Introduction
A firm has to make constant endeavor to stay profitable in the market in the long term. It has to be well informed about the market structure, demand pattern, consumer choices etc. It also has to constantly carry on research and development to innovate new products to maintain a high market power. In this analysis we demonstrate how a firm utilizes market survey information to frame its pricing policy and also decide on the quantity to be supplied. We also get important ideas about advertisement policies of the firm. We consider a firm that produces low-calories frozen food. The market survey data is provided to us. We analyze the data to get meaningful results.
Demand Analysis
Our objective in this study is to show how the firm utilizes market survey data to make important analysis about demand pattern and consumer choice and make pricing decisions accordingly. To frame the pricing and sales promotion strategies demand analysis is of utmost importance to the firm.
We have with us the market survey results from 26 super markets. The result has been presented as two separate regression equations. Our first task would be to choose the appropriate regression equation on which we can base our analysis. The two regression results have been presented below as option 1 and option 2:
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
Calculation of Elasticities
The regression equation that we are considering here has four independent variables that affect the dependent variable that is quantity demanded. To find how sensitive the demand is to the four independent variables we are going to calculate the elasticities of demand with respect to each of the four independent variables as given below:
First let us calculate the total demand at the given values of the independent variables:
QD = -2000 -100*200 + 15*640 + 25*300 + 10*5000 = 45100
The elasticities have been calculated below:
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
We know that elasticity is the degree of responsiveness of demand to the change in the factor of demand . Based on this notion of elasticity let us interpret the values of the elasticities and analyze the implication of the value of the elasticity for the firm.
First of all we see that the price elasticity is quite low at 0.44. Since this is less than 1 we say that the demand is price inelastic. A 1% change in price produces only 0.44% change in demand. So price does not affect demand to a great extent. There is significant amount of brand loyalty among the consumers and they stick on to the product even when the price increases.
The elasticity with respect to advertisement expenditure is ony 0.21. This is quite low suggesting that increased advertisement expenditure tends to produce little effect on the demand for the product. So the firm should not invest much on advertisement as the advertisement campaigns have been proven to be futile as they cannot increase demand significantly. The firm should make the advertisement more effective or stop its advertisement campaigns.
The elasticity with respect to the close substitute is 0.17. That means the demand is inelastic to the changes in the price of the close competitor’s product. As the price of the close substitute falls the demand for our firm’s product does not fall to any great extent. That means the product of our firm possesses some unique characteristics that appeals to the consumer’s tastes and preferences and so even if a substitute is available at a lower price the consumers stick on to the product of our firm. In this sense the firm’s product actually has no close substitute.
Finally we find that the demand for the product is income elastic. The elasticity is 1.11 which is greater than 1. An increase in income produces a more than proportionate increase in demand. It is a normal good. So as the per capita income increases the demand for the product will increase. The demand will fall during recession when the income falls.
Should the Firm Cut the Price?
We have observed in the previous section that the demand for the product is price inelastic. So a rise in price will lead to a marginal fall in income and thus lead to increase in revenue for the firm. On the other hand a fall in price will lead to a rise in demand to a lower proportion than the fall in price leading to a fall in the revenue earned by the firm. So it is not advisable to reduce the price of the product as that will lead to revenue loss for the firm. In fact the firm should raise the price to increase its earnings.
Demand Curve and Supply Curve
QD = -2000 -100P+ 15*640 + 25*300 + 10*5000 = 65100-100P
The demand function obtained from the regression result is:
QD = 65100 -100P
The corresponding demand curve is shown below:
The supply function as given to us is :
Q = -7909.89 + 79.0989P
The corresponding supply curve is:
The intersection of the demand and supply curve gives us the equilibrium price and quantity as shown below:
The above diagram shows that the equilibrium price is around $400 and quantity is above 20000 units but below 30000 units.
Mathematically we can find the equilibrium price and quantity by equating the demand and supply functions:
65100 -100P = -7909.89 + 79.0989P
Price =$ 407.65
Quantity = 24335 units.
Conclusion
A change in the price of the product leads to a movement along the curve. A change in factor other than the price will lead to a shift in the demand curve. In our analysis three factors, namely income, advertisement expenditure and price of the close competitor’s product will lead to a shift in the demand curve. Apart from these factors a number of other factors will lead to a shift in demand. For example a faster lifestyle will increase the demand for frozen food that requires very little cooking time causing a rightward shift in the demand curve. On the other hand a shift in preference towards fresh food will lead to a leftward shift in the demand curve as demand decreases. An increase in health consciousness will cause a rightward shift in the demand curve as it is a low-calorie food.
Supply will be affected by the prices of inputs and also the production technique. An improvement in the production technique will lead to a rightward shift in the supply curve as supply increases. If there is a crop failure due to bad weather leading to the rise in the prices of farm products the supply curve will shift to the left as the firm uses agricultural raw materials to product the food product.
References
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Pindyck, R., & Rubinfield, D. (2009). Microeconomics (7th ed.). Prentice Hall.
Woolridge, J. M. (2009). Econometrics. Cengage Learning.
