Quiz 5: Demand Estimation and Forecasting

Business

Regression analysis estimates the relationship between the one dependent variable and one or more independent variable. This means, regression analysis studies the relationship between variables either positively or negatively. Regression equation is as follows: img Here, img In the problem, determinants of demand for furniture are given as follow: img Regression equation is as follows: img How these determinants determined the demand for furniture • Price of the furniture: there is an inverse relationship between price of the furniture and demand for furniture. • Tastes and preferences: there is a positive relationship between tastes and preferences and demand for the product. • Price of related goods: if the goods are substitutes, there is a positive relationship between the price of one commodity and demand for another commodity. • Income of the consumer: there is positive relationship between income of the consumer and demand for furniture, because furniture is a luxury good. • Cost of availability of credit: there is an inverse relationship between cost of the product and demand for furniture. • Number of consumer: there is a positive relationship between number of buyers and demand for furniture. • Future expectations: there is a positive relationship between prices of future expectation for the furniture and demand for furniture. Thus, a change in independent variable will affect the dependent variable either positively or negatively.

The sales for the company have grown from $500,000 five years ago to $1,050,150 this year. The compound growth rate can be calculated by using the following formula: img ……(1) Where, E = Last year's amount; B = First years amount; I = Growth rate; and n = Number of years. Substituting the values in equation (1) we get: img img img So, the compounded growth rate is 16%. If we expect your sales to grow at a rate of 10 percent for the next five years, than the sales after five years from now can be calculated as follows: img Therefore, sales after 5 years would be $1,691,277.

(a) The scatter diagram based on the 14 month data related to price and quantity sold of a basic automobile model is given below: img The demand equation for the given set of data can be calculated by using MS-Excel. The equation is given below: img …… (1) Where Q is the quantity demand and P is the Price. The regression model suggests that there is a negative relationship between price and quantity sold. If the discount is increase than the sales of the automobile is likely to increase. So, discounting is desirable as per the data available. (b) The demand of automobile will depend on a number of other factors which need to be considered in the regression model. The other factors are income of the consumer, price of other automobile models, price of fuel, taste and preference, future expectation. It will be difficult to finding an exact variable that can be used to measure taste and preference. The other factors can be measured relatively easily and can be used in the regression model.