計量經(jīng)濟學課程設計

1、第1章 引言 我國經(jīng)濟經(jīng)歷了持續(xù)30多年的高速增長，增加了城鄉(xiāng)居民的人均收入。人們在滿足最基本的生活需求的同時，追求高品質(zhì)生活方式是一種必然趨勢。外出旅游是提高生活品質(zhì)的重要方式，被長期壓抑的居民旅游需求將伴隨著其可支配收入的持續(xù)增長得到迅速釋放。 我國旅游業(yè)發(fā)展的階段性特征：我國旅游業(yè)起步較晚，但發(fā)展迅猛，在國民經(jīng)濟中的地位和作用日益加強。新中國成立前，我國經(jīng)濟蕭條，民生凋敝，旅游業(yè)發(fā)展基本停滯，旅游產(chǎn)業(yè)基本沒有形成。建國后到改革開放前的30年間，我國旅游業(yè)主要局限在為外交和民間往來活動服務的入境旅游，國內(nèi)旅游基本是一張白紙。1978年，我國接待入境旅游人數(shù)180萬人，僅占世界的0.7%，居

2、世界第41位；入境旅游收入2.6億美元，僅占全球的0.038%，居世界第47位。1978年黨的十一屆三中全會確立改革開放政策，旅游業(yè)才算真正起步。鄧小平非常重視旅游業(yè)，指出“旅游事業(yè)大有文章可做，要突出地搞，加快地搞?！?0多年來，隨著我國經(jīng)濟持續(xù)快速發(fā)展和居民收入水平較快提高，我國旅游人數(shù)和旅游收入都以年均兩位數(shù)以上的增速持續(xù)發(fā)展，已經(jīng)成國民經(jīng)濟的重要產(chǎn)業(yè)，成為繼住房、汽車之后增長最快的居民消費領域。據(jù)有關資料，2010年，我國旅游業(yè)總收入1.57萬億元，對經(jīng)濟的直接貢獻相當于GDP的2.5%，加上帶動其他產(chǎn)業(yè)，旅游業(yè)對經(jīng)濟的直接和間接貢獻總計相當于GDP的8.6%。旅游業(yè)直接從業(yè)人員135

3、0萬人，加上帶動其他就業(yè)，旅游業(yè)直接與間接就業(yè)總人數(shù)達7600余萬人，約占全國就業(yè)總數(shù)的9.6%。有研究表明，旅游對住宿業(yè)貢獻率超過90%，對民航和鐵路客運業(yè)貢獻率超過80%，對文化娛樂業(yè)貢獻率超過50%，對餐飲業(yè)和商品零售業(yè)貢獻率超過40%，旅游消費對社會消費的貢獻超過10%。目前，我國已經(jīng)躍居全球第四大入境旅游接待國和亞洲第一大出境旅游客源國。第2章 構建并分析模型2.1 相關數(shù)據(jù)表1 模型中所使用的相關數(shù)據(jù)時間國內(nèi)游客（百萬人次）居民消費水平（元）國民總收入（億元）就業(yè)人員（萬人）私人汽車擁有量（萬輛）2000744372198562.272085625.3320017843987108

4、683.472797770.782002878430111976573280968.9820038704606135718.9737361219.23200411025138160289.7742641481.66200512125771184575.8746471848.07200613946416217246.6749782333.32200716107572268631753212876.22200817128707318736.7755643501.39200919029514345046.4758284574.912010210310919407137.8761055938.7120

5、11264113134479576.1764207326.792012295714699532872.1767048838.62013326216190583196.77697710501.682014361117778636727.27725312339.362.2 構建模型對于已有數(shù)據(jù)，建立回歸模型，假設如下：其中 Y 國內(nèi)游客（百萬人次） X1 居民消費水平（元） X2 國民總收入（億元） X3 就業(yè)人員（萬人) X4 私人汽車擁有量（萬輛） 是常數(shù)項 是隨即干擾項2.2.1 散點圖對表1中的數(shù)據(jù)做散點圖，如下： 圖1 相關數(shù)據(jù)的散點圖2.2.2 最小二乘估計Dependent Vari

6、able: YMethod: Least SquaresDate: 06/21/16 Time: 14:19Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  X10.4249760.1334903.1835910.0098X2-0.0052970.002429-2.1805260.0542X30.0685590.0316712.1647300.0557X4-0.0499830.062935-0.7942090.4455C-5273.2422309.

