我國農(nóng)民收入影響因素的回歸分析

1、我國農(nóng)民收入影響因素的回歸分析自改革開放以來 , 雖然中國經(jīng)濟平均增長速度為 9.5 % , 但二元經(jīng)濟結(jié)構(gòu)給 經(jīng)濟發(fā)展帶來的問題仍然很突出。農(nóng)村人口占了中國總?cè)丝诘?70 %多, 農(nóng)業(yè)產(chǎn)業(yè) 結(jié)構(gòu)不合理 ,經(jīng)濟不發(fā)達 ,以及農(nóng)民收入增長緩慢等問題勢必成為我國經(jīng)濟持續(xù) 穩(wěn)定增長的障礙。正確有效地解決好“三農(nóng)”問題是中國經(jīng)濟走出困境, 實現(xiàn)長期穩(wěn)定增長的關(guān)鍵。其中 ,農(nóng)民收入增長是核心 , 也是解決“三農(nóng)”問題的關(guān)鍵。 本文力圖應(yīng)用適當?shù)亩嘣€性回歸模型 , 對有關(guān)農(nóng)民收入的歷史數(shù)據(jù)和現(xiàn)狀進行 分析,尋找其根源 ,探討影響農(nóng)民收入的主要因素 ,并在此基礎(chǔ)上對如何增加農(nóng)民 收入提出相應(yīng)的政策建議。農(nóng)

2、民收入水平的度量， 通常采用人均純收入指標。 影響農(nóng)民收入增長的因 素是多方面的， 既有結(jié)構(gòu)性矛盾因素， 又有體制性障礙因素。 但可以歸納為以下 幾個方面： 一是農(nóng)產(chǎn)品收購價格水平。 目前農(nóng)業(yè)收入仍是中西部地區(qū)農(nóng)民收入的 主要來源。 二是農(nóng)業(yè)剩余勞動力轉(zhuǎn)移水平。 中國的農(nóng)業(yè)目前仍以農(nóng)戶分散經(jīng)營為 主，農(nóng)業(yè)比較效益低， 盡快地把農(nóng)業(yè)剩余勞動力轉(zhuǎn)移出去是有效改善農(nóng)民收入狀 況的重要因素。三是城市化、工業(yè)化水平。中國多數(shù)地區(qū)城市化、工業(yè)化水平落 后于世界平均水平， 這種狀況極大地影響了農(nóng)民收入的增長。 四是農(nóng)業(yè)產(chǎn)業(yè)結(jié)構(gòu) 狀況。農(nóng)林牧漁業(yè)對農(nóng)民收入增長貢獻率是不同的。隨著我國“入世”后農(nóng)產(chǎn)品 市場的開

3、放和人民生活水平的提高、 農(nóng)產(chǎn)品需求市場的改變， 農(nóng)業(yè)結(jié)構(gòu)狀況直接 影響著農(nóng)民收入的增長。 五是農(nóng)業(yè)投入水平。 農(nóng)民收入與財政農(nóng)業(yè)支出、 農(nóng)村集 體投入、農(nóng)戶個人投入以及信貸投入都有顯著的正相關(guān)關(guān)系。 農(nóng)業(yè)投入是農(nóng)民收 入增長的重要保證。 但考慮到農(nóng)業(yè)投入主體的多元性， 既有國家、 集體和農(nóng)戶的 投入，又有銀行、企業(yè)和外資的投入，考慮到復(fù)雜性和可行性，所以對農(nóng)業(yè)投入 與農(nóng)民收入，本文暫不作討論。因此，以全國為例，把農(nóng)民收入與各影響因素關(guān) 系進行線性回歸分析，并建立數(shù)學(xué)模型。一、計量經(jīng)濟模型分析（ 一 ） 、數(shù)據(jù)搜集根據(jù)以上分析，我們在影響農(nóng)民收入因素中引入 7個解釋變量。即： x2 -財政用于

