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There are 6660 observations of data on houses sold from 1999-2002 in Stockton California in the file hedonic1.xls. Use the data of 2001 only to

There are 6660 observations of data on houses sold from 1999-2002 in Stockton California

in the file "hedonic1.xls". Use the data of 2001 only to estimate the next linear model and

answer the associated questions below.

LSP = ? 01 + ? 02 SFLA + ? 03 BEDS + ? 04 BATHS + ? 05 STORIES

+? 06 VACANT + ? 07 AGE + u, (1)

where u is an error term. Note that the sub-index i of each variable has been suppressed in the

above equation.

LSP = ln(Selling Price), which is a function of:

? SFLA - Size of Living Area (in square feet)

? BEDS - Number of Bedrooms

? BATHS - Number of Bathrooms

? STORIES - Number of Stories

? VACANT - Vacancy Status (1 if vacant, 0 if not at the time of the sale)

? AGE - Age of the House in Years

1

Questions: (20 marks in total)

1. Calculate the descriptive statistics for LSP and all explanatory variables (i.e., 7 VARI-

ABLES IN TOTAL), and report them in a table. (2 points)

2. Estimate the above hedonic model for the houses sold from in Stockton California.

(a). Write down the estimated model (including estimates of the coefficients and the

associated standard deviations, and R 2 at least).

  • (b). Discuss the estimation results using Goodness of fit.
    image text in transcribedimage text in transcribed
Equation: UNTITLED Workfile: HEDONIC1 (1)::Untitled\\ X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: LOG(SELLING_PRICE) Method: Least Squares Date: 04/19/21 Time: 21:12 Sample: 1 6660 IF YEAR=2001 Included observations: 1746 Variable Coefficient Std. Error t-Statistic Prob. C 11.46537 0.029939 382.9606 0.0000 SFLA 0.000544 1.68E-05 32.38581 0.0000 BEDS -0.058501 0.009692 -6.036237 0.0000 BATHS 0.051444 0.015735 3.269506 0.0011 STORIES -0.034838 0.015542 -2.241588 0.0251 VACANT -0.034768 0.011578 -3.002989 0.0027 AGE -0.004457 0.000275 -16.21832 0.0000View Proc Object Print Name Freeze Estimate Forecast Stats Resids JIL. LITOT TTOD. C 11.46537 0.029939 382.9606 0.0000 SFLA 0.000544 1.68E-05 32.38581 0.0000 BEDS -0.058501 0.009692 -6.036237 0.0000 BATHS 0.051444 0.015735 3.269506 0.0011 STORIES -0.034838 0.015542 -2.241588 0.0251 VACANT -0.034768 0.011578 -3.002989 0.0027 AGE -0.004457 0.000275 -16.21832 0.0000 R-squared 0.692720 Mean dependent var 12.01860 Adjusted R-squared 0.691660 S.D. dependent var 0.372115 S.E. of regression 0.206629 Akaike info criterion -0.311778 Sum squared resid 74.24789 Schwarz criterion -0.289868 Log likelihood 279.1822 Hannan-Quinn criter. -0.303678 F-statistic 653.3891 Durbin-Watson stat 1.320431 Prob(F-statistic) 0.000000

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