# chap4_App4A - Problems in Applying the Linear Regression...

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Slide 1 Problems in Applying the  Linear Regression Model Appendix 4A The assumptions of the linear regression model don’t always hold in the real world We now examine statistical problems, which is the central focus of the economic sub-field called econometrics 1. Autocorrelation 2. Heteroscedasticity 3. Specification and Measurement Error 4. Multicollinearity 5. Simultaneous equation relationships and the identification problem 6. Nonlinearities

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Slide 2 1. Autocorrelation also known as serial correlation Problem: » Coefficients are unbiased » but t-values are unreliable Symptoms: » look at a scatter of the error terms to see if there is a pattern, or » see if Durbin Watson statistic is far from 2. Cures: 1. Find more variables that explain these patterns 2. Take first differences of data: Q = a + b• P
Slide 3 Scatter of Error Terms Positive Autocorrelation Figure 4A.1 page 146 Y X 1 2 3 4 5 6 7 8

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Slide 4 2. Heteroscedasticity Problem: » Coefficients are unbiased » t-values are unreliable Symptoms: » different variances for different sub-samples » scatter of error terms shows increasing or decreasing dispersion Cures: 1. Transform data, e.g. , transform them into logs 2. Take averages of each sub-sample and use weighted least squares
Slide 5 Scatter of Error Terms Heteroscedasticity Height AGE 1 2 5 8 alternative log H t = a + b•AGE

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Slide 6 3. Specification  & Measurement Error Salary = a + b (Strike Outs) in baseball b is positive !!!
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