影響豬肉價(jià)格的因素分析復(fù)習(xí)課程

1、影響豬肉價(jià)格的因素分析影響豬肉價(jià)格的因素分析1 研究問題的背景在當(dāng)前通貨膨脹日益嚴(yán)重的情況下，各種物價(jià)飛漲，給人 們的日常生活帶來了極大地影響，生活中一些必需的物質(zhì)也在 漲，蔬菜肉的價(jià)格節(jié)節(jié)攀升，因此我覺得有必要研究一下究竟 是什么因素在影響著這些必需品的價(jià)格，從而控制這些因素的 上漲，使必需品的價(jià)格維持在一個(gè)比較穩(wěn)定的水平上。2 研究的主要內(nèi)容這里我選取了對(duì)人們生活影響較大的豬肉的價(jià)格，從城鎮(zhèn) 居民收入，豬的供給量，飼料價(jià)格，替代品雞蛋的價(jià)格，豬肉 供給量五個(gè)方面來研究，看看它們相不相關(guān)，是正相關(guān)還是負(fù) 相關(guān)，有多大的影響程度，從而調(diào)節(jié)這些變量使豬肉的價(jià)格比 較穩(wěn)定，對(duì)人們的生活產(chǎn)生較小的影

2、響。關(guān)鍵詞：豬肉價(jià)格3 選取數(shù)據(jù)年 豬肉價(jià) 城鎮(zhèn)居 飼料價(jià) 雞蛋價(jià) 豬肉供 份 格民收入 格格給量199610.54838.91.57.83158199712.25160.31.566.23596.3199810.15425.11.495.53883.719997.558541.25.24005.6200010.10262801.47255.093966200110.656859.61.3945.34051.7200210.237702.81.5225.394123.1200310.748472.21.65.254238.6200413.769421.61.696.394341200513.1

3、9104931.85256.574555.3200612.1311759.51.8686.224650.5200718.8113785.52.137.764287.8200823.4915780.82.627.844620.54建立模型將以上數(shù)據(jù)導(dǎo)入eviews,就可以建立以下equation其中y代表豬肉價(jià)格，x1表示城鎮(zhèn)居民收入，x2代表飼料價(jià) 格，x3代表雞蛋價(jià)格，x4表示豬肉的供給量.Depe ndent Variable: YMethod: Least SquaresDate: 12/18/10 Time: 14:25Sample: 1996 2008In eluded observ

4、ati ons: 13VariableCoeffieie ntStd. Errort-StatistieProb.C9.15743513.677330.6695340.5220X10.0004980.0005410.9196120.3847X210.258233.1922473.2134820.0124X3-0.4803610.861324-0.5577010.5923X4-0.0036890.002947-1.2515900.2461R-squared0.946997Mean depe ndent var12.56938Adjusted R-squared0.920496S.D. depen

5、dent var4.232883S.E. of regressi on1.193522Akaike info eriteri on3.475417Sum squared resid11.39596Schwarz eriteri on3.692706Log likelihood-17.59021F-statistie35.73401Durb in -Watson stat2.510756Prob(F-statistie)0.000038表中除x2夕卜，概率均大于0.05,說明其對(duì)y的影響不顯著，必須對(duì)其進(jìn)行修正，使其對(duì) y的影響顯著。經(jīng)修正的結(jié)果如下：Depe ndent Variable: Y

6、Method: Least SquaresDate: 12/18/10 Time: 13:42Sample (adjusted): 1997 2008In eluded observati ons: 12 after adjustme ntsVariableCoeffieie ntStd. Errort-StatistieProb.C26.351905.2969214.9749460.0016D(X1)0.0039440.0016512.3881830.0483LOG(X2)14.449493.6619583.9458360.0056D(X3)1.4456990.5840702.4752130

7、.0425X4(-1)-0.0060370.001353-4.4634710.0029R-squared0.973597Mean depe ndent var12.74183Adjusted R-squared0.958510S.D. dependent var4.373145S.E. of regressi on0.890771Akaike info criteri on2.900878Sum squared resid5.554310Schwarz criteri on3.102922Log likelihood-12.40527F-statistic64.53091Durb in -Wa

