實(shí)驗(yàn)八 內(nèi)生解釋變量問(wèn)題

實(shí)驗(yàn)八內(nèi)生解釋變量問(wèn)題【實(shí)驗(yàn)?zāi)康摹空莆展ぞ咦兞糠?、兩階段最小二乘法的使用以及內(nèi)生性檢驗(yàn)與過(guò)度識(shí)別約束檢驗(yàn)【實(shí)驗(yàn)內(nèi)容】利用美國(guó)各州的數(shù)據(jù)為樣本觀測(cè)值，建立香煙需求模型（見(jiàn)教材138頁(yè)例4.3.4）【實(shí)驗(yàn)步驟】表4.3.1 1995年美國(guó)48個(gè)州人均香煙消費(fèi)、收入與對(duì);香煙的課稅地區(qū)人均香煙消費(fèi)Q（盒）人均收入Y（千美兀）香煙平均銷(xiāo)售價(jià)格P（美分/盒）香煙平均消費(fèi)稅Tax（美分/盒）香煙平均的特別消費(fèi)稅Taxs（美分/盒）AL101.0912.92103.9226.570.92AR111.0412.17115.1936.425.49AZ71.9513.54130.3242.876.21CA56.8616.07138.1340.039.04CO82.5816.32109.8128.870.00CT79.4720.96143.2348.568.11DE124.4716.66108.6631.500.00FL93.0715.43123.1737.996.97GA97.4714.59102.7423.620.94IA92.4013.90125.2639.375.96ID74.8512.88117.8734.125.61IL83.2716.83130.2344.627.37IN134.2614.33101.4025.924.83KS88.7514.36114.9731.505.47KY172.6512.6195.7917.725.42LA105.1812.82110.1028.874.23MA76.6218.41142.4649.216.78MD77.4717.65122.0739.375.81ME102.4713.28129.4240.037.33MI81.3915.73158.0464.968.95MN82.9516.13144.5947.249.46MO122.4514.50103.1726.900.91MS105.5811.28111.0427.567.26MT87.1612.31102.5027.560.00NC121.5414.4098.4219.033.79ND79.8112.52126.1544.627.14NE87.2714.56119.5438.065.69NH156.3416.41109.3432.150.00NJ80.3719.21133.2641.997.54NM64.6712.37115.5829.535.50NV93.5316.93135.5638.718.87NY70.8218.19145.5852.495.60OH111.3815.02108.8531.505.18OK108.6812.73111.6430.845.32OR92.1614.87124.8740.680.00PA95.6415.58115.5936.096.54RI92.6015.78147.2852.499.64SC108.0812.78100.2720.344.77地區(qū)人均香煙消費(fèi)Q（盒）人均收入Y（千美兀）香煙平均銷(xiāo)售價(jià)格P（美分/盒）香煙平均消費(fèi)稅Tax（美分/盒）香煙平均的特別消費(fèi)稅Taxs（美分/盒）SD97.2213.02110.2630.844.24TN122.3214.30109.6224.288.12TX73.0814.12130.0542.657.36UT49.2712.37118.7533.145.65VA105.3916.05109.3617.395.21VT122.3314.02115.2528.875.49WA65.5315.67156.9052.8210.26WI92.4714.81132.1440.686.29WV115.5711.75109.2626.906.18WY112.2414.12104.0323.620.00資源來(lái)源：根據(jù)IntroductiontoEconometrics(2ndedition)整理。根據(jù)商品需求函數(shù)理論，對(duì)香煙的人均消費(fèi)需求Q與居民的收入水平Y(jié)及香煙的銷(xiāo)售價(jià)格P有關(guān)；慮到在市場(chǎng)均衡時(shí)香煙的銷(xiāo)售價(jià)格也同時(shí)受香煙的需求量的影響，則Q與P之間存在著雙向因果關(guān)系，P為內(nèi)生解釋變量，考慮到香煙價(jià)格中包含政府對(duì)煙草的課稅，而香煙的人均消費(fèi)量本身不會(huì)直接影響政府對(duì)香煙的課稅政策，因此香煙的消費(fèi)稅可能是價(jià)格的一個(gè)適當(dāng)?shù)墓ぞ咦兞俊Ｒ?、建立?duì)數(shù)線性模型：lnQ=&o+0]lnY+P2lnP+'對(duì)原模型做回歸分析結(jié)果如下:ViewProcObjectPrintNameFreezeEstimateForecastStatsResidsDependentVariable:LNQMethod:LeastSquaresDate:10/28/16Time:10:56Sample:148Includedobservations:48VariableCoefficientStd.Errort-StatisticProb.C10.S40941.02263310.112070.0000LNY0.3440320.2340831.4646960.1500LNP-1.4063760.251294-5,5965260.0000R-squared 0.4S2759Meandependentvar4.53S839從結(jié)果可以看出，價(jià)格確實(shí)是影響人均香煙消費(fèi)的重要因素，其彈性為-1.4，特別大。懷疑P具有」生性：七J生性。。：：_.m』：：二"?：::-:-:t-:- ：；-：：：二、工具變量法 -"：；乙 ?1. --5：瀾年費(fèi)稅作為P的工具變量，重新對(duì)原模型進(jìn)行回歸""二把lnQlnYlnP作為一個(gè)組打開(kāi)，詵擇Proc/MakeEquation/Method中的Tsls點(diǎn)擊確定EquationEstimationSpecificationOptionsEquBtionspecificstion.L1DependerLtv：=q-iablefoilowedbylistofregreesoreand.FDLtermE,ORanexplici+equationlikeInqCInylnpEstimationsettings；仁匕一TELS一TwcrSt色既LeqtSguarEsCT^HLSandAFJAA]Method:[咨-LeutSquare，(HLSandAjjTELS一TwcrSt色既LeqtSguarEsCT^HLSandAFJAA]CjfilM一GerLer：dliiedMethodofMurnenteLIML一LimitedIn￡urmationMaxiewtiLikelihoodand.瓦一匚1as:Specification結(jié)果如下圖:(=]Equation:UISFTTTLEDWorkf?[e:UNTTrLED::Untitled\Specification結(jié)果如下圖:(=]Equation:UISFTTTLEDWorkf?[e:UNTTrLED::Untitled\在Instrumentlist中寫(xiě)入工具變量，沒(méi)有工具變量的直接把解釋變量包括常數(shù)項(xiàng)寫(xiě)上，有工具變量的就直接把工具變量寫(xiě)上，如本例lnP的工具變量是tax,如下圖，點(diǎn)擊確定EquationEstimationEquationspecificationIlHperLdtjrLtProcObje吐PrintNameFreezeEstimateForecastStatsResidsViewDependentVariable:LNQMethod:Two-StageLeastSquaresDate:10；20/16Time:11:26Sample:148Includedobservations:48Instrumentspecification:CLNYTAXVariableCoefficientStd.Errort-StatisticProb.C10.022961.0317189.2657750.0000LNY0.2939530.2403&41.2433030.2200LNP-1.3145950.270991-4.8510720.0000R-squared 0.4S1077Meandependentvar4.5S3339果。發(fā)現(xiàn)：吐具變量法得到的價(jià)格彈性要低于普通最小二乘借計(jì)的結(jié)

