Suppose that a researcher, by using a sample of transactions of residential houses, wants to estimate how the price of the houses is affected by the absence of an elevator in the building. To this end, he regresses the price of the house in thousands euro, price, on the dummy no_elevator indicating the absence of the elevator (dummy equal to 1) or the presence (dummy equal to 0): price, = ao +a1 no-elevator; + u; The OLS estimates are (standard errors in round brackets below the corresponding coefficient): price, = 199.937- 73.068 no-elevator; (10.735) R2 = 0.036 (5.482) Unfortunately, he makes an informatic mistake so that he uses the original dummy adding a value of 2, i.e. a variable that takes value 3 if there is not an elevator in the building and 2 if there is. How will the estimated value of the coefficients be affected by this mistake? O (a) The intercept will increase whereas the coefficient of the dummy will decrease O (b) The intercept will increase whereas the coefficient of the dummy will be unaffected O (c) The intercept will decrease whereas the coefficient of the dummy will be unaffected O (d) None of the above

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Suppose that a researcher, by using a sample of transactions of residential houses, wants to estimate how the price of the houses is affected by the absence of an
elevator in the building. To this end, he regresses the price of the house in thousands euro, price, on the dummy no_elevator indicating the absence of the elevator
(dummy equal to 1) or the presence (dummy equal to 0):
price; = a0 +a1 no_elevator; + u;
The OLS estimates are (standard errors in round brackets below the corresponding coefficient):
price;
= 199.937 – 73.068 no_elevator;
(5.482)
R2 = 0.036
(10.735)
Unfortunately, he makes an informatic mistake so that he uses the original dummy adding a value of 2, i.e. a variable that takes value 3 if there is not an elevator in the
building and 2 if there is.
How will the estimated value of the coefficients be affected by this mistake?
O (a) The intercept will increase whereas the coefficient of the dummy will decrease
O (b) The intercept will increase whereas the coefficient of the dummy will be unaffected
O (c) The intercept will decrease whereas the coefficient of the dummy will be unaffected
O (d) None of the above
Transcribed Image Text:Suppose that a researcher, by using a sample of transactions of residential houses, wants to estimate how the price of the houses is affected by the absence of an elevator in the building. To this end, he regresses the price of the house in thousands euro, price, on the dummy no_elevator indicating the absence of the elevator (dummy equal to 1) or the presence (dummy equal to 0): price; = a0 +a1 no_elevator; + u; The OLS estimates are (standard errors in round brackets below the corresponding coefficient): price; = 199.937 – 73.068 no_elevator; (5.482) R2 = 0.036 (10.735) Unfortunately, he makes an informatic mistake so that he uses the original dummy adding a value of 2, i.e. a variable that takes value 3 if there is not an elevator in the building and 2 if there is. How will the estimated value of the coefficients be affected by this mistake? O (a) The intercept will increase whereas the coefficient of the dummy will decrease O (b) The intercept will increase whereas the coefficient of the dummy will be unaffected O (c) The intercept will decrease whereas the coefficient of the dummy will be unaffected O (d) None of the above
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