1、陜西省建筑業(yè)總產(chǎn)值影響因素分析 實(shí)驗(yàn)0904 劉文樂 2009112827 指導(dǎo)老師 沈鳴 陜西省建筑業(yè)總產(chǎn)值影響因素分析前言 陜西，古為雍州、梁州之地（陜北、關(guān)中屬雍州、陜南為梁州），又稱為三秦大地，縱貫?zāi)媳?，連通東西，位于中國(guó)地理版圖的中心區(qū)，處于黃河中游和漢江中上游，歷史悠久，古老而神秘。是中華民族的搖籃和中華文明的發(fā)祥當(dāng)今的陜西猶如鑲嵌在中國(guó)內(nèi)陸腹地的一顆明珠，地域南北長(zhǎng)、東西窄，南北長(zhǎng)約880公里，東西寬約160490公里。全省縱跨黃河、長(zhǎng)江兩大水系，是第二亞歐大陸橋亞洲段的中心和中國(guó)西北、西南、華北、華中之間的門戶，周邊與山西、河南、湖北、四川、重慶、甘肅、寧夏、內(nèi)蒙古8個(gè)省、市、

2、區(qū)接壤，是國(guó)內(nèi)鄰接省區(qū)數(shù)量最多的省份，具有承東啟西、連接南北的區(qū)位之便?？偯娣e20.58萬平方公里，常住人口為3762萬人（2008年），漢族人口占總?cè)丝诘?9.4%以上，境內(nèi)還有回族、滿族、蒙古族、苗族、羌族等。 陜西歷史文化悠久，其中最具代表性的就是西秦文化。 西秦文化，是中國(guó)中心文明的重要發(fā)祥地，歷朝歷代的建都首選。從上古時(shí)代藍(lán)田猿人，到中華文明的發(fā)源華胥古國(guó)，再到伏羲氏、女媧氏、神農(nóng)氏“三皇”，從半坡的仰韶文化到西周定都豐鎬，再到近代的西安事變，一直到國(guó)家在西安宣布實(shí)施西部大開發(fā)，那里一直是中華文明的中心。 隨著改革開放的深入進(jìn)行，陜西省的經(jīng)濟(jì)也經(jīng)歷了前所未有的快速發(fā)展。截止到2008

3、，據(jù)初步核算，2008年陜西生產(chǎn)總值6851.32億元，比上年增長(zhǎng)15.6。其中，第一產(chǎn)業(yè)增加值753.72億元，增長(zhǎng)7.6，占生產(chǎn)總值的比重為11；第二產(chǎn)業(yè)增加值3842.08億元，增長(zhǎng)18.8，占56.1；第三產(chǎn)業(yè)增加值2255.52億元，增長(zhǎng)13，占32.9。人均生產(chǎn)總值18246元，比上年增長(zhǎng)15.2。規(guī)模以上工業(yè)企業(yè)完成工業(yè)增加值2988.07億元，比上年增長(zhǎng)21。2008年，全省全社會(huì)固定資產(chǎn)投資完成4835.15億元，比上年增長(zhǎng)32.8。2008年，全省社會(huì)消費(fèi)品零售總額2256.09億元，比上年增長(zhǎng)25.3，為1998年以來增幅最高的年份。全年接待國(guó)內(nèi)旅游人數(shù)9056萬人次，比

4、上年增長(zhǎng)13；國(guó)內(nèi)旅游收入561億元，增長(zhǎng)22.5。全年接待境外旅游人數(shù)達(dá)125.7萬人次，增長(zhǎng)2.1；旅游外匯收入6.6億美元，增長(zhǎng)8.2。2008年，全省外貿(mào)進(jìn)出口總值83.68億美元，比上年增長(zhǎng)21.5。其中，進(jìn)口29.61億美元，增長(zhǎng)33.6；出口54.07億美元，增長(zhǎng)15.7。2008年，全省新批外商投資項(xiàng)目156個(gè)，實(shí)際利用外資13.7億美元（含外商投資企業(yè)再投資部分），增長(zhǎng)14.6。2008年末，全省常住人口為3762萬人，比上年增加人口14萬人，其中男性1933.9萬人，占51.41；女性人口1828.1萬人，占48.59牞性別比為105.79（以女性為100，男性對(duì)女性的比例

