this section we discuss the empirical results of the VAR model analysis described in the previous section. In subsection 4.1 we analyse significance of coefficients in the model and apply Granger Causality test. In subsection 4.2 we present the results of impulse response functions analysis and variance decomposition. Afterwards, we turn to subsection 4.3 to test reliability of the VAR model. 4.1 Testing for significance and Granger-causality According to Wald test…

Introduction What is innovation? A using of new ideas to products, processes and other aspects of a firm activities lead to an increasing in value of the firm, benefits to customers or other enterprise, this situation is called innovation. A key issue to distinguish innovation, bringing a truly novel item that is produced by new techniques and designs into market; this item can be new to the firm, new to relevant market. Moreover, whether relevant market is domestic or global market is based…

Cohens d is usually calculated by mean difference (pooled) divided by standard deviation. Cohen (1988) defined effect sizes as "small, d = .2," "medium, d = .5," and "large, d = .8. (Borenstein, 2009) Thus, it can be safely concluded that the effect size of the intervention is small and not clinically significant. Association and causality is not proven in this case. The data set given was imported to Stata and summary statistics were used and graphs and scatter plots on Stata to visualise and…

Performance Evaluation In order to assess the model accuracy, it is necessary to use some quantitative measures of learning. In this study the Mean Squared Error (MSE) and regression analysis were used to evaluate the model performance. MSE is a useful measure of success for numeric prediction and is calculated using Eq. (1). It is worth mentioning that small values of MSE indicate better performance of the ANN model. It was found that the optimum performance of the model is at 25 neurons with…