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1、精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -我国农夫收入影响因素的回来分析自改革开放以来 , 虽然中国经济平均增长速度为9.5 % ,但二元经济结构给经济进展带来的问题仍旧很突出。农村人口占了中国总人口的70 %多, 农业产业结构不合理 , 经济不发达 , 以及农夫收入增长缓慢等问题势必成为我国经济连续稳固增长的障碍。正确有效的解决好“三农”问题是中国经济走出困境, 实现长期稳固增长的关键。其中, 农夫收入增长是核心 , 也是解决“三农”问题的关键。本文力图应用适当的多元线性回来模型, 对有关农夫收入的历史数据和现状进行 分析, 查找其根源 , 探
2、讨影响农夫收入的主要因素, 并在此基础上对如何增加农夫收入提出相应的政策建议。农夫收入水平的度量， 通常采纳人均纯收入指标。 影响农夫收入增长的因素是多方面的， 既有结构性冲突因素， 又有体制性障碍因素。 但可以归纳为以下几个方面： 一是农产品收购价格水平。 目前农业收入仍是中西部的区农夫收入的主要来源。二是农业剩余劳动力转移水平。中国的农业目前仍以农户分散经营为 主，农业比较效益低， 尽快的把农业剩余劳动力转移出去是有效改善农夫收入状况的重要因素。三是城市化、工业化水平。中国多数的区城市化、工业化水平落 后于世界平均水平， 这种状况极大的影响了农夫收入的增长。四是农业产业结构状况。农林牧渔业
3、对农夫收入增长奉献率是不同的。随着我国“入世”后农产品 市场的开放和人民生活水平的提高、农产品需求市场的转变， 农业结构状况直接影响着农夫收入的增长。 五是农业投入水平。 农夫收入与财政农业支出、农村集体投入、农户个人投入以及信贷投入都有显著的正相关关系。农业投入是农夫收入增长的重要保证。 但考虑到农业投入主体的多元性，既有国家、 集体和农户的投入，又有银行、企业和外资的投入，考虑到复杂性和可行性，所以对农业投入 与农夫收入，本文暂不作争论。因此，以全国为例，把农夫收入与各影响因素关 系进行线性回来分析，并建立数学模型。可编辑资料 - - - 欢迎下载精品名师归纳总结一、计量经济模型分析 一
4、、数据搜集依据以上分析，我们在影响农夫收入因素中引入7 个说明变量。即：x2 - 财可编辑资料 - - - 欢迎下载精品名师归纳总结可编辑资料 - - - 欢迎下载精品名师归纳总结学习资料 名师精选 - - - - - - - - - -第 1 页，共 26 页 - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结政用于农业的支出的比重，x3 - 其次、三产业从业人数占全社会从业人数的比重，可编辑资料 - - - 欢迎下载精品名师归纳总结可
5、编辑资料 - - - 欢迎下载精品名师归纳总结x4 - 非农村人口比重，x5 - 乡村从业人员占农村人口的比重，x6 - 农业总产值可编辑资料 - - - 欢迎下载精品名师归纳总结可编辑资料 - - - 欢迎下载精品名师归纳总结占农林牧总产值的比重，x7 - 农作物播种面积，x8 农村用电量。可编辑资料 - - - 欢迎下载精品名师归纳总结年份y78 年可比价x2比重x3%x4%x5比重x6比重x7千公顷x8亿千瓦时1986133.6013.4329.5017.9236.0179.99150104.07253.101987137.6312.2031.3019.3938.6275.6314637
6、9.53320.801988147.867.6637.6023.7145.9069.25143625.87508.901989196.769.4239.9026.2149.2362.75146553.93790.501990220.539.9839.9026.4149.9364.66148362.27844.501991223.2510.2640.3026.9450.9263.09149585.80963.201992233.1910.0541.5027.4651.5361.51149007.101106.901993265.679.4943.6027.9951.8660.07147740.7
7、01244.901994335.169.2045.7028.5152.1258.22148240.601473.901995411.298.4347.8029.0452.4158.43149879.301655.701996460.688.8249.5030.4853.2360.57152380.601812.701997477.968.3050.1031.9154.9358.23153969.201980.101998474.0210.6950.2033.3555.8458.03155705.702042.201999466.808.2349.9034.7857.1657.53156372.
8、812173.452000466.167.7550.0036.2259.3355.68156299.852421.302001469.807.7150.0037.6660.6255.24155707.862610.782002468.957.1750.0039.0962.0254.51154635.512993.402003476.247.1250.9040.5363.7250.08152414.963432.922004499.399.6753.1041.7665.6450.05153552.553933.032005521.207.2255.2042.9967.5949.72155487.
9、734375.70资料来源中国统计年鉴2006 。二、计量经济学模型建立我们设定模型为下面所示的形式：Yt12 X 23 X 34 X 45 X 56 X 67 X78 X 8ut利用 Eviews 软件进行最小二乘估量，估量结果如下表所示：Dependent Variable: Y Method: Least SquaresDate: 06/08/07Time: 21:51Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-1102.373375.8283-2.933
10、1840.0136可编辑资料 - - - 欢迎下载精品名师归纳总结学习资料 名师精选 - - - - - - - - - -第 2 页，共 26 页 - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -X2-6.6353933.781349-1.7547690.1071X318.229422.0666178.8208990.0000X42.4300398.3703370.2903160.7770X5-16.237375.894109-2.7548470.0187X6-2.1552082.
