計(jì)量經(jīng)濟(jì)學(xué)第二版)龐皓科學(xué)出版社第七章練習(xí)題答案

1、第七章7.1表7.11中給出了 1970-1987年期間美國(guó)的個(gè)人消費(fèi)支出(PCE和個(gè)人可支配收入(PDI)數(shù)據(jù)，所有數(shù)字的單位都是10億美元(1982年的美元價(jià))。P CEtP CEtA1B1A2P DItB2P DIttB3P CEt 1 t表7.11 1970 -1987年美國(guó)個(gè)人消費(fèi)支出(PCE)和個(gè)人可支配收入(PDI)數(shù)據(jù)年份PCEPDI年份PCEPDI年份PCEPDI19701492.01668.119761803.92001.019822050.72261.519711538.81728.419771883.82066.619832146.02331.919721621.917

2、97.419781961.02167.419842249.32469.819731689.61916.319792004.42212.619852354.82542.819741674.01896.619802000.42214.319862455.22640.919751711.91931.719812042.22248.619872521.02686.3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?練習(xí)題7.1參考解答：1) 第一個(gè)模型回歸的估計(jì)結(jié)果如下,Depen de nt Variable: PCEMethod: Least Square

3、sDate: 07/27/05Time: 21:41Sample: 1970 1987In cluded observati ons: 18VariableCoefficie ntStd. Errort-StatisticP rob.C-216.426932.69425-6.6197230.0000PDI1.0081060.01503367.059200.0000R-squared0.996455Mean dependent var1955.606Adjusted R-squared0.996233S.D. dependent var307.7170S.E. of regressi on18.

4、88628Akaike info criteri on8.819188Sum squared resid5707.065Schwarz criteri on8.918118Log likelihood-77.37269F-statistic4496.936Durbi n-Watson stat1.366654P rob(F-statistic)0.000000回歸方程：pCE?t216.42691.008106 PDI t(32. 69425)( 0.015033 )(-6.619723 )(67.05920 )2R =0.996455F=4496.936第二個(gè)模型回歸的估計(jì)結(jié)果如下，Depe

5、ndent Variable: PCEMethod: Least SquaresDate: 07/27/05Time: 21:51Samp le (adjusted): 1971 1987In cluded observati ons: 17 after adjustme ntsVariableCoefficie ntStd. Errort-StatisticP rob.C-233.273645.55736-5.1204360.0002PDI0.9823820.1409286.9708170.0000P CE(-1)0.0371580.1440260.2579970.8002R-squared

6、0.996542Mean dependent var1982.876Adjusted R-squared0.996048S.D. dependent var293.9125S.E. of regressi on18.47783Akaike info criteri on8.829805Sum squared resid4780.022Schwarz criteri on8.976843Log likelihood-72.05335F-statistic2017.064Durbi n-Watson stat1.570195P rob(F-statistic)0.000000回歸方程：pcEt23

7、3.27360.9824PDIt 0.0372PCE 1(45.557 )(0.1409 )( 0.1440 )t =(-5.120 )(6.9708 )( 0.258 )R2 =0.9965 F=2017.064MPC=0.9824,由于模型二為自回歸模型, 我們可以從庫(kù)伊克變換倒推得到長(zhǎng)期2）從模型一得到 MPC=1.008;從模型二得到，短期 要先轉(zhuǎn)換為分布滯后模型才能得到長(zhǎng)期邊際消費(fèi)傾向，MPC=0.9824/（ 1+0.0372）=0.9472。7.2表7.12中給出了某地區(qū)1980-2001年固定資產(chǎn)投資 丫與銷(xiāo)售額X的資料。年份YX年份YX198036.9952.80519911

8、28.68168.129198133.6055.9061992123.97163.351198235.4263.0271993117.35172.547198342.3572.9311994139.61190.682198452.4884.7901995152.88194.538198553.6686.5891996137.95194.657198658.5398.7971997141.06206.326某地區(qū)1980-2001年固定資產(chǎn)投資 Y與銷(xiāo)售額X的資料（單位：億元）表 7.12198767.48113.2011998163.45223.541198878.13126.90519991

