計(jì)量經(jīng)濟(jì)學(xué)實(shí)驗(yàn)報(bào)告模板

《計(jì)量經(jīng)濟(jì)學(xué)》實(shí)驗(yàn)報(bào)告【實(shí)驗(yàn)?zāi)康摹客ㄟ^(guò)這次實(shí)驗(yàn)，熟悉eviews軟件的使用方法?！緦?shí)驗(yàn)原理】普通最小二乘法，擬合優(yōu)度的判定系數(shù)R2檢驗(yàn)、參數(shù)顯著性t檢驗(yàn)、異方差性檢驗(yàn)、序列相關(guān)檢驗(yàn)、多重共線性檢驗(yàn)等。【實(shí)驗(yàn)要求】通過(guò)對(duì)統(tǒng)計(jì)量的分析，建立一個(gè)合理的模型?！緦?shí)驗(yàn)步驟】1、 提出問題（即：理論背景）探討糧食的產(chǎn)量受到農(nóng)業(yè)化肥施用量，糧食播種面積，成災(zāi)面積，以及農(nóng)業(yè)機(jī)械總動(dòng)力的影響。2、 建立模型（包括變量選擇與變量解釋）Y郅0+p1*X1+p2*X2+p3*X3+p4*X4+|J3、 準(zhǔn)備數(shù)據(jù)（需要列出原始數(shù)據(jù)）年份糧食產(chǎn)量/萬(wàn)噸Y農(nóng)業(yè)化肥施用量/萬(wàn)千克X1糧食播種面積/千公頃X2成災(zāi)面積/公頃X3農(nóng)業(yè)機(jī)械總動(dòng)力/萬(wàn)千瓦X41983年38728166011404716209180221984年40731174011288415264194971985年37911177610884522795209131986年39151193111093323656229501987年40208199911126820392248361988年39408214211012323944265751989年40755235711220524448280671990年44624259011346617819287081991年43529280611231427814293891992年44264293011056025894303081993年45649315211050923133318171994年44510331810954431383338021995年46662359411006022267361181996年50454382811254821233385471997年49417398111291230309420161998年51230408411378725181452081999年50839412411316126731489962000年46218414610846334374525744、模型估計(jì)(即：回歸分析方法，得到回歸分析輸出表和有關(guān)圖形)DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:43Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X16.1641000.6429729.5868840.0000X20.4155810.1167873.5584400.0035X3-0.1683770.054771-3.0741880.0089X4-0.0943150.061112-1.5433040.1467C-13006.8713482.19-0.9647440.3523R-squared0.982710Meandependentvar44127.11AdjustedR-squared0.977390S.D.dependentvar4409.100S.E.ofregression662.9835Akaikeinfocriterion16.06151Sumsquaredresid5714113.Schwarzcriterion16.30884Loglikelihood-139.5536F-statistic184.7178Durbin-Watsonstat1.799563Prob(F-statistic)0.0000005、模型檢驗(yàn)（包括：擬合優(yōu)度、方程顯著性檢驗(yàn)、參數(shù)顯著性檢驗(yàn)、異方差性檢驗(yàn)、序列相關(guān)檢驗(yàn)、多重共線性檢驗(yàn)等等）通過(guò)回歸，可以看到擬合優(yōu)度的判定系數(shù)為0.982710，調(diào)整后的擬合優(yōu)度的判定系數(shù)為0.977390，說(shuō)明模型擬合的很好。F統(tǒng)計(jì)量為184.7178，說(shuō)明方程顯著。X1,X2,X3的t統(tǒng)計(jì)量的絕對(duì)值也均大于2。（1）多重共線性檢驗(yàn)與修正X1 X2 X3 X4X1 1 0.0118251473933 0.639053950701 0.960246021666X2 0.0118251473933 1 -0.456657253673 -0.0384793573122X3 0.639053950701 -0.456657253673 1 0.688595415334X40.960246021666-0.03847935731220.688595415334 1由表中數(shù)據(jù)可以發(fā)現(xiàn)X1與X4間存在高度相關(guān)性。對(duì)模型進(jìn)行優(yōu)化，分別做Y對(duì)XI、X2、X3和X4的回歸DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:45Sample:19832000

Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X14.5764290.398200 11.492790.0000C30866.141206.382 25.585720.0000R-squared0.891953Meandependentvar44127.11AdjustedR-squared0.885200S.D.dependentvar4409.100S.E.ofregression1493.895Akaikeinfocriterion17.56060Sumsquaredresid35707568Schwarzcriterion17.65953Loglikelihood-156.0454F-statistic132.0841Durbin-Watsonstat1.856042Prob(F-statistic)0.000000DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:46Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X20.6988800.613273 1.1395900.2712C-33822.4168409.15 -0.4944140.6277R-squared0.075073Meandependentvar44127.11AdjustedR-squared0.017265S.D.dependentvar4409.100S.E.ofregression4370.873Akaikeinfocriterion19.70775Sumsquaredresid3.06E+08Schwarzcriterion19.80668Loglikelihood-175.3698F-statistic1.298665Durbin-Watsonstat0.118043Prob(F-statistic)0.271231DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:46Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X30.3488860.200982 1.7359050.1018C35737.464931.901 7.2461830.0000R-squared0.158487Meandependentvar44127.11AdjustedR-squared0.105892S.D.dependentvar4409.100S.E.ofregression4169.125Akaikeinfocriterion19.61324Sumsquaredresid2.78E+08Schwarzcriterion19.71217Loglikelihood-174.5192F-statistic3.013367Durbin-Watsonstat0.933056Prob(F-statistic)0.101794

DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:47Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X40.3799670.054448 6.9785870.0000C31918.721828.715 17.454180.0000R-squared0.752707Meandependentvar44127.11AdjustedR-squared0.737252S.D.dependentvar4409.100S.E.ofregression2260.060Akaikeinfocriterion18.38861Sumsquaredresid81725964Schwarzcriterion18.48754Loglikelihood-163.4975F-statistic48.70067Durbin-Watsonstat1.109488Prob(F-statistic)0.000003可見，糧食生產(chǎn)受農(nóng)業(yè)化肥施用量的影響比較大，與經(jīng)驗(yàn)相符合，因此選X1與Y作為初始的回歸模型。接下來(lái)進(jìn)行逐步回歸，消除多重共線性DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:48Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X14.5613670.24697118.469270.0000X20.6704870.1300025.1575170.0001C-43872.9614510.60-3.0235120.0086R-squared0.961041Meandependentvar44127.11AdjustedR-squared0.955846S.D.dependentvar4409.100S.E.ofregression926.4747Akaikeinfocriterion16.65166Sumsquaredresid12875330Schwarzcriterion16.80006Loglikelihood-146.8650F-statistic185.0093Durbin-Watsonstat_2.016506_Prob(F-statistic) _0.000000在初始模型中引入x2,模型的擬合優(yōu)度提高，且參數(shù)符號(hào)合理，變量也通過(guò)了t檢驗(yàn)DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:48

Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X15.2540980.26873619.551130.0000X20.4078260.1223023.3345870.0049X3-0.1943760.054627-3.5582100.0031C-11910.2214112.24-0.8439640.4129R-squared0.979542Meandependentvar44127.11AdjustedR-squared0.975158S.D.dependentvar4409.100S.E.ofregression694.9317Akaikeinfocriterion16.11863Sumsquaredresid6761021.Schwarzcriterion16.31649Loglikelihood-141.0677F-statistic223.4428Durbin-Watsonstat1.529226Prob(F-statistic)0.000000在初始模型中引入X3，模型的擬合優(yōu)度提高，且參數(shù)符號(hào)合理，變量也通過(guò)了t檢DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:07:49Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X16.1641000.6429729.5868840.0000X20.4155810.1167873.5584400.0035X3-0.1683770.054771-3.0741880.0089X4-0.0943150.061112-1.5433040.1467C-13006.8713482.19-0.9647440.3523R-squared0.982710Meandependentvar44127.11AdjustedR-squared0.977390S.D.dependentvar4409.100S.E.ofregression662.9835Akaikeinfocriterion16.06151Sumsquaredresid5714113.Schwarzcriterion16.30884Loglikelihood-139.5536F-statistic184.7178Durbin-Watsonstat_1.799563_Prob(F-statistic) _0.000000引入X4，模型的擬合優(yōu)度提高仍略有提高，X4變量未通過(guò)t檢驗(yàn)，說(shuō)明X4是多余的。綜上，最終的糧食生產(chǎn)函數(shù)應(yīng)以Y=f(X1，X2,X3)為最優(yōu)，擬合結(jié)果如下：Y=5.254097757*X1+0.4078261772*X2-0.1943760119*X3-11910.22289⑵異方差性檢驗(yàn)1000-500-0-500-1/-1000-/I-1500—-55000-50000-45000-40000-3500084 86 88 90 92 94 96 98 00ResidualActualFittedPark檢驗(yàn)DependentVariable:LOG(RESIDA2)Method:LeastSquaresDate:12/15/09Time:07:56Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.LOG(X1)-0.5251101.116474 -0.4703290.6445C16.053338.852115 1.8135030.0886R-squared0.013637Meandependentvar11.89331AdjustedR-squared-0.048011S.D.dependentvar1.478244S.E.ofregression1.513314Akaikeinfocriterion3.770920Sumsquaredresid36.64189Schwarzcriterion3.869850Loglikelihood-31.93828F-statistic0.221209Durbin-Watsonstat1.719470Prob(F-statistic)0.644467DependentVariable:LOG(RESIDA2)Method:LeastSquaresDate:12/15/09Time:07:56Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.LOG(X2)0.26899140.842730.0065860.9948C-3.591376474.6737-0.0075660.9941R-squared0.000003Meandependentvar-0.465166AdjustedR-squared-0.062497S.D.dependentvar2.536590S.E.ofregression2.614654Akaikeinfocriterion4.864580Sumsquaredresid109.3826Schwarzcriterion4.963510

