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Save Answer Question 28 6 points An researcher uses "In price" as dependent variable, where price is the selling price and studies the effect of different characteristics of house on its selling price. The regressors are size house size in square feet, pool-binary variable (I if the house has a swimming pool, O otherwise), view = binary variable (1 if the house has a nice view, otherwise), condition - binary variable (if the house is in excellent condition, otherwise). The regression results for different specifications are presented in the table below. The numbers in the bracket represent standard errors of the coefficient Regressor 1 3 In size .720.055) .65(2005) 7380.063) 2 In size 2 .0086(16) Pool .0766,037) .027.028) .092.034) .0270.031) View Pool X View 0820038) .0270.033) 0029.12) .166.037) 6.62(43) 102 Condition .130.035) .220.038) 6.60641) 7.12(7.52) Intercept SER .104 108

Answer 1

Answer, * keeping all other variables constant except pool and view, the regression equation in specification (3), can be written as, * In (price) - constant +0.08R POOT+0.08.7*upew +0.0089*poolxview * For House without a pool and with a view, (pool = 0, view = 1) * In (price_without pool) - constant to.027 * For House with a pool and view, (pool=4, view= 1) * In (price with pool) = constant +0.082+0.007+0.0029 * In (price with pool) = constant +0.1119. * The expected change = 'In (psece- with pool).In porce-without peol). -0.1119-0.027 = 0.0849. * In (poice with pool/ porce-without pool) = 0.0819. * Poice with pool/ price without pool - explo-0849) price with pool = 1.088608* poice, without pool. * The police will be increased by a factor of 1088608, by 8.8603%. THANK You

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