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7. You estimate the parameters of the following regression using the OLS estimator In(price) = a+B.In(nor) +e 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(nor) +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

7. You estimate the parameters of the following regression using the OLS estimator In(price) = a+B.In(nor) +e 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(nor) +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

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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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
Transcribed Image 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
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