计量经济学课后习题答案_庞浩主编

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13(2.334781)(-1.712019)InXxt,InX4z0.273414-0.0323710.955687(1.754955)(-0.241854)InX,”,k0.1613190.0621850.956811(1.660515)(0.671050)InXk,lnX6,0.296971-0.0795180.956262(2.447204)(-0.506227)In,”,0.251591-0.7207900.96281217.32755)(-1.715632)ᵫ$☢&'ᐭᔜ)Ḅt,-ᙳ/0—18—3)=2.131,1ᦪ34℉6In^^2,ஹIn3fஹInX4ஹlnX,,InX^ஹInX7fḄ1ᦪ:;<⚜>?@ABCDEᐭFḄ5GHIJKLMNᐳPឋ஺ᒆ◀)ḄDEULnY=9.163051+0.2358511nX,t1(0.125193)(0.011918)T=73.1914019.78948R=0.958295^=0.960748F=391.6234DW=32.78552ABCᙠᐸ\]3Ḅ^_`abᦈᐭd$ᓣ1%ghijklmᙳn0.23585%,,4.7opᳮrDEUcsB஺+BஹNZ,+BGZ'+BIPOPBCUMஹ+BsSZMN,ᎷpDEtuvᐺᎷpᵨᨬ/z{|}~-ᵨ᪵-1ᦪAC5=-ll793.34468-1.535089612NZ+0.8987877567GZ-1.527089125JZZ+0.1511598429"-0.03683557SZM(3191.096)(0.129778)(0.245466)(1.206242)(0.033759)(0.105329)T=-3.695704-11.828613.661558-1.2659894.4776460.963783(0.018460)-1.995382⌕ᢣ᪗ᑖ᪆&&ᦪU0.995,Ḅ&ᦪU0.993,DEF,-U632.10,DE᦮$4℉஺TḄ

14⊤C◀nஹn᜜ᐸ\]¢£¤ᦈᐭḄ¥¦I34℉6n§¨nḄᦪ©ª«ᦪABC&h¬ᙠNḄMNᐳPឋ஺᪷¯᪵ᦪ¯°ᑮᔜGHḄ᪵?ᐵᦪ³▣᝞:⊤4.3᪵?ᐵᦪ³▣NZGZJZZTP0PCUMSZMNZ1.0000.9810.9820.9460.9850.590GZ0.9811.0000.9990.9040.9990.570JZ0.9820.9991.0000.9040.9980.567ZTP0.9460.9040.9041.0000.9170.6390PCU0.9850.9990.9980.9171.0000.575MSZ0.5900.5700.5670.6390.5751.000MGH¿À?ᐵᦪÁÂᱯĪnஹnஹ§¨nஹᨬÅjk¿À?ᐵᦪIᙠ0.9Æ$஺A⊤CDE¬ᙠḼMNᐳPឋ஺Èᵨ⌲|GMNᐳPឋÉ⚪,ᑖÄËCS¢NZஹGZஹJZZஹTP0PஹCUMஹSZMḄÌᐗ,᝞:NZGZJZZTP0PC1Î一参0.9358230.3486152.2247800.467431()数估计值T10.7582419.6467918.555507.5487601,-可0.8282520.9414630.9348370.703644()决系数一修0.8210960.9390240.9321220.691296().正可系」ᐸÏᐭGZḄḄ&ᦪᨬᜧÆGZUÑẠ
ᐭᐸ⌲变量NZGZJZZTP0PCUMGZஹ-1.110.72NZ29

15-8.6716.279GZஹ1.26-5.8JZZ0412.49-1.9934GZஹ0.41-0.1TPO717P10.5-1.9930GZஹ0.78-0.3CUM5282.46-1.3472GZஹ0.36SZM16.63ᙠGZḄÑᑴB$ᑖÄᐭᐸÚ)ÛÜNZஹJZZஹTPOPஹCUMஹSZMḄᦪU«<⚜>-ÓÔ஺\ÕAÖIJKLNḄMNᐳPឋ஺ḄUCS=93.08109437+0.3486152401GZ(412.5593)(0.017744)T=0.22561919.64679R2=0.941463RÌ=0.939024F=385.9965ABCᙠᐸ\]3Ḅ^_ndn1Þᐗ£¤ᦈᐭmᙳn0.348615Þᐗ஺ßàáâãឋä)⚪1ὃæᫀ5.1(1)\U=ᡠÆé%=_!_,ᵨì{ípDEîï°X2i(Ì=41-+᜛2+᜛3ò+òA2iA2/A2/A2i$óDEḄôõöã⚗ḄãUÌøpùᦪᓽU1oVar(—2-)=—5-Var(M.)=b((2)᪷ᩗᨬḄᦪ•*B\=Y-PX-fiX2233>CMὃ

16A(E%y&4)(E()HZ(2M4)(E%)))A=-----------------------------------------------o-------ᐸ"y*_2%ᐭ2,y*_y*_Z%ᓃ2=^T,=4=X2ᔆᐘX=X3Ky*=ᓃ-:5.2(1)I,ஹ1,yஹI஻Y_/3\X&ஹY_W.•>ln(w)=ln(-----)=ln(l+----4—)«----4—=u-1Ḝ@/3\XA4X.u=ln(M)+lI&E[ln(஻)]=0.-.E(஻)=E[ln(u)+1]=E[ln(w)]+1=1(2)E[ln(஻)]=Z஽InN=InO஻/=0=>"=1E(஻)=zn஻j=iVWXYZ=iᡠ\E(4=1]V^_ᨵE(In//=0(3)bcdeᑖ&1nXTn*_]=4(1nXi-Xi-)+(1n஻j-1n஻i)ᑣᨵ&E[(ln஻j-ln஻”])]=05.3(1)ijk᪵mnoḄpᑏr:Y=11.44213599+0.6267829962*X(3.629253)(0.019872)t=3.15275231.54097R2=0.944911R2=0.943961S.E.=9.158900DW=1.597946F=994.8326(2)✌ᐜ,ᵨGoldfeld-Quandtde஺a.᪵mXᢥ⌴᣸"1/4Ḅ᪵mᑖᑖḄ᪵mᓽ"]=n=222b.ᑖbᑖḄ᪵mᨬᑮᑖḄᓽ

