EVIEWS 操作 實(shí)驗(yàn)題目： 多重共線性實(shí)驗(yàn)類型： 基本操作實(shí)驗(yàn)?zāi)康模?掌握利用Eviews進(jìn)行多元線性回歸；存在多重共線性的基礎(chǔ)上掌握逐步回歸法的基本操作；及方差擴(kuò)大因子的計(jì)算方法。實(shí)驗(yàn)內(nèi)容：（按要求完成下面題目）4.6 理論上認(rèn)為影響能源消費(fèi)需求總量的因素主要有經(jīng)濟(jì)發(fā)展水平、收入水平、產(chǎn)業(yè)發(fā)展、人民生活水平提高、能源轉(zhuǎn)換技術(shù)等因素。為此，收集了中國(guó)能源消費(fèi)總量Y (萬(wàn)噸標(biāo)準(zhǔn)煤)、國(guó)內(nèi)生產(chǎn)總值(億元)X1(代表經(jīng)濟(jì)發(fā)展水平)、國(guó)民總收入(億元)X2(代表收入水平)、工業(yè)增加值(億元)X3、建筑業(yè)增加值(億元)X4、交通運(yùn)輸郵電業(yè)增加值(億元)X5(代表產(chǎn)業(yè)發(fā)展水平及產(chǎn)業(yè)結(jié)構(gòu))、人均生活電力消費(fèi) (千瓦小時(shí))X6(代表人民生活水平提高)、能源加工轉(zhuǎn)換效率(%)X7(代表能源轉(zhuǎn)換技術(shù))等在1985-2002年期間的統(tǒng)計(jì)數(shù)據(jù)，具體如下：年份能源消費(fèi)國(guó)民總收入工業(yè)建筑業(yè)交通運(yùn)輸郵電人均生活電力消費(fèi)能源加工轉(zhuǎn)換效率yX1X2X3X4X5X6X71985766828989.18964.43448.7417.9406.921.368.2919868085010201.410202.23967.0525.7475.623.268.3219878663211954.511962.54585.8665.8544.926.467.4819889299714922.314928.35777.2810.0661.031.266.5419899693416917.816909.26484.0794.0786.035.366.5119909870318598.418547.96858.0859.41147.542.467.2199110378321662.521617.88087.11015.11409.746.965.9199210917026651.926638.110284.51415.01681.854.666199311599334560.534634.414143.82284.72123.261.267.32199412273746670.046759.419359.63012.62685.972.765.2199513117657494.958478.124718.33819.63054.783.571.05199613894866850.567884.629082.64530.53494.093.171.5199713779873142.774462.632412.14810.63797.2101.869.23199813221476967.278345.233387.95231.44121.3106.669.44199913011980579.482067.535087.25470.64460.3118.170.45200013029788254.089468.139047.35888.05408.6132.470.96200113491495727.997314.842374.66375.45968.3144.670.412002148222103935.3105172.345975.27005.06420.3156.369.78資料來(lái)源：中國(guó)統(tǒng)計(jì)年鑒2004、2000年版，中國(guó)統(tǒng)計(jì)出版社。要求：(1)建立對(duì)數(shù)線性多元回歸模型(2)如果決定用表中全部變量作為解釋變量，你預(yù)料會(huì)遇到多重共線性的問(wèn)題嗎？為什么？(3)如果有多重共線性，你準(zhǔn)備怎樣解決這個(gè)問(wèn)題？明確你的假設(shè)并說(shuō)明全部計(jì)算。實(shí)驗(yàn)步驟：一、設(shè)定模型Y=0+1X1+2X2+3X3+4X4+5X5+6X6+7X7+u二、估計(jì)參數(shù)1、各解釋變量的相關(guān)系數(shù)矩陣：X1X2X3X4X5X6X7X11.0000000.9999780.9996710.9988680.9918430.9934890.722545X20.9999781.0000000.9997280.9989480.9912510.992990.725681X30.9996710.9997281.0000000.9989830.9909460.9921480.732289X40.9988680.9989480.9989831.0000000.9878390.9888740.737354X50.9918430.9912510.9909460.9878391.0000000.9988290.682852X60.9934890.992990.9921480.9888740.9988291.0000000.680992X70.7225450.7256810.7322890.7373540.6828520.6809921.000000 可以看出，各解釋變量之間的相關(guān)系數(shù)較高，證明存在多重共線性。2、分別做Y對(duì)X1、X2、X3、X4、X5、X6、X7的一元回歸，結(jié)果如下：變量X1X2X3X4X5X6X7參數(shù)估計(jì)值0.6249740.6128461.3700078.80594910.14708464.97116689.491t統(tǒng)計(jì)量10.1548110.101639.6781139.8925998.7409639.3166753.023597R20.8656820.8644560.8541020.8594810.8268480.8443590.363618修正后的R20.8572870.8559850.8449840.8506980.8160260.8346310.323844 其中，加入X1的方程修正后的R2最大，以X1為基礎(chǔ)，應(yīng)順次加入其它變量步回歸。3、加入變量逐步回歸。