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Using a sample of 546 observations, a researcher is interested in finding factors that influence house prices (measured in ten thousands). The researcher run regression of Hedonic price model that explain house prices using lot size, bed rooms, bath rooms, stories all are measured in number of units and dummy variables 2 whether the house has air-conditioning, drive way, recreation room, glass show , full basement, garage place and preferred area the results are shown below.

Using a sample of 546 observations, a researcher is interested in finding factors that influence house prices (measured in ten thousands). The researcher run regression of Hedonic price model that explain house prices using lot size, bed rooms, bath rooms, stories all are measured in number of units and dummy variables 2 whether the house has air-conditioning, drive way, recreation room, glass show , full basement, garage place and preferred area the results are shown below.

ENGR.ECONOMIC ANALYSIS
ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN:9780190931919
Author:NEWNAN
Publisher:NEWNAN
Chapter1: Making Economics Decisions
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10 Using a sample of 546 observations, a researcher is interested in finding factors that influence house prices (measured in ten thousands). The researcher run regression of Hedonic price model that explain house prices using lot size, bed rooms, bath rooms, stories all are measured in number of units and dummy variables 2 whether the house has air-conditioning, drive way, recreation room, glass show , full basement, garage place and preferred area the results are shown below.

. reg price lotsize bedrooms bathrms airco driveway recroom fullbase gashw garagepl prefarea stories Source df MS Number of obs 546 F (11, 534) 99.97 Model 2.6158e+11 11 2.3780e+10 Prob > F 0.0000 Residual 1.2703e+11 534 237874666 R-squared 0.6731 Adj R-squared 0.6664 Total 3.8860e+11 545 713032635 Root MSE 15423 price Coef. Std. Err. P>|t]| [95% Conf. Interval] lotsize 3.546303 .3503 10.12 0.000 2.858168 4.234438 bedrooms 1832.003 1047 1.75 0.081 -224.7409 3888.748 bathrms 14335.56 1489.921 9.62 0.000 11408.73 17262.38 airco 12632.89 1555.021 8.12 0.000 9578.182 15687.6 driveway 6687.779 2045.246 3.27 0.001 2670.065 10705.49 recroom 4511.284 1899.958 2.37 0.018 778.9759 8243.592 fullbase 5452.386 1588.024 3.43 0.001 2332.845 8571.926 gashw 12831.41 3217.597 3.99 0.000 6510.706 19152.11 garagepl 4244.829 840.5442 5.05 0.000 2593.65 5896.008 prefarea 9369.513 1669.091 5.61 0.000 6090.724 12648.3 stories 6556.946 925.2899 7.09 0.000 4739.291 8374.6 cons -4038.35 3409.471 -1.18 0.237 -10735.97 2659.271 b. Write one equation for auxiliary regression for testing multi- collinearity? State the condition for the existence of multi- collinearity? c. Assuming there is no risk of hetroskedasticity answer the following questions i. Interpret R2 ii. Are all the variables jointly different from zero?
Transcribed Image Text:. reg price lotsize bedrooms bathrms airco driveway recroom fullbase gashw garagepl prefarea stories Source df MS Number of obs 546 F (11, 534) 99.97 Model 2.6158e+11 11 2.3780e+10 Prob > F 0.0000 Residual 1.2703e+11 534 237874666 R-squared 0.6731 Adj R-squared 0.6664 Total 3.8860e+11 545 713032635 Root MSE 15423 price Coef. Std. Err. P>|t]| [95% Conf. Interval] lotsize 3.546303 .3503 10.12 0.000 2.858168 4.234438 bedrooms 1832.003 1047 1.75 0.081 -224.7409 3888.748 bathrms 14335.56 1489.921 9.62 0.000 11408.73 17262.38 airco 12632.89 1555.021 8.12 0.000 9578.182 15687.6 driveway 6687.779 2045.246 3.27 0.001 2670.065 10705.49 recroom 4511.284 1899.958 2.37 0.018 778.9759 8243.592 fullbase 5452.386 1588.024 3.43 0.001 2332.845 8571.926 gashw 12831.41 3217.597 3.99 0.000 6510.706 19152.11 garagepl 4244.829 840.5442 5.05 0.000 2593.65 5896.008 prefarea 9369.513 1669.091 5.61 0.000 6090.724 12648.3 stories 6556.946 925.2899 7.09 0.000 4739.291 8374.6 cons -4038.35 3409.471 -1.18 0.237 -10735.97 2659.271 b. Write one equation for auxiliary regression for testing multi- collinearity? State the condition for the existence of multi- collinearity? c. Assuming there is no risk of hetroskedasticity answer the following questions i. Interpret R2 ii. Are all the variables jointly different from zero?
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