17Zd=624.3004ZW=2495.840F¡¢TVJ-2495.840=-----------39978Ze£624.3004¤_a=0.05,¥Fᑖ¦⊤¨©ª«஺5¬2°20®=2.12஺c.°±¨©ª²F¡¢ªᨵ³=4.1390>஺5¬2°20®=2.12,´µijkḄ¶·¸⚗ºᙠ஺ᐸ¼ᵨWhitede஺ᐹ¿ÀÁÂÃ⊤WhiteHeteroskedasticityTest:F-statistic6.105557Probability0.0039580bs*R-squared10.58597Probability0.005027¤_a=0.05,ᙠÉᵫË2Ã¥ᓱᑖ¦⊤#2=5.9915஺°±¨©ª²ᓱ¡¢ªᓽ஻*=10-864°>/=59915,Î᪵´µjk"Ḅ¶·¸⚗ºᙠ஺¬2®ᵨᩗᦪW=l/lelÏᩗᨬ᝞ÃÀÁDependentVariable:YMethod:LeastSquaresDate:05/28/07Time:00:20Sample:160Includedobservations:60Weightingseries:1/RVariableCoefficieStd.Errort-StatistiProb.ntcC27.500006.09E-084.52E+080.0000X0.5000007.16E-106.98E+080.0000WeightedStatisticsR-squared1.000000Meandependentvar70.01964AdjustedR-squared1.000000S.D.dependentvar379.8909S.E.ofregression8.44E-10Akaikeinfo-38.9162criterion2

18Sumsquaredresid4.13E-17Schwarzcriterion-38.84641Loglikelihood1169.487F-statistic4.88E+17Durbin-Watsonstat0.786091Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.883132Meandependentvar119.6667AdjustedR-squared0.881117S.D.dependentvar38.68984S.E.ofregression13.34005Sumsquaredresid10321.50Durbin-Watsonstat0.377804White:WhiteHeteroskedasticityTest:F-statistic2.357523Probability0.1038220bs*R-squared4.584017Probability0.101063TestEquation:DependentVariable:STD_RESID2Method:LeastSquaresDate:05/28/07Time:00:27Sample:160Includedobservations:60VariableCoefficieStd.Errort-StatistiProb.ntcC3.86E-191.73E-192.2337560.0294X3.21E-212.16E-211.4895320.1419X'2-7.59E-246.18E-24-1.2296410.2239R-squared0.076400Meandependentvar6.88E-19AdjustedR-squared0.043993S.D.dependentvar1.56E-19S.E.ofregression1.52E-19Sumsquaredresid1.32E-36F-statistic2.357523Durbin-Watsonstat1.191531Prob(F-statistic)0.1038225.4ÚY⊤ÛÜÝÞߪX1-X5ᑖ⊤ÛÜÝàáâஹãä☢æஹᓄèᵨ¢ஹᡝᙳë_ìßÜ·áâ஺íîjk&Y=0஺+1Xஹ+AX?+&X/஺CnoÀÁ᝞Ã&

19y=4.717198+0.039615X>0.036895X2+0.263256X+0.013463X+0.025469X345/=(0.516910)(1.452697)(-0.474813)(0.479104)(2.712997)(1.625993)R?=0.974539R2=0.953321DW=1.969898F=45.93047NnoÀÁ\ïZjkḄR2R2ªð±ñF¡¢òó℉஺õö◀X4Ḅøᦪó℉ù᜜ᐸûøᦪᙳVó℉jkWºᙠüýᐳÿឋ஺ᔜḄᐵᦪ஺ᐵᦪ▣XIX2X3X4X5XI1.0000000.8518670.9631730.4569130.892506X20.8518671.0000000.8435410.5493900.856933X30.9631730.8435411.0000000.5830480.924806X40.4569130.5493900.5830481.0000000.543765X50.8925060.8569330.9248060.5437651.000000ᵫᐵᦪ▣!"#$%Ḅᐵᦪ&'#(ᙠ*+ᐳ-ឋ஺.ᵨ⌲123Ḅ45#ᩭ7*+ᐳ-ឋ8⚪஺ᑖ;XIஹX2ஹX3ஹX4ஹX5Ḅ@ᐗ23#BC᝞E⊤ᡠHI@ᐗ23BCXIX2X3X4X5Zᦪ[\0.0840780.4567671.5264100.0352770.078269t]8.0976515.09937111.621322.9913268.197929R20.8676760.7222500.9310610.4722410.870476R20.8544430.6944750.9241670.4194650.857524ᐸKLᐭX3ḄNOP2ᨬᜧ#X3STẠ#VWLᐭᐸX⌲123#BC᝞E:Lᐭ^Ḅ23BC(@)XIX2X3X4X5R2X3,XI0.0026361.4819090.915816(0.089770)(2.879293X3,X20.0669091.3602910.9212040.7899585.456584X3,X41.3522910.0096910.9444929.7767642.159071X3,X51.1156800.0235520.929684(3.355936)(1.335921)bc&#^LᐭX4ḄNOR2=0.944492,ᦋeᨬᜧ஺fgbhijᩭ!#ᡝᙳmnop>qrsp\ᨵuv#wxyᶇX4,{LᐭᐸX⌲123#BC᝞E:Lᐭ^Ḅ23BC(|)XIX2X3X4X5R2

20X3,X4XI0.0354380.6966510.0128870.949360(1.365712)(1.399128)(2.638461)X3,X4X20.0474861.2415020.0092960.940595(1.487193)(5.528062)(1.984375)X3,X4,X50.9519240.0095940.0230590.952585(3.375236)(2.312344)(1.592574)LᐭXI~NOḄR2ᜧ#t\℉LᐭX2~R2#fᦪ℉Ꮇ᝞X5~NOḄR2ᜧ#t\℉஺*+ᐳ-ឋuvḄ23BCSIf=14.74802+1.352291X+0.00969IX134”1.8354419.7767642.159071R2=0.954584R2=0.944492DW=2.482223F=94.58409White:nR2=4.132927<%(5)=11.0705Ꮇ#(ᙠN஺5.5(1)᪵23஺K=192.9944+0.0319%(0.1948)(3.83)R2=0.4783,s.e.=2759.15,F=14,6692(2)ᑭᵨWhiteᑨ¢ᔲ(ᙠN஺WhiteHeteroskedasticityTest:F-statistic3.057161Probability0.076976Obs*R-squared5.212471Probability0.073812·n«=°O5º»ᵫ¼S2E#½ᓱNᑖ¿⊤#ÀÁÂ\/=59915#Äwhite]“R2=5.2125,ᨵᑣÆÇᎷ#ÈÉK(ᙠN஺(3)ᨵGlejserᑨ¢ᔲ(ᙠN஺bÌÍ#Î᝞EÏᦪÐÑ|!?|-Py[x+GT2À᪵[Ñ\e\=6.4435V%(4.5658)R2=0.2482ᵫx#!"KÒÓÔ⚗ᨵÖ(ᙠN஺(4)>NḄ஺ÎᩗᦪSw=UX,À᝞E[BC