5、）。全年出生人口38.64萬人牞出生率為10.29；死亡人口23.32萬人牞死亡率為6.21；自然增長(zhǎng)率為4.08。城鎮(zhèn)人口1583.8萬人，占42.1牞鄉(xiāng)村人口2178.2萬人牞占57.9。人口年齡構(gòu)成為014歲人口占17.75，1564歲人口占73.28，65歲及以上人口占8.97。全省城鎮(zhèn)居民人均可支配收入12858元，比上年增加2095元，增長(zhǎng)19.5，扣除價(jià)格因素實(shí)際增長(zhǎng)12.5；農(nóng)村居民人均純收入3136元，比上年增加491元，增長(zhǎng)18.6，扣除價(jià)格因素實(shí)際增長(zhǎng)10.6。 在經(jīng)濟(jì)快速發(fā)展的帶動(dòng)下，陜西省建筑業(yè)也經(jīng)歷了前所未有的增長(zhǎng)，以商洛市為例對(duì)其增長(zhǎng)因素分析如下：（一）固定資產(chǎn)投

6、資快速增長(zhǎng)，建筑企業(yè)施工量明顯增加。西部大開發(fā)以來，特別是新一輪西部大開發(fā)等措施實(shí)施以來，全市固定資產(chǎn)投資高速增長(zhǎng)。2010年全市計(jì)劃總投資50萬元以上的在建項(xiàng)目固定資產(chǎn)投資完成290.07億元，比上年增長(zhǎng)31.6。城鎮(zhèn)投資完成241.13億元，增長(zhǎng)26.0；農(nóng)村投資完成9.21億元，增長(zhǎng)17.2；城鎮(zhèn)房地產(chǎn)開發(fā)完成投資8.22億元，增長(zhǎng)38.4。城鎮(zhèn)基礎(chǔ)建設(shè)、房地產(chǎn)開發(fā)以及新農(nóng)村建設(shè)的力度加大，強(qiáng)有力地拉動(dòng)了商洛市建筑業(yè)經(jīng)濟(jì)的快速增長(zhǎng)。（二）承包工程經(jīng)營(yíng)范圍進(jìn)一步拓寬，打破只在本市內(nèi)施工的格局。鞏固和擴(kuò)大建筑業(yè)傳統(tǒng)優(yōu)勢(shì)市場(chǎng)，積極開拓市外市場(chǎng)和新農(nóng)村建設(shè)，不斷開辟建筑業(yè)新的發(fā)展空間。2010年

7、，商洛市建筑業(yè)企業(yè)施工步伐走向鄉(xiāng)鎮(zhèn)新農(nóng)村建設(shè)，走向了四川、青海等省市區(qū)，施工企業(yè)已打破只在本市區(qū)域內(nèi)發(fā)展的格局。（三）建筑業(yè)勞動(dòng)報(bào)酬提高。2010年，建筑企業(yè)全部從業(yè)人員平均人數(shù)3.93萬人，從業(yè)人員勞動(dòng)報(bào)酬7.18億元，人均月收入1522.4元/人，比上年的1423元，人均每月增加了99.4元。有的發(fā)展。 綜上所述，建筑業(yè)的發(fā)展是經(jīng)濟(jì)發(fā)展的一個(gè)重要組成部分，經(jīng)濟(jì)發(fā)展的好壞也在很大程度上反映在建筑業(yè)發(fā)展的好與壞上面，所以，對(duì)建筑業(yè)影響因素的分析也就具有了很高的實(shí)際價(jià)值。理論背景工業(yè)總產(chǎn)值。工業(yè)是現(xiàn)代經(jīng)濟(jì)發(fā)展的基礎(chǔ)產(chǎn)業(yè)，是推動(dòng)經(jīng)濟(jì)迅猛發(fā)展的首要?jiǎng)恿ΑｋS著工業(yè)的快速發(fā)展，工廠的數(shù)量規(guī)模必然逐步擴(kuò)大