11、770834-0.7778190.4531X70.0099620.0023284.2788100.0013X80.0633890.0212762.9793480.0125R-squared0.995823Mean dependent var345.5232Adjusted R-squared0.993165S.D. dependent var139.7117S.E. of regression11.55028Akaike info criterion8.026857Sum squared resid1467.498Schwarz criterion8.424516Log likelihood-
12、68.25514F-statistic374.6600Durbin-Watson stat1.993270ProbF-statistic0.000000表 1 最小二乘估量结果回来分析报告为：Y.-1102.373-6.6354X +18.2294X +2.4300X -16.2374X -2.1552X +0.0100X +0.0634Xi2345678SE375.833.78132.066618.370345.89412.77080.002330.02128t-2.9331.7558.820900.203162.7550.7784.278812.979322R0.995823R0.9931
13、65Df19DW1.99327F374.66二、计量经济学检验一、多重共线性的检验及修正、检验多重共线性a、直观法从“表 1 最小二乘估量结果”中可以看出，虽然模型的整体拟合的很好，但是 x4 x6 的 t 统计量并不显著，所以可能存在多重共线性。b、相关系数矩阵X2X3X4X5X6X7X8X21.000000-0.717662-0.695257-0.7313260.737028-0.332435-0.594699X3-0.7176621.0000000.9222860.935992-0.9457010.7422510.883804X4-0.6952570.9222861.0000000.98
14、6050-0.9377510.7539280.974675X5-0.7313260.9359920.9860501.000000-0.9747500.6874390.940436X60.737028-0.945701-0.937751-0.9747501.000000-0.603539-0.887428X7-0.3324350.7422510.7539280.687439-0.6035391.0000000.742781X8-0.5946990.8838040.9746750.940436-0.8874280.7427811.000000表 2 相关系数矩阵从“表 2 相关系数矩阵”中可以看出
15、，个个说明变量之间的相关程度较高，所以应当存在多重共线性。可编辑资料 - - - 欢迎下载精品名师归纳总结学习资料 名师精选 - - - - - - - - - -第 3 页，共 26 页 - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -、多重共线性的修正逐步迭代法A、一元回来Dependent Variable: Y Method: Least SquaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observatio
16、ns: 19VariableCoefficientStd. Errort-StatisticProb.C820.3133151.87125.4013740.0000X2-51.3783616.18923-3.1736140.0056R-squared0.372041Mean dependent var345.5232Adjusted R-squared0.335102S.D. dependent var139.7117S.E. of regression113.9227Akaike info criterion12.40822Sum squared resid220632.4Schwarz c
17、riterion12.50763Log likelihood-115.8781F-statistic10.07183Durbin-Watson stat0.644400ProbF-statistic0.005554表 3y 对x2的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-525.889164.11333-8.2024
18、920.0000X319.460311.41604313.742740.0000R-squared0.917421Mean dependent var345.5232Adjusted R-squared0.912563S.D. dependent var139.7117S.E. of regression41.31236Akaike info criterion10.37950Sum squared resid29014.09Schwarz criterion10.47892Log likelihood-96.60526F-statistic188.8628Durbin-Watson stat
19、0.598139ProbF-statistic0.000000表 4y 对x3的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-223.190569.92322-3.1919370.0053X418.650862.2422408.3179560.0000R-squared0.802758Mean dependent var3
20、45.5232可编辑资料 - - - 欢迎下载精品名师归纳总结学习资料 名师精选 - - - - - - - - - -第 4 页，共 26 页 - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -Adjusted R-squared0.791155S.D. dependent var139.7117S.E. of regression63.84760Akaike info criterion11.25018Sum squared resid69300.77Schwarz criteri
21、on11.34959Log likelihood-104.8767F-statistic69.18839Durbin-Watson stat0.282182ProbF-statistic0.000000表 5y 对x4的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-494.1440118.1449-4.1825260.00
22、06X515.779782.1987117.1768320.0000R-squared0.751850Mean dependent var345.5232Adjusted R-squared0.737253S.D. dependent var139.7117S.E. of regression71.61463Akaike info criterion11.47978Sum squared resid87187.14Schwarz criterion11.57919Log likelihood-107.0579F-statistic51.50691Durbin-Watson stat0.3189
23、59ProbF-statistic0.000002表 6y 对x5的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C1288.009143.80888.9563950.0000X6-15.523982.351180-6.6026350.0000R-squared0.719448Mean dependent var345.523
24、2Adjusted R-squared0.702945S.D. dependent var139.7117S.E. of regression76.14674Akaike info criterion11.60250Sum squared resid98571.54Schwarz criterion11.70192Log likelihood-108.2238F-statistic43.59479Durbin-Watson stat0.395893ProbF-statistic0.000004表 7y 对x6 的回来结果Dependent Variable: Y Method: Least S
25、quaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observations: 19可编辑资料 - - - 欢迎下载精品名师归纳总结学习资料 名师精选 - - - - - - - - - -第 5 页，共 26 页 - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -VariableCoefficientStd. Errort-StatisticProb.C-4417.766681.1678-6.4855770.0000X7