7、879-2.2829080.0456R-squared0.998126    Mean dependent var1785.467Adjusted R-squared0.997377    S.D. dependent var943.6307S.E. of regression48.33183    Akaike info criterion10.85526Sum squared resid23359.66    Schwarz cri

8、terion11.09128Log likelihood-76.41444    Hannan-Quinn criter.10.85275F-statistic1331.653    Durbin-Watson stat1.826495Prob(F-statistic)0.000000圖2 相關數(shù)據(jù)的最小二乘估計模型的估計結果為： (-2.282908) （3.183591) （-2.180526） （2.164730) （-0.794209）=0.998126 =0.997377 F=1331.653 D.W=1

9、.826495第3章 回歸模型的檢驗與修正3.1 回歸模型的統(tǒng)計檢驗 3.1.1 擬合優(yōu)度檢驗由最小二乘估計的結果得到=0.998126 =0.997377 都接近1，擬合優(yōu)度較好。 3.1.2 方程總體線性的顯著性檢驗（F檢驗）當顯著性水平=0.05時，(4,10)=3.48 < 1331.653,模型的線性關系在95%的顯著性水平下顯著成立。3.1.3 變量的顯著性檢驗（T檢驗）當顯著性水平=0.05時，(10)=2.2281，只有變量X1的T檢驗值 的絕對值3.183591>(10)=2.2281,所以四個變量中只有X1 是顯著的。3.2 多重共線性的檢驗與修正3.2.1 簡

10、單相關系數(shù) 表2X1X2X3X4X110.9963030.8504840.988825X20.99630310.8794070.974283X30.8504840.87940710.790268X40.9888250.9742830.7902681變量之間相關系數(shù)較高，說明存在多重共線性。3.2.2 多重共線性的修正采用逐步回歸法：首先對Y 分別與X1,X2,X3,X4 做回歸，結果如下： Dependent Variable: YMethod: Least SquaresDate: 06/21/16 Time: 14:40Sample: 2000 2014Included observati

11、ons: 15VariableCoefficientStd. Errort-StatisticProb.  X10.2001000.00312064.128890.0000C18.5451930.993500.5983570.5599R-squared0.996849    Mean dependent var1785.467Adjusted R-squared0.996606    S.D. dependent var943.6307S.E. of regression54.97016

12、0;   Akaike info criterion10.97502Sum squared resid39282.34    Schwarz criterion11.06943Log likelihood-80.31268    Hannan-Quinn criter.10.97402F-statistic4112.515    Durbin-Watson stat1.473655Prob(F-statistic)0.000000 圖3=18.5

13、4519+0.200100 (0.598357) (64.12889)=0.996849 =0.996606 F=4112.515 D.W=1.473655Dependent Variable: YMethod: Least SquaresDate: 06/21/16 Time: 14:41Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  X20.0051250.00013039.472710.0000C214.791845.960154.6734

14、360.0004R-squared0.991726    Mean dependent var1785.467Adjusted R-squared0.991089    S.D. dependent var943.6307S.E. of regression89.07685    Akaike info criterion11.94044Sum squared resid103150.9    Schwarz criterion12.0

15、3485Log likelihood-87.55331    Hannan-Quinn criter.11.93944F-statistic1558.095    Durbin-Watson stat0.985650Prob(F-statistic)0.000000 圖4=214.7918+0.005125 (4.673436) (39.47271) =0.991726 =0.991089 F=1558.095 D.W=0.985650Dependent Variable: YMethod: Least Squar

16、esDate: 06/21/16 Time: 14:42Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  X30.5545360.0628108.8287410.0000C-39840.174715.757-8.4483100.0000R-squared0.857059    Mean dependent var1785.467Adjusted R-squared0.846064  

17、60; S.D. dependent var943.6307S.E. of regression370.2309    Akaike info criterion14.78970Sum squared resid1781922.    Schwarz criterion14.88410Log likelihood-108.9227    Hannan-Quinn criter.14.78869F-statistic77.94667   

18、 Durbin-Watson stat0.260036Prob(F-statistic)0.000001 圖5=-39840.17+0.554536 (-8.448310) (8.828741)=0.857059 =0.846064 F=77.94667 D.W=0.260036Dependent Variable: YMethod: Least SquaresDate: 06/21/16 Time: 14:43Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.

