If you are interested in investigating the marginal effect of the percentage change of lot size on the change of house price, then in your linear regression analysis you should apply the logarithm transformation on: Select one: a. The house price variable. b. Both the house price variable and the lot size variable. c. The lot size variable. d. The bedroom variable. e. Both the bedroom variable and the house price variable.

If you are interested in investigating the marginal effect of the percentage change of lot size on the change of house price, then in your linear regression analysis you should apply the logarithm transformation on: Select one: a. The house price variable. b. Both the house price variable and the lot size variable. c. The lot size variable. d. The bedroom variable. e. Both the bedroom variable and the house price variable.

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Question 3 Consider the table below with regression output from two OLS regressions estimating the share of household budget devoted to food and adult goods (tobacco and alcohol) in some country using the Working-Leser Engel curve specification: K-1 w; = a; + B,ln () + niln(n)+ E Vik + T;z + ui k=1 where w; is the share of total household expenditure on good i (either food or tobacco and alcohol) measured as a proportion between 0 and 1, y is total household expenditure, n is household size, n; e {1, .., K} is the number of people in age-sex category j, z is a vector of other household characteristics, and u is an error term for the ith good. Assume that all coefficients are statistically significant. Table 1: OLS regression coefficients of household share of expenditure spent on food and adult goods Food Tobacco and Alcohol In (4) -0.70 -0.33 In(n) -0.02 0.12 Ratio of males: 0-2 years -1.46 -0.42 3-4 years -1.63 -0.12 5-14 years -4.78 -0.17 15-54 years -4.63 0.57 55+ years -5.11 0.87…
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1. Suppose output (Q) is related to labor (L) and capital (K) in the following nonlinear way: Q = albKc When taking log to this equation, it is transformed into a linear LnQ = Ina + b In(L) + c Ln (K) One hundred twenty-three observations are used to obtain the following regression results: Dependant Variable: Observations: Variable Intercept L K Q 123 5.5215 Parameter Standard Estimate error 0.650 R-square 0.350 0.7547 0.9750 0.2950 0.1450 F-ratio 184.56 t-ratio 5.66 2.20 2.41 p-value on F 0.00001 p-value 0.0001 0.0295 0.0173 a. Write the regression equation based on the output either in the transformed linear form or the original non-linear form.
number 1 please