四川省農(nóng)民收入結(jié)構(gòu)分析

1、四川省農(nóng)民收入結(jié)構(gòu)分析 一、 文章寫作目的 農(nóng)民收入結(jié)構(gòu)直接關(guān)系到農(nóng)民人均收入的高低。連續(xù)數(shù)年農(nóng)民收入增幅下降，一些地區(qū)農(nóng)民收入不升反降,農(nóng)民收入增長緩慢這一問題也就成為當(dāng)前我國農(nóng)業(yè)和農(nóng)村經(jīng)濟(jì)中表現(xiàn)最為突出的問題，增加農(nóng)民收入也是關(guān)系到我國國民經(jīng)濟(jì)穩(wěn)步發(fā)展的關(guān)鍵問題之一。本文擬從我國農(nóng)民收入的構(gòu)成入手，探討現(xiàn)階段農(nóng)民收入的主要構(gòu)成，為政府通過多種途徑提高農(nóng)民收入提供參考。二、 建立模型y=1+2x2+3x3+4x4+ux2勞動(dòng)者報(bào)酬收入 x3家庭經(jīng)營純收入x4接受政府轉(zhuǎn)移獲得的收入 y=平均每個(gè)農(nóng)民每年的可支配收入三、 收集數(shù)據(jù)以四川統(tǒng)計(jì)年鑒為根據(jù)，采用時(shí)間序列數(shù)據(jù)。見表（一）注：數(shù)據(jù)中的各項(xiàng)

2、收入都是平均每個(gè)人的一項(xiàng)收入，不是農(nóng)戶的收入 。四、 參數(shù)估計(jì)根據(jù)回歸的結(jié)果（見表二）可知道樣本回歸函數(shù)：y=41.341193+1.19166x2+1.950657x3-2.874068x4 (0.664679) (4.589561) (7.198040) (-0.964461) =0.993192 =0.991733 f=680.7665五、模型檢驗(yàn)（一）經(jīng)濟(jì)意義檢驗(yàn)通過回歸我們可以知道：x4的系數(shù)不符合經(jīng)濟(jì)意義。因?yàn)檎D(zhuǎn)移支出的增加一般會(huì)增加農(nóng)民的收入，而不是減少農(nóng)民的收入。故我們需要對(duì)設(shè)定的模型進(jìn)行統(tǒng)計(jì)檢驗(yàn)和計(jì)量檢驗(yàn)，通過進(jìn)一步的修正來改進(jìn)設(shè)定的模型。（二）統(tǒng)計(jì)檢驗(yàn)1、擬合優(yōu)度檢驗(yàn)可

3、決系數(shù)和修正可決系數(shù)的值都比較好，說明樣本回歸函數(shù)對(duì)樣本觀測(cè)數(shù)據(jù)的擬合優(yōu)度可以接受。2、參數(shù)顯著性檢驗(yàn)由回歸結(jié)果可知，常數(shù)項(xiàng)和x4系數(shù)的t值都不顯著。3、方程顯著性檢驗(yàn)由參數(shù)估計(jì)表得f統(tǒng)計(jì)量為680.7665，在5的顯著性水平下，查自由度為（3，14）的f分布表，得臨界值f0.05（3，14）=3.34。因?yàn)閒=680.7665f0.05(3,14)=3.34,故模型總體是顯著的。（三）計(jì)量檢驗(yàn)1多重共線性檢驗(yàn) correlation matrixx2x3x4x2 1.000000 0.926620 0.857506x3 0.926620 1.000000 0.959251x4 0.85750

4、6 0.959251 1.000000通過此表，我們可以看出解釋變量之間存在高度的線性相關(guān)。雖然可決系數(shù)和修正可決系數(shù)的值表明方程對(duì)變量的擬合度較好，但是x4參數(shù)估計(jì)值的符號(hào)與經(jīng)濟(jì)意義相反。表明模型中存在解釋變量之間的多從共線性。下面通過逐步回歸法，來糾正模型。根據(jù)調(diào)整后可決系數(shù)最大原則（見表四、五、六），選取x3作為進(jìn)入回歸模型的第一個(gè)解釋變量，形成一元回歸模型。將其它解釋變量分別加入模型，進(jìn)一步回歸，得到相應(yīng)的二元回歸模型（見表七、八）。又根據(jù)調(diào)整后可決系數(shù)最大原則，選取x3、x2作為進(jìn)入回歸模型的兩個(gè)解釋變量，形成二元回歸模型（見表九）。將x4加入模型，從回歸的結(jié)果中發(fā)現(xiàn)調(diào)整后可決系數(shù)小

