Demand Estimation
Introduction
Low-caloric foods which have already been frozen and can be warmed in a microwave have over the recent past continued to receive wide acceptance by consumers prompting many big food manufacturing companies to embark on expansion strategies both in the production potential and market share (Wall & Griffiths, 2012). The economic aspect in the demand estimation of the firm’s food for managerial and marketing decisions is to be covered in this paper. The basis of the assignment is on focused on two regression models or equations highlighting two marketing options, and the data used in the demand estimations is for the month of April from 26 supermarkets that sell the firm’s foods. Thus, for effective marketing decisions to be made it becomes inevitable to adopt a multifaceted approach by considering a wide range of factors that have potential to influence the demand and supply of the firm’s foods (Frank, 2013; Samuelson & Marks, 2013).
Calculations
In demand estimation, it is very imperative to apply analysis of demand in managerial economics to achieve the biggest market share possible (Sullivan & Sheffrin, 2013; McGuigan, Moyer & Harris, 2014; Metcalf, 2015). The estimation of demand of either a single a multiple products in the market are very essential to provide a firm’s management as well as marketers with necessary market insights (Frank, 2013; Metcalf, 2015). This is a very important step in devising and planning for an appropriate marketing strategy based on informed decisions that are data based as evidence (Frank, 2013; Sullivan & Sheffrin, 2013).
For the first option, the regression equations or model used in the calculation of the firm’s demand elasticities as well as the allowable standard errors and regression statistics are shown below:
The independent variables are composed of:
Solution:
The demand elasticities obtained through calculations for option 1 that were carried out are show in table 1 below.
Table 1: Option 1 Elasticities
For the second option, the regression equations or model used in the calculation of the firm’s demand elasticities as well as the allowable standard errors and regression statistics are shown below:
The independent variables are composed of:
Solution:
The demand elasticities obtained through calculations for option 2 that were carried out are show in table 2 below.
Table 2: Option 2 Elasticities
Elasticity Implications
The implications of elasticity have far reaching effect on the quantities demanded as well as supplied in a market (Pettinger, 2012). According to Samuelson and Marks (2013), reiterate that this is because it provides important insights on demand estimation and making vital marketing decisions on whether the firm should embrace a discounting strategy or increasing or decreasing prices for its foods for increased generation of revenue. Elasticity implications are a true manifestations of the law of demand to determine market equilibrium, whereby this phenomenon concurs with the law of demand and market dynamics, which outlines that demand is inversely related to prices whereby the former increases with a decrease in the latter and vice versa (Wall & Griffiths, 2012; Samuelson & Marks, 2013). According to Frank (2013), calculation of elasticitiees allows the determination of the nature of demand in the market whether it is elastic or inelastic and also if it is absolute or in absolute value so that the sensitivity of consumers to prices can be established for an appropriate pricing strategy to be devised. The calculated elasticity values are shown in the table:
Table 3: Option 1 Elasticity Values’ Classification
Table 4: Option 2 Elasticity Values’ Classification
Pricing Recommendations
The firm’s price demand elasticity obtained through calculations is a 1.19 absolute value, which means that it is elastic. According to Wall and Griffiths (2012), this elasticity implies that price discounting is definitely that more appropriate marketing strategy that the firm can adopt. This is mainly because, this strategy has a very high potential to optimize market expansion and increase sales significantly (Frank, 2013). This means that, by the firm reducing the prices of its foods, a significant influence of the foods supply and demand as well as sales levels. As a result, income elasticities of 1.62 and 1.11 are obtained through demand estimation calculation for both option 1 and option 2 respectively, which means that both are elastic an indication that the is a significant influence of the quantities demanded by consumers based on per capita income (Wall & Griffiths, 2012; Metcalf, 2014). Therefore, in a market where consumers’ sensitivity to changes in prices is high because of their per capita income provides the company with an effective economic condition to embrace reduction of prices or provision of discounts in order to increase sales (Pettinger, 2012; Metcalf, 2015).
The Demand Curve
The firm’s calculated demand and supply based on the changing factor, that is, the price as well as the plotted firm’s demand and supply curves assuming that, apart from prices all other factors that affect the foods’ demand remained constant. Therefore, firm’s food prices utilized in plotting demanded and supplied food quantities of the firm are increasing at a fixed interval of 100 cents between 100 and 600.
Table 5: The Firm’s Demand and Supply Calculations
Figure 1: The Firm’s Demand and Supply Curve
Equilibrium Price and Quantity
According to Wall and Griffiths (2012), the determinant of market equilibrium is the relationship between the market demand and market supply. For instance, the market equilibrium for the food prices of the firm foods obtained through calculations is equivalent to the equations quantity supplied () and for quantity demanded (
). Therefore, the intersection at where the two curves meet is referred to as point P, and which at the market equilibrium price value of 384.48 (Frank, 2013; Metcalf, 2015). The most significant factors that can cause a shift in demand as well as supply curves are prices and income per capita within the region considered for statistical analysis of market dynamics (Wall & Griffiths, 2012). For instance, when the prices of the firm’s foods is decreased by 300 cents from 500 cents to 200 cents, an inelastic demand of 0.44 in demand elasticity results leading to an increased supply of demanded units of the firm’s foods by 284,400. According to Wall and Griffiths (2012), this phenomenon concurs with the law of demand and market dynamics, which outlines that demand is inversely related to prices whereby the former increases with a decrease in the latter and vice versa. Alternatively, there is a likely for the supply and demand curves of firm’s foods to be shifted by consumer income whereby decreasing consumer income levels, especially during a recession leads to an outright decrease in demand (Pettinger, 2012; Wall & Griffiths, 2012).
In conclusion, it is evidently clear that demand regression equation calculations are an ideal technique for the estimation of demand in the market for food products and in particular low-calorie and microwavable foods. Therefore, these calculations and modeling as well as demand plots can be can be a very important way through which informed marketing decisions can be made. However, it is also imperative to consider other factors that inform purchasing decisions in order to come up with an appropriate marketing strategy for the expansion of the firm’s market share as well as continue gaining more market competitiveness.
References
Frank, R. (2013). Microeconomics and Behavior, (7th ed.). New York, NY: McGraw-Hill.
McGuigan, B. P., Moyer, R. C., & Harris, F. H. (2014). Managerial economics: Applications, strategies and tactics, (13th ed.). Stamford, CT: Cengage Learning.
Metcalf, T. (2015). How to Calculate Demand Elasticity with Sales & Price. Retrieved October 26, 2016, from6
Pettinger, T. (2012).Understanding Elasticity.
Samuelson, W. & Marks, S. (2013). Managerial Economics, (4th ed.). Hoboken, NJ: John Wiley & Sons Inc.
Sullivan, A. & Sheffrin, S. M. (2013). Economics: Principles in Action. Upper Saddle River, NJ: Pearson Prentice Hall.
Wall, S. & Griffiths, A. (2012).Economics for Business and Management. New York, NY: Financial Times Prentice Hall.
