Lecture notes
Managerial Economics I Revision / Lecture Notes
- Module
- Managerial Economics I
- Institution
- The University Of Manchester (UOM)
Full and Complete Revision / Lecture notes for Managerial Economics I. ECON20000
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Sunday, 22 January 2017Managerial Economics Revision Notes
Estimation of Demand
Statistical Estimation of Demand Functions
Linear Regression Models / Nonlinear Regression Models
• How to estimate demand
• What kind of research is available
• How to get data
• How to analyse the data
• How to interpret the results
How to find the Demand Function
What kind of resource/information is available to the manager?
- Using Marketing Research
• Consumer Surveys
- Questioning a relevant and representative group of people (consumers,
managers, brokers, etc..)
• Advantages:
- Get a feeling for future business (+/-)
- Willingness to invest / credit availability
- Propensity to buy products
• Disadvantages:
- Lack of accurate answers
- Sample of people might not be representative
- Hypothetical answers
- Legal barriers (privacy concerns etc.)
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, Sunday, 22 January 2017
• Consumer Clinics
- Experiments in the laboratory, where individuals are given money to spend on
specific items
• Market Experiments
- Experiments are conducted in (a part of) the real market
• Advantage
- Observe behaviour in the real market
- High likelihood of reliable observations
• Problems
- Cost
- Scale on which it is conducted (reliability)
- Risks a loss in customers by changing ads
• Approach is useful in estimating:
- price/cross elasticity
- effect of advertising campaign
- acceptance of new products
- All aim at factors like: willingness to pay, sensitivity to price changes awareness of
alternatives, impact of advertising,…
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, Sunday, 22 January 2017
Statistical Estimation
Econometric tools are available:
• Statistical test of economic relationships by empirical evidence
• Important also for estimating cost and production, and other forecasts
• Play a specific role in demand estimation
Techniques we focus on:
• Regression
• Correlation
Identification of Variables
The general model:
Y = Y (X1, X2, X3, X4,..)
• Dependent variable (Y = demand)
• Independent variables (X1 = price, ... )
- Price of good in question, Price of substitutes (own, competing), Population size,
Income (per capita), Marketing expenditures
Independent Variables
• Managers must know/learn as much as possible about factors that may influence
demand.
• Exclusion of variables may lead to heavy distorted predictions (hence decisions are
negatively affected).
• Cost for obtaining data may be too high (models with few variables, 4-6).
- Hence a tradeoff between precision and expenditures is required.
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