5、于以x3、x2作為解釋變量得到的調(diào)整后可決系數(shù)，故不能將x4加入到模型中，暫?；貧w。我們得到一個(gè)帶有常數(shù)項(xiàng)的二元回歸模型，但發(fā)現(xiàn)常數(shù)項(xiàng)的回歸系數(shù)不顯著，而且p值很大。2、異方差檢驗(yàn)常數(shù)項(xiàng)和x4系數(shù)的t值都不顯著，且x4估計(jì)的系數(shù)不符合經(jīng)濟(jì)意義，u存在異方差。因?yàn)橥ㄟ^white檢驗(yàn)，得到=0.597719，*18=4.781752，而為0.710721，前者大于后者，拒絕接受h0,說明存在異方差。3、自相關(guān)檢驗(yàn)由表2得d的統(tǒng)計(jì)量為0.966878，樣本容量為n=18，在有三個(gè)解釋變量的情況下，給定顯著性水平=0.05，則查dw表的dl=0.933,du=1.696,4-du=2.304,4-dl

6、=3.067,這時(shí)有0.933d=0.9668781.696,不能判斷是否存在自相關(guān)，則需要改變樣本容量大小或者改變模型的函數(shù)形式，采用其他檢驗(yàn)方法。六、模型修改綜合對(duì)模型的檢驗(yàn)和修正，我們得到下面的二元回歸模型。 y=1.182556x2+1.787749x3 (28.46965) (6.972621) =0.992632 = 0.991771 f=4.198969但是通過驗(yàn)證，在給定顯著水平為0.05的情況下，f（3，12）=3.4940198969，說明f值不夠顯著。但參數(shù)的p值都很小，又說明參數(shù)的估計(jì)很好。同時(shí)可決系數(shù)和修正可決系數(shù)都比較大。我們認(rèn)為出現(xiàn)這樣的結(jié)果可能是因?yàn)槲覀儧]有不影

7、響農(nóng)民收入的其他主要因素考慮進(jìn)來，比如財(cái)產(chǎn)繼承收入，農(nóng)民外出打工收入等。特別是從90年代起農(nóng)民外出打工收入越來越成為農(nóng)民收入的重要成分。七、模型分析 家庭經(jīng)營純收入和勞動(dòng)者報(bào)酬收入實(shí)行成農(nóng)民收入的主要構(gòu)成部分，而政府轉(zhuǎn)移支出對(duì)農(nóng)民收入的影響較小。八、得出結(jié)論 農(nóng)民收入的組成結(jié)構(gòu)比較單一，收入增加很緩慢，缺乏新的增長動(dòng)力。目前，我國的城鄉(xiāng)差距非常明顯，國家有必要對(duì)農(nóng)業(yè)加大投入，通過多種途徑增加農(nóng)民的收入。當(dāng)前農(nóng)民收入增長緩慢，城、鄉(xiāng)收入差距擴(kuò)大，經(jīng)過模型分析我們得知，在農(nóng)民收入構(gòu)成中，家庭經(jīng)營純收入和勞動(dòng)者報(bào)酬收入是如今影響農(nóng)民收入的重要組成部分。從長期分析，推動(dòng)制度創(chuàng)新實(shí)現(xiàn)土地資源大范圍內(nèi)的流

8、轉(zhuǎn)和合理配置，促進(jìn)農(nóng)業(yè)產(chǎn)業(yè)化的發(fā)展。加大對(duì)農(nóng)業(yè)的投入國家應(yīng)選擇適度的傾斜政策，各級(jí)財(cái)政應(yīng)進(jìn)一步調(diào)整財(cái)政支出結(jié)構(gòu)，繼續(xù)增加農(nóng)業(yè)投入以及同時(shí)加強(qiáng)農(nóng)業(yè)的基礎(chǔ)設(shè)施建設(shè)，使農(nóng)民有效地規(guī)避自然風(fēng)險(xiǎn)和市場(chǎng)風(fēng)險(xiǎn)，還應(yīng)大力搞活農(nóng)產(chǎn)品流通，降低交易成本，確保農(nóng)產(chǎn)品價(jià)值的實(shí)現(xiàn)，迅速轉(zhuǎn)化為貨幣收入。轉(zhuǎn)移農(nóng)村剩余勞動(dòng)力，增加就業(yè)等途徑切實(shí)減輕農(nóng)民負(fù)擔(dān)，為農(nóng)民增收創(chuàng)造可行條件。九、參考文獻(xiàn)1、四川省統(tǒng)計(jì)年鑒（1986，1989，1992，1996，2000，2001，2002年）2、農(nóng)民收入、農(nóng)民負(fù)擔(dān)與農(nóng)民結(jié)構(gòu)調(diào)整，夏永祥、趙文娟、陳雄偉等著，中國農(nóng)業(yè)出版社出版十、相關(guān)附表表一：數(shù)據(jù)收集 obsx2x3x4y1984 4

9、.580000 85.37000 9.870000 420.83001985 17.56000 271.4100 24.48000 460.26001986 17.26000 293.8300 25.81000 499.76001987 18.98000 321.3400 27.96000 552.99001988 21.52000 393.5600 32.50000 680.75001989 23.88000 432.0700 37.04000 760.90001990 24.36000 493.5500 38.85000 846.69001991 22.28000 520.1500 47.

