第七章練習(xí)題及參考解答(第四版)計(jì)量經(jīng)濟(jì)學(xué)

1、精選優(yōu)質(zhì)文檔-傾情為你奉上第七章練習(xí)題及參考解答7.1 表7.4中給出了1981-2015年中國(guó)城鎮(zhèn)居民人均年消費(fèi)支出(PCE)和城鎮(zhèn)居民人均可支配收入(PDI)數(shù)據(jù)。表7.4 1981-2015年中國(guó)城鎮(zhèn)居民消費(fèi)支出(PCE)和可支配收入(PDI)數(shù)據(jù) （單位：元）年度城鎮(zhèn)居民人均消費(fèi)支出PCE城鎮(zhèn)居民人均可支配收入PDI年度城鎮(zhèn)居民人均消費(fèi)支出PCE城鎮(zhèn)居民人均可支配收入PDI1981456.80500.4019994615.915854.021982471.00535.3020004998.006280.001983505.90564.6020015309.016859.60198455

2、9.40652.1020026029.887702.801985673.20739.1020036510.948472.201986799.00900.9020047182.109421.601987884.401002.1020057942.8810493.0019881104.001180.2020068696.5511759.5019891211.001373.9320079997.4713785.8019901278.901510.20200811242.8515780.7619911453.801700.60200912264.5517174.6519921671.702026.60

3、201013471.4519109.4419932110.802577.40201115160.8921809.7819942851.303496.20201216674.3224564.7219953537.574283.00201318022.6426955.1019963919.474838.90201419968.0829381.0019974185.645160.30201521392.3631790.3119984331.615425.10估計(jì)下列模型：(1) 解釋這兩個(gè)回歸模型的結(jié)果。(2) 短期和長(zhǎng)期邊際消費(fèi)傾向（MPC）是多少？分析該地區(qū)消費(fèi)同收入的關(guān)系。(3) 建立適當(dāng)?shù)姆?/p>

4、布滯后模型，用庫(kù)伊克變換轉(zhuǎn)換為庫(kù)伊克模型后進(jìn)行估計(jì)，并對(duì)估計(jì)結(jié)果進(jìn)行分析判斷?！揪毩?xí)題7.1參考解答】(1) 解釋這兩個(gè)回歸模型的結(jié)果。Dependent Variable: PCEMethod: Least SquaresDate: 03/10/18 Time: 09:12Sample: 1981 2005Included observations: 25VariableCoefficientStd. Errort-StatisticProb. C149.097524.567346.0.0000PDI8400.0000R-squared0. Mean dependent v

5、ar2983.768Adjusted R-squared0. S.D. dependent var2364.412S.E. of regression77.70773 Akaike info criterion11.62040Sum squared resid.3 Schwarz criterion11.71791Log likelihood-143.2551 F-statistic22196.24Durbin-Watson stat0. Prob(F-statistic)0.收入跟消費(fèi)間有顯著關(guān)系。收入每增加1元，消費(fèi)增加0.76元。Dependent Variable: PCEMethod

6、: Least SquaresDate: 03/10/18 Time: 09:13Sample(adjusted): 1982 2005Included observations: 24 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C147.688626.735795.0.0000PDI.0000PCE(-1).2803R-squared0. Mean dependent var3089.059Adjusted R-squared0. S.D. dependent va

7、r2354.635S.E. of regression77.44504 Akaike info criterion11.65348Sum squared resid.4 Schwarz criterion11.80074Log likelihood-136.8418 F-statistic10620.10Durbin-Watson stat0. Prob(F-statistic)0.(2) 短期和長(zhǎng)期邊際消費(fèi)傾向（MPC）是多少？分析該地區(qū)消費(fèi)同收入的關(guān)系。短期MPC=0.68，長(zhǎng)期MPC=0.679/(1-0.111)=0.764(3) 建立適當(dāng)?shù)姆植紲竽Ｐ?，用?kù)伊克變換轉(zhuǎn)換為庫(kù)伊克模型后

