CHAP4 - Empirical Price Analysis An economist is a trained...

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1 Chapter 4 Empirical Price Analysis An economist is a trained professional paid to guess wrong about the economy. An econometrician is a trained professional paid to use computers to guess wrong about the economy. Why is empirical price analysis useful? Aid decision-makers 1. Knowledge of elasticities important, e.g.: –estimate costs/benefits of a policy option, e.g., taxes and subsidies. Recall that tax incidence is determined by the relative size of price elasticities of D and S –help business pricing decisions Recall that total revenue depends on price elasticities of D; price discrimination –determine impacts of S and D shifts on price Income elasticity, advertising elasticity, etc. 2. Better estimates of future price important for optimal decision making, e.g.: in May, E(Oct corn price) = $1.50, actual Oct price = $3.40 => too little corn planted in May w/forecast, E(Oct corn price) =$2.90 more corn planted in May 3. Price analysis models cheaper than market experimentation Examples: –Simulate price impacts of alternative advertising scenarios using S-D model –Simulate price impacts of reducing supply
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2 Chapter 4 Objectives: 1. Examine quantitative methods in price analysis for policy and business decisions (focusing on perfection competition) 2. Present general steps in quantitative analysis 3. Provide overview of econometric price analysis Supply functions Demand functions 4. Explain “deflating” 5. Two empirical examples Basics of Regression Model: Y = b 0 + b 1 X 1 + b 2 X 2 +...+ b k X k dependent variable . the variable (Y) that is predicted or explained using X1 to Xk Independent or explanatory variable . X1 to Xk used to predict or explain values of the dependent variable (Y). Multiple linear regression. You regress the dependent variable, Y, which you are trying to predict, on the independent variables X1 to Xk. If there is only one X, this is simple linear regression. b k ’s = coefficients to be estimated Econometrics– estimate economic relationships using regression techniques and data Not as hard as you think, MS Excel can do this. Types of Data Data--time series, cross sectional, or both time series = data over time –values of a single firm’s cost and output over time –Coke demand data in the U.S., 1970-2005 cross sectional = data over individuals –values of the economic variables for a number of different firms, at any one point in time –in 2005, coke demand data in the U.S., CAN, and MEX both = data over time and individuals
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3 Chapter 4 Steps in quantitative analysis Step 1: Problem definition Precisely define problem of interest Would a 10% increase in advertising increase profits? What if AGE2044 decreases by 1 percentage point from 2005 to 2006? Hypotheses:
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This note was uploaded on 10/08/2008 for the course AEM 4150 taught by Professor Kaiser,h.m. during the Fall '07 term at Cornell University (Engineering School).

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CHAP4 - Empirical Price Analysis An economist is a trained...

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