217=-243.4910+0.0367X(-1.7997)(5.5255)R2=0.1684,s.e.=694.2181,F=30.53095.623BC᝞EIK1=0.89+0.237200%If=(4.356086)(15.89724)se=(0.2043120.014921R?=0.933511R2=0.929817DW=1.363966F=252.7223=0.32ᕖ=2024=6.7467»EO5(88)=3.44ÆÇÚ#(ᙠN஺ÎᩗᦪSÛ=%,Lᩗ~23BC:f1=0.752923+0.249487%ise=(0.0982550.011723t=(7.662934)(21.28124)R?=0.765382R2=0.752348DW=1.240480F=452.89145.7(1)Ü23[Ñ஺K=4.6103+0.7574%(4.2495)(5.0516)*=0.5864,s.e.=3.3910/=25.5183ÝÞḄßN>Ḅᦣáâ302520X15105001020304050RESIDA2ᵫâÐ!"#ᨵÖ(ᙠN஺

22(2)ãᣵåᑭḄᦪæ~#23Àᑮ᝞E/=6.7381+0.2215X(2.8254)(0.3987)R2=0.0093,se=3.3906,F=0.1589ÝÞßN>Ḅᦣáâ108X6-010203040RESIDA2gâÐ!"#NḄO¼é஺(3)᝞Cãᣵåᑭᦪæ~À"(ᙠNḄBê#ᑣÈÉNឋëìwSí\Ḅ"îÄpï஺5.8(1)23BC᝞EIY=12.12542711+0.1043661755*X(19.51012)(0.008439)t=(0.621494)(12.36777)R2=0.854718R2=0849130S.E.=56.89947DW=1.212859F=152.9617├óᦈᐭõö@ᐗ#├óᑭ÷ßᙳö0.104366ᐗ·na=0.05ø=12.36777>kg(26)=2.056,ÆÇᎷ#ÈÉ├óᦈᐭ>├óᑭ÷ᨵ℉ឋuv஺û=152.9617>405(1#26)=4.23R2=0.854696,⊤ÉNO℉#füºO¼&ý(2)âÐ5I

235000-4000-3000x2000-1000-0--200-1000100RESIDgâK!"#e?,.ᨵÒḼX
ᜧ
ᜧḄᡠᙠ஺ᵨGlejserᔲᙠ஺!"#᝞%&ᦪ()|e|=/3>[X+ci20᪵234)|e1=1.049787"'t=8.075394/?2=0.306629EᦪF℉HI0,ᵫLMNOPQR⚗ᨵᙠ஺WhiteWWhiteHeteroskedasticityTest:F-statistic3.609579Probability0.041959Obs*R-squared6.273796Probability0.043417nR2=6.273796>^2(2)=5.91147005ijkᎷmᙠ஺

24W=n(3)qḄrs஺#ᩗᦪI/X
0᝞%34uvDependentVariable:YMethod:LeastSquaresDate:05/28/07Time:00:16Sample:128Includedobservations:28Weightingseries:1/X^2VariableCoefficienStd.Errort-StatisticProb.tC6.4548963.4856341.8518570.0754X0.1070750.0109849.7481670.0000WeightedStatisticsR-squared0.922863Meandependentvar67.93474AdjustedR-squared0.919896S.D.dependentvar75.46572S.E.ofregression21.35880Akaikeinfocriterion9.029554Sumsquaredresid11861.15Schwarzcriterion9.124711Loglikelihood-124.4137F-statistic95.02675Durbin-Watsonstat1.909174Prob(F-statiStic)0.000000UnweightedStatisticsR-squared0.854132Meandependentvar213.4650AdjustedR-squared0.848522S.D.dependentvar146.4895S.E.ofregression57.01397Sumsquaredresid84515.42Durbin-Watsonstat1.244888———WhiteWWhiteHeteroskedasticityTest:F-statistic3.143257Probability0.060574Obs*R-squared5.626143Probability0.060020nR-=5.626143<^2(2)=5.91147005Hᙠ.5.9(1)᪵2&ᦪ஺F=43.8967+0.8104%(2.1891)(37.7771)R2=0.9854,se=60.4920,F=1427.11234ḄuvMᔜ⚗ᢣ᪗ᙳF℉qᦣMNᙠ஺

25(2)ᵨWhiteᑨ¡ᔲᙠ஺WhiteHeteroskedasticityTest:F-statistic9.509463Probability0.001252Obs*R-squared11.21085Probability0.003678ᵫ¢⊤¤஻¦=112109,§¨a=0.()5,ᙠ©ᵫªI2%«ᓱᑖ®⊤0¯°±I/=5.9915,Fᯠ“R2=11.2109>/=5.9915,ᑣijkᎷm¶·ᙠ஺¸¹ºᵨARCHᑨ¡ᔲᙠ஺!"⌱¼½▤ᦪI1,ᑣARCHuv¿%⊤ARCHTest:F-statistic9.394796Probability0.006109Obs*R-squared7.031364Probability0.008009ᵫ¢⊤¤(஻¹஻À2=7.0314,ᙠ&=().()5©ᵫªIi%«ᓱᑖ®⊤0¯°±IÃ஺5(1)=3.8415,Fᯠ,(஻-p)R2=7.0314ுÅÆ(1)=3.8415,ᑣ¶·OPQR⚗ᙠ஺(3)rs஺#ᩗᦪIW=l/e2,0᝞%34uvDependentVariable:YMethod:LeastSquaresDate:05/28/07Time:02:15Sample:19782000Includedobservations:23Weightingseries:W2VariableCoefficieStd.Errort-StatistiProb.ntcC6.6590270.25376126.241330.0000X0.8686910.000985881.79380.0000WeightedStatisticsR-squared1.000000Meandependentvar224.0761

