计量经济学导论第四版答案中文版

计量经济学导论第四版答案中文版计量经济学导论第四版答案中文版【篇一：计量经济学导论(伍德里奇第三版)课后习题答案chapter1】>solutionstoproblems1.1(i)ideally,wecouldrandomlyassignstudentstoclassesofdifferentsizes.thatis,eachstudentisassignedadifferentclasssizewithoutregardtoanystudentcharacteristicssuchasabilityandfamilybackground.forreasonswewillseeinchapter2,wewouldlikesubstantialvariationinclasssizes(subject,ofcourse,toethicalconsiderationsandresourceconstraints).(ii)anegativecorrelationmeansthatlargerclasssizeisassociatedwithlowerperformance.wemightfindanegativecorrelationbecauselargerclasssizeactuallyhurtsperformance.however,withobservationaldata,thereareotherreasonswemightfindanegativerelationship.forexample,childrenfrommoreaffluentfamiliesmightbemorelikelytoattendschoolswithsmallerclasssizes,andaffluentchildrengenerallyscorebetteronstandardizedtests.anotherpossibilityisthat,withinaschool,aprincipalmightassignthebetterstudentstosmallerclasses.or,someparentsmightinsisttheirchildrenareinthesmallerclasses,andthesesameparentstendtobemoreinvolvedintheirchildren’seducation.(iii)giventhepotentialforconfoundingfactors–someofwhicharelistedin(ii)–findinganegativecorrelationwouldnotbestrongevidencethatsmallerclasssizesactuallyleadtobetterperformance.somewayofcontrollingfortheconfoundingfactorsisneeded,andthisisthesubjectofmultipleregressionanalysis.1.2(i)hereisonewaytoposethequestion:iftwofirms,sayaandb,areidenticalinallrespectsexceptthatfirmasuppliesjobtrainingonehourperworkermorethanfirmb,byhowmuchwouldfirma’soutputdifferfromfirmb’s?(ii)firmsarelikelytochoosejobtrainingdependingonthecharacteristicsofworkers.someobservedcharacteristicsareyearsofschooling,yearsintheworkforce,andexperienceinaparticularjob.firmsmightevendiscriminatebasedonage,gender,orrace.perhapsfirmschoosetooffertrainingtomoreorlessableworkers,where―ability‖mightbedifficulttoquantifybutwhereamanagerhassomeideaabouttherelativeabilitiesofdifferentemployees.moreover,differentkindsofworkersmightbeattractedtofirmsthatoffermorejobtrainingonaverage,andthismightnotbeevidenttoemployers.(iii)theamountofcapitalandtechnologyavailabletoworkerswouldalsoaffectoutput.so,twofirmswithexactlythesamekindsofemployeeswouldgenerallyhavedifferentoutputsiftheyusedifferentamountsofcapitalortechnology.thequalityofmanagerswouldalsohaveaneffect.(iv)no,unlesstheamountoftrainingisrandomlyassigned.themanyfactorslistedinparts(ii)and(iii)cancontributetofindingapositivecorrelationbetweenoutputandtrainingevenifjobtrainingdoesnotimproveworkerproductivity.1.3itdoesnotmakesensetoposethequestionintermsofcausality.economistswouldassumethatstudentschooseamixofstudyingandworking(andotheractivities,suchasattendingclass,predictorofconsumptionatverylow-incomelevels.ontheotherhand,onanannualbasis,$124.84isnotsofarfromzero.?=–124.84+.853(30,000)=25,465.16dollars.(ii)justplug30,000intotheequation:cons(iii)thempcandtheapcareshowninthefollowinggraph.eventhoughtheinterceptisnegative,thesmallestapcinthesampleispositive.thegraphstartsatanannualincomelevelincreaseshousingprices.(ii)ifthecitychosetolocatetheincineratorinanareaawayfrommoreexpensiveneighborhoods,thenlog(dist)ispositivelycorrelatedwithhousingquality.thiswouldviolateslr.4,andolsestimationisbiased.