Loglikelihood -41.78122 F-statistic 4.34E-05Durbin-Watsonstat 1.952688 Prob(F-statistic) 0.994827DependentVariable:LOG(RESIDA2)Method:LeastSquaresDate:12/15/09Time:07:57Sample:19832000因而方程不存在Includedobservations:18因而方程不存在VariableCoefficientStd.Errort-StatisticProb.LOG(X3)-2.5432591.788804 -1.4217650.1743C26.1077318.01068 1.4495690.1665R-squared0.112167Meandependentvar0.506316AdjustedR-squared0.056678S.D.dependentvar1.636344S.E.ofregression1.589296Akaikeinfocriterion3.868898Sumsquaredresid40.41378Schwarzcriterion3.967828Loglikelihood-32.82008F-statistic2.021414Durbin-Watsonstat_1.456375_Prob(F-statistic)0.174295通過(guò)以上檢驗(yàn)可以看出，t統(tǒng)計(jì)值均小于經(jīng)驗(yàn)數(shù)據(jù)2,F也不顯著，異方差性。⑶序列相關(guān)性檢驗(yàn)-1500-1-55000"50000■45000■40000'3500084 86 88 90 92 94 96 98 00ResidualActualFittedDependentVariable:YMethod:LeastSquaresDate:12/15/09Time:08:00Sample:19832000Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.X15.2540980.26873619.551130.0000X20.4078260.1223023.3345870.0049

X3-0.1943760.054627 -3.5582100.0031C-11910.2214112.24 -0.8439640.4129R-squared0.979542Meandependentvar44127.11AdjustedR-squared0.975158S.D.dependentvar4409.100S.E.ofregression694.9317Akaikeinfocriterion16.11863Sumsquaredresid6761021.Schwarzcriterion16.31649Loglikelihood-141.0677F-statistic223.4428Durbin-Watsonstat_1.529226_Prob(F-statistic) _0.000000可以看出，D-W統(tǒng)計(jì)值為1.529226，因此可能存在序列相關(guān)。6、模型優(yōu)化（如果所建模型經(jīng)檢驗(yàn)存在問題，則需改善模型。例如，存在異方差，則需采用一種方法對(duì)模型進(jìn)行改進(jìn)。）序列相關(guān)的修正加入人&1）項(xiàng)，得回歸結(jié)果DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:08:03Sample（adjusted）:19842000Includedobservations:17afteradjustingendpointsConvergenceachievedafter9iterationsVariableCoefficientStd.Errort-StatisticProb.X15.0327930.24628520.434860.0000X20.5269350.1114234.7291360.0005X3-0.1950490.043798-4.4534190.0008C-24407.5212541.91-1.9460770.0754AR(1)0.1141390.2569730.4441670.6648R-squared0.987497Meandependentvar44444.71AdjustedR-squared0.983329S.D.dependentvar4327.367S.E.ofregression558.7280Akaikeinfocriterion15.72913Sumsquaredresid3746123.Schwarzcriterion15.97419Loglikelihood-128.6976F-statistic236.9422Durbin-Watsonstat1.667555Prob(F-statistic)0.000000InvertedARRoots.11加入入日(2)項(xiàng)，得回歸結(jié)果DependentVariable:YMethod:LeastSquaresDate:12/15/09Time:08:04Sample(adjusted):19852000Includedobservations:16afteradjustingendpointsConvergenceachievedafter10iterationsV