4) Consider the following regression model: ln(price-0 + 1 ln(assess) + 2 ln (lo

Question

4) Consider the following regression model: ln(price-0 + 1 ln(assess) + 2 ln (lots ize) + 3 In (sqrft) + 4bdrms + u where price : house price; assess : the assessed housing value (before the house was sold); lotsize : size of the lot, in feet; sqrft: square footage: and bdrms number of bedrooms. The econometrician uses Stata 'reg' command, i.e., uses OLS estimation, to get the following results. Interpret the coefficient estimates in terms of the marginal effects (or elasticity) on the price; statistical significance of the coefficients; and the economic meaning of the coefficients (whether they make sense). assess: t Source df MS Number of obs - F(4, 83) 70.58 Prob > F R-squared = 0.7728 Adj R-squared 0.7619 Root MSE 6.196074734 1. 54901868 Residual 1.8215287983L02194613 Model 0.0000 Total8.01760352 87 .092156362 14814 P>It! (95% Conf. Interval] coef. Std. Err. t 00743790385615 263743569664746 1price lassess1.043065 151446 6.89 0.00074184531. 344285 11otsize 0.19 0.8480692593 0841352 1sqrft1032384-1384305 07S0458378571 1720942 1:53 0.1290101135 0777918 .0338392 0220983 bdrms -cons 0.64586929721.396783

Explanation / Answer

The coefficients are interpreted as follows-

Cons=0.263 represents the price of the house when all other parameters are 0, which means when all other things aren't present there is no house in existence and which also means that this value is negligible

lassess=1.04 which means that the actual price of the house is very highly correlated with the assessed value before the sale and it more or less interprets the actual price quite significantly

llotsize=0.007 which means there is weak but positive correlation between the price of the house and the size of the lot, in feet

lsqrft=-0.103 which means that there is a weak negative correlation between the price of the house and this factor

bdrms=0.033 which means that there is a positive and weak correlation between the number of bedrooms and the price of the house.

The extent to which they are significant can be known by the t-values. Hope this helps

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