Question

Assume you are interested in housing prices. You believe that the number of bedrooms will mpact the price of a home. Let bedroom, represent the number of bedrooms in home , and price, its price (in dollars). In this case the unit of observation is the home. a) Write the population model of interest. b) Name two factors not accounted by the model that could affect the price a home, i.e. two factors that are in the error term. Briefly explain why you believe these factors would affect your dependent variable. b) Assume the following random sample from the Toronto housing market { (bedroom i, price.) : İ-1, . . . , 4)) {(3.500000), (2, 300000), (7, 1000000), (4, 600000)) Using the OLS estimator, calculate estimates of the intercept and the slope parameter. You are to do it by hand and show your work d) Interpret the estimate of interest e) Graph (to scale) the sample points, and the estimated line. Put the ber of bedrooms on the horizontal axis and the price on the vertical axis

Answer 1

Assume you are interested in housing prices you beloved that the number of bedrooms will impact the price of a home explain A) the population model of interest B_the econometric model for housing project is a simple linear regression model with price of home as dependent variable and number of bedrooms as independent variable and number of bedrooms as independent variable it can be represented as price = y (bedrooms) the population model of interest is price = bet_0 + beta_1 bedrooms + e the sample models is price I = beta_0 + beta_1 = bedrooms I + E_i b) the factors that could affect the price of home are garage and age of the house the presence of garage affect the price of home positively A house with garage is mortify desired and hence commands high price the age of a house would have a negative relationship with house price since an old house commands a lower price compared to a newly built house