8、，這就帶動(dòng)了建筑面積的迅速提高，同時(shí)也拉動(dòng)了工業(yè)總產(chǎn)值的提高。所以，把工業(yè)總產(chǎn)值作為X1。社會(huì)消費(fèi)品零售總額。消費(fèi)是居民的主要經(jīng)濟(jì)活動(dòng)，居民將收入的多大部分用于消費(fèi)直接影響其對(duì)投資的比例，而居民對(duì)固定資產(chǎn)投資多少，對(duì)建筑業(yè)總產(chǎn)值的影響也是極其深遠(yuǎn)的。所以，把社會(huì)消費(fèi)品零售總額作為X2。外貿(mào)進(jìn)出口總值。對(duì)外經(jīng)濟(jì)的繁榮程度對(duì)本地區(qū)經(jīng)濟(jì)具有極其重要的影響，一個(gè)地區(qū)的外貿(mào)進(jìn)出口直接影響外資在本地區(qū)的投資程度，外商對(duì)當(dāng)?shù)氐耐顿Y的增長(zhǎng)必然帶動(dòng)本地區(qū)建筑業(yè)的發(fā)展。所以，將外貿(mào)進(jìn)出口總值作為X3。人民可支配收入。居民的收入情況直接影響其消費(fèi)與投資，就建筑業(yè)來說，居民對(duì)固定資產(chǎn)投資需求的情況，對(duì)建筑業(yè)的發(fā)展具有

9、重要影響。因此，將人民可支配收入作為X4。社會(huì)固定資產(chǎn)投資總額。建筑業(yè)的核心商品就是各種商品房及商業(yè)倉庫，寫字樓等，這些都屬于固定資產(chǎn)投資范疇，居民的固定資產(chǎn)投資總額直接影響建筑業(yè)的發(fā)展?fàn)顩r。所以，將社會(huì)固定資產(chǎn)投資總額作為X5。模型的選擇與建立本模型研究的是19762009年間陜西省建筑業(yè)生產(chǎn)總值影響的因素之間的定量關(guān)系。確定的變量有：X1 陜西省工業(yè)總產(chǎn)值X2 社會(huì)消費(fèi)品零售總額X3 外貿(mào)進(jìn)出口總值X4 陜西省居民可支配收入X5 社會(huì)固定資產(chǎn)投資總額確定模型的數(shù)學(xué)形式，如下：Y=+X+X+X+X+X數(shù)據(jù)來源與分析1、時(shí)間序列的變量及原始數(shù)據(jù)：由于解釋變量和被解釋變量中都是以“憶元”作單位，

10、數(shù)據(jù)的口徑均同質(zhì)可比，沒有實(shí)物量指標(biāo)，故可用現(xiàn)價(jià)數(shù)據(jù)，而不用調(diào)整為可比價(jià)。年份Y建筑業(yè)總產(chǎn)值（億元）X1工業(yè)總產(chǎn)值（億元）X2消費(fèi)品零售總額（億元）X3外貿(mào)進(jìn)出口總值（億元）X4人民可支配收入（億元）X5固定資產(chǎn)投資總額（億元）19766.111272.396425.35581.18820.003414.187319777.276683.574429.08821.38150.003916.993519788.664296.478333.37001.60630.004420.354819799.1932105.793036.60001.86760.005321.162219809.7607109

11、.957843.38002.17150.005427.802019818.2528108.639147.52002.52480.006422.924419829.8176117.706650.65002.93550.007629.4805198311.0401131.767754.90003.41320.008430.8266198413.9234150.696063.00003.96850.011040.3864198516.4405192.082783.01004.61410.013057.9881198618.3081219.262191.40008.09750.015363.53001

12、98720.8180258.4397106.160012.91010.017380.8912198824.2409331.7423140.070018.34880.021694.7210198927.3554406.7087153.650020.01160.025595.1793199032.5034442.5767159.670027.61590.0302103.7154199136.0774508.8160176.600043.30500.0312124.9323199247.9806599.5407208.370061.70350.0371142.4653199375.1613793.7

13、800245.530086.19740.0464228.2062199498.02601009.7561305.9500137.95180.0594283.29121995106.56121068.7123369.4600144.73680.0746324.32501996129.45021168.5390432.1400148.33030.0926371.99551997164.24931284.1366490.5000143.75590.1078424.09871998187.98041318.8077520.0100169.84410.1217544.89161999218.300915

