Demand estimation allows a company to measure the amount of demand a business should produce for their product or service. An estimate can give the management team a range on production levels and help to make important company decisions. In reference to Option 1, the demand equation is for the brand product that uses data from 26 supermarkets around the country for the month of April. Management asked employees to compute the elasticity’s for each independent variable.
As a maker of a leading brand of low-calorie, frozen microwavable food it is important to compute elasticity’s for quantity demanded, price of the product, price of leading competitors, per capita income of the metropolitan statistical area, and monthly advertising expenditures. The elasticity’s of these variables are able to establish short-term and long-term pricing strategies for the company. Price is often the single most important factor in a customer’s decision when purchasing a product. It is necessary to determine how price will affect the demand and supply of the product. Moreover, it is essential to conclude what other factors may play a role in the shifts of demand and supply (McGuigan, Moyer and Harris, 2014).
Below is a regression equation and the calculations for each independent variable.
QD= -5200 - 42P + 20Px +5.2I + .20A + .25M
(2.002) (17.5) (6.2) (2.5) (0.09) (0.21)
R2 = 0.55 n = 26 F = 4.88
The elasticity’s for each independent variable are as follows:
Q = Quantity demanded of 3-pack units
P (in cents) = Price of the product = 500 cents per 3-pack unit
PX (in cents) = Price of leading competitor’s product = 600 cents per 3-pack unit
I (in dollars) = Per capita income of the standard metropolitan statistical area (SMSA) in which the supermarkets are located = $5,500
A (in dollars) = Monthly advertising expenditures = $10,000
M = Number of microwave ovens sold in the SMSA in which the supermarkets are located = 5,000
P= 500, PX=600, I=5,500, A=10,000, M=5,000
QD= -5200 -42(500) +20(600) +5.2(5500) +.20(10000) +.25(5000) =
QD = -5200-21000+12000+28600+2000+1250= 17,650
The elasticity for each independent variable are:
Price Elasticity (Ep) = (dQ/dP) (P/QD)
EP= (-42) (500/17650) = -1.19
Advertising Elasticity (EA) = EA = (dQ/dP) (A/QD)
EA= (.20) (10000/17650) = .11
Income Elasticity (EI) = EI = (dQ/dP) (I/QD)
EI= (5.2) (5500/17650) =1.62
Microwave Elasticity = EM = (dQ/dP) (M/QD)
EM= (.25) (5000/17650) = .07
Competitive Price Elasticity = EPx = (dQ/dP) (PX/QD)
EPx= (20) (600/17650) =.68
Supply change or quantity demand are measured by elasticity in any variables that influence the demand and supply functions. Price elasticity is a ratio of the percentage change in the quantity demand to the percentage change in the price, assuming that all other factors manipulating the demand remain unchanged (McGuigan, Moyer and Harris, 2014).
After calculating the elasticity’s for each variable, in terms of long-term and short term-pricing can be brainstormed. The price elasticity is -1.19. The demand for goods and services are affected by price when the value is greater than 1 and is insensitive to price when the value is less than 1(Investopedia, 2014). With the price elasticity being -1.19, what that represents is that as price goes up by some percent change, and then the quantity goes down by that percent change multiplied by -1.19. As a result, the product would be considered elastic. When the demand of a good is elastic, a drop in price will increase sales and plays a critical role in long-term and short-term pricing strategies. Demand elasticity can assist in forecasting long-term profit. A company can set prices based on desired levels of profits they wish to obtain over a period of time. Demand elasticity enables a company to foresee the percentages in which the quantity of the product will increase or decrease