4、農(nóng)業(yè)的支出的比重，X3 -第二、三產(chǎn)業(yè)從業(yè)人數(shù)占全社會從業(yè)人數(shù)的比重,X4 -非農(nóng)村人口比重，X5 -鄉(xiāng)村從業(yè)人員占農(nóng)村人口的比重，X6 -農(nóng)業(yè)總產(chǎn)值占農(nóng)林牧總產(chǎn)值的比重，X7 -農(nóng)作物播種面積，X8 -農(nóng)村用電量。yx2x3x4x5x6x7x8年份:78年可比價比重%比重比重千公頃億千瓦時1986133.6013.4329.5017.9236.0179.99150104.07253.101987137.6312.2031.3019.3938.6275.63146379.53320.801988 J147.867.6637.60 :23.7145.90P 69.25143625.87508.9

5、01989196.769.4239.9026.2149.2362.75146553.93790.501990220.539.9839.9026.4149.9364.66148362.27844.501991223.2510.2640.30 :26.9450.92:63.09149585.80963.201992 J233.1910.0541.50 :27.4651.53：61.51149007.101106.901993265.679.4943.6027.9951.8660.07147740.701244.901994 335.169.2045.7028.5152.12:58.22148240

6、.601473.901995411.298.4347.80：29.0452.41:58.43149879.301655.701996460.688.8249.5030.4853.2360.57152380.601812.701997477.968.3050.1031.9154.9358.23153969.201980.101998474.0210.6950.20 :33.3555.84:58.03155705.702042.201999466.808.2349.9034.7857.1657.53156372.812173.452000466.167.7550.0036.2259.3355.68

7、156299.852421.302001；469.80：7.7150.00 :37.6660.62:55.24155707.862610.782002468.957.1750.0039.0962.0254.51154635.512993.402003476.24p.1250.9040.5363.7250.08152414.963432.922004499.399.6753.10 :41.7665.64:50.05153552.553933.032005 1521.207.2255.2042.9967.5949.72155487.734375.70資料來源中國統(tǒng)計年鑒 2006。（二）、計量經(jīng)濟

8、學(xué)模型建立我們設(shè)定模型為下面所示的形式：Y = 12X23X34X45X56X67X7：8乂8 Ut利用Eviews軟件進行最小二乘估計，估計結(jié)果如下表所示：Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07 Time: 21:51Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.-1102.373375.8283-2.9331840.0136X2-6.6353933.781349-1.7547690.

9、1071X318.229422.0666178.8208990.0000X42.4300398.3703370.2903160.7770X5-16.237375.894109-2.7548470.0187X6-2.1552082.770834-0.7778190.4531X70.0099620.0023284.2788100.0013X80.0633890.0212762.9793480.0125R-squared0.995823Mean depe ndent var345.5232Adjusted R-squared0.993165S.D.dependent var139.7117S.E.

10、of regressi on11.55028Akaike info criteri on8.026857Sum squared resid1467.498Schwarz criteri on8.424516Log likelihood-68.25514F-statistic374.6600Durbi n- Watson stat1.993270Prob(F-statistic)0.000000表1最小二乘估計結(jié)果回歸分析報告為:Y = -1102.373-6.6354焉 + 18.2294X3 +2.4300X36.2374X5 -2.1552X6 +0.0100X7 +0.0634X8SE

11、=375.833.78132.066618.370345.89412.77080.002330.02128t 二 -2.933-1.7558.820900.20316-2.755-0.7784.278812.97932 2R =0.995823 R =0.993165 Df =19 DW =1.99327 F =374.66、計量經(jīng)濟學(xué)檢驗(一)、多重共線性的檢驗及修正、檢驗多重共線性(a)、直觀法從“表1最小二乘估計結(jié)果”中可以看出，雖然模型的整體擬合的很好,但是x4 x6的t統(tǒng)計量并不顯著，所以可能存在多重共線性。(b)、相關(guān)系數(shù)矩陣從“表2相關(guān)系數(shù)矩陣”中可以看出，個個解釋變量之間的相關(guān)

12、程度較高,X2X3X4X5X6X7X8X21.000000-0.717662-0.695257-0.7313260.737028-0.332435-0.594699X3-0.7176621.0000000.9222860.935992-0.9457010.7422510.883804X4-0.6952570.9222861.0000000.986050-0.9377510.7539280.974675X5-0.7313260.9359920.9860501.000000-0.9747500.6874390.940436X60.737028-0.945701-0.937751-0.9747501