14、01.0536557.0400166.28250.1335619.27432000242.30461714.1770607.6100177.16520.0965745.84372001279.73881946.9447665.1200170.87370.1044850.65622002347.35362205.9818728.1600184.17730.1189974.62982003440.95642708.8616853.2300230.41880.12911278.71972004523.16393389.8759966.4900301.47980.14491544.1935200565

15、8.64114109.32211322.4100369.36010.16251982.03892006830.69665248.39301522.0000432.58290.18682610.220520071173.46486587.41131800.9100537.86640.22273861.880020081655.62398358.86472256.0900608.37600.27204851.410020092309.26749553.70212699.6700574.47480.30516553.3900數(shù)據(jù)來源：上表中19782009的數(shù)據(jù)來自于電子版陜西省統(tǒng)計(jì)年鑒2009。1

16、976和1977年數(shù)據(jù)根據(jù)內(nèi)差預(yù)測(cè)法推測(cè)產(chǎn)生。以散點(diǎn)圖分析解釋變量與被解釋變量間的擬合程度1）、工業(yè)總產(chǎn)值X1與建筑總產(chǎn)值Y的關(guān)系 2）、消費(fèi)品零售額X2與Y的關(guān)系3)、外貿(mào)進(jìn)出口總值X3與Y的關(guān)系 4）、人民可支配收入X4與Y的關(guān)系 5）、固定資產(chǎn)投資總額X5與Y的關(guān)系由各解釋變量與被解釋變量的散點(diǎn)圖可以看出，解釋變量X1、X2、X5的散點(diǎn)圖各數(shù)據(jù)點(diǎn)基本呈現(xiàn)線性趨勢(shì)；而解釋變量X3、X4的散點(diǎn)圖各數(shù)據(jù)點(diǎn)總體趨勢(shì)明顯，但線性關(guān)系呈現(xiàn)不是很明顯，也就是從散點(diǎn)圖角度，各變量對(duì)于被解釋變量的影響是有差異的，這就需要對(duì)模型進(jìn)行檢驗(yàn)、篩選和對(duì)數(shù)據(jù)的處理，進(jìn)而得到較為合理的模型及其參數(shù)估計(jì)。五元模型的自相

17、關(guān)、異方差處理1 .在基本假設(shè)條件下，以含有截距項(xiàng)的線性回歸模型為理論依據(jù)，由模型數(shù)據(jù)，利用最小二乘法進(jìn)行模型參數(shù)估計(jì)，構(gòu)建各種檢驗(yàn)以篩選模型，并對(duì)數(shù)據(jù)進(jìn)行有效地處理，以得到合理的模型。在95%置信概率下，各元數(shù)的t檢驗(yàn)和F檢驗(yàn)的臨界值、DW值如表所示：一元二元三元四元五元t檢驗(yàn)2.0452.0482.02.0522.048F檢驗(yàn)4.183.342.962.742.6D w值(dl,du)1.65，2.351.73，2.271.82，2.18在基本假設(shè)條件下，利用最小二乘法對(duì)各元模型進(jìn)行參數(shù)估計(jì)和t檢驗(yàn)、F檢驗(yàn)等基本回歸分析，各元模型參數(shù)估計(jì)和檢驗(yàn)如下表所示：每個(gè)變量下的數(shù)值即為該變量的系數(shù)值

18、，符號(hào)*表示該項(xiàng)系數(shù)值通過顯著性水平為0.05的t檢驗(yàn)；R2表示該模型的可決系數(shù)；F表示對(duì)應(yīng)的模型整體的F檢驗(yàn)值，若出現(xiàn)*號(hào)則表明通過了顯著性水平為0.05的F檢驗(yàn)；若是偏回歸系數(shù)和方程整體都通過了各自的假設(shè)檢驗(yàn)，則“是否合格”一欄中注上“是”，若有任一項(xiàng)沒有通過檢驗(yàn)，則該欄用空格標(biāo)注。 各元模型參數(shù)估計(jì)和檢驗(yàn)CX1X2X3X4X5R2F合格五元-13.59329*0.0499470.049712-1.030092981.4846*0.303083-0.9985833947.433四元-45.93829*0.361681-0.098058-2.769073*1620.617*-0.994886