(iii)sizeofthehouse,numberofbathrooms,sizeofthelot,ageofthehome,andqualityoftheneighborhood(includingschoolquality),arejustahandfuloffactors.asmentionedinpart(ii),thesecouldcertainlybecorrelatedwithdist[andlog(dist)].2.7(i)whenweconditiononince(u|inc?e|inc)=?e(e|inc?0becausee(e|inc)=e(e)=0.(ii)again,whenweconditiononincvar(u|inc?e|inc2var(e|inc)=?e2incbecausevar(e|inc)=?e2.(iii)familieswithlowincomesdonothavemuchdiscretionaboutspending;typically,alow-incomefamilymustspendonfood,clothing,housing,andothernecessities.higherincomepeoplehavemorediscretion,andsomemightchoosemoreconsumptionwhileothersmoresaving.thisdiscretionsuggestswidervariabilityinsavingamonghigherincomefamilies.2.8(i)fromequation(2.66),?n??n2???1=??xiyi?/??xi?.?i?1??i?1?plugginginyi=?0+?1xi+uigives?n??n2???1=??xi(?0??1xi?ui)?/??xi?.?i?1??i?1?afterstandardalgebra,thenumeratorcanbewrittenas?0?xi??1?x??xiui.2nnni?1i?1ii?1?asputtingthisoverthedenominatorshowswecanwrite?1?n??n2??n??n2???1=?0??xi?/??xi?+?1+??xiui?/??xi?.?i?1??i?1??i?1??i?1?conditionalonthexi,wehave?n??n2??e(?1)=?0??xi?/??xi?+?1?i?1??i?1??isgivenbythefirstterminthisequation.becausee(ui)=0foralli.therefore,thebiasin?1thisbiasisobviouslyzerowhen?0=0.itisalsozerowhen?xi=0,whichisthesameasi?1n=0.inthelattercase,regressionthroughtheoriginisidenticaltoregressionwithanintercept.【篇二：计量经济学导论第五版第一章上机作业】betivestatistc*tabstatpratemratetotpart,stat(maxminmeanp50sdn)结果stats|pratemratetotpart---------+------------------------------max|1004.9158811min|3.0150mean|87.36291.73151241354.231p50|95.7.46276sd|16.71654.77953934629.265n|153415341534过程summarize全部的加总summarizepratemrate两个变量summarizesoleprate,detail结果summarizevariable|obsmeanstd.dev.minmax-------------+--------------------------------------------------------prate|153487.3629116.716543100mrate|1534.7315124.7795393.014.91totpart|15341354.2314629.2655058811totelg|15341628.5355370.7195170429age|153413.181239.171114451-------------+--------------------------------------------------------totemp|15343568.49511217.9458144387sole|1534.4876141.500009601ltotemp|15346.6860341.4533754.06044311.88025summarizepratemratevariable|obsmeanstd.dev.minmax-------------+--------------------------------------------------------prate|153487.3629116.716543100mrate|1534.7315124.7795393.014.91summarizesoleprate,detail=1if401kisfirmssoleplan-------------------------------------------------------------percentilessmallest1%005%0010%00obs153425%00sumofwgt.153450%0mean.4876141largeststd.dev..500009675%1190%11variance.250009695%11skewness.049558999%11kurtosis1.002456participationrate,percent-------------------------------------------------------------percentilessmallest1%31.435%53.88.810%62.714.925%7817.450%95.7largest75%10010090%10010095%10010099%100100.endofdo-file过程*cdf*tabulateprate结果累积participati|onrate,|percent|freq.percent------------+-----------------------------------3|10.078.8|10.0714.9|10.0717.4|10.0719.3|10.0720.1|10.0720.6|10.0721|10.0721.3|10.0722.1|10.0725.1|10.0726.1|10.0728.6|10.0729|10.0730.5|10.0731.4|10.07obssumofwgt.meanstd.dev.varianceskewnesskurtosiscum.0.070.130.200.260.330.390.460.520.590.650.720.780.850.910.981.041534153487.3629116.71654279.4426-1.5196265.25835933.5|10.071.1734.2|10.071.2435.6|10.071.3035.8|10.071.3737|10.071.4337.5|10.071.5037.7|10.071.5638