# Wk2 OLS - 8 Least Squares Estimation 9 Derivations of OLS...

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Introduction to  Econometrics   Spring 2010 Wk2. Ordinary Least  Squares

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2 Regression    Y=f(X )
3 Type of data • Cross-sectional data • Time-series • Pooled data • Panel data

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4 Simple Regression
5 Population Regression  Function (PRF)

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6 The Stochastic Term ( u i ) • 1. Vagueness of theory • 2. Unavailability of data • 3. Core vs. peripheral data • 4. Randomness of human behavior • 5. Poor proxy variables • 6. Parsimony • 7. Wrong functional form
7 Sample Regression  Function or

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Unformatted text preview: 8 Least Squares Estimation 9 Derivations of OLS • Differentiating gives the “Normal Equations” • The idea is to minimize the sum of residuals squared, i.e. 10 OLS Estimators & S.E 11 Estimating the Error Variance • But we don’t usually know σ 2 , so how can we use these formulas? • By bootstrapping! Estimate the population variance σ 2 with the sample regression variance, i.e. • where • hence...
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## This note was uploaded on 03/14/2010 for the course ECON econmetric taught by Professor Yy during the Spring '10 term at Seoul National.

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Wk2 OLS - 8 Least Squares Estimation 9 Derivations of OLS...

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