9、83.80232.724198995.13143.9362000192.61239.4591990112.60154.3912001182.81235.142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:*Yt1 ）設(shè)定模型Xt Ut其中Yt*為預(yù)期最佳值。2）設(shè)定模型YtXteut其中Yt為預(yù)期最佳值。3）設(shè)定模型YtXt Ut其中Xt為預(yù)期最佳值。練習(xí)題7.2參考解答：1)在局部調(diào)整假定下，先估計(jì)一階自回歸模型: 回歸的估計(jì)結(jié)果如下，Dependent Variable: YMethod: Least SquaresDate: 25/

10、02/10 Time: 22:42Sam pie (adjusted): 1981 2001In eluded observati ons: 21 after adjustme ntsYt0 Xt1 Yt 1UtVariableCoefficie ntStd. Errort-StatisticP rob.C-15.104034.729450-3.1936130.0050X0.6292730.0978196.4330310.0000丫(-1)0.2716760.1148582.3653150.0294R-squared0.987125Mean dependent var109.2167Adjus

11、ted R-squared0.985695S.D. dependent var51.78550S.E. of regressi on6.193728Akaike info criteri on6.616515Sum squared resid690.5208Schwarz criteri on6.765733Log likelihood-66.47341F-statistic690.0561Durbi n-Watson stat1.518595P rob(F-statistic)0.000000回歸方程：Yt15.104030.629273Xt0.271676Y 1(4.729450)(-3.

12、193613)(0.097819)(6.433031)(0.114858)(2.365315)2R =0.987125F=690.0561 DW=1.518595根據(jù)局部調(diào)整模型的參數(shù)關(guān)系，有11, ut ut將上述估計(jì)結(jié)果代入得到:111 0.2716760.72832420.73806400.864001故局部調(diào)整模型估計(jì)結(jié)果為:20.738064 0.864001Xt經(jīng)濟(jì)意義：該地區(qū)銷(xiāo)售額每增加 運(yùn)用德賓h檢驗(yàn)一階自相關(guān)：1億元，未來(lái)預(yù)期最佳新增固定資產(chǎn)投資為0.864001 億元。(1212 1.518595N1-21 0114858-1.29728在顯著性水平O.05上，查標(biāo)準(zhǔn)正態(tài)分

13、布表得臨界值h/ 1.96，由于h 1.29728 h&1.96，則接收原假設(shè)0，說(shuō)明自回歸模型不存在一階自相關(guān)問(wèn)題。2）先對(duì)數(shù)變換模型，有InY lnln XtutInX0 lnXt1 lnYt1 ut在局部調(diào)整假定下，先估計(jì)一階自回歸模型: 回歸的估計(jì)結(jié)果如下，Depen de nt Variable: LNYMethod: Least SquaresDate: 25/02/10 Time: 22:55Sam ple (adjusted): 1981 2001In cluded observati ons: 21 after adjustme ntsVariableCoeffici

14、e ntStd. Errort-StatisticP rob.-1.0780460.184144-5.8543660.0000LNX0.9045220.1112438.1310390.0000LNY(-1)0.2600330.0877992.9616840.0084R-squared0.993725 Mean depen de nt var4.559823A回歸方程：lnYt1.0780460.904522ln Xt0.260033ln Yt 1(0.184144)(-5.854366)(0.111243)(8.131039)(0.087799)(2.961684)Adjusted R-squ

15、ared0.993028S.D. dependent var0.562953S.E. of regressi on0.047007Akaike info criteri on-3.145469Sum squared resid0.039774Schwarz criteri on-2.996251Log likelihood36.02742F-statistic1425.219Durbi n-Watson stat1.479333P rob(F-statistic)0.0000002R =0.993725 F=1425.219 DW1=1.479333根據(jù)局部調(diào)整模型的參數(shù)關(guān)系,有 lnIn將上

