求帮忙做一道关于计量经济学多元回归的英文大题

答案用中英文皆可 认真回答就给确认悬赏 谢谢！

1.You wish to predict the sale price of single-family residences in Massachusetts using property features (commonly called a “hedonic pricing model”).  You collect price and property features data on properties sold in the state for the year 2010 and obtain the following regression:
Pricei = 14407.60 – 759.92*houseagei + .24*lotsizei + 354.35*bldareai + 12015.61*roomsi + μi
              (6433.23)   (89.67)                       (.115)              (265.39)                   (8516.47)

Observations = 2691         R2 = 0.49             F = 65.10
Where:
        houseage = age of the house (in years)
lotsize = total square feet of the land
        bldarea = total square feet of the interior of the house
        rooms = total number of rooms in the house

A.How would you categorize, or label, this dataset?  Defend your answer.

B. What is the interpretation of the constant term in this regression?  Why is it included?

C.How do we interpret the coefficient on lotsize? Why is the coefficient on lotsize nominally small if we expect it to have a large impact on the price of a house?

D.What is the predicted price of a house that is 7 years old, with a lot size of 800 square feet, a building interior of 400 square feet, and 5 rooms?  Will this predicted price be close to the actual price?  Why or why not?

E.Explain what is meant that the value of the R2 = .49.  What is one good reason and one bad reason to use R2 as a measure of the “goodness of fit” of a regression?

F.Test the significance of each independent variable in the model using α = .05.  Are these findings expected?  Why or why not, and what could explain your findings?

G.Construct a 95% confidence interval for houseage in the model above.  What this measure is telling us?  How will consistency in your OLS estimation affect your confidence intervals?

H.After thinking about your model further, you wish to add median income as variable in your regression.  You collect data on the median income of each census tract in Massachusetts in the year 2010, and match that to your housing data.  Assuming you believe that your original form of the model suffered from omitted variable bias, in what direction would you expect your estimates to change with the inclusion of median income?  Defend your answers.

I.Suppose you ran the same model as above only using log(price) instead of price and obtain an R2 of 0.54 and an F-statistic of 68.17.  Based on this information, are we able to say which version (level or log) of the model is better?  Explain why or why not.

1.如何给这个数据集定义标签，并解释
a.编辑数据库，然后对变量进行双击，打开变量定义窗口，在value label下面点击define/modify，打开值标签定义窗口，若生成新的值标签，则先点击窗口左下方的define，打开值标签命名窗口，输入名称，点击OK，然后开始输入“值”（即数字化的分类资料，如1、2、3……）和“值标签”（表示的分类资料的各个属性，如性别中的“男”、“女”或血型中的“A”、“B”、“O”、“AB”等），点击OK，直至定义完成。

b.语法定义：

label value varname labelname

label define labelname 1 "male" 2 "female"

亦可完成定义。

若定义多个相同变量值标签，则只需重复label value varname(2、3、4、……) labelname即可。


2.回归中连续的解释变量，并解释

lotsize  bldarea  都是，因为它们表示的是面积（自己再补充两句，我就是答重点）

3.如何解释lotsize的系数，为什么lotsize的系数表面上看比较小
lotsize增大一平方英尺，房价上升0.24美元，它表面上看比较小我觉得是因为bldarea与lotsize高度相关，所以bldarea分担了lotsize的一部分影响（这句话好像有点别扭，但我不知道该怎么组织语言了）

4.hosehold=7,lotsize=800,bldarea=400,rooms=5,求price的预测值
这个自己带下公式吧，我觉得预测值应该是否可信应该是要求预测值在95%的置信水平下的p值，但是我忘了怎么求了，伍德里奇的书上有，我回去翻翻再补充

先答这么多，你的题太多了，我一次没答完，回去再继续

这种问题最好是看课本问你的TA或是找老师请教。不然别人给说了答案自己也不理解

dorisdaidai 发表于 2016-2-15 17:05
1.如何给这个数据集定义标签，并解释
a.编辑数据库，然后对变量进行双击，打开变量定义窗口，在value labe ...

好的 谢谢回答 答全了马上设置最佳

后半部分在txt里，有些解释的我懒得打了，就把课本名称和页码发给你了，可以自己看下，书上讲的很明白

dorisdaidai 发表于 2016-2-16 17:30
后半部分在txt里，有些解释的我懒得打了，就把课本名称和页码发给你了，可以自己看下，书上讲的很明白

多谢认真回答 请问你的计量经济学是中文版的第几版的

cosmarthon 发表于 2016-2-17 02:06
多谢认真回答 请问你的计量经济学是中文版的第几版的

第四版

为什么还显示的未解决啊？

dorisdaidai 发表于 2016-2-26 11:00
为什么还显示的未解决啊？

不好意思 我明明记得我上次设置了的
很久没看论坛了
刚刚设置了