19、  X40.2463120.00811230.362120.0000C715.733946.1553315.507070.0000R-squared0.986094    Mean dependent var1785.467Adjusted R-squared0.985024    S.D. dependent var943.6307S.E. of regression115.4764    Akaike info criterion12.45958Sum

20、 squared resid173352.3    Schwarz criterion12.55398Log likelihood-91.44681    Hannan-Quinn criter.12.45857F-statistic921.8582    Durbin-Watson stat0.783083Prob(F-statistic)0.000000 圖6=715.7339+0.246312 (15.50707) (30.36212)=0.986094 =0.9850

21、24 F=921.8582 D.W=0.783083其中對Y的擬合優(yōu)度最高，保留作為基變量。將Y關于，做回歸，結果如下： Dependent Variable: YMethod: Least SquaresDate: 06/21/16 Time: 15:09Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  X10.2391440.0522044.5809310.0006X2-0.0010050.001341-0.7493020.4681C-18.3

22、870958.51097-0.3142500.7587R-squared0.996990    Mean dependent var1785.467Adjusted R-squared0.996488    S.D. dependent var943.6307S.E. of regression55.92149    Akaike info criterion11.06263Sum squared resid37526.55    Sc

23、hwarz criterion11.20424Log likelihood-79.96973    Hannan-Quinn criter.11.06112F-statistic1987.172    Durbin-Watson stat1.418274Prob(F-statistic)0.000000 圖7=-18.38709+0.239144-0.001005 (-0.314250) (4.580931) (-0.749302)= 0.996990 =0.996488 F=1987.172 D.W=1.4182

24、74將Y關于，做回歸，結果如下： Dependent Variable: YMethod: Least SquaresDate: 06/21/16 Time: 15:22Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  X10.1939040.00817223.727670.0000X30.0200800.0244240.8221210.4270C-1434.0141767.122-0.8114970.4329R-squared0.997017&#

25、160;   Mean dependent var1785.467Adjusted R-squared0.996520    S.D. dependent var943.6307S.E. of regression55.66850    Akaike info criterion11.05356Sum squared resid37187.79    Schwarz criterion11.19517Log likelihood-79.90172

26、    Hannan-Quinn criter.11.05205F-statistic2005.329    Durbin-Watson stat1.556820Prob(F-statistic)0.000000 圖8=-1434.014+0.193904+0.020080 (-0.811497) (23.72767) (0.822121)= 0.997017 =0.996520 F=2005.329 D.W=1.556820將Y關于，做回歸，結果如下： Dependent Variable: YMethod: L

27、east SquaresDate: 06/21/16 Time: 15:23Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  X10.1966450.0307066.4040850.0000X40.0043000.0380030.1131390.9118C30.37670109.43230.2775850.7861R-squared0.996852    Mean dependent var1785.467A

28、djusted R-squared0.996328    S.D. dependent var943.6307S.E. of regression57.18426    Akaike info criterion11.10729Sum squared resid39240.48    Schwarz criterion11.24890Log likelihood-80.30468    Hannan-Quinn criter.11.10

29、578F-statistic1900.115    Durbin-Watson stat1.476242Prob(F-statistic)0.000000 圖9=30.37670+0.196645+0.004300 (0.277585) (6.404085) (0.113139)=0.996852 =0.996328 F=1900.115 D.W=1.476242由回歸結果可知,的顯著性都小于(10)=2.2281，且的系數(shù)不符合其經(jīng)濟意義，因此只保留作為Y的基變量。 最終的模型為：=18.54519+0.2001003.3 異方差的檢驗與修正3.2.1

30、懷特檢驗 Heteroskedasticity Test: White F-statistic1.496206    Prob. F(2,12)0.2629Obs*R-squared2.993926    Prob. Chi-Square(2)0.2238Scaled explained SS1.614510    Prob. Chi-Square(2)0.4461Test Equation:Dependent Variable: RESID2Method: Least Sq