8、進(jìn)行估計(jì)，并對(duì)估計(jì)結(jié)果進(jìn)行分析判斷。在滯后1-5期內(nèi)，根據(jù)AIC最小，選擇滯后5期，其回歸結(jié)果如下:Dependent Variable: PCEMethod: Least SquaresDate: 03/10/18 Time: 09:25Sample(adjusted): 1986 2005Included observations: 20 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C167.959033.277935.0.0002PDI.0001PDI(-1).4

9、263PDI(-2)-0.0.-0.0.5818PDI(-3)-0.0.-0.0.8358PDI(-4).3940PDI(-5)-0.0.-1.0.1429R-squared0. Mean dependent var3596.396Adjusted R-squared0. S.D. dependent var2254.922S.E. of regression67.79561 Akaike info criterion11.54009Sum squared resid59751.18 Schwarz criterion11.88860Log likelihood-108.4009

10、 F-statistic3501.011Durbin-Watson stat1. Prob(F-statistic)0.當(dāng)期收入對(duì)消費(fèi)有顯著影響，但各滯后期影響并不顯著。不顯著可能是分布滯后模型直接估計(jì)時(shí)共線性造成的，也可能是真沒(méi)顯著影響。庫(kù)伊克模型估計(jì)結(jié)果見上表，PCE(-1)部分回歸結(jié)果t檢驗(yàn)不顯著。7.2 表7.5中給出了中國(guó)1980-2016年固定資產(chǎn)投資Y與社會(huì)消費(fèi)品零售總額X的資料。取阿爾蒙多項(xiàng)式的次數(shù)m=2，運(yùn)用阿爾蒙多項(xiàng)式變換法估計(jì)以下分布滯后模型：表7.5中國(guó)1980-2016年固定資產(chǎn)投資Y與社會(huì)零售總額X數(shù)據(jù) （單位：億元）年份固定資產(chǎn)投資Y社會(huì)消費(fèi)品零售總額X年份固定資

11、產(chǎn)投資Y社會(huì)消費(fèi)品零售總額X1980910.92140.0199929854.735647.91981961.02350.0200032917.739105.719821230.42570.0200137213.543055.419831430.12849.4200243499.948135.919841832.93376.4200355566.652516.319852543.24305.0200470477.459501.019863120.64950.0200588773.667176.619873791.75820.02006.276410.019884753.87440.02007.

12、989210.019894410.48101.42008.4.119904517.08300.12009.8.419915594.59415.62010.8.419928080.110993.72011.1.6199313072.314270.42012.7.0199417042.118622.92013.1.9199520019.323613.82014.7.1199622913.528360.22015.8.8199724941.131252.92016.7.3199828406.233378.1【練習(xí)題7.2參考解答】直接估計(jì)結(jié)果如下：Dependent Variable: YMetho

13、d: Least SquaresDate: 03/10/18 Time: 09:32Sample(adjusted): 1984 2016Included observations: 33 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C-23633.423701.825-6.0.0000X.6190X(-1).2265X(-2)-0.1.-0.0.7529X(-3).5379X(-4)-1.1.-1.0.3138R-squared0. Mean depen

14、dent var.7Adjusted R-squared0. S.D. dependent var.0S.E. of regression15497.23 Akaike info criterion22.29768Sum squared resid6.48E+09 Schwarz criterion22.56977Log likelihood-361.9117 F-statistic859.2660Durbin-Watson stat0. Prob(F-statistic)0.使用阿爾蒙變換估計(jì)結(jié)果如下：Dependent Variable: YMethod: Least SquaresDat

15、e: 03/10/18 Time: 09:37Sample(adjusted): 1984 2016Included observations: 33 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C-23683.133619.054-6.0.0000Z0.2089Z.7267Z2-0.0.-0.0.5206R-squared0. Mean dependent var.7Adjusted R-squared0. S.D. dependent var.0S.E. of r

