
Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010X
Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge
Edition 6ISBN: 130527010XIn Section 4.5, we used as an example testing the rationality of assessments of housing prices. There, we used a log-log model in price and assess [see equation (4.47)]. Here, we use a level-level formulation.
(i) In the simple regression model
price = ?0+ ?1 Possess + u,
the assessment is rational if ?1 = 1 and ?0 = 0. The estimated equation is
First, test the hypothesis that H0: ?0 = 0 against the two-sided alternative. Then, test H0: ?1 = 1 against the two-sided alternative. What do you conclude?
(ii) To test the joint hypothesis that ?0 = 0 and ?1 = 1, we need the SSR in the restricted model. This amounts to computing
where n = 88, since the residuals in the restricted model are just pricei - assessi. (No estimation is needed for the restricted model because both parameters are specified under H0.) This turns out to yield SSR = 209,448.99. Carry out the F test for the joint hypothesis.
(iii) Now, test H0: ?2 = 0, ?3 = 0, and ?4 = 0 in the model
price = ?0 + ?1 assess + ?2 lotsize + ?3 sqrft + ?4 bdrms + u.
The R-squared from estimating this model using the same 88 houses is .829.
(iv) If the variance of price changes with assess, lotsize, sqrft, or bdrms, what can you say about the F test from part (iii)?
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Regression analysis is a statistical analysis through which relationship among variables can be identified. It investigates the strength by which a dependent variable is dependent on an independent variable.
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Other![In Section 4.5, we used as an example testing the rationality of assessments of housing prices. There, we used a log-log model in price and assess [see equation (4.47)]. Here, we use a level-level formulation. <blockquote> (i) In the simple regression model price = ?<span class=sub>0</span>+ ?<span class=sub>1</span> Possess + u, the assessment is rational if ?<span class=sub>1</span> = 1 and ?<span class=sub>0</span> = 0. The estimated equation is First, test the hypothesis that H0: ?<span class=sub>0</span> = 0 against the two-sided alternative. Then, test H0: ?<span class=sub>1</span> = 1 against the two-sided alternative. What do you conclude? (ii) To test the joint hypothesis that ?<span class=sub>0</span> = 0 and ?<span class=sub>1</span> = 1, we need the SSR in the restricted model. This amounts to computing where n = 88, since the residuals in the restricted model are just price<span class=sub>i</span> - assess<span class=sub>i</span>. (No estimation is needed for the restricted model because both parameters are specified under H<span class=sub>0</span>.) This turns out to yield SSR = 209,448.99. Carry out the F test for the joint hypothesis. (iii) Now, test H<span class=sub>0</span>: ?<span class=sub>2</span> = 0, ?<span class=sub>3</span> = 0, and ?<span class=sub>4</span> = 0 in the model price = ?<span class=sub>0</span> + ?<span class=sub>1</span> assess + ?<span class=sub>2</span> lotsize + ?<span class=sub>3</span> sqrft + ?<span class=sub>4</span> bdrms + u. The R-squared from estimating this model using the same 88 houses is .829. (iv) If the variance of price changes with assess, lotsize, sqrft, or bdrms, what can you say about the F test from part (iii)? </blockquote>](https://d2lvgg3v3hfg70.cloudfront.net/SMCC2709/08465ce0_abb6_4bc0_82d8_e7560c8a9d43_SMCC2709_11.jpg)
where n = 88, since the residuals in the restricted model are just price
