Introduction
The sign of a successful firm is the constant endeavor that it makes to expand and enhance. To remain profitable and expand its operations a firm has to be well informed about the market conditions. It is important to collect and analyze market information to take strategic decisions. The firm utilizes information on the demand conditions, the activities of the close competitors, government policies, technological and product innovations and such others to frame its policies from time to time. The firm also uses the information to estimate future costs and benefits of the long term changes which helps it in taking long-term policy decisions.
Demand Analysis
In our present analysis we demonstrate how a firm uses a market survey information and knowledge about its own production technology to take important decisions regarding pricing, supply, advertisement expenses etc . The regression analysis of the survey has been provided to us which we use to make mathematical analysis and interpret the results to suggest strategies to be taken by the firm.
The firm we are discussing here is the producer of a low-calories frozen food. The survey on the demand for the low-calorie widgets has been conducted in 26 supermarkets. We have with us two sets of regression equations. Before we start our analysis we have to decide which regression result we are going to base our decision making strategy on. The two sets of regression equations are given below:
Option 1Note: The following is a regression equation. Standard errors are in parentheses for the demand for widgets.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
Q = Quantity demanded of 3-pack unitsP (in cents) = Price of the product = 500 cents per 3-pack unitPX (in cents) = Price of leading competitor’s product = 600 cents per 3-pack unitI (in dollars) = Per capita income of the standard metropolitan statistical area(SMSA) in which the supermarkets are located = $5,500A (in dollars) = Monthly advertising expenditures = $10,000M = Number of microwave ovens sold in the SMSA in which thesupermarkets are located = 5,000
Option 2Note: The following is a regression equation. Standard errors are in parentheses for the demand for widgets.
QD = -2,000 - 100P + 15A + 25PX + 10I(5,234) (2.29) (525) (1.75) (1.5)R2 = 0.85 n = 120 F = 35.25
Q = Quantity demanded of 3-pack unitsP (in cents) = Price of the product = 200 cents per 3-pack unitPX (in cents) = Price of leading competitor’s product = 300 cents per 3-pack unitI (in dollars) = Per capita income of the standard metropolitan statistical area(SMSA) in which the supermarkets are located = $5,000A (in dollars) = Monthly advertising expenditures = $640
Studying the two regression models we see that in the first equation in Option 1 the value of R2 is 0.55 whereas in Option 2 the value of R2 is 0.85> since Option 2 has a higher value of R2 we can say that option 2 has a higher predictability. In addition to that option 2 has a higher F value so the coefficients of the independent variables have greater significance in option 2 . Also the number of observations taken in option two is much higher compared to option 1. So we base our analysis on the second regression result.
Calculation of Elasticities
As a first step let us calculate the elasticities of demand with respect to the four independent variables of the regression equation. The demand for the good can be found by putting the values of the independent variables in the demand equation:
QD = -2000 -100*200 + 15*640 + 25*300 + 10*5000 = 45100
Elasticity of demand with respect to Price
Ep = dq/dp*p/q = -100*200/45100 = 0.44
Elasticity of demand with respect to Advertisement expenditure
Ea = dq/dA*A/q = 15*640/45100 = 0.21
Elasticity of demand with respect to Price of the close substitute
Epx = dq/dPX*PX/q = 25*300/45100 = 0.17
Elasticity of demand with respect to Income of the consumers
EY = dq/dY*Y/q = 10*5000/45100 = 1.11
Interpretation of Elasticities
The value of the elasticities computed above has important implications for the firm’s operations.
The price elasticity of demand for the frozen food is 0.44 which is less than 1 so we can say that the demand is inelastic with respect to own price of the product. A rise in price will lead to less than proportionate fall in demand and a fall in price will not lead to only a small rise in demand.
The elasticity with respect to advertisement expenditure is also quite low at 0.21. This low value implies that advertisement expenditure have little impact on the demand. So advertisement does not seem to be a a fruitful strategy to be adopted by the firm.
The price of the close substitute of the firm’s product has little influence on the demand for the widgets. This is clear from the cross price elasticity of demand which is 0.17. The demand is inelastic to the change in price of the close competitor’s product. This information also tells us that the market for the product possesses monopoly characteristics.
The good is income elastic which is clear from the value of income elasticity which is 1.11. Change in income produces positive and significantly large change in income.
Should The firm Cut Price?
Since the demand for the product is price inelastic, it is not advisable for the firm to adopt a strategy of price cutting. A fall in the price will only lead to a fall in the revenue earned by the firm. So the firm should not reduce the price to increase market share more so because the demand is unaffected by the competitor’s pricing decision.
Demand Curve and Supply Curve
Now let us find the equilibrium price and quantity. First let us construct the demand function from the regression equation .
QD = -2000 -100P+ 15*640 + 25*300 + 10*5000 = 65100-100P
The demand as a function of price is given as:
QD = 65100 -100P
The demand curve for this function is represented below:
We have also been provided with the supply function for the product as :
Q = -7909.89 + 79.0989P
The supply curve corresponding to this function is represented below:
Mathematically we can find the equilibrium price and quantity as:
65100 -100P = -7909.89 + 79.0989P
Price =$ 407.65
Quantity = 24335 units.
Conclusion
There are a number of factors that can cause a shift in the demand curve. Three of them, namely income, price of substitute product and advertisement expenditure. All three of them have a positive impact on demand. An increase in these factors cause a rightward shift in the demand curve. Apart from these three factors, there are other factors which can influence demand. A faster lifestyle will increase the demand for this ready to eat reducing cooking time. Increase in health awareness will also cause a rightward shift of demand as the good is low-calories food product.
The good is a food item so raw materials like spices, salt, poultry products, fish, meat and vegetables are used in its production. Changes in the prices of such agricultural products will shift the supply curve. Change in wages will also affect supply as food items usually involve labor intensive techniques.
References
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McGuigan, j. R., Moyer, R. C., & Harris, F. H. (2014). Managerial economics: applications, strategies and tactics. Stanford CT: Cengage Learning.
Pindyck, R., & Rubinfield, D. (2009). Microeconomics (7th ed.). Prentice Hall.
Woolridge, J. M. (2009). Econometrics. Cengage Learning.