19、1410.541-7.595150*-0.0277140.301661-0.6716290.3255670.9981623937.7021.169107-0.1075280.160448254.4295*0.4271620.9976873126.996-13.40849*0.063272-1.0541201092.330*0.3007960.9985745078.835-11.05997*0.130790-0.822249773.5867*0.3343240.99955614621.56*三元-39.69548*0.2896350.32005-2.370962*0.9936801572.246

20、-32.70335*0.1931030.339534-2429.803*0.973912373.31641.469808-0.1155130.2350200.4199340.9976494242.990-46.80336*0.359845-2.747067*1406.688*0.9948491931.3934.640082*0.036911-0.4381230.3291460.9973543769.3922.971075*-0.074661574.1434*0.4292300.9975844128.507-65.33501*1.497226-2.076217*-1820.123*0.98426

21、4625.4986-8.639932*0.278735-0.7807680.3036610.9981365354.431-7.051621*-0.6759151031.526*0.362488-0.9984116283.2453.803876*-0.186988616.5333*0.3904510.9969563275.163二元-42.86199*0.345061-0.4917030.969679495.6886-27.07924*0.361950-2.142886*0.9927702128.216-29.21917*0.266111-1777.374*0.973448568.25109.1

22、35499*-0.0352150.3952680.9971175361.559-90.47035*1.420367-2.607910*0.981146806.5917-45.81271*1.197274-3831.055*0.970810515.49495.148753*-0.0549500.3634800.9967064689.525-119.1843*1.8100491946.129*0.85855394.081987.836511*-0.2327310.3650470.9972975719.4790.370558-103.5737*0.3446700.9965424466.723一元-6

23、9.11706*0.2089420.966837932.9177-104.9185*0.7461930.951541628.3539-92.42180*2.684774*0.854564188.0284是-161.4634*5803.580*0.842192170.7776是-3.242746*0.3395350.9965029114.9752、方程的檢驗(yàn)與處理（自相關(guān)、異方差、多重共線性）1）、在“是否合格”一欄注明了“是”的方程可認(rèn)為其解釋變量的共線性未嚴(yán)重到需要處理的程度，也就是說認(rèn)為該方程不存在多重共線性，進(jìn)行自相關(guān)、異方差的檢驗(yàn)與處理。2)、首選五元模型進(jìn)行處理和檢驗(yàn)：Y=-13.5

24、9329+0.049947X1+0.049947X2-1.030092X3+981.4846X4+0.303083X5Dependent Variable: YMethod: Least SquaresDate: 06/09/11 Time: 12:59Sample: 1976 2009Included observations: 34VariableCoefficientStd. Errort-StatisticProb. C-13.593296.911413-1.9667900.0592X10.0499470.0469031.0649030.2960X20.0497120.1154240.

25、4306920.6700X3-1.0300920.244706-4.2095020.0002X4981.4846340.18142.8851800.0074X50.3030830.0354568.5481530.0000R-squared0.998583 Mean dependent var286.7266Adjusted R-squared0.998330 S.D. dependent var512.4641S.E. of regression20.93969 Akaike info criterion9.079955Sum squared resid12277.17 Schwarz cri

26、terion9.349312Log likelihood-148.3592 F-statistic3947.433Durbin-Watson stat1.391880 Prob(F-statistic)0.000000(1)自相關(guān)檢驗(yàn)在五元模型最小二乘估計(jì)的結(jié)果中，DW=1.391880，因?yàn)閐l=1.21DW1.73=du, 所以，該模型不確定是否存在自相關(guān)，則認(rèn)為存在自相關(guān)。（2）利用夸特法對(duì)六元模型進(jìn)行異方差檢驗(yàn)將Xi按升序排列，i=1，2，3，4，5刪掉排在中間的n/4個(gè)，即34 個(gè)，刪掉8個(gè)。將其余樣本點(diǎn)劃分為樣本容量各為13個(gè)的兩個(gè)子樣本。分別用兩個(gè)子樣本做回歸。求出大 和小 ，并