26AdjustedR-squared1.000000S.D.dependentvar988.1865S.E.ofregression0.206384Akaikeinfo-0.23521criterion9Sumsquaredresid0.894478Schwarzcriterion-0.136481Loglikelihood4.705022F-statistic777560.3Durbin-Watsonstat1.281139Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.980282Meandependentvar633.0004AdjustedR-squared0.979343S.D.dependentvar490.5345S.E.ofregression70.50182Sumsquaredresid104380.6Durbin-Watsonstat0.279924Y=6.65902728+0.8686910728*XWhiteWhiteHeteroskedasticityTest:F-statistic1.0213370.378144ProbabilityObs*R-squared2.1313890.344489Probabilit_yḄ⊤Èᨵ·FḄÉÊ஺5.10ᒆ◀ᱥ΢ÏÐѽḄuv᝞%W7=36.66453+0.753946%”(3.516150)(22.43266)R2=0.959941R2=0.958033F=503.2243ᐸOyÓ⊤Ô▭Ö×ØNxÓ⊤Ô▭ØÚᦈᐭᵨWhiteÝᩭᔲᙠWWhiteHeteroskedasticityTest:F-statistic1.647288Probability0.217647Obs*R-squared3.252914Probability0.196625TestEquation:DependentVariable:RESID2Method:LeastSquaresDate:05/07/07Time:17:14

27Sample:19782000Includedobservations:23VariableCoefficieStd.Errort-StatistiProb.ntcC105.9636475.51820.2228380.8259XI0.2642903.0373300.0870140.9315Xr20.0009670.0043920.2200610.8281R-squared0.141431Meandependentvar275.8818AdjustedR-squared0.055574S.D.dependentvar272.6726S.E.ofregression264.9875Akaikeinfo14.11835criterionSumsquaredresid1404368.Schwarzcriterion14.26646Loglikelihood-159.3610F-statistic1.647288Durbin-Watsonstat1.456581Prob(F-statistic)0.217647nW=3.252914V/2(2)=5.9915,⊤·Hᙠ஺005G-QWDependentVariable:Y1Method:LeastSquaresDate:05/07/07Time:17:18Sample:19781986Includedobservations:9VariableCoefficieStd.Errort-StatistiProb.ntcC4.18512418.099180.2312330.8237XI0.8619550.0868519.9245250.0000R-squared0.933647Meandependentvar180.2601AdjustedR-squared0.924168S.D.dependentvar39.01106S.E.ofregression10.74272Akaikeinfo7.779464criterionSumsquaredresid807.8425Schwarzcriterion7.823292Loglikelihood-33.00759F-statistic98.49620Durbin-Watsonstat2.717044Prob(F-statistic)0.000022DependentVariable:Y1Method:LeastSquaresDate:05/07/07Time:17:18Sample:19922000Includedobservations:9VariableCoefficieStd.Errort-StatistiProb.ntcC104.093620.845324.9936220.0016

28XI0.5960560.05136711.603900.0000R-squared0.950583Meandependentvar339.0480AdjustedR-squared0.943523S.D.dependentvar62.54899S.E.ofregression14.86470Akaikeinfo8.428985criterionSumsquaredresid1546.715Schwarzcriterion8.472813Loglikelihood-35.93043F-statistic134.6506Durbin-Watsonstat0.987995Prob(F-statistic)0.000008>,W=807.8425,\^á=1546.715,F=1546.715/807.8425=1.9146,F…(7,7)2i-<0.05=3.79,⊤·Hᙠ஺⊤·ᒆ◀ᱥ΢.ÏÐÑã½Ḅä⚪ᨵᡠᦋᗐ஺èé⚪6.1êὃìW(1)ᦈᐭ¹Ö×IY,=-9.4287+0.9359%,Se=(2.5043)(0.0075)t=(-3.7650)(125.3411)/=0.9978,F=15710.39,df=34,=0.5234(2)q᪵2I36ஹ¹îḄஹ5%F℉ð«஻/ñ4⊤¤d=1.411,&=1.525,O஻/᜛<&,FᯠÖ×Oᨵ©óᐵ஺(3)õᵨö÷ᑖÝe-0.72855e,_1tY,=-3.7831+0.9484X,(1.8710)(0.0189)t=(-2.022)(50.1682)R*2=0.9871R2=0.9867F=2516.848DW=2.097157«5%F℉ðḄ஻/ñ4⊤¤&=1.402,4=1.519,O஻ᓝù2,0972>d,¶·ö÷ᑖOúû©óᐵ஺üýᑨ¨EᦪR\tஹFñ4ᙳþᑮᳮ
஺ᵫᑖ2*-37831᜛=;/(I_Q)=—°°஺=-13.93660°1-0.72855=0.9484ᡠᨬḄY,=-13.9366+0.9484%,⚪6.2"ὃ$%(1))*n=16,k'=\,ᙠa=0.05Ḅ/℉123DW67⊤92

294=1.106%=1.371஺@஺A=0.8252<4,ᡠᑨG@HᙠIJKᐵ஺)*n=16,k'=2,ᙠa=0.05Ḅ/℉123DW67⊤92d=0.982%=1.539஺@O<஺A=L82<4-%,ᡠᑨG@RHᙠLJKᐵ஺(2)JKᐵSᵫT6.1ḄUV2WX᣸◀[\]Ḅ⚗஺(3)_ᎷJKᐵaᵫTḄUV⌼ᡂḄ2Wde⌕ghSḄiᦪkᨵᐜn9o஺pIḄJKᐵaqrstᑖuvuᩭxI஺⚪6.3"ὃ$%(1)ᦈᐭ{Y,=79.930+0.690%,(6.38)=(12.399)(0.013)t=(6.446)(53.621)R2=0.994DW=0.515(2)஺ᵨ=0.575,}஺=5%,3~14=118,஻=L40,(ᔴU⚗HᙠIJKᐵ஺(3)ᵨstᑖuᵨqᨬu7PḄ7P,e-0.657e,_(t=(0.178)”(3.701)g*=36.010+0.669%Se=(8.105)(0.021)f=(4.443)(32.416)R2=0.985OW=1.830஺1.830,9=1.158d=1.391,@<஺A=1.83<4-%Wd2ᙠstvᑖ@JKᐵ஺ᵫᑖ*,3601=/?/(i-p)=25=104.985001-0.657¡M=0N=0.669Wd2xI¢Ḅ£¤¥Y,=104.985+0.669%,6.4"ὃ$%(1)£¤¦§᝞1