16、述估計(jì)結(jié)果代入得到:111 0.2600330.739967lnln1.456881.22238故局部調(diào)整模型估計(jì)結(jié)果為:InY*1.456881.22238InXt，也即Y*0.232961Xt1.22238經(jīng)濟(jì)意義：該地區(qū)銷(xiāo)售額每增加 運(yùn)用德賓h檢驗(yàn)一階自相關(guān)：1%未來(lái)預(yù)期最佳新增固定資產(chǎn)投資為1.22238%。在顯著性水平h 1.3031321nVar(1.479333)(21 21 0.08779920.05上，查標(biāo)準(zhǔn)正態(tài)分布表得臨界值hy 1.96，h&1.96，則接收原假設(shè)1.30313由于0，說(shuō)明自回歸模型不存在一階自相關(guān)。3)在自適應(yīng)預(yù)期假定下，先估計(jì)一階自回歸模型:

17、回歸的估計(jì)結(jié)果如下，Dependent Variable: YMethod: Least SquaresDate: 25/02/10 Time: 22:42Sam ple (adjusted): 1981 2001In eluded observati ons: 21 after adjustme ntsYtoXt1X1 UtVariableCoefficie ntStd. Errort-StatisticP rob.A回歸方程：Yt15.104030.629273Xt0.271676Y 1(4.729450)(-3.193613)(0.097819)(6.433031)(0.114858)(

18、2.365315)C-15.104034.729450-3.1936130.0050X0.6292730.0978196.4330310.0000丫(-1)0.2716760.1148582.3653150.0294R-squared0.987125Mean dependent var109.2167Adjusted R-squared0.985695S.D. dependent var51.78550S.E. of regressi on6.193728Akaike info criteri on6.616515Sum squared resid690.5208Schwarz criteri

19、 on6.765733Log likelihood-66.47341F-statistic690.0561Durb in -Watson stat1.518595P rob(F-statistic)0.0000002R2 =0.987125F=690.0561 DW=1.518595根據(jù)局部調(diào)整模型的參數(shù)關(guān)系,11UtUt將上述估計(jì)結(jié)果代入得到:111 0.2716760.72832420.73806400.864001故局部調(diào)整模型估計(jì)結(jié)果為:20.738064 0.864001Xt0.864001 億元。經(jīng)濟(jì)意義：該地區(qū)銷(xiāo)售額每增加1億元，未來(lái)預(yù)期最佳新增固定資產(chǎn)投資為 運(yùn)用德賓h檢驗(yàn)一階

20、自相關(guān)：(1 訶 1 nVar( J(1212 1.5185951-21 0.11485821.29728在顯著0.05準(zhǔn)正態(tài)分布表得臨界值h/1.96，由于1.29728 h&1.96，則接收原假設(shè)0，說(shuō)明自回歸模型不存在一階自相關(guān)。7.3 利用表7.12的數(shù)據(jù)，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)分布滯后模型:Yt0Xt1 Xt 12Xt 23Xt 34Xt 4 Ut練習(xí)題7.3參考解答：1分布滯后模型:Yt0Xt1Xt14X t 4 Ut s=4 ，取 m=2假設(shè)0016(*)則模型可變?yōu)?0Z0t2Z2t Ut，其中:ZotXtXtXt 2Xt 3 XtZ1t

21、乙tXt1Xt 12Xt 2 3Xt 3 4Xt 44Xt 2 9Xt 3 16Xt 4估計(jì)的回歸結(jié)果如下，Dependent Variable: YMethod: Least SquaresDate: 25/02/10 Time: 23:19Samp le (adjusted): 1984 2001In cluded observati ons: 18 after adjustme ntsVariableCoefficie ntStd. Errort-StatisticP rob.C-35.492348.192884-4.3320930.0007Z00.8910120.1745635.104

22、2480.0002Z1-0.6699040.254447-2.6327830.0197Z20.1043920.0623111.6753380.1160R-squared0.984670Mean dependent var121.2322Adjusted R-squared0.981385S.D. dependent var45.63348S.E. of regressi on6.226131Akaike info criteri on6.688517Sum squared resid542.7059Schwarz criteri on6.886378Log likelihood-56.1966

