中国国防预算的影响因素分析

1、东华理工大学抚州校区课程论文目：中国国防预算的影响因素分析系 部：经济管理系专 业：国际经济与贸易班 级：10207502学 生：姜凌学 号：1020750280中国国防预算的影响因素分析国无防则无家，一个国家的发达程度与其的国防力量不可不无关 系，每年每个国家在国防支出这块都需要做出认真的预算。但是一 个国家的国防预算是怎么做出的，下面我们就来研究一下。首先我们先假设影响中国国防预算(CXDB)的几个因素：1、日木的国防预算(JXDB)2、美国的国防预算(AXDB)3、中国的 GDP (CGDP)4、中国的财政收入(FINANCIAL)1. 建立一个理论假说中国国防收入与日本国防收入、美国国

2、防收入、中国GDP和中国 财政收入呈正相关关系2. 收集数据中国国防预算数据(单位：亿美元)中国GDP中国财政收入日本国防预算美国国防预算198966. 79284. 1303. 560. 00452664.9199060. 69287. 25299. 330. 00392937. 1199162. 05325. 58273. 290. 00413149.48199268. 52359. 38298. 350. 00493483. 37199373.9417.31291.090. 00614348. 95199463.9458.21281. 640. 00565218. 1199576. 24

3、502.17272. 060.00736242. 2199686.61445. 42255. 750. 00867407. 99199798. 02408.9270. 510. 00958651. 141998112.9377. 33268. 210.01029875. 951999130. 03432.98274. 790.010811444.082000145. 87457. 99294.390.01213395. 232001174.22407. 72304.760.013216386. 042002206. 33395. 23348. 480.014518903. 642003230.

4、5427.2404. 780.016421725.252004265.8453. 14455. 850.019326396. 472005302. 13440. 58495. 330. 022631649.292006373. 74413.9521. 840. 027138760. 22007467. 51407. 74551. 290.03551321. 782008590. 55462.2616. 10. 045261330. 352009692. 24509.94690. 310. 049968518.33. 建立数学模型CXDB二 B1JXDB+ B2AXDB+ B3CGDP+ B4F

5、INANCIAL+C4. 简历经济计量模型CNDB= B1JXDB+ B2AXDB+ B3CGDP+ BdFINANCIAL+C+u5. 估计经济计量模型参数Dependent Variable: CNDBMethod: Least SquaresDate: 11/16/12 Time: 10:34Sample: 1989 2009Included observations: 21VariableCoefficientStd Error t-Statistic ProbJNDB-0.0644020. 046864-1. 3742430. 1883ANDB0.2144350.0820132. 6

6、146400. 0188CGDP10077. 452626. 6783. 8365760. 0015FINANCIAL0.0011980. 0020080. 5968610. 5590C-27. 9937531.67151-0. 8838780. 3899Mean dependentR-squared0. 997561 varS D dependent207.0733Adjusted R-squared0. 996951 var183. 5485Akaike infoS E of regression10.13435 criterion7. 673994Sum squared resid164

7、3. 280Schwarz criterion7. 922690Log likelihood-75. 57694F-statistic1636. 137Prob(FstatisticDurbin-Watson stat1. 169171 )0. 000000CNDB二-0. 0644JXDB+0. 2144ANDB+10077. 45CGDP+0. 0012FINANCIAL-27. 9938Bl=-O. 0644 B2=0. 2144 B3=10077. 45 B4=0. 0012根据回归结果表明，中国的国防预算每提高一个单位，日本的国防 预算就下降0. 0644个单位，t值约为-1. 37

8、42,美国的国防预算上升0.2144个单位，t值约为2.6146, GDP上升10077. 45个单位，t值 约为3. 8366,财政收入上升0. 0012个单位，t值约为0. 5969。截距 项的系数C也是高度显著的，而且他们所对应的p值都是小于0. 5 的，拒绝原假设，中国的国防预算与这几个因素是有关系的。R2 约为0. 9976,表明这些因素解释了中国国防预算99. 76%的变异，R 2的值相当高。检验1.异方差检验e2lne2-0. 555710. 308817-1. 175010. 1744810. 030444-3. 491887. 31690253. 537053. 980374

9、2.1278534.5277571.510227-0. 334780. 11208-2.18855-1.677192.8129511. 034234-2. 810727. 9001682.066884-7. 0958750.351373. 919026-11. 7624138.35394. 929815-6. 9443948.224543. 8758684.43289119.650522. 9781043. 24946310. 559012. 3569810.46116109. 43584. 69533816. 2739264. 83975. 5791257. 90156162. 434664

10、.134121-0. 901640. 812955-0. 20708-13. 397179.47925.190059-3. 060139.3644222.236918-10. 6676113. 79754.734421-12. 802163. 89225. 09920920. 07124402. 85485. 998576重新设计模型为ln2二 BllnJNDB+u二 B21nANDB+u2二 B31nCGDP+uln2二 B41nFINAXCIAL+u 进行回归ln2二 BllnJNDB+uDependent Variable: LNE2Method: Least SquaresDate:

11、12/07/12 Time: 21:19Sample: 1989 2009Included observations: 21LNE2=C(1 )+C(2)* LO G(LN JND B)CoefficientStd. Errort-StatisticProb.c(1)-44.5076820.66851-2.1534050.0443C(2)7.8560893.4365102.2860660.0339R-squared0.215722Mean dependent var2.726513Adjusted R-squared0.174444S.D. dependent var2.659638S.巳 o

12、f regression2.416560Aka ike info criterion4.692952Sum squared resid110.9646Schwarz criterion4.792430Log likelihood-47.27599Durbin-Watson stat1.697343lne2= B21nANDB+uDependent Variable: LNE2Method: Least SquaresDate: 12/07/12 Time: 21:22Sample: 1989 2009Included observations: 21LNE2=C(1)+C(2rLOG(LNAN

13、DB)CoefficientStd. Error t-StatisticProb.C(1)-147299410.66277-1.3814370.1832c2.9775271.8162501.6393820.1176R-squared0.123922Mean dependent var2.726613Adjusted R-squared0.077813S.D. dependont var2.659638S E. of regression2.554066Aka ike info criterion4.803643Sum squared resid123.9418Schwarz criterion

14、4.903121Log likelihood-48.43825Durbin-Watson stat1.439324ln2二 B31nCGDP+uDependent Variable: LNE2Method: Least SquaresDate: 12/07/12 Time: 21:26Sample: 1989 2009Included observations: 21LNE2=C(1)+C(2)rLOG(LNCGDP)Coefficie ntStd. Error t-StatisticProb.c(1)12.070512.8053114.3027360.0004%)2.1012810.6219

15、183.3787110.0032R-squared0.375322Mean dependent var2.726513Adjusted R-squared0.342445S.D. dependent var2.659638S E. of regression2.156695Aka ike info criterion4.465424Sum squared resid88.37533Schwarz criterion4.564902Log likelihood-44.88696Durbin-Watson stat1.953608ln2二 B41nFINAXCIAL+uDependent Vari

16、able: LNE2Method: Least SquaresDate: 12/7/12 Time: 21:28Sample: 1989 2009Included observations: 21LN E2=C(1 + C(2fLO G(LNFINANCIAL)CoefficientStd. Errort-StatisticProb.c(1)-12.330314.345815-2.8372830.0105C1.6015230.4595893.4846860.0025R-squared0.389912Mean dependent var2.726513Adjusted R-squared0.35

17、7802S.D. dependent var2.669638S.E. of regression2.131361Akaike info criterion4.441792Sum squared resid86.31132Schwarz criterion4.641270Log likelihood-44.63881Durbin-Watson stat1.969447这几个变量的系数都很显著，因此帕克检验表明，回归模型存在异方差。2.自相关检验显著水平设定0. 05Correlogram of CNDBDate: 12/07/12 Time: 21:49Sample: 1989 2009Incl

18、uded observations: 21AC PAC Q-Stat ProbAutocorrelation Partial CorrelationSI10.5010.5016.0533O.OU20.2860.0478.13380.01730.2100.0669.31510.02540.1720.04710.1560.03850.1490.03910.8300.05560.1270.02411.3610.07870.1040.01311.7260 11080.0790.00011.9560.16390.050-0.01412.0540.210100.016-0.02812.0660.28111

19、0.000 -0.01412.0660.359120.000-0.00012.0660.440由得到的数据表明概率大于显著水平，不存在自相关。3.共线性检测Viwwprou|Object| Print|NaonlSample |Sheet| Stats| Spec|Pairv/ise Correlation MatrixCNDBJNDBANDBCGDPFINANCIALCNDB1.0000000.4690910.9724500.9970360.997437JNDB04690911.0000000.3939060.5022740.482311ANDB0.9724500.3939061.00000

20、00.9596900.970197CGDP0.9970360.5022740.9595901.0000000.997266FINANCIAL0.9974370.4823110.9701970.9972661.000000Itrr发现CNDB与ANDB, CGDP, FINANCIAL的相关系数都在0. 9以上，所以认为存在共线性。所以分别做 CNDB 与 JNDF, ANDB, CGDP, FINANCIAL 的回归CNDB 与 JXDFDependent Variable: CNDBMethod: Least SquaresDate: 12/10/12 Time: 20:USample: 1

21、989 2009Included obsep/ations: 21VariableCoefficientStd. Error t-StatisticProb.JNDB1.4301920.6177242.3152690.0319C-383.6823267.7256-1.4887240.1530R-squared0.220046Mean dependent var207.0733Adjusted R-squared0.178996S.D. dependent var183.5485S.E. of regression166.3119Akaike info criterion13.15600Sum