13、.000000-0.603539-0.887428X7-0.3324350.7422510.7539280.687439-0.6035391.0000000.742781X8-0.5946990.8838040.9746750.940436-0.8874280.7427811.000000表2相關(guān)系數(shù)矩陣所以應(yīng)該存在多重共線性。、多重共線性的修正一一逐步迭代法A、一元回歸Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07 Time: 21:52Sample: 1986 2004In cluded observati ons: 19

14、VariableCoefficie ntStd. Errort-StatisticProb.C820.3133151.87125.4013740.0000X2-51.3783616.18923-3.1736140.0056R-squared0.372041Mean depe ndent var345.5232Adjusted R-squared0.335102S.D.dependent var139.7117S.E. of regressi on113.9227Akaike info criteri on12.40822Sum squared resid220632.4Schwarz crit

15、eri on12.50763Log likelihood-115.8781F-statistic10.07183Durbi n- Watson stat0.644400Prob(F-statistic)0.005554表3 y對x2的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07 Time: 21:52Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-525.889164.11333-8

16、.2024920.0000X319.460311.41604313.742740.0000R-squared0.917421Mean depe ndent var345.5232Adjusted R-squared0.912563S.D.dependent var139.7117S.E. of regressi on41.31236Akaike info criteri on10.37950Sum squared resid29014.09Schwarz criteri on10.47892Log likelihood-96.60526F-statistic188.8628Durbi n- W

17、atson stat0.598139Prob(F-statistic)0.000000表4 y對x3的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07 Time: 21:52Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-223.190569.92322-3.1919370.0053X418.650862.2422408.3179560.0000R-squared0.802758Mea

18、n depe ndent var345.5232Adjusted R-squared0.791155S.D.dependent var139.7117S.E. of regressi on63.84760Akaike info eriteri on11.25018Sum squared resid69300.77Sehwarz eriteri on11.34959Log likelihood-104.8767F-statistie69.18839Durbi n- Watson stat0.282182Prob(F-statistie)0.000000表5 y對x4的回歸結(jié)果Depe ndent

19、 Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52Sample: 1986 2004In eluded observati ons: 19VariableCoeffieie ntStd. Errort-StatistieProb.C-494.1440118.1449-4.1825260.0006X515.779782.1987117.1768320.0000R-squared0.751850Mean depe ndent var345.5232Adjusted R-squared0.737253S.D.dependent var

20、139.7117S.E. of regressi on71.61463Akaike info eriteri on11.47978Sum squared resid87187.14Sehwarz eriteri on11.57919Log likelihood-107.0579F-statistie51.50691Durbi n- Watson stat0.318959Prob(F-statistie)0.000002表6 y對x5的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52Sample: 1

21、986 2004In eluded observati ons: 19VariableCoeffieie ntStd. Errort-StatistieProb.C1288.009143.80888.9563950.0000X6-15.523982.351180-6.6026350.0000R-squared0.719448Mean depe ndent var345.5232Adjusted R-squared0.702945S.D.dependent var139.7117S.E. of regressi on76.14674Akaike info eriteri on11.60250Su

22、m squared resid98571.54Sehwarz eriteri on11.70192Log likelihood-108.2238F-statistie43.59479Durbi n- Watson stat0.395893Prob(F-statistie)0.000004表7 y對x6的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52Sample: 1986 2004In eluded observati ons: 19VariableCoefficie ntStd. Errort-

23、StatisticProb.C-4417.766681.1678-6.4855770.0000X70.0315280.0045076.9949430.0000R-squared0.742148Mean depe ndent var345.5232Adjusted R-squared0.726980S.D.dependent var139.7117S.E. of regressi on73.00119Akaike info criteri on11.51813Sum squared resid90595.96Schwarz criteri on11.61754Log likelihood-107

24、.4222F-statistic48.92923Durbi n- Watson stat0.572651Prob(F-statistic)0.000002表8 y對x7的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C140.162528.966164.8388350.0002X80.1198270.0145438.23

25、95030.0000R-squared0.799739Mean depe ndent var345.5232Adjusted R-squared0.787959S.D.dependent var139.7117S.E. of regressi on64.33424Akaike info criteri on11.26536Sum squared resid70361.21Schwarz criteri on11.36478Log likelihood-105.0209F-statistic67.88941Durbi n- Watson stat0.203711Prob(F-statistic)

