Slide 1Direct Methods of Demand EstimationDirect Methods of Demand EstimationEmpirical Demand FunctionsEmpirical Demand FunctionsEmpirical Demand FunctionsEmpirical Demand FunctionsExample: Grocery PricingExample: Wilpen CompanyExample: Pizza on CampusExample: Cigarette ConsumptionNonlinear Empirical Demand SpecificationSlide 137-1Chapter 7:Demand Estimation7-2Direct Methods of Demand EstimationMarket studies & experiments~Market studies attempt to hold everything constant during the study except the price of the good~Lab experiments use volunteers to simulate actual buying conditions~Field experiments observe actual behavior of consumersConsumer interviews~Range from stopping shoppers to speak with them to administering detailed questionnaires7-3Direct Methods of Demand EstimationPotential problems with consumer interviews~Selection of a representative sample, which is a sample (usually random) having characteristics that accurately reflect the population as a whole~Response bias, which is the difference between responses given by an individual to a hypothetical question and the action the individual takes when the situation actually occurs~Inability of the respondent to answer accurately7-4Empirical Demand FunctionsDemand equations derived from actual market dataUseful in making pricing & production decisions7-5Empirical Demand FunctionsIn linear form, an empirical demand function can be specified aswhere Q is quantity demanded, P is the price of the good or service, M is consumer income, PR is the price of some related good R, and N is the number of buyersRQ a bP cM dP eN= + + + +7-6Empirical Demand FunctionsIn linear form~b = Q/P~c = Q/M~d = Q/PRExpected signs of coefficients~b is expected to be negative~c is positive for normal goods; negative for inferior goods~d is positive for substitutes; negative for complementsRQ a bP cM dP eN= + + + +7-7Empirical Demand FunctionsEstimated elasticities of demand are computed asRQ a bP cM dP eN= + + + +ˆˆPE bQ=ˆˆMME cQ=ˆˆRXRPE dQ=7-8Example: Grocery Pricing7-9Example: Wilpen CompanyExample questions in notes7-10Example: Pizza on CampusSales = 149,240 – 5,174(Price) + 2.2(Enroll) - 23,269(MealPlan) - 9,267(Competitors)7-11Example: Cigarette ConsumptionA 1984 study of cigarette demand in the following logarithmic regression equation:where Q=annual cigarette consumption; P=average price of carton of cigarettes; Y=per capita income; A=total spending on cigarette advertising; w=dummy variable (w=1 after 1953 when American Cancer Association warned that smoking is linked to lung cancer, and w=0 otherwise.)a. What does the coefficient of ln P represent?b. Are cigarette purchases sensitive to advertising?c. What does the coefficient of the dummy variable w represent?wAYPQ 1.0ln8.0ln09.0ln29.055.2ln 7-12To estimate a log-linear demand function, covert to logarithmsIn this form, elasticities are constantNonlinear Empirical Demand SpecificationWhen demand is specified in log-linear form, the demand function can be written asM XRˆ ˆˆ ˆ ˆˆE b E c E d= = =b c d eRQ aP M P N=RlnQ ln a b ln P c ln M d ln P e ln N= + + + +7-13Excel Model