30Y=50.87454+0.637437%,t(8.291058)(0.021242)t=(6.136073)(30.00846)R2=0.975095R2=0.974012F=900.5078DW=0.352762(2)¬n£¤¦§®2"ᦪᙳ/℉2°±²³஺´Ḅ¬nqrwhite¬n9RHᙠ´஺DW¬n)*n=25,᱄=1,ᙠa=0.05Ḅ/℉123DW67⊤92<=1.288B=1.454஺@஺A=0.352762<(2ᡠᑨG@HᙠIJKᐵ஺(3)ᵨstᑖuxI@HᙠḄJKᐵ¹⚪e,=0.850961%f=6.68271y=13.97334+0.535125Xf=2.9175337.154796R2=0.6699417R2=0.685754F=51.1911DW=2.37766)*n=24,Z'=l,ᙠa=0.05Ḅ/℉123DW67⊤92=1.273=1.446«@%A=2.37766<4—%,ᡠᑨG@RHᙠJKᐵ஺ᵫᑖÁ=/?/(1-p)=13.97334/(1-0.85096)=93.75566=4=0.535125ᡠxI¢ḄY,=93.7556+0.535125%,6.5"ὃ%ᫀ(1)ÃÄ◤gg=-1690.309+0.387979X,t=(-3.824856)(21.93401)R2=0.96587R2=0.963863F=481.1009DW=0.523859)*n=19,k'=l,ᙠa=0.05Ḅ/℉123DW67⊤92=1.18ÇজᑘÊ@DW=0.523859

31ὡ=0.920175%t=3.745896Y*=-921.9201+0.626368Xf=-3.3833179.101192R2=0.838109R2=0.82799F=82.83169DW=0.7150686.6"ὃ$%(1)£¤¦§᝞1ln^=2.171041+0.95109Int=(9.007529)(30.00846)R2=0.969199R2=0.967578F=597.8626DW=1.159788)*n=21,%'=1,ᙠa=0.05Ḅ/℉123DW67⊤924=1.221^=1.42஺@DW=1.159788

32)*n=20,k'=l,ᙠa=0.05Ḅ/℉123DW67⊤924=1.201%=1.411஺@%<஺A=1.590363<4-%,ᡠᑨGßᓄᦪá¢Ḅ@RHᙠJKᐵ஺⚪7.1"ὃ$%(1)ᐜᵨä{壤2¦§᝞1PCE=-216.4269+1.008106PDIt=(-6.619723)(67.0592)2R2=0.996455R=0.996233DW=1.366654F=4496.936ᑭᵨäåÃ磤2¦§᝞1PCE,=—233.2736+0.982382PZ)/,+0.037158PCÁτII1—1t=(-5.120436)(6.970817)(0.257997)R2=0.996542R2=0.996048DW=1.570195F=2017.064(2){ᑮMPC=L008106ᑮ2ìíMPC=0.982382,îíMPC=0.982382+(0.037158)=1.01954⚪7.2"ὃ%ᫀ(1)ᙠïðñ᦮Ꮇ*12ᐜ7᝞1kḄ{▤J£¤ᓃ+£ஹ+஻7¦§᝞1Y,=-15.10403+0.629273X,+0.271676K.se=(4.72945)(0.097819)(0.114858)t=(-3.193613)(6.433031)(2.365315)R2=0.987125R2=0.985695F=690.0561DW=1.518595᪷áïðñ᦮Ḅ"ᦪᐵø2ᨵa=6a=S/30N=\-3u,=Su,ùú7¦§Ñᐭᑮ3=1-Q=1-0.271676=0.728324a=-=-20.7380644=2=0.86400188ᦑïðñ᦮7¦§R*=-20.738064+0.86400IX,üýþt$ÿ
ᙢ├1ᐗᩭ⚜ᨬᢗ0.864001ᐗ஺"ᵨ$%h'()▤+,ᐵ

33n/1=(1—2)ஹl-nVar(jff^)(l-|xl.518595)22=1.34021-22x0.1148582ᙠ<℉ឋ?@a=005BC᪗EF᝱ᑖI⊤KLMNe/=1.96,ᵫR/2S=1.3402

34a=a=-20.7380642=2=0.864001yYᦑ+〉bcnoz{Y,=-20.738064+0.864001X¡
ᙢ├⚜1ᐗ¢ᐸᢗ@ᙳ0.864001ᐗ஺"ᵨ$%h'()▤+,ᐵfl-|xl.518595g22=1.3400891-22x0.1148582ᙠ<℉ឋ?@¥=005B,C᪗EF᝱ᑖI⊤KLMN¦=1.96,ᵫRW=1.340089

35Sumsquaredresid542.7059Schwarzcriterion6.886378Loglikelihood-56.19666F-statistic299.7429Durbin-Watsonstat1.130400Prob(F-statiStic)0.000000ᓽa=-35.49124,a=0.89101,a,=-0.66990,a=0.1043902ᵫ(*)r¨K=0.89101,4=0.32550,&=-0.03123,^=-0.17917,/7=-0.1183334ᵫÄÅℳÇ⚗r±ᣚ¨K᝞lnoz{Y,I=-35.49234+0.89101XI,+0.32550Xr—,I,-0.03123Xl—,£,-0.17917%1—,J,-0.11833%<—,44ÊË⚪7.3ὃÍᙠhij᦮ᎷÎ+〉ᎷlBÏbcᨬÐÑÒᓄ)▤+`abc஺Ôᐜno᝞lqrḄ)▤+`abcᓃ=a*+AX+£Ö+஻noz{᝞lX=1.896645+0.102199X,+0.0147E.se=(1.167127)(0.024782)(0.182865)t=(1.625255)(4.123961)(0.080389)R2=0.58475R2=0.557066F=21.12278DW=1.901308Øz{ÙtNFNÑÚ<℉R?dÛÚÜ஺(1)᪷hij᦮bcḄᦪᐵᨵa*=Ý0*="0
=\—3uN=Su,,Bnoz{ᐭKᑮ8=0.9853,£=0.1037,a=1.9249ᦑhij᦮bcÞ*=1.9249+0.1037X,ßàᑮᐰḕÞã¦NḄoᑜNåæ)çᩭ⚜Ḅᨬè஺ᐰḕÞã¦Noᑜ1(ᐗ)ᑣᩭ⚜ᨬè0.1037ᐗ஺(2)᪷+〉bcḄᦪᐵᨵa*=ya0*=20N=l—yuN=%—(l—y)kVᐭKᑮ/=0.9853,/7=0.1037,a=1.9249ᦑ+〉bcY=1.9249+0.1037XtḄ±ᓄ°éRᐰḕÞã¦NḄ⚜N஺ᐰḕÞã¦N⚜1(ᐗ)¢è0.1037(ᐗ)஺(3)hij᦮bcÎ+〉bcḄêᙠRhij᦮bcÛ³±èḄhij᦮ëKᑮḄë+〉bcÛᵫ¡±èḄ+〉ìíëKᑮḄ஺ᵫ`az{¨îYª«)Ḅ`aᦪïd<℉^_ðçbcḄ\Ñdᔠᳮ஺ÊË⚪7.4ὃÍ(1)ᙠhij᦮Ꮇlᐜno᝞lqrḄ)▤+`abcὡ=/+ôõ+.ö,+÷ø+“noz{᝞l