10、28000 915.75001992 25.63000 556.9200 51.75000 975.00001993 120.9800 527.8300 45.55000 1094.3201994 161.9800 708.9000 56.36000 1518.6501995 208.5800 860.4300 67.92000 1864.9201996 299.2000 1066.130 63.74000 2364.4901997 365.4100 1216.070 85.97000 2636.0801998 446.4600 1231.190 94.16000 2738.3901999 5

11、30.4000 1191.600 101.7400 2696.9402000 597.1600 1203.960 82.52000 2829.7802001 651.7900 1231.990 70.86000 2946.510表二：運(yùn)用ols法進(jìn)行參數(shù)估計(jì)dependent variable: ymethod: least squaresdate: 05/03/04 time: 15:20sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c41.3411962.197

12、200.6646790.5171x21.1916600.2596464.5895610.0004x31.9506570.2709987.1980400.0000x4-2.8740682.979974-0.9644610.3512r-squared0.993192 mean dependent var1489.056adjusted r-squared0.991733 s.d. dependent var956.8680s.e. of regression87.00281 akaike info criterion11.96289sum squared resid105972.9 schwarz

13、 criterion12.16075log likelihood-103.6660 f-statistic680.7665durbin-watson stat0.966878 prob(f-statistic)0.000000表三：white heteroskedasticity test:f-statistic2.724017 probability0.071322obs*r-squared10.75895 probability0.096118test equation:dependent variable: resid2method: least squaresdate: 05/04/0

14、4 time: 10:18sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c47727.4712741.113.7459440.0032x2105.9312111.15840.9529750.3611x22-0.1298730.115783-1.1216960.2859x3-112.2811188.1352-0.5968110.5627x320.0635680.0908980.6993370.4989x4-280.00842425.960-0.1154220.9102

15、x420.47727215.104100.0315990.9754r-squared0.597719 mean dependent var5887.381adjusted r-squared0.378294 s.d. dependent var12608.31s.e. of regression9941.442 akaike info criterion21.53211sum squared resid1.09e+09 schwarz criterion21.87837log likelihood-186.7890 f-statistic2.724017durbin-watson stat1.

16、483731 prob(f-statistic)0.071322表四：dependent variable: ymethod: least squaresdate: 05/04/04 time: 11:14sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c686.695887.915697.8108440.0000x24.0591470.29737213.650050.0000r-squared0.920919 mean dependent var1489.056ad

17、justed r-squared0.915976 s.d. dependent var956.8680s.e. of regression277.3659 akaike info criterion14.19299sum squared resid1230909. schwarz criterion14.29192log likelihood-125.7369 f-statistic186.3238durbin-watson stat0.362057 prob(f-statistic)0.000000表五：dependent variable: ymethod: least squaresda

18、te: 05/04/04 time: 11:15sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c-192.054668.30711-2.8116340.0125x32.4003870.08554628.059660.0000r-squared0.980083 mean dependent var1489.056adjusted r-squared0.978838 s.d. dependent var956.8680s.e. of regression139.1956

19、 akaike info criterion12.81408sum squared resid310006.7 schwarz criterion12.91301log likelihood-113.3267 f-statistic787.3446durbin-watson stat0.765750 prob(f-statistic)0.000000表六：dependent variable: ymethod: least squaresdate: 05/04/04 time: 11:15sample: 1984 2001included observations: 18variablecoe

20、fficientstd. errort-statisticprob. c-337.4843192.5772-1.7524620.0988x434.092793.24585210.503500.0000r-squared0.873341 mean dependent var1489.056adjusted r-squared0.865425 s.d. dependent var956.8680s.e. of regression351.0222 akaike info criterion14.66401sum squared resid1971465. schwarz criterion14.7

21、6295log likelihood-129.9761 f-statistic110.3234durbin-watson stat1.036959 prob(f-statistic)0.000000表七：dependent variable: ymethod: least squaresdate: 05/04/04 time: 11:29sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c28.5741060.630600.4712820.6442x31.7281660

22、.14187512.180930.0000x21.2655650.2475035.1133430.0001r-squared0.992739 mean dependent var1489.056adjusted r-squared0.991771 s.d. dependent var956.8680s.e. of regression86.80011 akaike info criterion11.91610sum squared resid113013.9 schwarz criterion12.06450log likelihood-104.2449 f-statistic1025.458

23、durbin-watson stat0.979106 prob(f-statistic)0.000000表八：dependent variable: ymethod: least squaresdate: 05/04/04 time: 11:32sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c-130.378375.96440-1.7163080.1067x32.8409600.2893279.8192150.0000x4-6.9104694.353208-1.58

24、74430.1333r-squared0.982948 mean dependent var1489.056adjusted r-squared0.980674 s.d. dependent var956.8680s.e. of regression133.0206 akaike info criterion12.76990sum squared resid265417.1 schwarz criterion12.91829log likelihood-111.9291 f-statistic432.3305durbin-watson stat0.874533 prob(f-statistic)0.000000表九：dependent variable: ymethod: least squaresdate: 05/04/04 time: 11:34sample: 1984 2001included observations: 18variablecoefficientstd. errort-statisticprob. c41.3411962.197200.6646790.5171x31.9506570.2709987.1980400.0000x21.1916600.2596464.5895610.0004x4-2.8740682.979974-0.964