結(jié)果如下:X1X2 X3 X4修正后的R2X1、X210.28141（-1.116582）-9.475974（-1.048732）0.858172X1、X36.684434（-3.479306）-13.3771（-3.15504）0.908496X1、X41.30268（0.983296）-9.59419（-0.850389）0.850389X1X5X6X7修正后的R2X1、X51.179318(2.470651)-9.285(-1.17089)0.860521X1、X60.906371(1.638631)-213.371(-0.51207)0.850388X1、X70.695311(7.861804)-1607.71(-1.10068)0.859149 可看出，加入X3的方程修正后的R2=0.908496，改進(jìn)最大，而且t檢驗(yàn)顯著，所以保留X3在進(jìn)行其他新變量逐步回歸，結(jié)果如下：X1X2X3X4修正后的R2X1、X3、X25.430737（0.69231）1.397928（0.165208）-13.75428（-2.782426）0.902151X1、X3、X46.493408（3.239566）-14.2539（-3.05389）8.327015（0.516298）0.903792X1X5X3X6X7修正后的R2X1、X3、X58.16383（4.50398）-13.22339（-2.298483）-14.90018（-3.923403）0.928821X1、X3、X68.865468（4.346008）-16.3046（-3.97593）-648.286（-2.0569）0.924712X1、X3、X77.302892（3.106956）-14.81073（-2.812505）707.1907（0.483645）0.903571 在X1、X3的基礎(chǔ)上加入X5后修正后的R2增大，t檢驗(yàn)都通過(guò)，保留X5在進(jìn)行其他新變量逐步回歸，結(jié)果如下：X1X2 X3X4X5修正后的R2X1、X3、X5、X225.51688（2.960009）-18.1294（-2.05021）-11.1351（-2.86458）-23.0032（-3.26329）0.942074X1、X3、X5、X48.491949（4.262976）-14.2715（-3.4544）-7.49693（-0.46926）-14.619（-2.20652）0.924622X1X3X5X6X7修正后的R2X1、X3、X5、X68.030362（3.539131）-14.6622（-3.22677）-14.9044（-0.87292）95.57242（0.105081）0.92341X1、X3、X5、X77.922042（3.754384）-14.2592（-3.03983）-13.782（-2.16713）-347.945（-0.25055）0.923714 在X1、X3、X5的基礎(chǔ)上加入X2后修正后的R2增大，t檢驗(yàn)都通過(guò)，保留X2在進(jìn)行其他新變量逐步回歸，結(jié)果如下：X1X2X3X4X5修正后的R2X1、X2、X3、X5、X427.52311(3.076038)-19.62574(-2.169206)-9.724614(-2.313009)-13.11404(-0.915199)-26.25169(-3.309586)0.941342X1X2X3X6X5修正后的R2X1、X2、X3、X5、X626.43234（2.972852）-19.94364(-2.124857)-9.294377(-1.953592)587.9565(0.700319)-34.32343(-1.940065)0.939711X1X2X3X7X5修正后的R2X1、X2、X3、X5、X730.36959（2.888412）-22.3521（-2.16922）-12.4078（-2.93672）1166.868（0.827505）-23.4077（-3.27249）0.940635 當(dāng)分別加入X4、X6、X7時(shí)t檢驗(yàn)均不顯著，并且修正后的R2變小了，說(shuō)明X4、X6、X7引起嚴(yán)重多重共線性，應(yīng)予剔除。實(shí)驗(yàn)結(jié)果：Dependent Variable: YMethod: Least SquaresDate: 05/01/10 Time: 16:01Sample: 1985 2002Included observations: 18VariableCoefficientStd. Errort-StatisticProb.C-80155.52108510.7-0.7386880.4771X136.8423211.641463.1647500.0101X2-28.2335011.33756-2.4902620.0320X3-10.326374.845876-2.1309610.0589X4-17.5264317.94658-0.9765890.3518X5-34.4999518.88123-1.8272090.0976X6336.4866992.14180.3391520.7415X71952.5731535.8321.2713450.2324R-squared0.964563Mean dependent var114898.3Adjusted R-squared0.939758S.D. dependent var22162.37S.E. of regression5439.605Akaike info criterion20.34190Sum squared resid2.96E+08Schwarz criterion20.73762Log likelihood-175.0771F-statistic38.88476Durbin-Watson stat1.842204Prob(F-statistic)0.000002由以上結(jié)果可見(jiàn)，該模型的R2=0.964563，修正后的R2=0.939758可決系數(shù)很高，F(xiàn)檢驗(yàn)值為38.88476，顯著。但是但=0.05時(shí)t/2(18-8)=2.228，x4、x5、x6、x7系數(shù)的t檢驗(yàn)不顯著，而且 x6的系數(shù)的符號(hào)與預(yù)測(cè)的相反，這可能存在嚴(yán)重的多重共線性。最后修正多重共線性影響的回歸結(jié)果為： Y=62734.65+25.51688X1-18.1294X2-11.1351X3 -23.0032X5 t=(12.42854) (2.960009) (-2.0502