36Y=6596.228+0.04745IX.,+0.274838X,,+0.405275/.se=(4344.078)(0.03961)(0.090543)(0.187220)t=(1.518442)(1.19794)(3.035736)(2.164699)R2=0.967247R2=0.963738F=275.6267DW=2.109534᪷hij᦮bcḄᦪᐵᨵa*=úû=_)᜛=ýþ=1—5஻=Su,Bnoz{ᐭKᑮb=1-£=1-0.405275=0.594725a=ÿ=11091.22367=0.07978/="=0.4621263313ᦑ᦮/*=11091.22367+0.07978X„+0.462126X,2!"#$%&ᙠᐸ)ᩩ+,-Ḅ/0123ᙢ567ᖪ9:;<=>?1@ᐗ2ᑣ⚜DEFGHIJK>?0.07978@ᐗ஺M᪵2ᙠᐸ)ᩩ+,-Ḅ/0123ᙢ5OPQRSTU<=>?1@ᐗ2ᑣ⚜DEFGHIJK>?0.462126@ᐗ஺(2)ᙠ᦮ᎷW12ᐜ᝞1Z[Ḅ\▤^_`Ing=a*+5InX”+0NInX+/?gInh+஻g2l᝞1ln£=0.644333+0.20623InX„+0.180168InX,+0.531445InE.2se=(l.677888)(0.255557)(0.154913)(0.10926)t=(0.384014)(0.806984)(1.163031)(4.864049)R2=0.968959R2=0.965633F=291.3458DW=1.914829᪷x᦮Ḅyᦪᐵ|2ᨵIna*=bIna]=ᵨ஺£g=ᱥg=1\bᐭᑮb=1-᜛g=1-0.531445=0.468555Ina=^y-=1.375149ᱏ=,=0.44014/=ᓤ=0.384518ᦑ᦮Ing*=1.375149+0.440141nX),+0.3845181nX,2(3)ᵫ(1)2DGHIJ◤Y=6596.228+0.047451X.,+0.274838X,,+0.405275/.Iir/rr—τDGHIJ◤^=11091.22367+0.07978X,,+0.462126X,2

37ᵫ(2),In/=0.644333+0.20623In+0.180168InX+0.531445InY_2/rtIng*=1.375149+0.44014In+0.384518InX2lᡠ2GH◤67ᖪ9:;<ḄDឋ0.20623,Dឋ0.44104஺GH◤OPQRSTU<ḄDឋ0.180168,Dឋ0.384518஺⚪7.5yὃ%(1)✌ᐜM¡\D¢£°\¥)ᑮ(1-ᱏ)MT=(1-¨©+(1-%)ẓ:+(1-ᱏ)9+A-.=>M-(1\ᱏ)MT=+A[K-(1-/i)M-(1\%)ᵨ\1=a%+᜛/+ᔛ2&+A(/i-/)Ci+-(i-/i)A-i...প2M,_-(1-7,)^,_=a/,+A/l^-l+A/2^-1+^2(/l-/2)<2+Z<-1-0-/l)A-2t2.•.(1-7)[A/,_-(1-/)A/,_]=21I2(I-/2W1+(l-/)Ariy,-l+0-72)Z?2/2/?-l+Z?2(7|-n)0-72)^22(+(1-%)[஻,—)%]……ফ(1)-(2)ÉÊ?2⊤ÌM=7"+ᗓ--(1-Î)2J+%-—ÐT)R-]+(%-%)MT+(1-7,)(1-%)Ñ.2+4,-(2+%-%)4-1+(1-/)(1-72)4-2(*)(2)஻2=஻2\(2+%\%)A,-1+(1-/1)(1-/)஻-2,ÒÓÔÕÖ×ØÙÚ᡾Ü⚗Ḅ^Þ2ᐵ஺ÒÓÔÕÖ×ᩭḄÊᨵàḄ2áâ,Ê\Ö஺(3)ᑭᵨ(*)äå_`2᝞1DependentVariable:MTMethod:LeastSquaresDate:07/26/05Time:00:18Sample(adjusted):19551985Includedobservations:31afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C9266.49084918.13741.88410.0717Y0.13230.10961.20680.2392Y(-l)-0.12840.1236-1.03890.3091R-0.39570.4883-0.81040.4256R(-l)0.95330.66121.44160.1623MT(-l)0.47290.23612.00280.0566

