代做ETF2100/5910 Introductory Econometrics Assignment 1代写留学生Matlab语言程序

ETF2100/5910 Introductory Econometrics

Assignment 1 — A Case Study on the House Price of Stockton California

Important notes:

1. This is an individual assignment. The calculation and plotting required below have to be done using R. Once you have all results ready, report them properly in a word or pdf file. All of your solutions need to be typed properly. No hand writing is allowed when answering the questions.

2. This assignment is worth 20% of this unit’s total mark. Marks will be deducted for late submission on the following basis: 10% for each day late, up to a maximum of 3 days. Assignments more than 3 days late will not be marked.

3. Submission deadline for coursework is 11:55pm Friday of Week 7 (i.e., 19/Apr/2024). Please submit a soft copy through Moodle. Pdf file is preferred, but word file is also fine. On the title page, please provide your student ID and name correctly, and submit your R script. as well.

4. Notation used in the assignment needs to be typed correctly and properly. Incorrect (or inconsistent) notations are treated as wrong answers.

Please pay attention to the words in bold.

There are many observations on houses sold from 1999-2002 in Stockton California in the file “hedonic1.xls”.

Question 1: (10 marks in total) Use the data of 1999 and 2000 only to estimate the next linear model and answer the associated questions below.

SP = β1 + β2 Age + u,                (1)

where u is an error term. Note that the sub-index i of each variable has been suppressed in the above equation. SP = Selling Price, which is a function of Age (in years).

1. (a). Generate the descriptive statistics for SP and Age (i.e., 2 VARIABLES IN TOTAL), and report them in a table. (1 point)

(b). Plot SP (y-axis) against Age (x-axis). Do you observe any pattern? (1 point)

2. Estimate the model (1) for the houses sold in Stockton California.

(a). Write down the estimated model (including estimates of the coefficients and the associated standard deviations), and comment on the estimation result using Goodness of fit. (2 points — 1 points for reporting the results properly, and 1 point for commenting on Goodness of fit correctly)

(b). Plot the estimated error terms, and calculate the mean squared errors (i.e., ). (2 points — 1 point for plotting, and 1 point for mean squared errors)

3. At the 5% significance level, test if Age has NEGATIVE impacts on SP. Keep two decimals for the calculation involved. (4 points)

Question 2: (10 marks in total) Use the data of 2001 only to estimate the next linear model and answer the associated questions below.

log(SP) = β1 + β2 Baths + u,                        (2)

where u is an error term. Note that the sub-index i of each variable has been suppressed in the above equation.

1. (a). Generate the descriptive statistics for log(SP) and Baths (i.e., 2 VARIABLES IN TOTAL), and report them in a table. (1 point)

(b). Plot log(SP) (y-axis) against Baths (x-axis). Do you observe any pattern? (1 point)

2. Estimate the model (2) for the houses sold in Stockton California.

(a). Write down the estimated model (including estimates of the coefficients and the associated standard deviations), and comment on the estimation result using Goodness of fit. (2 points — 1 points for reporting the results properly, and 1 point for commenting on Goodness of fit correctly)

(b). Plot the estimated error terms, and calculate the mean squared errors (i.e., ). (2 points — 1 point for plotting, and 1 point for mean squared errors)

3. At the 5% significance level, test if Baths has POSITIVE impacts on log(SP). Keep two decimals for the calculation involved. (4 points)