practice1

practice1 - sentences. 6. Consider (3) again. Estimate the...

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2 a. Briefly explain why using a semi-log model is logical here. b. Report in a table the OLS estimates, standard errors, and p-values of classical t- tests. Call this Table 2 . Just below the table , report the standard error of the regression, R 2 adjusted R 2 and the p-value of the classical F-test. c. Compare (1) and (2) as models for explaining statewide mortality rates. Use your sense of what should be true, and the statistical evidence (estimate significance, R 2 , F-stat.) to support your answer. This should be no more than 4-5 sentences. d. Now create the natural log of mortality, and estimate the model i i i i i i u aged pc tob pc alc pc inc mort 11 4 3 2 1 ) _ ln( ) _ ln( ) _ ln( ) ln( ) 3 ( Present the same type of results as before in Table 3 . Use (3) to estimate the tobacco elasticity of mortality. Test the one sided hypothesis that it is zero or negative. e. Why is it not reasonable to compare (1) and (3) statistically? or (2) and (3)? Restrict your answer to 2-3
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Unformatted text preview: sentences. 6. Consider (3) again. Estimate the model and generate residuals ( u_hat i ) and predicted variables ( mort_hat i ). a. Compute the sample correlations between the residuals and log-tobacco, residuals and log-alcohol, and residuals and log-income. Present the correlations and their p-values. Explain why the result is trivial. b. Create a scatter plot of mort_hat (X-axis) and mort (Y-axis). Call it Figure 1 : Mortality and Predicted Mortality . Add labels, etc., using full names. Regress mort on mort_hat (i. .e. mort is the dependent or left-hand variable). Present the usual output in Table 4 . Use the scatter plot and Table 4 results to discuss how well (3) works as a model of mortality. Compare the R-squared in Tables 3 and 4 . What's going on? Can you prove why this must be so....
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practice1 - sentences. 6. Consider (3) again. Estimate the...

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