（3）由于我国的统计数据含有一定的水分，而导致了我们赖以进行参数估计的数字基础不具备可靠性，可能也是重要原因之一。
参考文献：
1.《台湾教育与经济发展》 罗祥喜编著 台湾教育丛书
2.《家庭消费经济学》 顾纪瑞 著 中国财政经济出版社
3.《中国高等教育改革》 中国财政经济出版社
4.《中国物价及城镇居民家庭收支调查统计年鉴》 1999年
附表： 一：
obs 教育经费支出（X2） 总小学数（X3） 教育经费支出（X2） 人均图书流转量（X4） 人均GDP（X1） 文盲比例
（Y）
1 1930682. 2169.000 1930682. 166364.0 22460.00 4.230000
2 579702.8 2323.000 579702.8 106067.0 17993.00 4.930000
3 1382482. 36465.00 1382482. 364172.0 7663.000 6.650000
4 694615.7 37451.00 694615.7 166999.0 5137.000 4.180000
5 533015.7 10147.00 533015.7 81519.00 5872.000 9.120000
6 1252493. 13356.00 1252493. 285093.0 11226.00 4.760000
7 837866.3 9435.000 837866.3 140619.0 6847.000 4.570000
8 1044767. 13995.00 1044767. 144853.0 8562.000 5.100000
9 1744476. 1034.000 1744476. 464494.0 34547.00 5.400000
10 2617051. 19110.00 2617051. 672121.0 11773.00 6.310000
11 1828191. 11841.00 1828191. 339527.0 13461.00 7.060000
12 1034184. 24281.00 1034184. 299645.0 4867.000 10.06000
13 1042182. 13935.00 1042182. 226189.0 11601.00 7.200000
14 658618.3 21082.00 658618.3 201314.0 4851.000 5.160000
15 2087357. 26017.00 2087357. 498772.0 9555.000 8.460000
16 1531727. 41269.00 1531727. 535956.0 5444.000 5.870000
17 1538421. 23372.00 1538421. 327262.0 7188.000 7.150000
18 1397292. 34521.00 1397292. 332143.0 5639.000 4.650000
19 3144558. 24202.00 3144558. 433409.0 12885.00 3.840000
20 840142.7 16109.00 840142.7 226460.0 4319.000 3.790000
21 212244.1 4167.000 212244.1 52290.00 6894.000 6.980000
22 601278.1 14730.00 601278.1 140457.0 5157.000 6.950000
23 1375095. 43326.00 1375095. 387233.0 4784.000 7.640000
24 433565.9 17985.00 433565.9 101817.0 2662.000 13.89000
25 900880.6 22151.00 900880.6 148437.0 4637.000 11.39000
26 76981.00 842.0000 76981.00 2329.000 4559.000 32.50000
27 85250.90 33336.00 85250.90 224395.0 4549.000 7.290000
28 476792.9 21557.00 476792.9 105627.0 3838.000 14.34000
29 106626.5 3429.000 106626.5 12546.00 5087.000 18.03000
30 128222.1 3267.000 128222.1 19960.00 4839.000 13.40000
31 606396.7 6718.000 606396.7 91738.00 7470.000 5.560000
表二：
Dependent Variable: Y
Method: Least Squares
Date: 07/10/98 Time: 14:43
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 15.24285 2.065306 7.380433 0.0000
X1 0.000200 0.000467 0.428899 0.6717
X2 0.016095 0.007187 2.239541 0.0343
X3 -0.00925 0.007686 -1.204243 0.2398
X4 -0.020311 0.046189 -0.439733 0.6639
X5 -0.294092 0.079633 -3.693076 0.0011
R-squared 0.546863 Mean dependent var 8.272903
Adjusted R-squared 0.456235 S.D. dependent var 5.686135
S.E. of regression 4.192978 Akaike info criterion 5.876685
Sum squared resid 439.5267 Schwarz criterion 6.154231
Log likelihood -85.08862 F-statistic 6.034186
Durbin-Watson stat 1.780219 Prob(F-statistic) 0.000856
表三：
Dependent Variable: Y
Method: Least Squares
Date: 07/10/98 Time: 14:52
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 15.47034 1.964463 7.875098 0.0000
X2 0.017015 0.006750 2.520606 0.0182
X3 -0.000106 6.86E-05 -1.550419 0.1331
X4 -0.004643 0.027818 -0.166900 0.8687
X5 -0.281111 0.072493 -3.877762 0.0006
R-squared 0.543529 Mean dependent var 8.272903
Adjusted R-squared 0.473302 S.D. dependent var 5.686135
S.E. of regression 4.126653 Akaike info criterion 5.819500