23、6F-statistic299.7429Durb in -Watson stat1.130400P rob(F-statistic)0.000000回歸方程：Y35.49243 0.891012Z0t 0.669904 Z1t 0.104392Z2t35.49124,00.89101, 10.66990, 20.10439由（* ）式可得,00.89101, 10.32550, 20.03123, 30.17917, 40.11833由阿爾蒙多項(xiàng)式變換可得如下估計(jì)結(jié)果:AYt -35.492340.89101Xt 0.32550Xt 1-0.03123Xt 2-0.17917Xt 3-0.11

24、833Xt 47.4表7.13中給出了 1962-1995年某地區(qū)基本建設(shè)新增固定資產(chǎn)丫和全省工業(yè)總產(chǎn)值 X按當(dāng)年價(jià)格計(jì)算的歷史資料。設(shè)定模型YtXtt作自適應(yīng)預(yù)期假定，估計(jì)參數(shù)，并作解釋。年份YX年份YX19620.944.9519792.0642.6919631.696.6319807.9351.6119641.788.5119818.0161.519651.849.3719826.6460.7319664.3611.2319831664.6419677.0211.3419848.8166.6719685.5519.9198510.3873.7819696.9329.4919866.269

25、.5219707.1736.8319877.9779.6419712.3321.19198827.3392.4519722.1818.14198912.58102.9419732.3919.69199012.47105.6219743.323.88199110.88104.8819755.2429.65199217.7113.319765.3940.94199314.72127.1319771.7833.08199413.76141.4419780.7320.3199514.42173.75設(shè)定模型Yt*(1)表7.13 1962 -1995年某地區(qū)基本建設(shè)新增固定資產(chǎn)丫和全省工業(yè)總產(chǎn)值 X單

26、位：億元）Xt t作局部調(diào)整假定，估計(jì)參數(shù)，并作解釋。比較上述兩種模型的設(shè)定及擬合情況，你覺(jué)得哪一個(gè)模型較好，為什么?練習(xí)題7.4參考解答：1）在局部調(diào)整假定下，先估計(jì)一階自回歸模型,Yt0X t1Yt 1 ut回歸的估計(jì)結(jié)果如下，Dependent Variable: YMethod: Least SquaresDate: 07/27/05Time: 22:31Samp le (adjusted): 1963 1995In cluded observati ons: 33 after adjustme ntsVariableCoefficie ntStd. Errort-StatisticP

27、 rob.1.8966451.1671271.6250550.11460.1021990.0247824.1239610.0003丫（-1）0.0147000.1828650.0803890.9365R-squared0.584750Mean dependent var7.804242Adjusted R-squared0.557066S.D. dependent var5.889686S.E. of regressi on3.919779Akaike info criteri on5.656455Sum squared resid460.9399Schwarz criteri on5.792

28、502Log likelihood-90.33151F-statistic21.12278Durbi n-Watson stat1.901308P rob（F-statistic）0.000002A回歸方程：Yt 1.89660.1022X,t 0.0147丫 1（1.167）（0.0248）（0.182865）t =（ 1.625）（4.1239）（0.080389）2R =0.584750 F=21.12278可以看出,Xt的回歸系數(shù)顯著，而 Yt 1的回歸系數(shù)不顯著， R2不是很高，模型整體上對(duì)樣本數(shù)據(jù)擬合一般。t，將上述估計(jì)結(jié)果代入得到:0.9853,0.1037,1.9249故局部調(diào)

29、整模型為:Y 1.9249 0.1037Xt t根據(jù)局部調(diào)整模型的參數(shù)關(guān)系，有0.1037 億元。2）在自適應(yīng)預(yù)期假定下，先估計(jì)一階自回歸模型,Yt0 X t 1 Yt 1 ut經(jīng)濟(jì)意義：為了達(dá)到全省工業(yè)總產(chǎn)值的計(jì)劃值，尋求一個(gè)未來(lái)預(yù)期新增固定資產(chǎn)的最佳量。 全省工業(yè)總產(chǎn)值每計(jì)劃增加1 （億元），則未來(lái)預(yù)期最佳新增固定資產(chǎn)量為回歸的估計(jì)結(jié)果如下，Dependent Variable: YMethod: Least SquaresDate: 07/27/05Time: 22:31Samp le （adjusted）: 1963 1995In cluded observati ons: 33 af