26、0.000000表9 y對x8的回歸結(jié)果綜合比較表39的回歸結(jié)果，發(fā)現(xiàn)加入x3的回歸結(jié)果最好。以x3為基礎(chǔ)順次加入其他解釋變量，進行二元回歸，具體的回歸結(jié)果如下表1015所示:Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07 Time: 21:53Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-754.4481149.1701-5.0576370.0001X321.788651.93268911

27、.273750.0000X213.450708.0127451.6786630.1126R-squared0.929787Mean depe ndent var345.5232Adjusted R-squared0.921010S.D.dependent var139.7117S.E. of regressi on39.26619Akaike info criteri on10.32254Sum squared resid24669.34Schwarz criteri on10.47167Log likelihood-95.06417F-statistic105.9385Durbi n- Wa

28、tson stat0.595954Prob(F-statistic)0.000000表10加入x2的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:53Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-508.678175.73220-6.7168020.0000X317.882003.7521214.7658370.0002X41.7533513.8443050.456

29、0900.6545R-squared0.918481Mean depe ndent var345.5232Adjusted R-squared0.908291S.D.dependent var139.7117S.E. of regressi on42.30965Akaike info criteri on10.47185Sum squared resid28641.71Schwarz criteri on10.62097Log likelihood-96.48254F-statistic90.13613Durbi n- Watson stat0.596359Prob(F-statistic)0

30、.000000表11加入x4的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:54Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-498.155067.21844-7.4109860.0000X323.975163.9671836.0433700.0000X5-4.3205663.553466-1.2158740.2417R-squared0.924405Mean de

31、pe ndent var345.5232Adjusted R-squared0.914956S.D.dependent var139.7117S.E. of regressi on40.74312Akaike info criteri on10.39639Sum squared resid26560.02Schwarz criteri on10.54551Log likelihood-95.76570F-statistic97.82772Durbi n- Watson stat0.607882Prob(F-statistic)0.000000表12 加入x5的回歸結(jié)果Depe ndent Va

32、riable: YMethod: Least SquaresDate: 06/08/07Time: 21:54Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-1600.965346.9265-4.6147090.0003X329.937683.5347538.4695280.0000X69.9801353.1841763.1342910.0064R-squared0.948835Mean depe ndent var345.5232Adjusted R-squ

33、ared0.942440S.D.dependent var139.7117S.E. of regressi on33.51927Akaike info eriteri on10.00606Sum squared resid17976.66Schwarz eriteri on10.15518Log likelihood-92.05754F-statistie148.3576Durbi n- Watson stat1.125188Prob(F-statistie)0.000000表13加入x6的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate:

34、 06/08/07Time: 21:54Sample: 1986 2004In eluded observati ons: 19VariableCoeffieie ntStd. Errort-StatistieProb.C-2153.028327.1248-6.5816730.0000X314.404971.35835510.604720.0000X70.0122680.0024475.0140150.0001R-squared0.967884Mean depe ndent var345.5232Adjusted R-squared0.963869S.D.dependent var139.71

35、17S.E. of regressi on26.55648Akaike info eriteri on9.540364Sum squared resid11283.94Sehwarz eriteri on9.689485Log likelihood-87.63345F-statistie241.0961Durbi n- Watson stat0.690413Prob(F-statistie)0.000000表14加入x7的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:54Sample: 1986 20

36、04In eluded observati ons: 19VariableCoeffieie ntStd. Errort-StatistieProb.C-400.5635103.0301-3.8878320.0013X315.542712.9163585.3294930.0001X80.0292330.0192331.5199290.1480R-squared0.927840Mean depe ndent var345.5232Adjusted R-squared0.918820S.D.dependent var139.7117S.E. of regressi on39.80687Akaike

37、 info eriteri on10.34990Sum squared resid25353.40Sehwarz eriteri on10.49902Log likelihood-95.32401F-statistie102.8643Durbi n- Watson stat0.559772Prob(F-statistie)0.000000表15加入x8的回歸結(jié)果綜合表1015所示，加入x7的模型的R最大，以x3、x7為基礎(chǔ)順次加入其他解釋變量，進行三元回歸，具體回歸結(jié)果如下表 1620所示:Depe ndent Variable: YMethod: Least SquaresDate: 06/

38、08/07 Time: 21:55Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-2133.921340.6965-6.2634060.0000X314.960232.0946457.1421340.0000X70.0118430.0027864.2509080.0007X22.1952436.1704030.3557700.7270R-squared0.968153Mean depe ndent var345.5232Adjusted R-squared0.

