Discussion Questions

1. Analyze the estimated demand function by using the estimated coefficients to discuss the impact of each of the explanatory variables, P, CP, M, and PE, on the quantity of Maa mustard oil demanded. In discussing the impact, consider a one unit change in each variable while holding the others constant.

Overall Purpose

A manager or owner of a firm should understand the economic environment in which his / her firm operates. This knowledge is essential when deciding the firms strategic move towards profit maximization. While the consumers characteristics, revealed in the demand function, motivate the firms pricing behavior, the decisions of competitors may also influence the firms pricing strategy. In a price-competitive market environment, the pricing decisions of competitors becomes a crucial factor in the firms pricing behavior. In this case study, we explore and discuss the pricing dilemma faced by the manager of Hind Oil Industries, a producer (and seller) in Asansols Mustard Oil Market. Focusing on maximizing total revenue, this discussion uses a real-world example to explore and understand optimal pricing.

Description of the Report

This analysis report (3 to 5 pages) describes the demand for Hind Oil Industries product and discusses the possible market outcomes in different scenarios (which are characterized by competitors pricing decisions) Hind Oil Industries faced in 2015. The discussion questions below, which guides the analysis, should be clearly answered in the report.

Additional Case Information

Consider that Abhishek Khemka was able to model and estimate the demand function that Hind Oil Industries faces for its mustard oil. As a firm with some market power over the price it charges, the factors he considered are specific to his product. Using the data from April 2011 to September 2015, the estimated demand function is: QD = 3934.25 121.15P + 113.49CP 0.31M + 7.99PE + D where QD is the quantity of Maa mustard oil demanded, measured in kilograms.1 The explanatory (independent) variables are P, Hind Oil Industries own price per kilogram of Maa Mustard Oil (measured in Indian rupees); CP, the average price per kilogram of competitors mustard oil (measured in Indian rupees); M, the income level of consumers (measured in Indian rupees); and PE, promotional expenditure (measured in Indian rupees) of Hind Oil Industries.2 D is a set of 11 seasonal dummy variables with March being the base (excluded) month. The estimated values for each month are presented below.3

1 In this case, we assume that the quantity sold is the quantity demanded. In other words, we are assuming that Hind Oil Industries can meet the total quantity demanded each month for its product.

2 The monthly per capita Net State Domestic Product of West Bengal is used as a proxy for the income level of consumers. Additionally, one can consider that any promotional expenditure incurred by Hind Oil Industries is geared towards influencing consumer tastes and preferences in a positive manner.

3 A set of 12 dummy variables are created. Each variable takes the value of 1 for a particular month, and 0 for all other months. For example, using the estimated coefficients from D, in the month of June the value of D is 793.62.

1

ECO 9730 Firms in a Global Economy

Month D

Month D

January

392.61

August

648.43

February

16.89

September

53.66

April

655.01

October

283.72

May June July

459.81 793.62 577.63

November

565.55

December

794.68

The coefficient of determination, R2 from the estimation suggests that 83% of the variation in the sales of Maa mustard oil is explained by the model.

what info is needed? there is a HBR article that this question references