31、uaresDate: 06/21/16 Time: 16:18Sample: 2000 2014Included observations: 15VariableCoefficientStd. Errort-StatisticProb.  C-2638.8304397.836-0.6000290.5596X11.4543981.0151451.4327000.1775X12-7.69E-054.86E-05-1.5806090.1400R-squared0.199595    Mean dependent var2618.822Adj

32、usted R-squared0.066194    S.D. dependent var3248.257S.E. of regression3138.909    Akaike info criterion19.11799Sum squared resid1.18E+08    Schwarz criterion19.25960Log likelihood-140.3850    Hannan-Quinn criter.19.1164

33、9F-statistic1.496206    Durbin-Watson stat2.502178Prob(F-statistic)0.262941 圖10在=0.05的顯著性水平下，（2）=5.99，=2.993925<5.99,故由懷特檢驗得異方差性不存在。3.2.2 G-Q檢驗（1） 前6組數(shù)據(jù)如下： 表3國內(nèi)游客（百萬人次）居民消費水平（元）74437217843987878430187046061102513812125771做最小二乘估計： Dependent Variable: Y1Method: Least SquaresDate

34、: 06/21/16 Time: 18:09Sample: 1 6Included observations: 6VariableCoefficientStd. Errort-StatisticProb.  X10.2407970.0421375.7146260.0106C-172.0129184.4956-0.9323420.4199R-squared0.915865    Mean dependent var875.6000Adjusted R-squared0.887820    S.D.

35、 dependent var138.7473S.E. of regression46.47103    Akaike info criterion10.80471Sum squared resid6478.669    Schwarz criterion10.64848Log likelihood-25.01177    Hannan-Quinn criter.10.38542F-statistic32.65696    Durbin-

36、Watson stat2.831448Prob(F-statistic)0.010631 圖11（2）后6組數(shù)據(jù)如下： 表4國內(nèi)游客（百萬人次）居民消費水平（元）19029514210310919264113134295714699326216190361117778做最小二乘估計： Dependent Variable: Y2Method: Least SquaresDate: 06/21/16 Time: 18:13Sample: 2010 2014Included observations: 6VariableCoefficientStd. Errort-StatisticProb.&#

37、160; X20.2174500.00468846.386880.0000C-247.799669.08554-3.5868520.0371R-squared0.998608    Mean dependent var2914.800Adjusted R-squared0.998144    S.D. dependent var579.0097S.E. of regression24.94699    Akaike info criterion9.560557Sum

38、 squared resid1867.056    Schwarz criterion9.404333Log likelihood-21.90139    Hannan-Quinn criter.9.141265F-statistic2151.743    Durbin-Watson stat2.222186Prob(F-statistic)0.000022 圖12=4.28,F=6478.669/1867.056=3.4699<4.28,因此由G-Q檢驗得到異方差性不

39、存在。3.4 序列相關性的檢驗與修正3.3.1 D.W 檢驗法由表5可以得到D.W=1.473655，=1.36,=1.08,<1.473655<4-，因此得到一階序列相關性不存在。3.3.2 拉格朗日檢驗一階序列相關性的檢驗如下：Breusch-Godfrey Serial Correlation LM Test:F-statistic0.791936    Prob. F(1,12)0.3910Obs*R-squared0.928636    Prob. Chi-Square(1)0.3352Tes

40、t Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 06/27/16 Time: 16:10Sample: 2000 2014Included observations: 15Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.  X0.0003380.0031680.1067200.9168C-2.38961731.35971-0.0762000.9405R

41、ESID(-1)0.2549190.2864560.8899080.3910R-squared0.061909    Mean dependent var6.25E-14Adjusted R-squared-0.094439    S.D. dependent var52.97057S.E. of regression55.41540    Akaike info criterion11.04445Sum squared resid36850.40    Schwarz criterion11.18606Log likelihood-79.83337    Hannan-Quinn criter.11.04294F-statistic0.395968    Durbin-Watson stat2.027080Prob(F-statistic)0.681506 圖13（1）