.1|10.071.6338.4|10.071.6938.7|139.4|139.6|139.8|141.5|142.1|142.4|142.5|143.1|143.3|143.6|143.8|144.1|144.3|144.7|245.5|145.8|146.9|347.3|147.7|148.2|148.6|248.8|148.9|349.2|149.6|249.7|150|150.2|150.3|150.7|150.9|251|151.3|151.5|151.9|152.3|152.4|152.7|153.1|10.071.760.071.830.071.890.071.960.072.020.072.090.072.150.072.220.072.280.072.350.072.410.072.480.072.540.072.610.132.740.072.800.072.870.203.060.073.130.073.190.073.260.133.390.073.460.203.650.073.720.133.850.073.910.073.980.074.040.074.110.074.170.134.300.074.370.074.430.074.500.074.560.074.630.074.690.074.760.074.8253.7|10.074.9553.8|10.075.0254.1|10.075.0854.2|10.075.1554.9|20.135.2855.1|10.075.3555.5|10.075.4155.7|10.075.4855.9|10.075.5456.2|256.3|256.4|156.7|356.8|157|257.6|257.7|157.8|258|158.2|358.3|158.4|258.6|258.7|158.8|159|159.1|259.2|259.4|159.6|359.8|159.9|260.1|260.2|160.3|160.4|160.6|260.8|260.9|261.1|161.2|361.3|161.4|161.5|161.6|161.7|261.8|262|262.2|10.135.670.135.800.075.870.206.060.076.130.136.260.136.390.076.450.136.580.076.650.206.840.076.910.137.040.137.170.077.240.077.300.077.370.137.500.137.630.077.690.207.890.077.950.138.080.138.210.078.280.078.340.078.410.138.540.138.670.138.800.078.870.209.060.079.130.079.190.079.260.079.320.139.450.139.580.139.710.079.7862.6|10.079.9162.7|20.1310.0462.9|20.1310.1763|30.2010.3763.3|20.1310.5063.4|10.0710.5663.6|10.0710.6363.7|10.0710.6964|10.0710.7664.3|164.4|364.6|464.7|164.9|265|265.1|365.3|165.5|365.6|265.7|166.2|166.3|266.5|166.6|566.9|267|167.1|167.2|267.3|367.6|267.8|168|168.3|168.5|168.6|168.7|368.8|268.9|269.2|169.3|169.4|169.6|169.8|169.9|270|270.2|270.3|270.5|170.6|20.0710.820.2011.020.2611.280.0711.340.1311.470.1311.600.2011.800.0711.860.2012.060.1312.190.0712.260.0712.320.1312.450.0712.520.3312.840.1312.970.0713.040.0713.100.1313.230.2013.430.1313.560.0713.620.0713.690.0713.750.0713.820.0713.890.2014.080.1314.210.1314.340.0714.410.0714.470.0714.540.0714.600.0714.670.1314.800.1314.930.1315.060.1315.190.0715.250.1315.38【篇三：伍德里奇计量经济学导论计算机习题第六章第13题c_6.13】>%c6.13by%打开文字文件和数据文件importdata(meap00_01.des);data=xlsread(meap00_01);%检验所用数据是否为非空isnan=isnan(data(:,[3,5,8,9]));a=sum(isnan);b=find(a==0);data1=data(b,:);%变量命名math4=data1(:,3);lunch=data1(:,5);leoll=data1(:,8);lexppp=data1(:,9);%ols估计result1=ols(math4,[ones(length(math4),1),lunch,leoll,lexppp]);vnames=char(math4,constant,lunch,leoll,lexppp);prt(result1,vnames)%回归结果%ordinaryleast-squaresestimates%dependentvariable=math4%r-squared=0.3729%rbar-squared=0.3718%sigma^2=234.1638%durbin-watson=1.7006%nobs,nvars=1692,4%***************************************************************%variablecoefficientt-statistict-probability%constant91.9324844.6054440.000004%lunch-0.448743-30.6476310.000000%leoll-5.399153-5.7412650.000000%lexppp3.5247421.6801720.093109%由回归结果中的p值发现lunch,leoll是在5%的水平上显著的,而lexppp在5%水平上不显著,%但在10%的显著水平上是显著的.%求出回归的拟合值及其取值范围yhat=result1.yhat;std_yhat=std(yhat);mean_yhat=mean(yhat);yhat_qujian=[mean_yhat-2*std_yhat,mean_yhat+2*std_yhat]%yhat的取值范围是(49.1090,96.2665)%求出math4的实际取值范围math4_qujian=[min(math4),max(math4)]%math4的实际取值范围是(0,100),可见拟合值的取值范围要比实际范围窄%求出回归残差resid=result1.resid;max_resid=max(resid);row=find(resid==max_resid)school_code=data1(row,2)%学校类型是school_code=1141,说明该学校的实际数学考试通过率要比估