27、做F檢驗(yàn)。結(jié)果如下表所示：X1X2X3X4X5大4926.6974926.6975832.4334926.6974926.697小0.8781480.8781480.8781480.8781480.878148F-statistic5610.32650535610.32650536641.7426225610.32650535610.3265053F臨界值5.055.055.055.055.05由上表可知，均大于（5，5）5.05所研究數(shù)據(jù)存在異方差。3.異方差的處理對(duì)數(shù)據(jù)進(jìn)行調(diào)整：Genr E5 = abs (resid)；Genr CE5=1/E5Genr YE5=Y/E5；Genr X1

28、E5=X1/E5；Genr X2E5=X2/E5；Genr X3E5=X3/E5；Genr X4E5=X4/E5；Genr X5E5=X5/E5； obsCE5YE5X1E5X2E5X3E5X4E5X5E519760.06033265548081.9610164341626.70182756499.633315100621.666140580496.2574254962619774.2942255689760.562775817721.02036830480.0037136777526114.870458432419780.7262305910928.603298920823.01318196

29、4530.0004040424155181.6859620475519791.5345129507617.65878351390.0008846667796873.5323576085119800.2371990006352.315228285526.08188027210.28969264766.5946066156619810.291647883212.4069116505531.684363548813.85910741010.7363525755286.6858527338519820.6085216695365.9742223428471.627016747430.821622562

30、1.786315360920.0046247646884717.939523078819830.94557891215910.86031803813.77995059680.0005067968223372.2082696924119840.4782594411116.6589975023772.071784737730.130344791.897972592050.0052608538522219.315177092519851.2472477783213.88845425224.803750878640.2312335941370.0006333983777652.930158477211

31、9861.9222474927323.02128686089.596485754160.8501919408576.6702925597619870.08352520398571.7388276965721.58622866058.867035655121.078318735986.7564539806519880.0598581580551.4510156235919.85748302698.384332198761.098325370525.6698245891219890.04934619033021.3498847749620.06952491917.582042144230.9874

32、962224114.6967358532919900.7992707845638.82402938866105.31807295943.87996607252.728071041870.0067138745903324.638800767419911.7738148471720.72437852528.956197832390.4978290858746.2565100051119920.080919205795710.475007374194.557247821334.968425592612.00277007140.0074931184566830.101580419619936.8413

33、599830172.251740288122.34872356697.845892008250.0042234381684720.771870158719940.034607260889857.2966082426289.27741141578.077095220821.05422695110.00941317496201167.8940115531995114.45649484339.779284092711.77962785440.0070826483651227.197617901119960.047061999144413.165067166291.627109805531.30187

34、687098.04165792320.0049132727106740.033581356619970.32702458216653.7135587035419.944235059160.41863853647.01171313140.0352532499575138.69070016519984.70571636879884.5824452926205.934981182447.01956894799.2381615130.5726856820822564.1053213419990.055528695056412.121964106683.351547617730.93170429429.

35、233450235720.0074019750510234.38749376120000.554941359259134.464844079951.2677143933731629690140.0535518411685413.90284632120010.02277018584362.232070237522.99233405376.966538358846.45059327185200244.488033729282.53570057793.260604295323.5888902102124.82773581720030.038484802935241.1291

36、82259914.21859529245.570167225470.0028709662989712.48158371220040.050734203530726.5423037825171.98265385449.034100370415.29533753360.007351386091678.343427319820050.046501170395130.6275820203191.0882871861.493612742217007556440189292.167128618620060.044699572292537.1317827249234.6009223

37、2368.032749029219.33627061110.00834988010424116.675739939200717.648756514699.073801016727.08544993838.089440033470.0033493787592158.0821681304200812.075966325324.9746349832712.121447110303.57674322782.529668291.5590072519115441.776029920090.0569526573388131.518914936544.108722018153.75338043832.7178

38、664342373.232975077Dependent Variable: YE5Method: Least SquaresDate: 06/09/11 Time: 21:25Sample: 1976 2009Included observations: 34VariableCoefficientStd. Errort-StatisticProb. CE5-8.6295631.805186-4.7804280.0001X1E50.0512590.0119394.2934600.0002X2E5-0.0278920.056453-0.4940650.6251X3E5-0.7879450.101

39、937-7.7297220.0000X4E5861.382679.7144410.805850.0000X5E50.3166320.00889535.596900.0000R-squared0.999999 Mean dependent var201.3591Adjusted R-squared0.999999 S.D. dependent var917.9514S.E. of regression0.935279 Akaike info criterion2.862842Sum squared resid24.49291 Schwarz criterion3.132199Log likeli

