Multiple Regression Analysis

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. CHAPTER 4: RESULTS AND DICUSSIONS 4.0 Introduction This chapter discusses the results of analysis on the topic of factors that affecting demand for Proton cars in Malaysia. Eviews with version 7 is used to run the data in order to do the analyses of particular test. The analysis embraces of the multiple regression analysis, bivariate correlation, standard error of coefficient (t-test), analysis of variance (F-test), p-value analysis, coefficient of determination, serial correlation ramsey RESET test, serial correlation, white’s heteroscedastic test and granger causality test. The empirical results are presented systematically as below. 4.1 Multiple Regression Analysis The multiple regression analysis is a technique of statistical for determining and modeling the relationship between dependent variable (DPC) and explanatory variables (INF, GDP and FP). It also explains how the DPC affected by INF, GDP and FP. Whereas, the multiple linear regression model is an analysis of relationship in which the effects of two or more independent variables on a single, interval scaled or ratio-scaled dependent variable are estimated at the same time (Gujariti and Porter, 2009). It is useful for demonstrating and interprets the truthful of empirical result. The double log model is chosen as empirical model in this study due to its coefficient of variation is smaller than other models (Table 6.4 in Appendix). It is linear in the logarithm of dependent and independent variables. Therefore, double log model is employed through Ordinary Least Square (OLS) method for determining the elasticity of dependent variable and independent variables. The empirical model of demand for Proton car can be represented as follows: (lnDPC) ̂=β_0+β_1 lnINF+β_2 lnG... ... middle of paper ... ...ignificant to the demand for Proton car. The evidence of the inflation was not a determinant of Proton cars sales is because of the Proton cars were sold at cheapest prices with high quality. Therefore, the Proton cars still increasing during the session of inflation due to the reason of the requirement of consumers has been achieved (Wan, 2013). For the independent variable of fuel price, it also does not granger cause the dependent variable of demand for Proton car. It means that the fuel price variable is no significant to the demand for Proton car. However, many studies discovered that the fuel price is a significant response to Proton demand. According to the Johansson and Schipper (1997), the vehicle types and distance driven were affected by the hike of fuel price. This means that the consumers still purchasing the vehicles when the fuel price increased.

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