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1、-对影响通货膨胀的因素分析摘要:随着国内商品价格上涨,CPI数据的攀升,通胀已经影响到人们的生活。通过对CPI指数历年的水平和现状的研究,建立影响通货膨胀的经济模型,研究各解释变量对通货膨胀的影响程度,从而为我国避免严重的通货膨胀以确保经济的持续稳定发展提供理论依据。关键词:通货膨胀 多因素分析 模型 计量经济 检验 修正一、 问题的提出通货膨胀是指流通中的货币数量超过经济运行所需的货币数量而引起的货币贬值和价格水平全面、持续上涨的经济现象。衡量通货膨胀的常用指标有消费者价格指数(CPI) 、生产者价格指数(PPI)和GDP折算数, 其中最为常用的是消费者价格指数。所以,本文就影响CPI的因素
2、来解释影响通货膨胀的因素。影响通货膨胀的因素有很多,但由于许多因素之间相互重叠,同时为了反映影响通货膨胀的主要因素,因此,综合考虑各方面的因素,我考虑以下一些变量:1.固定资产投资总额(GDZCTZZE)。我国当前需求的增长主要由政府主导的投资拉动的,主要用于基础设施建设。我国固定资产膨胀主要又表现为一般加工业投资增长过快,这就造成投资结构向加工工业和非生产性建设倾斜,造成能源、原材料的供应和交通运输极度紧张,增加物价上涨的压力。2.货币供应量(HBGYL)。货币供应量过多,会引起货币贬值,价格水平上涨。3.国内生产总值(GDP)。GDP增长对增加对货币的需求,也会增加对货币的供给,所以会给通
3、胀埋下一些隐患。4.外汇储备(WHCB)。外债负担过重、外贸逆差过大及国际市场价格与国内市场价格相当悬殊可能引起通货膨胀。二、模型的选择和变量的设定我将CPI作为因变量,即被解释变量;将固定资产投资总额、货币供应量、国内生产总值、外汇储备作为解释变量,对模型进行回归分析。(一)收集的数据如下:CPIGDZCTZZE(亿元)HBGYL(亿)GDP(亿)WHCB(亿美元)103.1451715293.418718.3111103.45594.519349.921826.2217.12106.48080.125402.226937.3194114.713072.334879.835260211.99
4、124.117042.9446923.548108.5516.2117.120019.2660750.559810.5735.97108.322974.0376094.970142.51050.49102.82531890995.378060.81398.999.228406.17104498.583024.3145098.629854.71119897.988479.21546.75100.432917.73134610.398000.51655.74100.737213.49158310.9108068.22121.6599.243499.91185007119095.72864.0710
5、1.255566.61221222.81351744032.51103.970477.4254107159586.76099.32101.888773.6298755.7184088.68188.72101.5109998.2345603.6213131.710663.44104.8137323.9403442.2259258.915282.49105.9172828.4475166.6302853.419460.3105.222484660622533535323992(二)建立数学模型及模型的检验建立线性模型:CPI=0+1*GDZCTZZE+2*HBGYL+3*GDP+4*WHCB对模型
6、显著性的假设为: H0:1=2=3=4=0 H1:1,2,3,4不全为零1. 模型显著性检验:用EVIEWS进行回归操作,结果如下:Dependent Variable: CPIMethod: Least SquaresDate: 12/10/10 Time: 17:10Sample: 1990 2009Included observations: 20VariableCoefficientStd. Errort-StatisticProb.C102.97154.95018920.801520.0000GDZCTZZE0.0010610.0004622.2950790.0366HBGYL-0.
7、0003180.000117-2.7167180.0159GDP0.0001640.0001421.1528000.2670WHCB-0.0040190.002706-1.4850750.1582R-squared0.476580Mean dependent var105.1150Adjusted R-squared0.337001S.D. dependent var6.552723S.E. of regression5.335538Akaike info criterion6.398975Sum squared resid427.0195Schwarz criterion6.647908Lo
8、g likelihood-58.98975F-statistic3.414416Durbin-Watson stat0.693276Prob(F-statistic)0.035621Estimation Command:=LS CPI C GDZCTZZE HBGYL GDP WHCB Estimation Equation:=CPI = C(1) + C(2)*GDZCTZZE + C(3)*HBGYL + C(4)*GDP + C(5)*WHCBSubstituted Coefficients:=CPI = 102.9714588 + 0.001061271087*GDZCTZZE - 0
9、.000317535485*HBGYL + 0.0001639031138*GDP - 0.004019161098*WHCB将上述Eviews输出的回归分析表中的P-Value值与给定的显著性水平=0.05进行比较。C、固定资产投资总额、货币供应量的P-Value值0.05,说明这三个解释变量对CPI的影响是显著的,而另外两个不显著。因此,我对估计量进行修正,结果如下:Dependent Variable: CPIMethod: Least SquaresDate: 12/10/10 Time: 17:13Sample: 1990 2009Included observations: 20V
10、ariableCoefficientStd. Errort-StatisticProb.C103.61804.67236322.176780.0000GDZCTZZE0.0017180.0005792.9655030.0102HBGYL-0.0003960.000119-3.3244060.0050GDP2.64E-050.0001560.1692540.8680WHCB-0.0040680.002546-1.5977160.1324WHCB2-9.63E-085.61E-08-1.7166780.1081R-squared0.567600Mean dependent var105.1150A
11、djusted R-squared0.413171S.D. dependent var6.552723S.E. of regression5.019699Akaike info criterion6.307942Sum squared resid352.7633Schwarz criterion6.606662Log likelihood-57.07942F-statistic3.675480Durbin-Watson stat0.957758Prob(F-statistic)0.024718Estimation Command:=LS CPI C GDZCTZZE HBGYL GDP WHC
12、B WHCB2Estimation Equation:=CPI = C(1) + C(2)*GDZCTZZE + C(3)*HBGYL + C(4)*GDP + C(5)*WHCB + C(6)*WHCB2Substituted Coefficients:=CPI = 103.6179755 + 0.001718217201*GDZCTZZE - 0.0003955515982*HBGYL + 2.638904124e-005*GDP - 0.004068304053*WHCB - 9.630845615e-008*WHCB2结果显示对被解释的影响还是不显著,继续修正:Dependent Va
13、riable: CPIMethod: Least SquaresDate: 12/10/10 Time: 17:22Sample (adjusted): 1991 2009Included observations: 19 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.C101.56914.63787021.899950.0000GDZCTZZE0.0020470.0004764.3013860.0009HBGYL-0.0003969.76E-05-4.0608600.0013GDP2.94E-050.0001180.2490860.8072