26、0.0315280.0045076.9949430.0000R-squared0.742148Mean dependent var345.5232Adjusted R-squared0.726980S.D. dependent var139.7117S.E. of regression73.00119Akaike info criterion11.51813Sum squared resid90595.96Schwarz criterion11.61754Log likelihood-107.4222F-statistic48.92923Durbin-Watson stat0.572651Pr
27、obF-statistic0.000002表 8y 对x7的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:52 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C140.162528.966164.8388350.0002X80.1198270.0145438.2395030.0000R-squared0.799739Mean dependent var345.5232Adjus
28、ted R-squared0.787959S.D. dependent var139.7117S.E. of regression64.33424Akaike info criterion11.26536Sum squared resid70361.21Schwarz criterion11.36478Log likelihood-105.0209F-statistic67.88941Durbin-Watson stat0.203711ProbF-statistic0.000000表 9y 对x8 的回来结果综合比较表 39 的回来结果， 发觉加入 x3 的回来结果最好。 以 x3 为基础顺次
29、加入其他说明变量，进行二元回来，详细的回来结果如下表1015 所示：Dependent Variable: Y Method: Least SquaresDate: 06/08/07Time: 21:53 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-754.4481149.1701-5.0576370.0001X321.788651.93268911.273750.0000X213.450708.0127451.6786630.1126R-squared0.92
30、9787Mean dependent var345.5232Adjusted R-squared0.921010S.D. dependent var139.7117S.E. of regression39.26619Akaike info criterion10.32254Sum squared resid24669.34Schwarz criterion10.47167Log likelihood-95.06417F-statistic105.9385可编辑资料 - - - 欢迎下载精品名师归纳总结学习资料 名师精选 - - - - - - - - - -第 6 页，共 26 页 - - -
31、 - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -Durbin-Watson stat0.595954ProbF-statistic0.000000表 10加入x2 的回来结果Dependent Variable: Y Method: Least SquaresDate: 06/08/07Time: 21:53 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-508.
32、678175.73220-6.7168020.0000X317.882003.7521214.7658370.0002X41.7533513.8443050.4560900.6545R-squared0.918481Mean dependent var345.5232Adjusted R-squared0.908291S.D. dependent var139.7117S.E. of regression42.30965Akaike info criterion10.47185Sum squared resid28641.71Schwarz criterion10.62097Log likel
33、ihood-96.48254F-statistic90.13613Durbin-Watson stat0.596359ProbF-statistic0.000000表 11加入x4 的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:54 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-498.155067.21844-7.4109860.0000X323.975163.9671
34、836.0433700.0000X5-4.3205663.553466-1.2158740.2417R-squared0.924405Mean dependent var345.5232Adjusted R-squared0.914956S.D. dependent var139.7117S.E. of regression40.74312Akaike info criterion10.39639Sum squared resid26560.02Schwarz criterion10.54551Log likelihood-95.76570F-statistic97.82772Durbin-W
35、atson stat0.607882ProbF-statistic0.000000表 12加入x5 的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:54 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-1600.965346.9265-4.6147090.0003X329.937683.5347538.4695280.0000可编辑资料 - - - 欢迎下载精品名师归纳总结学
36、习资料 名师精选 - - - - - - - - - -第 7 页，共 26 页 - - - - - - - - - -可编辑资料 - - - 欢迎下载精品名师归纳总结资料word 精心总结归纳 - - - - - - - - - - - -X69.9801353.1841763.1342910.0064R-squared0.948835Mean dependent var345.5232Adjusted R-squared0.942440S.D. dependent var139.7117S.E. of regression33.51927Akaike info criterion10.00
37、606Sum squared resid17976.66Schwarz criterion10.15518Log likelihood-92.05754F-statistic148.3576Durbin-Watson stat1.125188ProbF-statistic0.000000表 13加入x6 的回来结果Dependent Variable: YMethod: Least SquaresDate: 06/08/07Time: 21:54 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-S
38、tatisticProb.C-2153.028327.1248-6.5816730.0000X314.404971.35835510.604720.0000X70.0122680.0024475.0140150.0001R-squared0.967884Mean dependent var345.5232Adjusted R-squared0.963869S.D. dependent var139.7117S.E. of regression26.55648Akaike info criterion9.540364Sum squared resid11283.94Schwarz criteri
39、on9.689485Log likelihood-87.63345F-statistic241.0961Durbin-Watson stat0.690413ProbF-statistic0.000000表 14加入x7 的回来结果Dependent Variable: Y Method: Least SquaresDate: 06/08/07Time: 21:54 Sample: 1986 2004Included observations: 19VariableCoefficientStd. Errort-StatisticProb.C-400.5635103.0301-3.8878320.0013X315.542712.9163