8、tson stat1.689968Prob(F-statistic)0.000013從表中可以看出，t檢驗(yàn)的概率均小于0.05,此時(shí)的變量對(duì)y的 影響是顯著的，此模型才是可以用的。還可以看出F檢驗(yàn)的值也較大，所以拒絕原假設(shè)，總體的顯著性成立。可以得到下列模型：Estimati on Comma nd:LS Y C D(X1) LOG(X2) D(X3) X4(-1)Estimati on Equati on:Y = C(1) + C(2) *D(X1) + C(3) *LOG(X2) + C( 4)*D(X3) + C(5)*X4(-1)Substituted Coefficie nts:Y

9、= 26.35189582 + 0.003943975368*D(X1) + 14.44948848*LOG(X2) + 1.44569861*D(X3)-0.006037331562*X4(-1)5異方差檢驗(yàn)(懷特檢驗(yàn))原假設(shè)HO:殘差項(xiàng)不存在異方差備擇假設(shè)H1:殘差項(xiàng)存在異方差White Heteroskedasticity Test:F-statistic0.975116Probability0.568784Obs*R-squared8.666952Probability0.371165Test Equati on:Depe ndent Variable: RESIDA2Method:

10、Least SquaresDate: 12/18/10 Time: 14:44Sample: 1997 2008In eluded observati ons: 12VariableCoefficie ntStd. Errort-StatisticProb.C9.59299477.996970.1229920.9099D(X1)0.0023160.0021471.0788210.3597(D(X1)F22.08E-078.06E-070.2584460.8128LOG(X2)1.6597335.6856470.2919160.7894(LOG(X2)A2-4.5993656.490699-0.

11、7086090.5297D(X3)0.2440161.1780230.2071400.8492(D(X3)A2-0.6373930.997492-0.6389950.5683X4(-1)-0.0023800.037570-0.0633530.9535X4(-1)A2-5.31E-084.56E-06-0.0116440.9914R-squared0.722246Mean depe ndent var0.462859Adjusted R-squared-0.018431S.D. dependent var0.471484S.E. of regressi on0.475809Akaike info

12、 criteri on1.466105Sum squared resid0.679182Schwarz criteri on1.829785Log likelihood0.203370F-statistic0.975116Durb in -Watson stat2.734176Prob(F-statistic)0.568784從表中可以看出懷特檢驗(yàn)的概率均大于0.05,所以接受原假設(shè)，說明殘差項(xiàng)不存在異方差。6自相關(guān)檢驗(yàn)（LM僉驗(yàn)）Breusch-Godfrey Serial Correlation LM Test:F-statistic0.263214Probability0.778599O

13、bs*R-squared1.143077Probability0.564656Test Equati on:Depe ndent Variable: RESIDMethod: Least SquaresDate: 12/18/10 Time: 14:47Presample miss ing value lagged residuals set to zero.VariableCoefficie ntStd. Errort-StatisticProb.C-0.4681376.037956-0.0775320.9412D(X1)0.0002890.0019010.1522180.8850LOG(X

14、2)-0.7251874.286532-0.1691780.8723D(X3)-0.2234790.730846-0.3057810.7721X4(-1)0.0001390.0015390.0906470.9313RESID(-1)0.1161500.5420630.2142740.8388RESID(-2)-0.4161950.575909-0.7226750.5023R-squared0.095256Mean depe ndent var-2.09E-15Adjusted R-squared-0.990436S.D. dependent var0.710589S.E. of regress

15、i on1.002519Akaike info criteri on3.134108Sum squared resid5.025226Schwarz criteri on3.416970Log likelihood-11.80465F-statistic0.087738Durb in -Watson stat1.851760Prob(F-statistic)0.994924從表中可以看出，檢驗(yàn)之后的概率均大于0.05,接受原假設(shè)，說明殘差之間不存在二階自相關(guān)，通過了 LM僉驗(yàn)。7正態(tài)分布檢驗(yàn)54 -3 -21Series: ResidualsSample 1997 2008Observatio

