321_F11_slides5

321_F11_slides5 - Click to edit Master subtitle style Econ...

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Unformatted text preview: Click to edit Master subtitle style Econ 321-Stéphanie The Simple Regression Model Chapter 2 Econ 321 Introduction to Econometrics Econ 321-Stéphanie 11 Econ 321-Stéphanie Outline • Population regression equation • Deriving the OLS Estimates • Interpretation and Evaluation of Results – Units of measurement and functional form • Properties of OLS Econ 321-Stéphanie 22 Econ 321-Stéphanie Last Time • Population with parameter (characteristic) µ for a random variable Y (household income) • Random sample Y1,..,Yn • Estimate µ with Y • Make inference about population from sample information Econ 321-Stéphanie 33 Econ 321-Stéphanie A Conditional Model • We now are interested in analyzing a variable of interest Y as a function of another variable X (bivariate regression) • We establish a conditional model – A model of vacation expenditure conditional on household income – A model of worker productivity (job performance) conditional on training information Econ 321-Stéphanie 44 Econ 321-Stéphanie Econ 321-Stéphanie 55 Population Regression Function Econ 321-Stéphanie Formally • The population mean for Y is now a function of another variable X • E(Y|X) = β0 + β1 X • The mathematical expression for a straight line • This is our “certainty” model • What is the statistical model? Econ 321-Stéphanie 66 Econ 321-Stéphanie Randomness Econ 321-Stéphanie 77 Econ 321-Stéphanie Population Regression Equation Dependent Variable Intercept Slope Coefficient Explanatory Variable Error yi = β0 + β1 xi + ui Econ 321-Stéphanie Error or Disturbance Term • What the econometrician cannot observe or measure • It represents the influence of the variables other than Xi (not included in the model) • Even if we observed and measured these additional factors, there would...
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321_F11_slides5 - Click to edit Master subtitle style Econ...

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