39、961783S.D.dependent var139.7117S.E. of regressi on27.31242Akaike info criteri on9.637224Sum squared resid11189.52Schwarz criteri on9.836053Log likelihood-87.55363F-statistic151.9988Durbi n- Watson stat0.712258Prob(F-statistic)0.000000表16加入x2的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08

40、/07Time: 21:55Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-2226.420353.4425-6.2992430.0000X315.667292.4431136.4128390.0000X70.0127030.0025894.9063730.0002X4-1.6013622.553294-0.6271750.5400R-squared0.968705Mean depe ndent var345.5232Adjusted R-squared0.9

41、62445S.D.dependent var139.7117S.E. of regressi on27.07472Akaike info criteri on9.619741Sum squared resid10995.60Schwarz criteri on9.818571Log likelihood-87.38754F-statistic154.7677Durbi n- Watson stat0.704178Prob(F-statistic)0.000000表17加入x4的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/

42、07Time: 21:55Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-2110.381306.2690-6.8906130.0000X318.601562.6173817.1069370.0000X70.0121390.0022855.3116650.0001X5-3.9648782.163262-1.8328230.0868R-squared0.973760Mean depe ndent var345.5232Adjusted R-squared0.96

43、8512S.D.dependent var139.7117S.E. of regressi on24.79152Akaike info criteri on9.443544Sum squared resid9219.289Schwarz criteri on9.642373Log likelihood-85.71367F-statistic185.5507Durbi n- Watson stat0.733972Prob(F-statistic)0.000000表18加入x5的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/0

44、7 Time: 21:55Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-2418.859323.7240-7.4719790.0000X320.998873.3971206.1813740.0000X70.0099200.0024953.9766600.0012X65.3591842.5719502.0837050.0547R-squared0.975093Mean depe ndent var345.5232Adjusted R-squared0.9701

45、12S.D.dependent var139.7117S.E. of regressi on24.15359Akaike info criteri on9.391407Sum squared resid8750.940Schwarz criteri on9.590236Log likelihood-85.21837F-statistic195.7489Durbi n- Watson stat1.084023Prob(F-statistic)0.000000表19加入x6的回歸結(jié)果Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07

46、Time: 21:56Sample: 1986 2004In cluded observati ons: 19VariableCoefficie ntStd. Errort-StatisticProb.C-2013.355361.8657-5.5638180.0001X313.015782.0324206.4040780.0000X70.0116150.0025584.5403220.0004X80.0123750.0134160.9224010.3709R-squared0.969608Mean depe ndent var345.5232Adjusted R-squared0.963529

47、S.D.dependent var139.7117S.E. of regressi on26.68115Akaike info criteri on9.590455Sum squared resid10678.26Schwarz criteri on9.789285Log likelihood-87.10933F-statistic159.5158Durbi n- Watson stat0.672264Prob(F-statistie)0.000000表20 加入x8的回歸結(jié)果綜合上述表1620的回歸結(jié)果所示，其中加入x6的回歸結(jié)果最好，以 x3 x6x7為基礎(chǔ)一次加入其他解釋變量，作四元回歸

48、估計，估計結(jié)果如表2124所示：Depe ndent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:57Sample: 1986 2004In eluded observati ons: 19VariableCoeffieie ntStd. Errort-StatistieProb.C-2405.108339.7396-7.0792690.0000X321.268503.6997875.7485730.0001X65.3105432.6655691.9922730.0662X70.0096890.0027663.5033860.0035X21.3026055.6553900.2303300.8212R-squared0.975187Mean depe ndent var345.5232Adjusted R-squared0.968098S.D.dependent var139.7117S.E. of regressi on24.95411Akaike info