38MT(-2)-0.05500.2883-0.19080.8502R-squared0.9691Meandependentvar56687.1935AdjustedR-squared0.9614S.D.dependentvar40415.2055S.E.ofregression7932.428Akaikeinfo20.9909criterionSumsquaredresid1510162034Schwarzcriterion21.3147Loglikelihood-318.3602F-statistic125.7918Durbin-Watsonstat2.1446Prob(F-statiStic)0⚪7.6yὃ%(1)Døù|ᦪ0.1408,Døù|ᦪ0.1408+0.2306=0.3714(2)ᑭᵨúᐹ-Kü஺⌱ᵨX-ᩭþú_௃2äå஺Z=a*+Z?gX,+/?X-+஻g⚪7.7yὃ%(1)ÿὃ
ᦈᐭḄᡃ✌ᐜᓃᐵXḄᓽ᝞Y,=a+/3X,+u,0᝞(⊤7.7.1)஺⊤7.7.1Method:LeastSquaresDate:03/09/05Time:22:30Sample:19752004Includedobservations:30VariableCoefficientStd.Errort-StatisticProb.C27.765947.9450833.4947330.0016X0.8077310.02284035,365420.0000R-squared0.978103Meandependentvar262.1725AdjustedR-squared0.977321S.D.dependentvar159.3349S.E.ofregression23.99515Akaikeinfocriterion9.257921Sumsquaredresid16121.49Schwarzcriterion9.351334Loglikelihood-136.8688F-statistic1250.713Durbin-Watsonstat1.280986Prob(F-statistic)0.000000(ᩭ*t,-.ஹF,-.1R245℉7ᙠ5℉ឋ:;a=005ᓃDW.1=1.28<4=1.3,GH᡾J⚗LᙠMNOᐵ◤QRSᦋ஺UVWXYZ[\XYᦈᐭḄ]^_\`aᔜYᦈᐭ:;ḄcdᡃᙠWefghijᦈᐭklXḄmnopQRᑖ᪆஺᝞sᡠeᑖumnvwQRxyzLᙠNᵫ|}ᜫᐳឋ⚪஺(2)⌱QRᑖ᪆ᓽxy᝞ᓄᓃ=a*+&X,+4+“ᑭᵨᡠᦪ(⊤7.7.2)஺⊤7.7.2

39DependentVariable:YMethod:LeastSquaresDate:03/09/05Time:22:37Sample(adjusted):19762004Includedobservations:29afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C-6.9056864.179931-1.6521050.1105X0.2518650.0436385.7717170.0000Y(-1)0.8136280.06299112.916570.0000R-squared0.997002Meandependentvar268.0696AdjustedR-squared0.996772S.D.dependentvar158.7886S.E.ofregression9.021969Akaikeinfocriterion7.334900Sumsquaredresid2116.294Schwarzcriterion7.476344Loglikelihood-103.3560F-statistic4323.744Durbin-Watsonstat1.215935Prob(F-statistic)0.0000005t,-.ஹF,-.1R245℉7(l-|x1.215935)291-29x0.062912=2.2442h=1.96aᙠ5℉ឋ:;஺=005W᪗M᝱ᑖu⊤.2,ᵫττh=1.96a\h\=2,2442>5,ᑣ¡Ꮇ£°¥°,GHNLᙠ•▤NOᐵ◤¨Q©ªSᦋ஺«3☢ᡃᣚ©®¯|QRᑖ᪆஺ὅḄ±©®²ᩖḄR´`µ©¶☢⚜¸ᦈᐭḄᜧº»¼zᓽὅzᢥ᯿ᦈᐭ⚜¸¿ÀNÁḄyᑜÃÄ©¶☢V▭ÆÆÇ⚜yḄÈÉLᙠÊËὅz⚜¸ḄyᑜQRÌ᦮஺cdᡃ»Îὃ⇋ÐᵨÑÒÌ᦮©N〉Ô¸ÕÖᔠQRᑖ᪆஺᝞sᡠeᙠÑÒÌ᦮Ꮇ£N〉ÔᎷ£ÑÒÌ᦮©N〉Ô¸ÕÖᔠ»ᓄ´᝞ØÙḄNᓄᓃ=/+/ÃÛ,+ÜÃᓃ7+/ᓃ©2+஻ᑭᵨᡠᦪQRxy(⊤7.7.3)஺DependentVariable:YMethod:LeastSquaresDate:03/09/05Time:22:42Sample(adjusted):19772004Includedobservations:28afteradjustingendpointsVariableCoefficientStd.Errort-StatisticProb.C-1.7922983.834594-0.4674020.6444X0.2356820.0339476.9426190.0000Y(-1)1.2870230.12102110.634740.0000Y(-2)-0.5144770.126037-4.0819450.0004R-squared0.998325Meandependentvar273.7470AdjustedR-squared0.998115S.D.dependentvar158.6766S.E.ofregression6.888881Akaikeinfocriterion6.829258Sumsquaredresid1138.960Schwarzcriterion7.019573Loglikelihood-91.60961F-statistic4766.971Durbin-Watsonstat2.228279Prob(F-statistic)0.0000005t,-.ஹF,-.1Þ245℉^

40h=Q-^-)1n—rr2y1-nVar(j3)}_/.1r”ãஹI28—(1—x2.2283)J------------2Vl-28x0.1212=0.786h=1.96aᙠ5℉ឋ:;a=°O5W᪗M᝱ᑖu⊤.5,ᵫ.h=1.96a□=0.786îᑣw\¡Ꮇ£᜛¥°,᡾J⚗ZLᙠ©▤ðᑡOᐵ஺ᨬóḄxy´Y=I-1.7923+0.2357%,I+1.287/1—.1-0.514477r—Z2t=(-0.4674)(6.943)(10.63)(-4.08)R2=0.9983F=4766DW=2.2283ö÷øᙢúûüᡠὃ
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ᦈᐭḄᐵ஺⚪8.1ὃ(1)ᙠᐸᩩḄ!"#ᦪ%ᙳᦈᐭ'(1%,ᑣ,ᙳ⚜./012'(30.09397஺89:;<=>?@"#ᦪ%ᙳᦈᐭInX#.D/0YḄFGHI℉஺KLḄMᔠOP"1QRSQTUVᐳXឋZᐸ[;\]^_Ḅ<=஺(2)aᐭ2(MX-7)Ḅfghi9jklm᳛opK☢ὃrs%ᙳᦈᐭtu1097vᐗḄxyz{|}xḄ~"xl}xḄ⚜./0hᔲᙠI℉Ḅ஺᝞?%ᙳᦈᐭᜧ1097vᐗ"M\|1,ᔲᑣ|0஺ᓽ1%ᙳᦈᐭᜧD,(ln(X)-7)=/0%ᙳᦈᐭ(3)#x"ᐸKL|:-2.40+9.39InX,.#}x"ᐸKL|-2.40+(9.39-3.36)InX,+3.36*7=21.12+6.03InX,⚪8.2ὃᫀᵫᨵp"g¡¢ᐭ£pM\[1R¥SJ11[0ᐸᐸ§ᐸ"g2(0(1)ᢥ᯿«¬®¢ᐭ£pM\"®|(«¬®Ḅ¯ᵨhᦋ²³z®Ḅjk´,)¥=4+aD+aD+%·3+BXஹ+4i[22>?᝞!:

