计量经济学第五六章作业

1、百度文库让每个人平等地捉升口我各地区农村居民家庭人均纯收入与家庭人均生活消费支出的数据（单位：元）（1）试根据上述数据建立2007年我国农村居民家庭人均消费支出对人均纯收入的线性回归 模型。（2）选用适当方法检验模型是否在异方差，并说明存在异方差的理由。（3）如果存在异方差，用适当方法加以修正。答：散点图线性回归分析图O Equation： UNTITLEDWorkffle： UNTITLED：:Untitled 卩口 回歯JMew|Proc|object| Prht|Ndme|Free?e| esthiate|Fo(ecdst|stats|Re$ds|Dependent Variable:

2、XMethod: Least SquaresDaw: 10/18/14 Time: 18:20Sample: 1 31Included observations 31VariableCoefficientStd. Errort-StatisticProbC T179.191607195D0221.57750.8087090 04570015.744110.4253 0 0000R-squarea Adjusted R-squared S.E. of regression Sum squared rssid Log likelihood F-statisticProb(F-stat) Stic)

3、0.8952500.891649493.62407066274. -2352084247.87590.000000Mean aGponaont/ar S.D. dependent var AKaiKe info criterion Schwarz criterion Hannan-Ouinn criter Durbin-Watscn stat3376.309 1499512 15.3037715.3962815.333921.473596由图建立样本回归函数左二+r2= Graph: UNTITLED Workfile: UNnTLED:Untitled&：有1辰虫w| Pro:| Objec

4、tj Print| Name AddTextlbnehacfe | RerroveT expiate | Optons | Zcon |由图形法可看岀残差平方随如的变动呈增大趋势，但还需进一步检验.White检验Z) Equation: UNTITLEDWorkfile: UNnTLED:Untitled | o | 回Vew|Proc|Objcct| Frint| None (Freeze | Estimate Forecast State |Rcsids|HeterosKedasticity Test: v/hite IF-slatistic1.859145Prob. F(2,10h0 2

5、059Obs*R-$quared3.623601Prob. Chi-Square(2)01717Scaled explained SS4.685299Prob Chi-Square(2)0 0961TestEquato n:Dependent Variable: RESIDA2Method: Least SquaresData 10/18/U Time: 22:27sample 19 31In eluded observations: 13VariableCoefficient Std. Error t-Statistic Prob.C-2455770.2773615-0 88E4040 39

6、67T738.598787274020.84629804172TA2-0.0400410.032834-0.6372500 5383由上述结果可知，该模型存在异方差，理由是从数据可看出一是截而数据，看出各省市经济发 展不平衡3）用加权最小二乘法修正，选用权数wlw2=4w3哉则XTlv j TirA mpl0r； 1 3*1 IcejdAd o*七 WcMgrtting sonosr W3ia. 231V4iriatlOomciAntStd. Errort-&tatottcRrotc X7G7.2O47-173.GG44.S32S340.066731l4O7-46O OOC O.OOCwagm

7、odStGrtioticoR-ouoroddjutod R.-aquarod S.E of rogro&oion Sum oQin -Wocoon etneQ.&MiWCSU0.944200219&N .482730rvioon cKpondont vor S .D. doponont var /KKciiKo into crttorion SoKwars 2rkorion F stotisttcRrokKP ot dt iotio)N 73.0(；14 2SNi4.227610-1.498O.OOOOC(JnwaigHted StatiacicaR-o)Lior9l&.巴 /ar S L.

8、depvrxSwrU vr ftuirr OQuorcd ro&d散点图回归结果匕ndioaie52汛9*|心“”|Dependent Variable: YMethod Least SquaresDate: 10/23/14 Time: 1823Sample: 1978 2011Included observations: 34VariableCoefficientStd. Error卜 StatisticProbC92.5544342.805572.1G22050.0382X0.7462430.01912039.030100.0000R-squared0.979425Mean depend

9、enivar1295.805Adjusted R-SQuared0.978783s.D deoendenivar1188 794S E of regression173.1908AKaike info criterion13 20334Sum squared resid9595096Schwarz aitenon13 29313Loo likelihood-2224558Hannan-Quinn alter.13 23396F-$tausnc1523 349Duran-watson stai1534480ProQ(F-statistic)OOOOOOOGoldfield-quanadt 检验L

10、J tquation: uzill Ltu woncrne: UN uiLtu：unt(tiea o | 凹 View|Prodobject| Print NameFreeze| Estimate|Forucost| Stats|Rc5ids|Dependent YariaDle: YMethod: Least SquaresCate: 10/23/14 Time: 18:37Sample: 113Included obseivations: 13variaoiecoemcientstd. Error t-statisticProD.C-18 868618 963780-21049840 05

11、91X0.9678390.0268793S.007710.0000R-squared0.991587Mean dependentyar280.1377Adjusted R-squared0.990823S.D. dependent var127.0409S.E. of rsaression1217039Akaike info entericn7.976527Sum squared resid1629.301SchwarzcritGri cn8.053442Log likelihood4984742Hannon -Quin n crite 匚7.958662F-stati 引 ic1296.55

12、5Durbin-Watson stat1.071505ProD(F-statistic)0.000000feiv|ProdObject| Priit| Name | Freeze | Estimate | Forecast | Stats | Resids | Dependentvariable: YMethod: Least SquaresDate: 10/23/14 Time: 18:44sample: 22 34In eluded obsRations: 13VariableCoefficientStd Error StatisticProbC179.4058202.87770.8843

