Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year, and obtains the regressions results in the table shown below. This table is used for Questions 1-6. Dependent variable: In(Price) Regressor (1) (2) (3) (4) (5) Size 0.00042 (0.000038) 0.57 (2.03) 0.69 (0.055) In(Size) 0.69 (0.054) 0.68 (0.087) In(Size)² 0.0078 (0.14) Bedrooms 0.0036 (0.037) 0.082 (0.032) 0.071 (0.034) 0.071 (0.034) 0.071 (0.036) 0.071 (0.035) Pool View 0.037 0.027 0.026 0.027 0.027 (0.030) (0.029) (0.028) (0.026) (0.029) Pool x View 0.0022 (0.10) 0.13 (0.045) 0.12 (0.035) 0.12 (0.035) Condition 0.12 (0.036) 0.12 (0.035) Intercept 10.97 6.60 (0.39) 6.63 (0.53) 7.02 (7.50) 6.60 (0.069) (0.40) Summary Statistics SER 0.102 0.098 0.099 0.099 0.099 R² 0.72 0.74 0.73 0.73 0.73 Variable definitions: Price = sale price ($); Size = house size (in square feet); Bedrooms = number of bedrooms; Pool = binary variable (1 if house has a swimming pool, O otherwise); View = binary variable (1 if house has a nice view, 0 otherwise); Condition = binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). A family purchases a 2000 square foot home and plans to make extensions totalling 500 square feet. The house currently has a pool, and a real estate agent has reported that the house is in excellent condition. However, the house does not have view, and this will not change as a result of the extensions. According to the results in column (1), what is the expected DOLLAR increase in the price of the home due to the planned extensions? (Report your answer to the nearest dollar and do not include any commas or $ signs.)
Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year, and obtains the regressions results in the table shown below. This table is used for Questions 1-6. Dependent variable: In(Price) Regressor (1) (2) (3) (4) (5) Size 0.00042 (0.000038) 0.57 (2.03) 0.69 (0.055) In(Size) 0.69 (0.054) 0.68 (0.087) In(Size)² 0.0078 (0.14) Bedrooms 0.0036 (0.037) 0.082 (0.032) 0.071 (0.034) 0.071 (0.034) 0.071 (0.036) 0.071 (0.035) Pool View 0.037 0.027 0.026 0.027 0.027 (0.030) (0.029) (0.028) (0.026) (0.029) Pool x View 0.0022 (0.10) 0.13 (0.045) 0.12 (0.035) 0.12 (0.035) Condition 0.12 (0.036) 0.12 (0.035) Intercept 10.97 6.60 (0.39) 6.63 (0.53) 7.02 (7.50) 6.60 (0.069) (0.40) Summary Statistics SER 0.102 0.098 0.099 0.099 0.099 R² 0.72 0.74 0.73 0.73 0.73 Variable definitions: Price = sale price ($); Size = house size (in square feet); Bedrooms = number of bedrooms; Pool = binary variable (1 if house has a swimming pool, O otherwise); View = binary variable (1 if house has a nice view, 0 otherwise); Condition = binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). A family purchases a 2000 square foot home and plans to make extensions totalling 500 square feet. The house currently has a pool, and a real estate agent has reported that the house is in excellent condition. However, the house does not have view, and this will not change as a result of the extensions. According to the results in column (1), what is the expected DOLLAR increase in the price of the home due to the planned extensions? (Report your answer to the nearest dollar and do not include any commas or $ signs.)
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
Related questions
Question
Transcribed Image Text:QUESTION 1
Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year, and obtains the regressions results in the table shown below. This table is
used for Questions 1-6.
Dependent variable: In(Price)
Regressor
(1)
(2)
(3)
(4)
(5)
0.00042
(0.000038)
Size
In(Size)
0.57
(2.03)
0.69
0.68
0.69
(0.055)
(0.054)
(0.087)
In(Size)²
0.0078
(0.14)
Bedrooms
0.0036
(0.037)
Рol
0.082
0.071
0.071
0.071
0.071
(0.032)
(0.034)
(0.034)
(0.036)
(0.035)
0.037
0.027
0.026
0.027
0.027
(0.030)
View
(0.029)
(0.028)
(0.026)
(0.029)
Pool x View
0.0022
(0.10)
0.12
(0.035)
Condition
0.13
0.12
0.12
(0.035)
0.12
(0.045)
(0.035)
(0.036)
6.63
(0.53)
Intercept
10.97
6.60
7.02
6.60
(0.069)
(0.39)
(7.50)
(0.40)
Summary Statistics
SER
0.102
0.098
0.099
0.099
0.099
R?
0.72
0.74
0.73
0.73
0.73
Variable definitions: Price = sale price ($); Size = house size (in square feet); Bedrooms = number of bedrooms; Pool = binary
variable (1 if house has a swimming pool, 0 otherwise); View = binary variable (1 if house has a nice view, 0 otherwise); Condition =
binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise).
A family purchases a 2000 square foot home and plans to make extensions totalling 500 square feet. The house currently has a pool, and a real estate agent has reported that the house is in
excellent condition. However, the house does not have a view, and this will not change as a result of the extensions.
According to the results in column (1), what is the expected DOLLAR increase in the price of the home due to the planned extensions? (Report your answer to the nearest dollar and do
not include any commas or $ signs.)
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 3 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, economics and related others by exploring similar questions and additional content below.Recommended textbooks for you
Principles of Economics (12th Edition)
Economics
ISBN:
9780134078779
Author:
Karl E. Case, Ray C. Fair, Sharon E. Oster
Publisher:
PEARSON
Engineering Economy (17th Edition)
Economics
ISBN:
9780134870069
Author:
William G. Sullivan, Elin M. Wicks, C. Patrick Koelling
Publisher:
PEARSON
Principles of Economics (12th Edition)
Economics
ISBN:
9780134078779
Author:
Karl E. Case, Ray C. Fair, Sharon E. Oster
Publisher:
PEARSON
Engineering Economy (17th Edition)
Economics
ISBN:
9780134870069
Author:
William G. Sullivan, Elin M. Wicks, C. Patrick Koelling
Publisher:
PEARSON
Principles of Economics (MindTap Course List)
Economics
ISBN:
9781305585126
Author:
N. Gregory Mankiw
Publisher:
Cengage Learning
Managerial Economics: A Problem Solving Approach
Economics
ISBN:
9781337106665
Author:
Luke M. Froeb, Brian T. McCann, Michael R. Ward, Mike Shor
Publisher:
Cengage Learning
Managerial Economics & Business Strategy (Mcgraw-…
Economics
ISBN:
9781259290619
Author:
Michael Baye, Jeff Prince
Publisher:
McGraw-Hill Education