Section_5_Spring2008 - 02 Educ 14 145 12(0 03(0 03(0 03...

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Practice Problem: F-test and OVB Econ 142 Spring 2008 Raymundo M. Campos-Vazquez February 20, 2008 Contents 1 Problem 1: F-tests 1 1 Problem 1: F-tests You want to estimate the causal e/ect of smoking on wages. You estimate the following regression: ln w = ° 0 + ° 1 Smoke + ° 2 Age + ° 3 Education + u Smoke is a dummy variable for smoking, Age is the age of indvidual, Education is the years of education. You are not sure about the speci°cation you should estimate and run two more regression models. One including a dummy variable for female, and the last model includes a dummy variable for female, age squared and an interaction term between age and education. The following table includes the parameters from the three regressions (Note: Numbers are fake, I do not claim the e/ects are correct). Column (1) refers to the °rst speci°cation, Column (2) includes female and (3) include female and other terms. Standard errors are shown in parentheses: 1
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(1) (2) (3) Smoke -0.10 -0.12 -0.11 (0 : 03) (0 : 01) (0 : 01) Age 0 : 05 0 : 05 0 : 10 (0 : 01) (0 : 01) (0 : 02)
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Unformatted text preview: : 02) Educ : 14 : 145 : 12 (0 : 03) (0 : 03) (0 : 03) Female & : 30 & : 32 (0 : 10) (0 : 10) Age 2 & : 05 (0 : 03) Age ± Educ : 10 (0 : 04) R 2 : 50 : 53 : 60 R 2 : 48 : 51 : 57 n 100 100 100 1. Using Column (1), what is the e/ect of smoking on wages? 2. Under which conditions would the coe¢ cient on smoking give you a causal interpreta-tion of smoking on wages? 3. Test the null hypothesis that the population parameter of smoking is equal to -0.15 agianst the alternative the paramter is di/erent from -0.15. 4. Using Column (1), test the signi&cance of the regression (i.e. test whether all parame-ters but the constant are equal to zero). 5. Comparing Column (1) and (2) you observe that the coe¢ cient on smoking is more negative in column (2) than in column (1). Why is this the case? 6. Test whether you should use Model (3) instead of Model 1 at the 5% signi&cance level. 2...
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