16、 ns12Mea n-2.09e-15Media n-0.286222Maximum1.122528Minimum-1.185263Std. Dev.0.710589Skew ness0.214591Kurtosis1.951146Jarque-Bera0.642146Probability0.725370-1.5-1.0-0.50.00.51.01.5從表中可以看出JB統(tǒng)計(jì)量的概率為0.725370,說明殘差有百分之72.5370的概率是正態(tài)分布，大于 0.05,通過了正態(tài)分布檢驗(yàn)。8白噪聲檢驗(yàn)Date: 12/18/10 Time: 15:00Sample: 1997 2008In elu

17、ded observati ons: 12Autocorrelati onPartial Correlati onACPAC Q-Stat Prob|* . |.|* . |10.1450.1450.32050.571*| . |.*1 . |2-0.213-0.2391.08060.583*| . |.*| . |3-0.243-0.1842.18230.535| . |.| . |4-0.040-0.0272.21610.696|* . |.| . |50.1200.0442.56210.767| . |.*| . |60.000-0.0892.56210.861| . |.| . |70

18、.0000.0342.56210.922| . |.| . |80.0000.0122.56210.959| . |.| . |90.000-0.0102.56210.979| . |.| . |100.0000.0002.56210.990從圖中可以看出，其自相關(guān)系數(shù)和偏自相關(guān)系數(shù)均落在二倍的標(biāo)注差以內(nèi)，說明其波動(dòng)性較小，且在幾階之后趨近于0，說明從長期來看，其是不相干的，屬于白噪聲。9偽回歸檢驗(yàn)Null Hypothesis: E1 has a un it rootExoge no us: NoneLag Len gth: 0 (Automatic based on SIC, MAXLAG

19、=2)t-StatisticProb.*Augme nted Dickey-Fuller test statistic-2.7565690.0107Test critical values:1% level-2.7921545% level-1.97773810% level-1.602074*MacKinnon (1996) one-sided p-values.Warning: Probabilities and critical values calculated for 20observati ons and may not be accurate for a sample size

20、of 11Augme nted Dickey-Fuller Test Equati onDependent Variable: D(E1)Method: Least SquaresDate: 12/18/10 Time: 15:11Sample (adjusted): 1998 2008In cluded observati ons: 11 after adjustme ntsVariableCoefficie ntStd. Errort-StatisticProb.E1(-1)-0.9714940.352429-2.7565690.0202R-squared0.417541Mean depe

21、 ndent var0.144408Adjusted R-squared0.417541S.D. dependent var0.956933S.E. of regressi onSum squared residLog likelihood0.730322 Akaike info criterion5.333700 Schwarz criterio n-11.62715 Durbi n-Watson stat從表中可以看出，其概率為 0.0107小于0.05,所以不存在偽回 歸，通過了檢驗(yàn)。9模型平穩(wěn)性和預(yù)測(cè)性檢驗(yàn)Recursive Residuals ±2 S.E.從圖中可以看出，

22、模型的穩(wěn)定性一直很好，始終在紅線的范圍 內(nèi)。CUSUM 5% Significanee從圖中可以看出，模型的預(yù)測(cè)能力較強(qiáng)，穩(wěn)定性也較強(qiáng)，符合 我們所需要的模型。CUSUM of Squares5% Sig nificanceOne-Step Probability Recursive Residuals從圖中可以看出，該模型的一步預(yù)測(cè)能力較好，因?yàn)樗{(lán)線一直 在紅線內(nèi)，處在預(yù)測(cè)能力之內(nèi)。* N-Step Probability Recursive Residuals從圖中可以看出，其 N步預(yù)測(cè)能力較好，藍(lán)線一直處在紅線之Recursive C(1) Estimates.±2 S.E.