Sum squared resid 442.7608 Schwarz criterion 6.050788
Log likelihood -85.20225 F-statistic 7.739664
Durbin-Watson stat 1.786424 Prob(F-statistic) 0.000301
表四：
Dependent Variable: Y
Method: Least Squares
Date: 07/10/98 Time: 14:59
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 15.43888 1.919874 8.041611 0.0000
X2 0.016833 0.006541 2.573503 0.0159
X3 -0.000106 6.74E-05 -1.579088 0.1260
X5 -0.286329 0.064218 -4.458686 0.0001
R-squared 0.543040 Mean dependent var 8.272903
Adjusted R-squared 0.492266 S.D. dependent var 5.686135
S.E. of regression 4.051681 Akaike info criterion 5.756055
Sum squared resid 443.2351 Schwarz criterion 5.941085
Log likelihood -85.21885 F-statistic 10.69536
Durbin-Watson stat 1.792203 Prob(F-statistic) 0.000083
表五：
Dependent Variable: Y
Method: Least Squares
Date: 07/10/98 Time: 15:02
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 13.26938 1.376316 9.641227 0.0000
X2 0.021674 0.005930 3.654938 0.0011
X5 -0.317662 0.062684 -5.067708 0.0000
R-squared 0.500838 Mean dependent var 8.272903
Adjusted R-squared 0.465184 S.D. dependent var 5.686135
S.E. of regression 4.158335 Akaike info criterion 5.779872
Sum squared resid 484.1690 Schwarz criterion 5.918645
Log likelihood -86.58802 F-statistic 14.04701
Durbin-Watson stat 2.138128 Prob(F-statistic) 0.000060
表六：
White Heteroskedasticity Test:
F-statistic 23.60129 Probability 0.000000
Obs*R-squared 25.58066 Probability 0.000108
Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 07/10/98 Time: 16:00
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 19.65554 13.46246 1.460026 0.1567
X2 0.300607 0.056692 5.302491 0.0000
X2^2 0.000489 0.000102 4.782576 0.0001
X2*X5 -0.013009 0.001911 -6.806030 0.0000
X5 -3.081696 0.458746 -6.717653 0.0000
X5^2 0.080169 0.009767 8.208089 0.0000
R-squared 0.825183 Mean dependent var 15.61836
Adjusted R-squared 0.790219 S.D. dependent var 30.28948
S.E. of regression 13.87313 Akaike info criterion 8.269771
Sum squared resid 4811.595 Schwarz criterion 8.547317
Log likelihood -122.1814 F-statistic 23.60129
Durbin-Watson stat 2.376012 Prob(F-statistic) 0.000000
表七：
Dependent Variable: LY
Method: Least Squares
Date: 07/10/98 Time: 16:02
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 3.285205 0.664639 4.942838 0.0000
LX2 0.009784 0.131254 0.074541 0.9411
LX5 -0.407599 0.071755 -5.680451 0.0000
R-squared 0.586595 Mean dependent var 1.970591
Adjusted R-squared 0.557066 S.D. dependent var 0.495294
S.E. of regression 0.329634 Akaike info criterion 0.710099
Sum squared resid 3.042444 Schwarz criterion 0.848872
Log likelihood -8.006541 F-statistic 19.86509
Durbin-Watson stat 1.679059 Prob(F-statistic) 0.000004
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教师点评：
本课程论文试图运用计量经济学方法分析文盲比例变动的影响因素，从而为降低文盲比例寻找有效途径和依据。从选题来看，具有现实价值。论文具有如下特点：
1. 在文献综述的基础上，从定性的角度比较全面地分析了影响文盲比例变动的主要方面，为数量分析奠定了基础。
2. 按照计量经济分析的规范完成了模型的估计、检验和修正。
3. 在模型检验中着重进行了经济意义检验，并根据估计结果与实际经济意义的相背而否定了模型的有效性。
4. 作者承认所建立的模型是一个失败的模型，并分析了失败的可能原因。
作为课程论文，主要目的在于能否熟练运用所学方法对实际问题进行分析，而不在于对实际问题的彻底解决。作者通过本文的研究，不仅掌握了计量经济分析的基本思想，而且明白了在特定的方法约束和数据约束下，计量经济分析能做什么和不能做什么，这也是一大收获。
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