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The following equation describes the median housing price in a community in terms of amount of pollution (nox for nitrous oxide) and the average number of rooms in houses in the community (rooms): log (price)= B,+B, log(nox)+B,rooms+u 1. What are the probable signs of ß, and B2? 2. What is the interpretation of ß,? Explain. 3. Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? Explain.

The following equation describes the median housing price in a community in terms of amount of pollution (nox for nitrous oxide) and the average number of rooms in houses in the community (rooms): log (price)= B,+B, log(nox)+B,rooms+u 1. What are the probable signs of ß, and B2? 2. What is the interpretation of ß,? Explain. 3. Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? Explain.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The following equation describes the median housing price in a community in terms of amount of pollution (nox for nitrous oxide) and the average number of rooms in houses in the community (rooms): log (price)= Bo+B,log(nox)+B2rooms+u 0. 1. What are the probable signs of B, and ß2? 2. What is the interpretation of B,? Explain. 3. Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? Explain. 4. If nox and rooms are negatively correlated, does the simple regression of log(price) on log(nox) produce an upward or downward biased estimator of B,? Explain. 5. Using the data available, the following equations were estimated: log (price) = 11.71-1.043/og(nox),n = 506,R² = 0.264 log (price)= 9.23-0.718/og(nox)+0.306rooms,n= 506,R² = 0.514 Is the relationship between the simple and multiple regression estimates of the elasticity of price with respect to nox what you would have predicted, given your answer in part (3) and (4)? Does this mean that -.718 is definitely closer to the true elasticity than -1.043?
Transcribed Image Text:The following equation describes the median housing price in a community in terms of amount of pollution (nox for nitrous oxide) and the average number of rooms in houses in the community (rooms): log (price)= Bo+B,log(nox)+B2rooms+u 0. 1. What are the probable signs of B, and ß2? 2. What is the interpretation of B,? Explain. 3. Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? Explain. 4. If nox and rooms are negatively correlated, does the simple regression of log(price) on log(nox) produce an upward or downward biased estimator of B,? Explain. 5. Using the data available, the following equations were estimated: log (price) = 11.71-1.043/og(nox),n = 506,R² = 0.264 log (price)= 9.23-0.718/og(nox)+0.306rooms,n= 506,R² = 0.514 Is the relationship between the simple and multiple regression estimates of the elasticity of price with respect to nox what you would have predicted, given your answer in part (3) and (4)? Does this mean that -.718 is definitely closer to the true elasticity than -1.043?
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