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Subject Code : BUS700
Country : Australia
Assignment Task:

Part I: Regression Analysis 

The first thing to do is to collect data on some variables and, then, specify a regression model. The table below (2.3. Example 1) shows the values of the factors that influence the average demand for energy bars: average income per person, tariff on energy bars imported, number of stores selling energy bars. The dependent variable (Y) is demand for energy; and the independent/explanatory variables (X) are income (X1); Tariff rate (X2); and number of stores (X3). 

1.2 Multiple Regression Model 

Y = α + β1X1 +β2X2 +β3X3 + β4X4 + εt (1) 

Demand = ( β1*Income)+ ( β2*Tariff)+ ( β3*No of Stores) + εt 

The slope/coefficient/parameter (β1, β2 etc.) should be interpreted as the impact (effect) of the explanatory variables (variable 1, variable 2 etc.) on the dependent variable. 

1.3 Multiple Log-Linear Regression Model 

LnY = α + β1lnX1 +β2lnX2 +β3lnX3 + β4lnX4 + εt (2) 

ln (Demand) = β1* ln (Income) + β2*ln (Tariff) + β3* ln (No of Stores) + εt 

The slope/coefficient/parameter (β1, β2 etc.) should be interpreted as the percentage of the dependent variable in response to percentage change in of the explanatory variable (variable 1, variable 2 etc.) or the elasticity of the dependent variable with respect to the explanatory variable. 

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  • Posted on : May 22nd, 2019

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