Question

data in KIELMC, only for the year 1981, to answer the following questions. The data are for that sold during 1981 in North Andover, Massachusetts; 1981 was the year construction began local garbage incinerator. To study the effects of the incinerator location on housing price, consider the simple regression model log(price) = ??? + ??log(dist) + u where price is housing price in dollars and dist is distance from the house to the incinerator measured in feet. Interpreting this equation causally, what sign do you expect for ?? if the presence of the incinerator depresses housing prices? Estimate this equation and interpret the results. To the simple regression model in part (i), add the variables log(intst), log(area), log(land), rooms, baths, and age, where intst is distance from the home to the interstate, area is square footage of the house, land is the lot size in square feet, rooms is total number of rooms, baths is number of bathrooms, and age is age of the house in years. Now, what do you conclude about effects of the incinerator? Explain why (i) and (ii) give conflicting results. Add [log(intst)]² to the model from part (ii). Now what happens? What do you conclude about the importance of functional form? Is the square of log(dist) significant when you add it to the model from part (iii)? data in WAGE1 for this exercise. Use OLS to estimate the equation log(wage) = ?? + ??educ + ??exper + ??exper² + u and report the results using the usual format. exper² statistically significant at the 1% level? Using the approximation %?wage ? 100(?? + 2??exper)?exper, find the approximate return to the fifth year of experience. What is the approximate return to the twentieth year of experience? At what value of exper does additional experience actually lower predicted log(wage)? How many people have more experience in this sample?

          data in KIELMC, only for the year 1981, to answer the following questions. The data are for
that sold during 1981 in North Andover, Massachusetts; 1981 was the year construction began
local garbage incinerator.
To study the effects of the incinerator location on housing price, consider the simple regression
model
log(price) = ??? + ??log(dist) + u
where price is housing price in dollars and dist is distance from the house to the incinerator
measured in feet. Interpreting this equation causally, what sign do you expect for ?? if the
presence of the incinerator depresses housing prices? Estimate this equation and interpret the
results.
To the simple regression model in part (i), add the variables log(intst), log(area), log(land),
rooms, baths, and age, where intst is distance from the home to the interstate, area is square
footage of the house, land is the lot size in square feet, rooms is total number of rooms, baths is
number of bathrooms, and age is age of the house in years. Now, what do you conclude about
effects of the incinerator? Explain why (i) and (ii) give conflicting results.
Add [log(intst)]² to the model from part (ii). Now what happens? What do you conclude about
the importance of functional form?
Is the square of log(dist) significant when you add it to the model from part (iii)?

data in WAGE1 for this exercise.
Use OLS to estimate the equation
log(wage) = ?? + ??educ + ??exper + ??exper² + u
and report the results using the usual format.
exper² statistically significant at the 1% level?
Using the approximation
%?wage ? 100(?? + 2??exper)?exper,
find the approximate return to the fifth year of experience. What is the approximate return to the
twentieth year of experience?
At what value of exper does additional experience actually lower predicted log(wage)? How
many people have more experience in this sample?

data in KIELMC, only for the year 1981, to answer the following questions. The data are for
that sold during 1981 in North Andover, Massachusetts; 1981 was the year construction began
local garbage incinerator.
To study the effects of the incinerator location on housing price, consider the simple regression
model
log(price) = ??? + ??log(dist) + u
where price is housing price in dollars and dist is distance from the house to the incinerator
measured in feet. Interpreting this equation causally, what sign do you expect for ?? if the
presence of the incinerator depresses housing prices? Estimate this equation and interpret the
results.
To the simple regression model in part (i), add the variables log(intst), log(area), log(land),
rooms, baths, and age, where intst is distance from the home to the interstate, area is square
footage of the house, land is the lot size in square feet, rooms is total number of rooms, baths is
number of bathrooms, and age is age of the house in years. Now, what do you conclude about
effects of the incinerator? Explain why (i) and (ii) give conflicting results.
Add [log(intst)]² to the model from part (ii). Now what happens? What do you conclude about
the importance of functional form?
Is the square of log(dist) significant when you add it to the model from part (iii)?

data in WAGE1 for this exercise.
Use OLS to estimate the equation
log(wage) = ?? + ??educ + ??exper + ??exper² + u
and report the results using the usual format.
exper² statistically significant at the 1% level?
Using the approximation
%?wage ? 100(?? + 2??exper)?exper,
find the approximate return to the fifth year of experience. What is the approximate return to the
twentieth year of experience?
At what value of exper does additional experience actually lower predicted log(wage)? How
many people have more experience in this sample?

Added by Lisa K.

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