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Microeconomics
- 1. Demand Analysis And Forecasting Of Tea Industry Using Multiple Regression Model ADITYA KANDOI (10P064) ANIRVAN SEN (10P067) ESHA SHARMA (10P075) KARTHIK V (10P083) SAMBHAV AHUJA (10P107) PUNEET BINDLISH (FPM)
- 3. Snapshot
- 8. I) MODEL SPECIFICATION Too many explanatory variables leads to econometric difficulties: a) Less Degree of Freedom b) Multicollinearity
- 9. II) DATA COLLECTION a) Prices of Tea
- 10. b) No. of Customers
- 11. c) Price of Sugar (Complementary Product)
- 12. d) Consumer Income
- 14. DEMAND EQUATION Qx = c + c1*Price + c2*No_customers + c3*Price_sugar + c4*Price_coffee + c5*Income + e C’s e Qx
- 21. Demand Forecasting Using Eview5, a graph is drawn for forecasting the demand of tea.
- 22. Outlook
- 24. On the contrary, prices continue to harden
- 25. Reasons ------------------Increase in consumption Demand for Restocking Excessive Rains in some parts of India
- 26. Pricing Strategies Important Strategic issue related to product positioning It affects other elements such as product features, channel decisions & promotions How to determine it
- 27. Methodology
- 29. Product Positioning
- 30. Tradeoff between quality & price
- 32. Price Elasticity of Demand is determined
- 34. Variable Cost
- 35. Fixed Cost
- 37. Neither too high
- 38. Nor too low
- 39. Legal Standpoint
- 40. Price Control – price ceiling
- 41. Too Low –may be ‘predatory’
- 52. Majorly sold in loose packets
- 53. Prices differ with quality & demand
- 54. Price is largely determined by the market forces, rather than the seller himself
- 56. Brooke Bond, Lipton of HUL
- 57. Tata Tea, Tata Agni of Tata Global Beverages
- 58. Prices differ with brand & its positioning, target segment & quality
- 62. THANK YOU