13、050.3954X0.7195660.05831212.339890.0000R-SQuared0.932628Meandependentvar2496.135Adjusted R squared0.926503S.D. dependent var1022.590s.E. or regression277.2268Aaike inro criterion1422819Sum squared resid845401.5Schwarz criterion1431510Log likelihood-90.48321Hannan-Q uinn criter1421032F-statistic152.2

14、728Durbin-Watson stat1.658399Prob(F-statistic)0.00000010所以模型存在异方差ViewpodObject Pnnt|NaniG|FrBezQ| Estmate|Forccastl Stats ResdsjDependent Vari abl e Y Meincd: Least squares Date: 10/23/14 Time: 18:57 Sample 1 34Included observations: 34Weighing series: W3VariableCoefficient Std. Error t-Statistic Pr

15、cb.C&3906693.6042992.4667400.0192X0 8521930 02015042293380 0000Weighted StatisticsR-scuaredAdjusted R-squ area S.E. of regression Sum squared res id Log likelihood F-statistic0.9824250.98187516.202728400 904-141.90941788 730Mean dependentvar S.D. aependentvr Akaike info aiterionSchwarz critefion Han

16、narrQuinn enter. Durbin-Watson sta123024342478 5550W8.495878 0604648 J Lt检验，F检验显著t= ( ) ( ) R2 = , dw=,f=剔除价格变动因素后的回归结果如下下表是北京市连续19年城镇居民家庭人均收入与人均支出的数据。表略(1) 建立居民收入一消费函数；残差图Dependent variaDie：Y Method: Least Squares Date: 10/25/U Time: 22:38 Sample: 1 19In eluded ooservati ent: 19Variabl

17、eCoefficientSid Errort-StatisticProb.C79.9300412.399196 4463900.0000X0 6904220 012877536206BoooooR-squared0.994122blxn dope ndent 归 r700.2747Adjusted R-sauared0.993776s.D. aeoendentvar246.4491S.E. ofregression19.44245Akaike info criteriGn8.972095Sum squared resid6426.149Schwarz criterion8.971510Log

18、likelihood82.28490Hannan-Quinn criler.3.888920F-s tali Stic2875.178Durbin-Watson stat0.574663Proo(F-statistic)0.000000#= 79.930+0.690/Se = (12.399)(0.013)t = (6.446) (53.621)R2 = 0.994 DIV =0.575（2）检验模型中存在的问题，并采取适当的补救措施预以处理：（2）DW=,取 tz = 5%,查 DW 上下界乙=1& dLi = 1.40,0.000000最小二乘法估汁回归模型为i3002527+XSe=R2

19、 二 F= DW=View Froc Object | Print | Name I Freeze 11 Estimate | Forecast | Stats Resids|Breusch-Godfrey Serial Correlation LM Test:F-statistic22.78058Prob. F(2,22)0.0000Obs*R-squared17.53360Prob. Chi-Square(2)0.0002Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 10/25/14 Time: 21:1

20、1Sample: 1981 2006inciuaea oDser*atio ns: 26Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.C2.959362180.26060.0164 仃0.9870X-0.0023630.040873-0.0578110.9544RESID(-1)1.1299130.1874226.0286980.0000RESID(-2)-0.4964920.192408-2.5804160.0171R-squared0.674

21、369Mean dependentvar1.27E-12Adjusted squared0 629965S D dependontvar820 6466S.E. of regression4992036Akaike info criterion15.40454Sum squared resid5482492.Schwarz criterio n15.59810Log likelihood-1962591Hannan-Quinn criter.15.46028F-statistic15.18705Durbin-Watso n stat1.978124Prob(F-statistic)0.0000

22、14LM=TZ?2=26*= P值为t检验和F检验不可信。所以需要补救广义差分法用科克伦奥科特迭代法Dependent Variable: YMethod: Least SquaresDate: 10/25/14 Time 21:54Sample (adjusted): 1983 2006In eluded observato ns: 24 after adjustments Convergence achieved after 15 iterationsVariableCoefficientStd Errort-StatisticProbC-2020.2802019.372-1.000450

23、03290X0.0914160.0349762.61369600166PR1.3033790.2151085.059178oooooAR-0.2712550.224475-1.20839802410squared Adusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic ProD(F-statlstic)09992290.99911484.54348142952.0-138.35108644.0330.000000Mean dependantwr S.D. dependent var Ak

24、aike info criterion Schwarz criterion Hannan -Quin n criter. Curbi nWatso n stat7642 2002839.89611.8634212.0597611.915511.731745Inserted AR Roots104.26Estimated AR process is nonstationaryse= ( ) ( ) t=()()R?二F= DW= 所以美国国内生产总值每增加10亿美元，股票价格指数增加下表给出了某地区1980-2000年的地区生产总值（X）与固宦资产投资额（X）的数据表略要求：（i）使用对数线性模

25、型 biYI=/3+/32biX!+ut进行回归，并检验回归模型的自相关性；（2）采用广义差分法处理模型中的自相关问题。（3）令X；（固定资产投资指数），Y； =Yt/Y （地区生产总值增长指数），使用模型LnY；=伏+佚LnX； +*，该模型中是否有自相关?答:散点图如下1 1 1 1 Dependent variable: LNYMethod: Least SquaresDate: 10/25/14 Time: 22:14Sample: 1980 2000included oDseanons: 21VariableCoefficientStd Errort-StatisticProb.c2

26、.1710410.24102590075290.0000LNX0.9510900.03889724.451230.0000R-scuared0.959199Mean dependent yar8.0393D7Adjusted R-s qua red0957578S D dependentvar0.565486S.E. ofregressi on0.101822Akaike info criterio n-1.6407B5Sum squared resid0.196987Schwarz criterion-1.541307LcgiiKeiincod19.22825Hannan-Quinn criter.-1.61919