7. You estimate the parameters of the following regression using the OLS estimator In(price) = a+B.In(nor) + e %3D where price are house prices (measured in $'000), and nor is the level of air...


7. You estimate the parameters of the following regression using the OLS estimator<br>In(price) = a+B.In(nor) + e<br>%3D<br>where price are house prices (measured in $'000), and nor is the level of air pollution<br>(measured in parts per million). e is an error term. If you believed that living closer to a<br>motorway (measured in km) decreased the value of housing but increased the amount of<br>air pollution, what problem could this potentially cause?<br>A. The OLS estimator for B will be biased upwards<br>B. The OLS estimator for B will be biased downwards<br>C. The amount of air pollution would be measured with error<br>D. The sample of house prices and air quality are non-random<br>E. none of the above<br>8. Consider the following Ordinary Least Squares estimates<br>log(price,) = 10.937+-0.179log(noz)+e;<br>(0.077)<br>(0.0135)<br>n = 506,<br>SSR = 62.689,<br>%3D<br>SSE= 21.895<br>where price, is house selling price, nor, is a measure of air quality, and numbers in<br>brackets are standard errors. Which of the following represents the R-squared for this<br>model?<br>A. 0.349<br>B. 0.650<br>C. 0.259<br>D. 0.741<br>E. 0.350<br>

Extracted text: 7. You estimate the parameters of the following regression using the OLS estimator In(price) = a+B.In(nor) + e %3D where price are house prices (measured in $'000), and nor is the level of air pollution (measured in parts per million). e is an error term. If you believed that living closer to a motorway (measured in km) decreased the value of housing but increased the amount of air pollution, what problem could this potentially cause? A. The OLS estimator for B will be biased upwards B. The OLS estimator for B will be biased downwards C. The amount of air pollution would be measured with error D. The sample of house prices and air quality are non-random E. none of the above 8. Consider the following Ordinary Least Squares estimates log(price,) = 10.937+-0.179log(noz)+e; (0.077) (0.0135) n = 506, SSR = 62.689, %3D SSE= 21.895 where price, is house selling price, nor, is a measure of air quality, and numbers in brackets are standard errors. Which of the following represents the R-squared for this model? A. 0.349 B. 0.650 C. 0.259 D. 0.741 E. 0.350

Jun 04, 2022
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