40、hood-42.66831 Durbin-Watson stat1.912226檢驗(yàn)異方差：X1E5X2E5X3E5X4E5X5E5大8.6582588.4894738.0638178.0638179.526173小0.0495170.0495170.0198590.0495170.049517F-statistic174.85425208171.44562473406.05352737162.84946584192.38186885F臨界值5.055.055.055.055.05由上表可知，存在異方差，所以再進(jìn)行異方差處理：genr E52=abs(resid)genr YE52=YE5/E

41、52genr X1E52=X1E5/E52genr X2E52=X2E5/E52genr X3E52=X3E5/E52genr X4E52=X4E5/E52genr X5E52=X5E5/E52產(chǎn)生新數(shù)據(jù)：obsCE52YE52X1E52X2E52X3E52X4E52X5E52197613.78360223434.827508847560.2262222455090.0006473284251222.7011301663919770.2090845234761.5214244435317.47411359886.081892435780.2890593537063.55307784969197

42、80.2320352867042.0104001310622.38637000127.74301751730.3727182810324.723031853819790.05913239403231.6175902917124.04965910489.085692343075.6281798713219800.275762448342.5351393400829.173736697310.09290560935.8357400842719810.06960189788671.6872126464823.08989368939.749137836991.277111303946.59276136

43、97219821.9609558156522.91084137659.901094386240.5503510373166.916584163119830.08943609636281.8618806540823.11383791329.494535989887.234593158119840.07045525629592.2900353774931.181854829111.24959077281.945685312347.30729508883198525.299347999110.54610170710.9343223038677.3303483747619863/p>

44、2.29915471189.786448810834.412676022439.0616598377519870.5385192559734.4442917156958.504247301525.59043504381.359653417480.0034465232382212.345230831619880.4503746244914.3959715972749.522202884819.53725121040.9779884970810.0024320229722512.5213153101198958.08667663520.16095398514.943771870470.003561

45、8446451614.262482171919900.3921043098595.4594251478959.088551078524.70257152111.556065953670.0043131474084515.835681499719910.05615541297235.9839881928260.01398055520.747178876718.2126043122199213.5401235716122.22586336945.200617691215.51492845450.0096856972235938.9096736667199312.203432539868.50570

46、1586918.72854106515.593534912880.0023159658701440.161572854199413.3180298445140.65198087343.506111093415.27354563740.0082217389106540.436461081719950.069642732121615.2030711006104.53747376538.79378750111.5803676040.0092833761918143.127954184719960.30841677106714.7980217258184.90840681764.26480258721

47、9.030394233543.93868781519970.057096919557915.9722237608111.1645449237.97630313649.756361903460.0059609184018548.5698486228199823.9149681397186.97240034571.423430548820.931095404361.749468025619990.029597130628724.5862357831155.33737321245.046832816912.80321259910.0055287440014577.255037108320003.87

48、10539758238.004459513455.64860191196.06888387511.3634789460.0294200102162114.12060673420010.058834958491738.7511217794241.77179518377.80393745921.7312861520.0095606807549116.61317641200259.5787000358386.044219421110.0653500734.3329778126175.855102643200379.0390456198943.36040901393.04386776624.43601

49、6930.0601378595489220.69592156820040.0546135740051126.117346047521.761816661147.43862733431.3741220038357.90404974920050.373042211646129.577555167822.924329523271.63441683268.7059073270.0443547189647363.5780561282006215.9409187381090.23608739294.25894815679.34970761060.0354766139198632.7632335912007

50、3.06186767483741.9046222025248.583145231860.4214179542.4563989840.2954702306212283.69308671200849.58273392529320.5821563665390.091287625783.51746858421.334819076.034218718727017.21522092009560.104889214246981.835571517246.62636477898.294624129058.69644772.3095411975716217.155904用新數(shù)據(jù)進(jìn)行回歸：Dependent Va

51、riable: YE52Method: Least SquaresDate: 06/09/11 Time: 22:59Sample: 1976 2009Included observations: 34VariableCoefficientStd. Errort-StatisticProb. CE52-6.0396880.749939-8.0535770.0000X1E520.0573390.0062999.1034390.0000X2E52-0.0911520.024912-3.6589840.0010X3E52-0.6345340.047906-13.245510.0000X4E52807

