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Case 1: Housing Price Structure In Mid City Sales of single-family houses have been brisk in Mid City this year. This has especially been true in older, more established neighborhoods, where housing is relatively inexpensive compared to the new homes being built in the newer neighborhoods. Nevertheless, there are also many families who are willing to pay a higher price for the prestige of living in one of the newer neighborhoods. The worksheet Q1.xls contains data on 128 recent sales in Mid City. For each sale, the file shows the neighborhood (1, 2, or 3) in which the house is located, the number of offers made on the house, the square footage, whether the house is made primarily of brick, the number of bathrooms, the number of bedrooms, and the selling price. Neighborhoods 1 and 2 are more traditional neighborhoods, whereas neighborhood 3 is a newer, more prestigious, neighborhood. Use regression to estimate and interpret the pricing structure of houses in Mid City. Here are some considerations. 1. Please draw the plots about Brick vs Price, Nbhd vs Price, Offers vs Price, respectively. Could you judge how Brick, Nbnd and Offers influence the house price? (5 points) 2. Please fill the table below (Hint: You could use the sample selection function in STATA or in the filter function in Excel) (5 points) Price Price Brick without Bricko-kod Mean my Mediamary Standard deviation 95th preventile 3. Is there a "premium" for a brick house, everything else being equal? (5 points) 4. Is there a premium for a house in neighborhood 3, everything else being equal? (5 points) 5. Is there an extra premium for a brick house in neighborhood 3, in addition to the usual premium for a brick house? (Hint: You need to regard an interaction effect) (5 points) 6. For purposes of estimation and prediction, could neighborhoods 1 and 2 be collapsed into a single "older" neighborhood? (5 points) 7. In your opinion, which factors are significant to affect the housing price? (5 points) (Hint: You would use the regression models to solve the questions 3-7. You need to create dummies for the characteristics of house by using STATA, such as brick, neighborhood, etc.) Case 1: Housing Price Structure In Mid City Sales of single-family houses have been brisk in Mid City this year. This has especially been true in older, more established neighborhoods, where housing is relatively inexpensive compared to the new homes being built in the newer neighborhoods. Nevertheless, there are also many families who are willing to pay a higher price for the prestige of living in one of the newer neighborhoods. The worksheet Q1.xls contains data on 128 recent sales in Mid City. For each sale, the file shows the neighborhood (1, 2, or 3) in which the house is located, the number of offers made on the house, the square footage, whether the house is made primarily of brick, the number of bathrooms, the number of bedrooms, and the selling price. Neighborhoods 1 and 2 are more traditional neighborhoods, whereas neighborhood 3 is a newer, more prestigious, neighborhood. Use regression to estimate and interpret the pricing structure of houses in Mid City. Here are some considerations. 1. Please draw the plots about Brick vs Price, Nbhd vs Price, Offers vs Price, respectively. Could you judge how Brick, Nbnd and Offers influence the house price? (5 points) 2. Please fill the table below (Hint: You could use the sample selection function in STATA or in the filter function in Excel) (5 points) Price Price Brick without Bricko-kod Mean my Mediamary Standard deviation 95th preventile 3. Is there a "premium" for a brick house, everything else being equal? (5 points) 4. Is there a premium for a house in neighborhood 3, everything else being equal? (5 points) 5. Is there an extra premium for a brick house in neighborhood 3, in addition to the usual premium for a brick house? (Hint: You need to regard an interaction effect) (5 points) 6. For purposes of estimation and prediction, could neighborhoods 1 and 2 be collapsed into a single "older" neighborhood? (5 points) 7. In your opinion, which factors are significant to affect the housing price? (5 points) (Hint: You would use the regression models to solve the questions 3-7. You need to create dummies for the characteristics of house by using STATA, such as brick, neighborhood, etc.)