30、ter adjustme ntsVariableCoefficie ntStd. Errort-StatisticP rob.C1.8966451.1671271.6250550.1146X0.1021990.0247824.1239610.0003Y（-1）0.0147000.1828650.0803890.9365R-squared0.584750Mean dependent var7.804242Adjusted R-squared0.557066S.D. dependent var5.889686S.E. of regressi on3.919779Akaike info criter

31、i on5.656455Sum squared resid460.9399Schwarz criteri on5.792502Log likelihoodDurbi n-Watson stat-90.33151 F-statistic1.901308P rob(F-statistic)21.122780.000002回歸方程:Yt 1.89660.1022Xt0.0147Y 1可以看出,(1.167)( 0.0248)(1.625)( 4.1239)(0.182865)(0.080389)2R =0.584750 F=21.12278Xt的回歸系數(shù)顯著，而Yt 1的回歸系數(shù)不顯著,R2不是很高

32、，模型整體上對(duì)樣本數(shù)據(jù)擬合一般。根據(jù)自適應(yīng)模型的參數(shù)關(guān)系， 有t t (1) t 1，代入得到:0.9853,0.1037,1.9249故局部調(diào)整模型為:Y 1.92490.1037X t ut全省工業(yè)總產(chǎn)值每預(yù)期增經(jīng)濟(jì)意義：新增固定資產(chǎn)的變化取決于全省工業(yè)總產(chǎn)值的預(yù)期值。0.1037 （億元）。加增加1 （億元），當(dāng)期新增固定資產(chǎn)量為3）局部調(diào)整模型和自適應(yīng)模型的區(qū)別在于：局部調(diào)整模型是對(duì)應(yīng)變量的局部調(diào)整而得到的；而自適應(yīng)模型是由解釋變量的自適應(yīng)過(guò)程而得到的。由回歸結(jié)果可見(jiàn)，丫滯后一期的回歸系數(shù)并不顯著，說(shuō)明兩個(gè)模型的設(shè)定都不合理。7.5表7.14給出某地區(qū)各年末貨幣流通量Y,社會(huì)商品零售額

33、 X1、城鄉(xiāng)居民儲(chǔ)蓄余額 X2的數(shù)據(jù)。年份年末貨幣流通量Y社會(huì)商品零售額X1城鄉(xiāng)居民儲(chǔ)蓄余額X2年份年末貨幣流通量Y社會(huì)商品零售額X1城鄉(xiāng)居民儲(chǔ)蓄余額X21953105187867641631970385002403322615619541408810143348881971471002745343094419551337510398956891972572002991973596119561835412452574061973600003140063966719571686712646791561974625003189544332019581851513444610193197564500

34、336015461841959225581549611393919766800035292448311表7.14某地區(qū)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）1960290361703701549519776300037811553313196141472149182125531978660004158306129019623482615456410080197976000452032700331963300001425481160219808500051254392800196424300143415150311981900005479561097071965293

35、00156998171081982101000591088133799196633900176387193011983100000646427164314196736100178162204851984160000733162201199196839600167074225721985192000919045277185Yt1 X1t 2X2t t利用表中數(shù)據(jù)設(shè)定模型:Xjx/e%其中，Y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。練習(xí)題7.5參考解答：0 X1t1 X2t2Yt 1Ut1）在局部調(diào)整假定下，先估計(jì)一階自回歸模型：Yt

36、回歸的估計(jì)結(jié)果如下：Dependent Variable: YMethod: Least SquaresDate: 26/02/10 Time: 15:56Samp le (adjusted): 1954 1985In cluded observati ons: 32 after adjustme ntsVariableCoefficie ntStd. Errort-StatisticP rob.C6596.2284344.0781.5184420.1401X10.0474510.0396101.1979400.2410X20.2748380.0905343.0357360.0051丫(-1)