16、egression15170.17 Akaike info criterion22.20526Sum squared resid6.67E+09 Schwarz criterion22.38666Log likelihood-362.3868 F-statistic1494.254Durbin-Watson stat0. Prob(F-statistic)0.根據(jù)可計(jì)算出0.802=1.051=0.833=0.149=-1.002直接使用軟件結(jié)果：Dependent Variable: YMethod: Least SquaresDate: 03/10/18 Time: 09:39Sample

17、(adjusted): 1984 2016Included observations: 33 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C-23683.133619.054-6.0.0000PDL0.2454PDL02-0.0.-3.0.0042PDL03-0.0.-0.0.5206R-squared0.Mean dependent var.7Adjusted R-squared0.S.D. dependent var.0S.E. of regression15170.17Aka

18、ike info criterion22.20526Sum squared resid6.67E+09Schwarz criterion22.38666Log likelihood-362.3868F-statistic1494.254Durbin-Watson stat0.Prob(F-statistic)0. Lag Distribution of XiCoefficientStd. ErrorT-Statistic . * |0 0.80168 0.62378 1.28520 . *|1 1.05067 0.42723 2.45927 . * |2 0.83302 0.70264 1.1

19、8555 .* |3 0.14873 0.31166 0.47722 * . |4-1.00221 0.92567-1.08269Sum of Lags 1.83190 0.18562 9.869017.3利用表7.5的數(shù)據(jù)，運(yùn)用局部調(diào)整假定或自適應(yīng)預(yù)期假定估計(jì)以下模型參數(shù)，并解釋模型的經(jīng)濟(jì)意義，探測(cè)模型擾動(dòng)項(xiàng)的一階自相關(guān)性：1）設(shè)定模型其中為預(yù)期最佳值。 2）設(shè)定模型其中為預(yù)期最佳值。3）設(shè)定模型其中為預(yù)期最佳值?！揪毩?xí)題7.3參考解答】1）設(shè)定模型 其中為預(yù)期最佳值。Dependent Variable: YMethod: Least SquaresDate: 03/10/18 Time:

20、 10:09Sample(adjusted): 1981 2016Included observations: 36 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C-5669.5052498.919-2.0.0299X.0000Y(-1).0000R-squared0. Mean dependent var.6Adjusted R-squared0. S.D. dependent var.8S.E. of regression8314.081 Akaike info c

21、riterion20.96894Sum squared resid2.28E+09 Schwarz criterion21.10090Log likelihood-374.4410 F-statistic7815.118Durbin-Watson stat0. Prob(F-statistic)0.根據(jù)回歸結(jié)果，可算出h統(tǒng)計(jì)量為3.64，明顯大于2，表明5%顯著水平下存在相關(guān)性。根據(jù)回歸數(shù)據(jù)，可算出調(diào)整系數(shù)為1-0.734=0.266，這表示了局部調(diào)整的速度。0.665/0.266=2.5 2）設(shè)定模型 其中為預(yù)期最佳值。假設(shè)調(diào)整方程為：，則轉(zhuǎn)化為一階自回歸模型后的回歸結(jié)果為:Dependen

22、t Variable: LOG(Y)Method: Least SquaresDate: 03/10/18 Time: 10:11Sample(adjusted): 1981 2016Included observations: 36 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C-0.0.-0.0.4396LOG(X).2615LOG(Y(-1).0006R-squared0. Mean dependent var10.25491Adjusted R-squared0

23、. S.D. dependent var1.S.E. of regression0. Akaike info criterion-1.Sum squared resid0. Schwarz criterion-1.Log likelihood32.57124 F-statistic6386.241Durbin-Watson stat0. Prob(F-statistic)0.根據(jù)回歸結(jié)果，計(jì)算h統(tǒng)計(jì)量時(shí)開方部分為負(fù)，沒(méi)法計(jì)算。故沒(méi)法根據(jù)h統(tǒng)計(jì)量判斷相關(guān)性。根據(jù)回歸數(shù)據(jù)，可算出調(diào)整系數(shù)為1-0.765=0.235，這表示了局部調(diào)整的速度。0.2997/0.235=1.2753）設(shè)定模型 其中為預(yù)

