## Assignment 1

###  Instructions: 计量经济学代考

– Answer the question by yourself. The assignment is open-book. Make sure you read, understood and comply with the University of Sydney Academic Honesty in Coursework Policy 2015 and the Academic Honesty Procedures 2016.
– Submit your typed answers to this assignment question on Canvas in a single PDF file. Attach a copy of your computer output (e.g. your STATA log) at the end of your answers (as an appendix, not in a separate file).
– Please set the PDF file name as ECMT6002A1-SID, or ECMT6702A1-SID (for students who take ECMT6702). Also put your SID on the first page of your answer book. Before submission, make sure that the pdf document is fully readable.
– Note: for hypothesis testing, present the complete hypothesis test, including null and alternative hypotheses, test statistics and its distribution under the null, decision rule and conclusion.
– Total marks: 100 (accounting for 10% of the total mark).

 Note: For this assignment, HPRIC3 contains observations for 321 houses sold in 1978 and 1981. For all the questions, if your SID ends with an even number (that is, the last digit of your SID is a even number, including 0), please use the observations from 1978 only; If your SID ends with an odd number, please use the observations from 1981 only.

### 1. We are interested in estimating hedonic pricing models of real estate market. The model is specified as follows 计量经济学代考

log(price) =β0 + β1rooms + β2baths + β3 log(area) + β4 log(land) + β5age + β6age2 + β7 log(cbd) + u, (1)

where price is the house selling price measured in dollars, rooms is the number of bedrooms, baths is the number of bathrooms, area is the interior size of the house, land is the land size, age is the age of house, cbd is the distance to central business district (CBD); see also the variable description.

Estimate model (1) by OLS and report the results before part (a) in the usual form (the equation with coefficients estimated and the standard errors, R2 , sample size). Note: Do not copy and paste the software output of estimation here, which should be put into the appendix. Make sure you use the right subset of the data for regression, which depends on the last digit of your SID.

(a) Report the summary statistics (sample mean, standard deviation, minimum and maximum values) for the variables in (1) in a table.

(b) Based on model (1), what is the interpretation of the coefficient β3? What sign of β3 do you expect? Explain briefly.

(c) Based on the estimation results, holding other factors constant, what is the partial effect of one extra bathroom? Is 100βˆ 2% a good approximation to the effect? Explain briefly.

(d) Based on the estimation results, calculate the 95% confidence interval for β4. Is the value of 0 within the 95% confidence interval, and what is the implication?

#### (e) Based on the estimation results, test H0 : β7 = 0 against H1 : β7 < 0 using a 10% significance level. Briefly explain the test result. 计量经济学代考

(f) Why age2 is also included in the model along with age? Based on the estimation results, holding other regressors constant, what is the age of house that leads to the lowest price?

(g) We want to confirm that the age of houses does affect pricing. Test the hypothesis that age and age2 are jointly insignificant in determining log(price), holding other regressors constant. Use a 1% significance level.
(h) We are concerned that the error u may not be homoskedastic. Perform the Breusch-Pagan test to address the concern. Use a 5% significance level

(i) If cbd were dropped from the regression (and be part of the error term), which regressor (or regressors) could be endogenous? Explain briefly (some common sense is sufficient).

(j) If buyers prefer houses with more bedrooms but do not like the bedrooms to be tiny, what kind of model you would propose? Explain briefly. You may modify equation (1) to suit your argument. Estimate the proposed model and verify the new model does capture the preference of buyers.
Note: 10 points for each part, 100 in total. 计量经济学代考  QQ在线咨询

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