37、0.4052750.1872202.1646990.0391R-squared0.967247Mean dependent var55355.97Adjusted R-squared0.963738S.D. dependent var40464.90S.E. of regressi on7705.604Akaike info criteri on20.85375Sum squared resid1.66E+09Schwarz criteri on21.03697Log likelihood-329.6600F-statistic275.6267Durbi n-Watson stat2.1095

38、34P rob(F-statistic)0.000000回歸方程：Yt6596.2280.04745%0.274838X2t0.405275Yt ,(4344.078)(1.518442)(0.039610)(1.197940)(0.090534)(3.035736)(0.187220)(2.164699)2R =0.967247 F=275.6267DW=2.109534根據(jù)局部調(diào)整模型的參數(shù)關(guān)系,有 lnIn將上述估計(jì)結(jié)果代入得到:In Y?lnY0 ln X1t1 ln X2t2lnYt 10.4052750.59472511091.223670-0.0797810.462126故局部調(diào)

39、整模型估計(jì)結(jié)果為Yt 11091.223670.07978 X1t 0.462126 X 2t經(jīng)濟(jì)意義：在其他條件不變的情況下，該地區(qū)社會(huì)商品零售額每增加1億元，幣流通量增加0.07978億元。同樣，在其他條件不變的情況下，該地區(qū)城鄉(xiāng)居民儲(chǔ)蓄余額每 增加1億元，則預(yù)期年末貨幣流通量增加0.462126 億元。則預(yù)期年末貨2）先對(duì)數(shù)變換模型形式,lnYtlnIn X1t 2 ln X2t ut在局部調(diào)整假定下，先估計(jì)一階自回歸模型:* * *2 ln Y 1utln Yt0 ln X1t 1 ln X2t回歸的估計(jì)結(jié)果如下：Depen de nt Variable: LNYMethod: Lea

40、st SquaresDate: 26/02/10 Time: 16:12Samp le (adjusted): 1954 1985In cluded observati ons: 32 after adjustme ntsVariableCoefficie ntStd. Errort-StatisticP rob.C0.6443331.6778880.3840140.7039LNX10.2062300.2555570.8069840.4265LNX20.1801680.1549131.1630310.2546LNY(-1)0.5314450.1092604.8640490.0000R-squa

41、red0.968959Mean dependent var10.70088Adjusted R-squared0.965633S.D. dependent var0.672279S.E. of regressi on0.124629Akaike info criteri on-1.210486Sum squared resid0.434905Schwarz criteri on-1.027269Log likelihood23.36778F-statistic291.3458Durb in -Watson stat1.914829P rob(F-statistic)0.000000回歸方程：I

42、nY,0.644333(1.677888)(0.384014)0.20623In X1t(0.255557)(0.806984)0.180168ln X2t(0.154913)(1.163013)0.531445ln Yt 1(0.531445)(4.864049)2R =0.968959 F=291.3458DW=1.914829根據(jù)局部調(diào)整模型的參數(shù)關(guān)系，有l(wèi)nIn將上述估計(jì)結(jié)果代入得到:In121 0.531445In1.3751490.46855500.4401410.384518故局部調(diào)整模型估計(jì)結(jié)果為：AInY*1.3751490.44014In X1t 0.384518lnX2t

43、經(jīng)濟(jì)意義：貨幣需求對(duì)社會(huì)商品零售額的長(zhǎng)期彈性為: 余額的長(zhǎng)期彈性為0.384518 。0.44104 ;貨幣需求對(duì)城鄉(xiāng)居民儲(chǔ)蓄7.6 設(shè) Mt1Y2Rtt其中：M為實(shí)際貨幣流通量,Y為期望社會(huì)商品零售總額，R為期望儲(chǔ)蓄總額，對(duì)于期望值作如下假定:1Yt(11)Y*1其中1, 2為期望系數(shù)，均為小于1的正數(shù)。(1)如何利用可觀測(cè)的量來(lái)表示Mt ？(2)分析這樣變換存在什么問(wèn)題?(3)利用7.5題的數(shù)據(jù)進(jìn)行回歸,估計(jì)模型，并作檢驗(yàn)。練習(xí)題7.6參考解答：1)首先將M滯后一期并乘上(11)得到(11)Mt1 (11)(11)1Y*1(11)2R*Rt再將原始方程減去該方程，得到2Rt(12)R 11