22、squared resid525533.6Schwarz citerion13.26548Log likelihood-136.1380F-statistic5.360423Durbin-Watson stat0.152206Prob(F-statistic0.031937CNDB二1. 4302JNDF-383. 6823匸2二022 D. W二0. 15(2. 12) (-1. 49)CNDB 与 ANDBDependent Variable: CNDBMethod: Least SquaresDate: 12/10/12 Time: 20:18Sample: 1989 2009Inclu

23、ded observations: 21VariableCoefficientStd. Errort-StatisticPob.ANDB1.3615660.07487918.183580.0000C-296.816629.32032-10.123240.0000R-squared0.945659Mean dependent var207.0733Adjusted R-squared0.942799S.D. dependent var183.5485S.E. of regression43.89889Akaike info criterion10.49205Sum squared resid36

24、615.15Schwarz criterion10.59153Log likelihood 108.1666F-statistic330.6427Durbin-Watson stat0.414831Prob(F-statistic)0.000000CXDB二1. 3616ANDB-296. 8166(18. 18) (-10. 12)才2二095 D. W二0. 41CNDB 与 CGDPDependent Variable: CNDBMethod: Least SquaresDate: 12/11/12 Time: 20:19Sample: 1989 2009Included observa

25、tions: 21VariableCoefficientStd. Error t-StatisticProb.CGDP13739.06243.220556.488110.0000C-9.2842234.96647348693800.0771R-squared0.994081Mean dependent var207.0733Adjusted R-squared0.993769S.D. dependent var183.5485S.匚.ofegeession14.48837Akaike info criterion8.274963Sum squared resid3988.346Schwarz

26、criterion8.374441Log likelihood84.88711F-statistic3190.907Dubin-Watson stat0721788Prob(F-statistic)0.000000CNDB二13739. 06CGDP-9. 2842(56. 49) (-1.87)R“2二0.99 D. W=0. 72CXDB 与 FINANCIALDependent Variable: CNDBMethod: Least SquaresDate: 12/10/12 Time: 20:21Sample: 1989 2009Included observations: 21Var

27、iableCoefficientStd. Error t-StatisticProb.FINANCIAL0.0092150.00016260.770120.0000C25.498674.1918116.0829720.0000R.-squared0.994881Mean dependent var207.0733Adjusted R-squared0.994612S D dependent var183.6485S.E. of regression13.47291Akaike info criterion8.129632Sum squared resid3448.866Schwarz crit

28、erion&229110Log likelihood-83.36113F-statistic3693.008Durbin-Watson stat1.006038Prob(F-statistic0.000000CXDB二0. 0092FINANCIAL+25. 4987(60. 77) (6. 08)甘2二0 99 D. W=l. 01由上而的结果看来CNDB受到FINANCIAL的影响最大，所以后 而慢慢放因素进去。CXDB二 B1JXDB+ B2FINANCIALDependent Variable: CNDBMethod: Least SquaresDate: 12/10/12 Time:

29、 20:4CSample: 1989 2009Included observations: 21VariableCoefficientStd. Errort-StatisticProb.JNDB-0.076130.057608-0.82649704193FINANCIAL0.0092840.00017553.187450.0000C43.7944222.536511.9432650.0678R-squared0.995069Mean dependent var207.0733Adjusted R-squared0.994521S.D. depend。nt var183.5485S.E. of

30、regression13.68669Akaike info criterion8.187622Sum squared resid3322.768Schwar2 criterion8.336840Log likelihood82.97003F-statistic1816.047Durbin-Watson stat1.121114Prob(F-statistic)0.000000CXDB二 B1JXDB+B2ANDB+B3FINANCIALVariableCoefficientStd. Errort-StatisticProb.JNDB-0.0271780.061632-0.4409750.664

31、8ANDB0.0972740.1023190.9506960.3551FINANCIAL0.0086320.00070812.185230.0000C12.2131340.176260.30398907648R-squared0.995318Mean dependent var207.0733Adjusted R-squared0.994491S.D. dependentvar183.5486S.E. of regression13.62314Akaike info criterion8.231059Sum squared r&sid3155.027Schwarz criterion8.430

32、016Log likelihood-82.42612F-statistic1204.531Durbin-Watson stat1.019860Prob(F-statistic)0.000000CXDB二 B1JXDB+B2 CGDP +B3FINANCIALDependent Variable: CNDBMethod: Least SquaresDate: 12/10/12 Time: 20:44Sample: 1989 2009Included obser/ations: 21VariableCoefficientStd Errort-StatisticProb.JNDB-0.0937570

33、.052734-1.7779270.0933CGDP7520.1992825.4412.6616020.0164FINANCIAL0.0043240.0018702.3124020.0335C42.1757119.492562.1636820.0450R-squared0.996519Mean dependent var207.0733Adjusted R-squared0.995905S.D. dependent var183.5485S.E. ofegression1174585Akaike info criterion7.934521Sum squared resid2345.406Schwarz criterion8.133477Log