……擊注0俏每丁Sumsquaredresid 1.不34獎(jiǎng)果。乘法13.26712Durbin-Watsonstat -1.942^91P有許多州對(duì)香煙有額外的特別消費(fèi)稅taxs它也可以做為p的工具變量。用tax和taxs兩個(gè)工具變量對(duì)原模型進(jìn)行兩階段最小二乘回歸：皿以「時(shí) 3把lnQlnYlnP作為一個(gè)組打開(kāi)，選擇Proc/MakeEquation/Method中的Tsls,點(diǎn)擊確定，在Instrumentlist中寫(xiě)入工具變量：Clnytaxtaxs點(diǎn)擊確定DependentVariable:LNQMethod:Two-StageLeastSquares□ate:10/23/16Time:11:38Sample:148Includedobservations:48Instrumentspecification:CLNYTAXTAXSVariableCoefficientStd.Errort-StatisticProb.C9.3936601.0585U9.34674-70.0000LNY0.23062302384761.1767340.2455LNP-1.2772760263114-4-.S544550.00000.429432Meandependentvar4.533339價(jià)格皇性進(jìn)一步下降了。0.404073S.D.dependentvar0.243351四、過(guò)渡識(shí)別約束檢驗(yàn)：判斷tax和taxs是否是外生變量 己京-己1、 用?蛭和taxs兩個(gè)工具變量對(duì)原模型進(jìn)行兩階纓小二乘估計(jì)后,記錄殘差項(xiàng)為ete「尋嗅典e=lnQ-(9.89砸巍lnY五漩nP) -進(jìn)行兩階段最小二乘后，在命令窗口：genret=resid2、 再做et關(guān)于工具變量tax及taxs以及原模型外生變量lnY的普通最小二乘回歸e=a+atax+ataxs+alnY+e在命令窗口：LsetctaxtaxsInyfviewlfProcl[object![printI[Name]fFreezeI[EstimateI[Forecast![StatsIfResidslIDependentVariable:ETMethod:LeastSquaresDate:10/28/16Time:15:58Sample:148Includedobservations:48VariableCoefficientStd.Errort-StatisticProb.C-0.0657750.500136-0.1133790.9102TAX-0.0015150.003681-0.4116620.6S26TAXS0.0063670.01178S0.5400910.5919LNY0.0317110.2331140.1360320.89243、根據(jù)結(jié)果進(jìn)行判斷 一(1)384m；瞰2w48-0；Q07::=0.336<X°.展⑴二一3.84,即不拒絕tax和taxs作為工具變量的外生性假設(shè)S.E.ofregression 0.189314-Akaikeinfocriterion -0.411162五、內(nèi)生性檢驗(yàn)：即判斷p是否為內(nèi)生變量，?利用豪斯曼檢驗(yàn)2三22：?Loglikelihood 13.86790Hannan-Quinncriter. -0.3522351、構(gòu)造輔助模型：lnP=#：+小ta^^.^taxs+步InY+e 二：二三廿二1 2 3命令窗口：Lslnpctaxtaxslny結(jié)果如下： 一ViewProcObjectPrintNameFreezeEstimateForecastStatsResidsDependentVariable:LNPMethod:LeastSquares□ate:10/28/16Time:16:21Sample:148Includedobservations:48VariableCoefTicientStd.Errort-StatisticProb.C41031530.09839241491110.0000TAX00093530.00062714.905530.0000TAXS0.0103900.0020095.4195110.0000LNY0.1002880.0397382.7250690.0092R-squared 0.940297Meandependentvar 4.7S1S79AdjustedR-squared 0.936227S.D.dependentvar 0.127790Q匚nfrahfoc-c-inn A Akailzoinfnqri+臼ricn □J□AQT!

2、命令窗口genre1=resid構(gòu)造輔助模型：lnQ=80+叩n7+P2lnP+P3e1+8命令窗口：Lsln