24、期最佳值。Dependent Variable: YMethod: Least SquaresDate: 03/10/18 Time: 10:09Sample(adjusted): 1981 2016Included observations: 36 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C-5669.5052498.919-2.0.0299X.0000Y(-1).0000R-squared0. Mean dependent var.6Adjusted R-squ

25、ared0. S.D. dependent var.8S.E. of regression8314.081 Akaike info criterion20.96894Sum squared resid2.28E+09 Schwarz criterion21.10090Log likelihood-374.4410 F-statistic7815.118Durbin-Watson stat0. Prob(F-statistic)0.可算出調(diào)節(jié)系數(shù)為1-0.734=0.266，這表示了預(yù)期修正的速度。0.665/0.266=2.57.4表7.6給出中國(guó)各年末貨幣流通量Y，社會(huì)商品零售額X1、城鄉(xiāng)居

26、民儲(chǔ)蓄余額X 2的數(shù)據(jù)。表7.6中國(guó)年末貨幣流通量、社會(huì)商品零售額、城鄉(xiāng)居民儲(chǔ)蓄余額數(shù)據(jù) （單位：億元）年份年末貨幣流通量Y社會(huì)消費(fèi)品零售總額X1城鄉(xiāng)居民儲(chǔ)蓄年底余額X219892344.08101.45184.5019902644.48300.17119.6019913177.89415.69244.9019924336.010993.711757.3019935864.714270.415203.5019947288.618622.921518.8019957885.323613.829662.3019968802.028360.238520.80199710177.631252.9462

27、79.80199811204.233378.153407.47199913455.535647.959621.83200014652.739105.764332.38200115688.843055.473762.43200217278.048135.986910.65200319746.052516.3.65200421468.359501.0.39200524031.767176.6.99200627072.676410.0.30200730334.389210.0.192008345200938620104469201150748.5.

28、6.89201254602013585720146024利用表中數(shù)據(jù)設(shè)定模型：其中，為長(zhǎng)期(或所需求的)貨幣流通量。試根據(jù)局部調(diào)整假設(shè)，作模型變換，估計(jì)并檢驗(yàn)參數(shù)，對(duì)參數(shù)經(jīng)濟(jì)意義做出解釋?！揪毩?xí)題7.4參考解答】利用表中數(shù)據(jù)設(shè)定模型： 其中，為長(zhǎng)期(或所需求的)貨幣流通量。試根據(jù)局部調(diào)整假設(shè)，作模型變換，估計(jì)并檢驗(yàn)參數(shù)，對(duì)參數(shù)經(jīng)濟(jì)意義做出解釋。假設(shè)局部調(diào)整方程為：，對(duì)，可轉(zhuǎn)化為回歸方程：，其回歸結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 03/10/18 Time: 10:03Samp

29、le(adjusted): 1990 2014Included observations: 25 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C1618.034732.14892.0.0383Y(-1).0000X1-0.0.-3.0.0049X.0301R-squared0. Mean dependent var23457.75Adjusted R-squared0. S.D. dependent var18266.54S.E. of regression972.7

30、612 Akaike info criterion16.74380Sum squared resid Schwarz criterion16.93882Log likelihood-205.2975 F-statistic2813.916Durbin-Watson stat1. Prob(F-statistic)0.各回歸系數(shù)在5%顯著水平下均顯著?？伤愠稣{(diào)整系數(shù)為1-0.981=0.019，這表示了局部調(diào)整的速度。假設(shè)局部調(diào)整方程為：，對(duì)，可轉(zhuǎn)化為回歸方程：，其回歸結(jié)果如下：Dependent Variable: LOG(Y)Method: Least SquaresDate: 03/10/18 Time: 10:04Sample(adjusted): 1990 2014Included observations: 25 after adjusting endpointsVariableCoefficientStd. Errort-StatisticProb. C.0273LOG(Y(-1).0041LOG(X1)0