41¸=6910.449-187.7317D,+1169.32D-417.1182D,+0.038008X,2t=(3.594792)(-0.28439)(1.3354460.)065093256914R2=0.517642R2=0.416093F=5.097454DW=0.39625(2)ᵫὃ⇋ᑭ»#├§½Ḅᓄ᳛¿ÀÁ"ᓽm᳛Ḅᦋ"g¡ᢥ᯿¬®¢ᐭ£pM\"®|Yi=Z?o+AXi+«iX,D+«\,0+^0+^1223>?᝞!ᓃ=7014.757+0.037068X-0.000933XD+0.00791XQ2-0.002385X^3iilt=(3.934394)(3.273896)(4))2167%)0.004018-0.58529R2=0.519733R2=0.418624F=5.140311DW=0.429628(3)ᢥ᯿«¬l¬Ä>ᔠḄKÅ¢ᐭ£pM\"®|Yj=00+cif|D|+a,D?+iZjDj+gX1++᜛jX]D?++4>?|1=10457.39-4752.26D,-3764.21D-4635.46D+0.0159Xj+0.029XD+0.03X]D2+0.0266XR23t=(2.566)(-0.87))(-0.686()0(832(=1).628)0824089960749R2=0.546701m=0.348383F=2.756686DW=0.464982Çu#£p®#Èᑖ᪆1Ë@Ì"Í£p®ḄᦪᙳI℉"®RlÎ├§½ḄᦪI℉"ᐸÏᦪÐI℉஺KLÑI℉"8MlLÑhÒP஺⚪83ὃ.ὃ⇋ᑮÔÕᨵ£pÖឋ"ᦑᙠᨵjk⚗ḄKLÙÚ2¢ᐭopM\"ᢥ«¬ÛÅ¢ᐭ"®³zÛÅ|ᓃ=+Ü3஺2+uiJ1ÝÔ_flÙÔD\=(0ᐸ[,2=[0ᐸ[஺ᐸÙ"ᓃ|àÌ"ᑣ>?᝞!VariableCoefficientStd.Errort-StatisticProb.C40.428570.55532972.801150.0000D1-5.7142860.785353-7.2760690.0000D29.1428570.78535311.641710.0000R-squared0.952909Meandependentvar41.57143AdjustedR-squared0.947676S.D.dependentvar6.423172AkaikeinfoS.E.ofregression1.469262criterion3.738961Sumsquaredresid38.85714Schwarzcriterion3.888178Loglikelihood-36.25909F-statistic182.1176Durbin-Watsonstat2.331933Prob(F-statistic)0.000000⊤Ḅ⊤ᙠᑖ᪆◤⌕ᵨᑮḄᦪ஺SumsquaredresidS.D.dependentvar'()*+Ḅ᪗-஺

42ᡠ/0TSS=(n-l)(y29:;ᦪ0ᨵ=TSS=6.4231722x(21-1)=825.1427708RSS=38.85714ESS=TSS-RSS=825.1427708-38.85714=786.2856F=ESS/(k-1)HI=182.1176RSS/(n—k)'T᝞V⊤ᡠḄWXYZ[\]^⊤5-4,ppl67Y`2᱐bbcde0WXfᐰhi஺ᩭklmᵫoFqrs786.2862393.143182.118rᑁ38.857182.158v825.14320J⚪8.6LὃNᫀPᐭRS*+=w
1xyᑴ11o{xyᑴ|}~=4++4~WX᝞V=Y,=1518.696+568.22740,f=12.393743.377868R2=0.195343R2=0.178223DW=1.96144F=11.40999Ey|D,=0=1518.696Ey|D,=1=1518.696+568.2274=2086.9234/0{xyᑴḄ├ᙳ1518.696,xyᑴḄ├ᙳ2086.9234o⊤xyᑴ├ᑮhḄ஺J⚪8.5Lὃ(NᙠEviewsᢥ᯿ᦪ¡¢£ᐭ0¤¥Quick,£ᐭgradecgpatucepsi,¤¥method,ᙠV«¬ᓫ0⌱¯binary=±⌱¯logit,ᑣᨵ=DependentVariable:GRADEMethod:ML-BinaryLogit(Quadratichillclimbing)Date:06/29/05Time:17:44Sample:132Includedobservations:32Convergenceachievedafter5iterationsCovariancematrixcomputedusingsecondderivativesVariableCoefficientStd.Errorz-StatisticProb.

43C-13.021354.931324-2.6405370.0083GPA2.82611312629432.2377230.0252TUCE0.0951580.1415540.6722350.5014PSI2.37868810645642.2344240.0255Meandependentvar0.343750>.D.dependentvar0.482559AkaikeinfoS.E.ofregression0.384716criterion1.055602Sumsquaredresid4.144171Schwarzcriterion1.238819Loglikelihood-12.88963Hannan-Quinncriter.1.116333Restr.log1ikelihood-20.59173Lvg.Iog1ikelihood-0.402801LRstatistic(3df)15.40419McFaddenR-squared0.374038Probability(LRstat)0.001502ObswithDep=021Totalobs32ObswithDep=l11(2.826]Ä.534]/(ᓽ)/=0.189x0.095=0.0180.499j(2.379Æ▭ᦔÉÊËxp-13.02135+2.8261x3.1172+0.0952x21.9375+2.3787x0.4375Pmno9h.τ/j^-13.02135+2.8261x3.1172+0.0952x21.9375+2.3787x0.4375\I+4+ᐸ0.———-------=0.188988746«0.189(1+0.3387)2GPATUCEPSIMean3.11718821.937500.437500Median3.06500022.500000.000000Maximum4.00000029.000001.000000Minimum2.06000012.000000.000000Std.Dev.0.4667133.9015090.504016Skewness0.122657-0.5251100.251976Kurtosis2.5700683.0483051.063492Jarque-Bera0.3266951.4737285.338708Probabi1ity0.8492960.4786120.069297Sum99.75000702.000014.00000SumSq.Dev.6.752447471.87507.875000Observations323232