Lecture 20 2010

# Lecture 20 2010 - V.ExtensionsofMultipleRegression A....

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1 V. Extensions of Multiple Regression A. Dummy Variables 1. Definition : A binary variable that indicates a quality, condition, characteristic, etc. exits. 2. Examples : Cross Section; Time Series. 3. Uses for Dummy Variables a. Shifting the Intercept b. Shifting the Slope 4. Interpretation 3. Uses of Dummy Variables b. Shifting the slope (as well as intercept): ± Incorporate the dummy variable in PRE. ± Incorporate an interaction term in PRE. Interaction Term : Multiply an independent variable by the dummy variable. ± Given: Y i = β 0 + β 1 X 1i + δ D i + γ D i *X 1i + u i ± There are two regressions : If D i = 0: Y i = β 0 + β 1 X 1i + u i If D i = 1: Y i = ( β 0 + δ )+ ( β 1 + γ ) X 1i + u i The regression equation is wage = - 4.66 + 1.49 yrsed + 0.155 exp -1. 03 f - 0.048 fexp Predictor Coef SE Coef T P Constant -4.657 2.184 -2.13 0.033 yrsed 1.4850 0.1499 9.91 0.000 exp 0 15522 0 03771 4 12 0 000 exp 0.15522 0.03771 4.12 0.000 f -1.031 1.311 -0.79 0.432 fexp -0.04778 0.05348 -0.89 0.372

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2 at2 22 20 18 f 0 1 Shifting the Intercept and Slope: Male vs. Female Wages exp wageh 60 50 40 30 20 10 0 16 14 12 4. Interpretations ± Model: Yi = β 0 + 1 X 1i + 2 X 2i + δ D i + γ (X 1i D i ) + u i ± The parameter δ
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## This note was uploaded on 12/08/2011 for the course ECON 312 taught by Professor Daniellass during the Winter '10 term at UMass (Amherst).

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Lecture 20 2010 - V.ExtensionsofMultipleRegression A....

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