23、Recursive C(2) Estimates±2 S.E.Recursive C(3) Estimates ±2 S.E.Recursive C(4) Estimates ±2 S.E.Recursive C(5) Estimates ±2 S.E.圖中的紅線代表預(yù)測(cè)能力，藍(lán)線處在兩條紅線之內(nèi)則代表穩(wěn)定 性較強(qiáng)，在預(yù)測(cè)期內(nèi)結(jié)構(gòu)未發(fā)生改變，說明該模型的預(yù)測(cè)能力 和穩(wěn)定性較好。10參數(shù)約束檢驗(yàn)(1) 約束條件：c(1)=0Wald Test:Equatio n: EQUATI0N2Test StatisticValuedfProbabilityF-sta

24、tistic24.75008Chi-square24.75008(1, 7)10.00160.0000Null Hypothesis Summary:Normalized Restriction (= 0)ValueStd. Err.C(1)26.351905.296921Restrictons are linear in coefficients.從表中可以看出，其概率小于0.05，所以拒絕原假設(shè)，說明參數(shù)c(1)=0不成立。(2) 約束條件：c(2)=0Wald Test:Equatio n: EQUATION2Test StatisticValuedfProbabilityF-stati

25、stic5.703420Chi-square5.703420(1, 7)10.04830.0169Null Hypothesis Summary:Normalized Restriction (= 0)ValueStd. Err.C(2)0.0039440.001651Restrictions are linear in coefficients.從表中可以看出，其概率小于 0.05，所以拒絕原假設(shè)，說明參數(shù)c(2)=0不成立。(3) 約束條件：c(3)=0Wald Test:Equatio n: EQUATI0N2Test Statistic0ValuedfProbabilityF-stat

26、istic15.56962(1, 7)0.0056Chi-square15.5696210.0001Null Hypothesis Summary:Normalized Restriction (= 0)ValueStd. Err.C(3)14.449493.661958Restrictons are linear in coefficients.從表中可以看出，其概率小于 0.05，所以拒絕原假設(shè)，說明參數(shù)c(3)=0不成立。(4) 約束條件：c(4)=0Wald Test:Equatio n: EQUATION2Test StatisticValuedfProbabilityF-stati

27、stic6.126678Chi-square6.126678(1, 7)10.04250.0133Null Hypothesis Summary:Normalized Restriction (= 0)ValueStd. Err.54)1.4456990.584070Restrictions are linear in coefficients.從表中可以看出，其概率小于0.05,所以拒絕原假設(shè)，說明參數(shù)c(4)=0不成立。(5) 約束條件：c(5)=0Wald Test:Equatio n: EQUATI0N2Test StatisticValuedfProbabilityF-statist

28、ic19.92258(1, 7)0.0029Chi-square19.9225810.0000Null Hypothesis Summary:Normalized Restriction (= 0)ValueStd. Err.C(5)-0.0060370.001353Restrictons are linear in coefficients.從表中可以看出，其概率小于0.05,所以拒絕原假設(shè)，說明參數(shù)c(5)=0不成立。11殘差圖檢驗(yàn)2420161284Residual Actual Fitted從圖中可以看出，回歸方程擬合的較好，殘差的波動(dòng)性不大， 模型較穩(wěn)定，預(yù)測(cè)能力比較強(qiáng)。12預(yù)測(cè)圖檢

29、驗(yàn)Forecast: YFActual: YForecast sample: 1996 2008 Adjusted sample: 1997 2008 In cluded observati ons: 12Root Mean Squared Error0.680338Mean Absolute Error0.587076Mea n Abs. Perce nt Error5.016306Theil In equality Coefficie nt0.025379Bias Proporti on0.000000Varia nee Proporti on0.006689Covaria nee Proporti on0.993311從圖中可以看出，藍(lán)線一直處在兩條紅線之內(nèi)，說明其預(yù)測(cè)的水平較好，一直處在預(yù)測(cè)能力之內(nèi)。13經(jīng)濟(jì)意義的檢驗(yàn)Estimati on Comma nd:LS Y C D(X1) LOG(X2) D(X3) X4(-1)Estimati on Equati on:Y = C(1) + C(2) *D