Question

The empirical demand function can be used in conjunction with historical data to predict pricing and sales of specific products. Regression analysis is extremely helpful in this forecasting. In your opinion what challenges exist when developing these studies? Please use specific examples

Answer 1

Answer: Such, to 1. Music freiche forecasting techniques could have following ultiplicative seasonality (cyclical variation) Example ample - Pind Time Home Deunad 150 Ql+ Quater 1 140 Q2 Qg Quater 2 Quatee 3 Q: 2018 9, 2018 Q₂ 2018 04 2018 Q1 2019 Q2.2019 Os 2019 64 2.019 127 180 130 136 19.0 159 Denaud 159 110 149 153 100t 04.pon Oport 177 ( 1) l'As the graph of the data shows that there is huge reasonately such a case there is going to be a seasonal bear if appropriate DUMMY VARIABLE is not added to the model Or we need to deseasonalise the data ley taking average for the demand in which ca has reasonality

(problem with The plot Referentative Data :- an consumer intervin) on of a sample that is selection cons not a represes at a representative of the whole for example, one population hence pe, one picked up a date in which the entrice of and represents only a specific income group precaeted the future sales would not la correctly foreca the fulture 3. Response Bias: This is the difference to the difference respondants and in their the responses collected actual behavian luon Team in the market. 4. Problem with Time sus date: It is a linear date and takes into consideration of anly are of the valuation where as fa demand consideration one has to keep looking for the change in prices and flys sincentaneously.