i) II) III) What are the probable signs of P₁and P₂? What are the interpretation of B₁and B₂? Explain. Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? If this is the case, does the simple regression of log(price) on log(nox) produce an upward or a downward biased estimator of B₁? Using the data in HPRICE2 the following equations were estimated: log(price) = 8.5 -0.98* log(nox) +u, n = 1500, R² = 0.30 log(price) = 6.4-0.56 * log(nox) + 0.34* room + u. n = 1500. R² = 0.54
i) II) III) What are the probable signs of P₁and P₂? What are the interpretation of B₁and B₂? Explain. Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? If this is the case, does the simple regression of log(price) on log(nox) produce an upward or a downward biased estimator of B₁? Using the data in HPRICE2 the following equations were estimated: log(price) = 8.5 -0.98* log(nox) +u, n = 1500, R² = 0.30 log(price) = 6.4-0.56 * log(nox) + 0.34* room + u. n = 1500. R² = 0.54
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
Related questions
Question
![Q.3 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):
i)
II)
E
log(price) = Po + B₁.log(nox) + f₂.room + u
What are the probable signs of B₁and B₂? What are the interpretation of B₁and
B₂? Explain.
Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? If
this is the case, does the simple regression of log(price) on log(nox) produce an
upward or a downward biased estimator of B₁?
Using the data in HPRICE2 the following equations were estimated:
log(price) = 8.5 0.98 * log(nox) + u, n = 1500, R² = 0.30
log(price) = 6.4 - 0.56 * log(nox) + 0.34 * room +u, n = 1500, R² = 0.54
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 (ii)?
Does this mean that -0.56 is definitely closer to the true elasticity than -0.98?](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fd1b8e444-2990-4108-ae64-5368bff23b70%2Fe4f86b63-d122-42c2-ae37-05287f6d4a55%2Fnpiyab_processed.png&w=3840&q=75)
Transcribed Image Text:Q.3 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):
i)
II)
E
log(price) = Po + B₁.log(nox) + f₂.room + u
What are the probable signs of B₁and B₂? What are the interpretation of B₁and
B₂? Explain.
Why might nox [or more precisely, log(nox)] and rooms be negatively correlated? If
this is the case, does the simple regression of log(price) on log(nox) produce an
upward or a downward biased estimator of B₁?
Using the data in HPRICE2 the following equations were estimated:
log(price) = 8.5 0.98 * log(nox) + u, n = 1500, R² = 0.30
log(price) = 6.4 - 0.56 * log(nox) + 0.34 * room +u, n = 1500, R² = 0.54
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 (ii)?
Does this mean that -0.56 is definitely closer to the true elasticity than -0.98?
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