52、.355618.0691544.681430.0000X5E520.3217480.00637650.463840.0000R-squared1.000000 Mean dependent var7585.623Adjusted R-squared1.000000 S.D. dependent var42330.28S.E. of regression0.865382 Akaike info criterion2.707495Sum squared resid20.96883 Schwarz criterion2.976852Log likelihood-40.02741 Durbin-Wat

53、son stat2.200916檢驗(yàn)異方差：X1E52X2E52X3E52X4E52X5E52大5.5335195.0935475.4662985.0935475.421338小0.137980.0692940.0648820.0692940.085972F-statistic40.1037759173.50632089484.24983816873.50632089463.059344903F臨界值5.055.055.055.055.05由上表可知，存在異方差，現(xiàn)在進(jìn)行自相關(guān)檢驗(yàn)0 1 .15 1 .81 2 .19 2 .85 4當(dāng)D.W值落在【1.81 2.19】之間時(shí)，不存在自相關(guān)，但

54、數(shù)據(jù)D.W值為2.200916，落在此區(qū)間之外，所以存在自相關(guān)，所以需要進(jìn)行自相關(guān)處理。Dependent Variable: YE52Method: Least SquaresDate: 06/10/11 Time: 14:27Sample(adjusted): 1977 2009Included observations: 33 after adjusting endpointsConvergence achieved after 13 iterationsVariableCoefficientStd. Errort-StatisticProb. CE52-7.0965770.525690

55、-13.499550.0000X1E520.0469580.0059147.9395210.0000X2E52-0.0446110.017692-2.5215360.0181X3E52-0.7066950.032199-21.947440.0000X4E52810.370211.8590968.333240.0000X5E520.3262100.00695846.882680.0000AR(1)0.6980990.1420734.9136690.0000R-squared1.000000 Mean dependent var7815.455Adjusted R-squared1.000000

56、S.D. dependent var42965.05S.E. of regression0.672362 Akaike info criterion2.229791Sum squared resid11.75383 Schwarz criterion2.547232Log likelihood-29.79156 Durbin-Watson stat1.542068Inverted AR Roots .700.698099Genr ye53=ye52-*ye52(-1)Genr ce53=ce52-*ce52(-1)Genr x1e53=x1e52-*x1e52(-1)Genr x2e53=x2

57、e52-*x2e52(-1)Genr x3e53=x3e52-*x3e52(-1)Genr x4e53=x4e52-*x4e52(-1)Genr x5e53=x5e52-*x5e52(-1)帶入數(shù)值得：Genr ye53=ye52-0.698099*ye52(-1)Genr ce53=ce52-0.698099*ce52(-1)Genr x1e53=x1e52-0.698099*x1e52(-1)Genr x2e53=x2e52-0.698099*x2e52(-1)Genr x3e53=x3e52-0.698099*x3e52(-1)Genr x4e53=x4e52-0.698099*x4e5

58、2(-1)Genr x5e53=x5e52-0.698099*x5e52(-1)補(bǔ)數(shù)據(jù)Ye531=*ye52ce531=*ce52x1e531=*x1e52x2e531=*x2e52x3e531=*x3e52x4e531=*x4e52x5e531=*x5e52產(chǎn)生新序列，如下：obsCE53YE53X1E53X2E53X3E53X4E53X5E5319760.1363199880.8330787129.8690763893.4565023550.161975410.0004634881.93401256819770.07617295690650.7091752778257.8517946600

59、32.711813335890.0003635303151851.667421581119780.08607358992150.94829524814610497254488630.0004517046440072.24263175927197913.54583418024.687512821510.2548196891460.0007488131288052.538596269119800.2578651350162.6261933585629.156046464312.49140389488.4473909911219810.2241131810331.37546

60、83400923.932846994611.95149951280.6769206257333.6041131363519823.4951142201234.9019038945414.806845181178.20422667910.41430625010.0270139957777105.50241338819834.45689008452.5081704317625.272575589256.16837597216.50318363920.0395997798322141.0284401121984-4.60577421444-49.7176535484-599.470406949-24