00:01
Hello students for the given problem the regression we will write the regression equation for that we will consider the demand and supply model in the economet.
00:10
So the equation that allows us to estimate this model is 2d that is quantity demanded equal to beta 0 that is the intercept term, beta 1, beta 2 and beta 3 are the coefficients that represented the expected change in the quantity demanded associated with income, price and advertisement expenditure respective and p is the price by denote the income of consumer, a represent the advertising expenditure and epsilon is the error term.
00:44
The functional form selected is a linear relationship assuming that changes in price, income and advertisement expenditure have a linear effect on quality demand.
00:55
Next the expected signs of the coefficient are beta 1 which is negative as price increases quantity demand that is qd decreases then b2 is expected to be positive as income increases quantity demand also increases and next is beta 3 which is also expected to be positive as advertisement increases quantity demand also increases.
01:38
Next is the data requirement to carry out this we need the data of the quantity like qd quantity demanded price income which is denoted by y and advertisement expenditure for a sample of a consumer or the market.
01:57
This can be collected through survey, market research report or database.
02:20
It is important to have a sufficiently large and representative sample to ensure the reliability and generability of the result.
02:29
Next is the hypothesis test so here we have to check the price elasticity of demand that is is the coefficient beta 1 statistically signant from 0 if it is significantly negative it suggests that the price has significant importance on a quantity demand.
03:00
Next is income elasticity of demand that is is the coefficient beta 2 statistically different from 0 if beta 2 is significantly positive it indicates that the income has a significant impact on quantity demand and third one is advertising effectiveness that is is the coefficient beta 3 statistically different from 0 if beta 3 is significantly positive it suggests that the advertising expenditure has a significant impact on quantity demand.
03:49
To test this hypothesis we can use hypothesis testing technique like ptest or ftech with proper level of significance.
04:05
Next the economic testing issue in this model some potential testing issue could occur...