44、 t 1Mt (11)Mt1111Y2Rt(1 1)R1t (11) t1111Y2R*(12 21)R*1t (11 ) t 1111Y2R*(12)R*1(12)R*1t (11) t1111Y2R*(12)R*12(12) Rt 1t (11) t 1111Y2 2Rt2(12)Rt 1t (11)t 1Mt(11)Mt 111 1Yt22Rt2( 12)R；1t (11) t1(1)Mt1(11)Mt 211 1Yt 122 Rt 12 (12 )Rt 2t 1(11) t 2(12)Mt 1(11)M(1(12 ) 12 ) t 1(12)(111Yt 11) t 2 (12Rt2)

45、(12 )Rt 2(1) - (2)于是Mt可表示為：(1 1)(111Yt2)M t 2(12)Yt 1(212)2)從上面的變化中可看出,隨機(jī)擾動(dòng)項(xiàng)變?yōu)?Rt(11)Rt1)(11(2) t1)Mt 1(21(11)(1而且不是一致這就可能導(dǎo)致出現(xiàn)隨機(jī)擾動(dòng)項(xiàng)的自相關(guān)，進(jìn)而導(dǎo)致估計(jì)出來(lái)的結(jié)果是有偏的,估計(jì)。3)對(duì)()回歸的估計(jì)結(jié)果如下，Dependent Variable: MTMethod: Least SquaresDate: 07/26/05 Time: 00:18Samp le(adjusted): 1955 1985In cluded observati ons: 31 after

46、 adjusti ng endpointsVariableCoefficie ntStd. Errort-StatisticP rob.C9266.49084918.13741.88410.0717Y0.13230.10961.20680.2392Y(-1)-0.12840.1236-1.03890.3091R-0.39570.4883-0.81040.4256R(-1)0.95330.66121.44160.1623MT(-1)0.47290.23612.00280.0566MT(-2)-0.05500.2883-0.19080.8502R-squared0.9691Mean depende

47、nt var56687.1935Adjusted R-squared0.9614S.D.dependentvar40415.2055S.E. of regressi on7932.428Akaike info criteri on20.9909Sum squared resid1510162034Schwarz criteri on21.3147Log likelihood-318.3602F-statistic125.7918Durbi n- Watson stat2.1446P rob(F-statistic)0回歸方程:M t 9266.4908 0.1323Yi 0.1284Yi 1

48、0.3957 Rt 0.9533Rt 1 0.4729Mt 1 0.0550Mt 2可以看到，只有Mt 4的回歸系數(shù)在10%的顯著性水平下是顯著的， 其他回歸系數(shù)均不顯著;F統(tǒng)計(jì)量較大，方程整體顯著;R2較高，模型整體上對(duì)樣本數(shù)據(jù)擬合較好。Y?tR20.727其中,y為通貨膨脹率，x為生產(chǎn)設(shè)備使用率。生產(chǎn)設(shè)備使用率對(duì)通貨膨脹率的短期影響和總的影響分別是多大?如果庫(kù)伊克模型為 丫 b, b2Xt b3Y； 1 t，你怎樣得到生產(chǎn)設(shè)備使用率對(duì)通貨膨脹率的短期影響和長(zhǎng)期影響?練習(xí)題7.7參考解答：1）該模型為有限分布滯后模型，故生產(chǎn)設(shè)備使用率對(duì)通貨膨脹的短期影響為影響為 0.1408+0.2306=0.3714。0.1408，總的利用工具變量法，用丫?1來(lái)代替