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1、 VAR模型的应用举例1 案例分析的目的 股市对居民储蓄存款存在分流的作用。一般来说，若股市出现牛市，资金会从存款性金融机构流向股市，居民储蓄存款下降或者增速会减缓。从当前我国经济发展趋势来看，居民储蓄存款与股市交易额均呈上升趋势。那么两者是否存在相互影响呢？本案例将分析居民储蓄与股市之间的这种联动效应。2 实验数据本实验选取从1996年到2008年4月的月度数据。整理如下。表1 股市交易额与居民存款余额 单位：亿元日期沪深股市交易总额居民储蓄存款余额日期沪深股市交易总额居民储蓄存款余额1996.1143.493230356.542002.43114.39279728.21996.263.94
2、16432026.252002.51924.59480394.31996.3217.75633296.482002.64303.07681711.791996.4873.422134018.532002.73227.30582527.91996.51163.7434622.12002.81946.36683275.971996.61812.86235457.912002.91460.39184139.051996.72718.6236048.672002.101181.98984725.131996.81685.59136705.82002.111908.61785693.491996.918
3、62.16437085.172002.121781.22886910.651996.104012.437671.422003.13060.93390677.631996.113818.9737917.262003.21666.80292824.211996.124238.9238520.82003.32120.63794567.841997.11829.17939038.182003.45848.29795194.121997.21493.92540869.122003.53209.4596351.671997.34263.841580.972003.62557.1597674.571997.
4、45127.9242112.162003.72351.91798590.91997.54640.9642295.162003.81519.42799255.581997.63080.9542771.162003.91661.203100888.61997.72415.7343312.52003.101615.799101381.91997.81858.37843914.922003.112824.502102235.41997.91625.71344139.452003.124359.423103617.71997.102081.67344720.332004.13649.76109232.7
5、1997.111586.9545068.432004.27215.755110646.41997.121570.19546279.82004.35792.181111872.21998.11716.977464832004.45270.107112175.41998.21171.90648537.542004.51823.421112610.21998.31703.31248686.482004.62627.057113792.51998.43624.4448984.62004.72548.009114253.21998.53322.3497002004.81880.649114489.619
6、98.62593.349949.892004.93978.274115458.71998.71761.80550749.822004.102893.0651160011998.81497.88250900.912004.113045.002117617.91998.92149.00851580.742004.122094.784119555.41998.101861.7952247.772005.11754.347122237.31998.112194.2452952.322005.22021.07127823.41998.121040.05853407.52005.33047.4321292
7、59.41999.11138.81954293.672005.43036.061129816.81999.2334.019656767.452005.51497.376130577.41999.31757.27757814.652005.63177.354132339.11999.42063.44558369.072005.72243.73133656.41999.52719.5958967.842005.84776.3331345051999.69562.5959173.482005.94132.053136316.31999.75538.0259147.552005.102097.6321
8、36827.11999.83665.4759187.262005.112301.058138504.31999.92705.1259364.312005.122350.0861410511999.101250.08759269.92006.13635.936148008.41999.111558.04959185.382006.23726.141151179.61999.121482.01359621.82006.34074.6251528192000.14443.45860241.82006.47308.7261534012000.26621.81962270.32006.510926.12
9、153523.42000.38877.35562492.292006.69159.456154996.92000.45960.92662536.122006.78197.536155131.92000.54298.7162195.392006.85526.955156282.12000.66251.17762842.382006.96705.497158108.92000.75436.68662841.52006.106793.858158033.42000.86650.38762861.112006.1110586.65159716.72000.93167.35963243.272006.1
10、215861.8161587.32000.102706.93163122.342007.126191.65161968.62000.115235.81863492.062007.217845.01171042.62000.123985.7964332.382007.332526.3172607.72001.13161.01666547.312007.449865.94170932.72001.22055.59167343.362007.559864.231680402001.35368.46568365.132007.655444.85169651.62001.45845.64668618.4
11、62007.733764.63169567.22001.54752.868393.542007.855638.96169171.52001.65190.08669628.582007.947008.27169038.12001.73344.07469677.772007.1035870.9163957.62001.82677.71170558.482007.1125750.72166561.12001.102147.89271818.812007.1229632.95172616.12001.122193.07173762.432008.147340.36174347.92002.12072.
12、05674953.712008.221457.51183960.22002.21341.43378114.332008.329058.96187414.92002.34917.91578728.32008.427832.14188389.14.3 VAR模型的构建4.3.1 数据平稳性检验考虑到本例中的数据是宏观经济月度数据，先消除季节性特征后再进行分析。另外数据变动趋势过大，本例还对数据进行了对数平滑处理。下图是两个变量经过季节性调整并取对数后的新序列，其中lsa表示居民储蓄额，ltr表示股市交易总额。在主窗口命令行中输入：genr lsa=log(savingsa)genr ltr=log
13、(tradingsa)图1 居民储蓄额与股市交易额对数值的对比图根据图形特征选取同时存在截距项和趋势项进行单位根检验。分别在lsa和ltr窗口中点击view/unit root test/。Lsa单位根检验的结果：Null Hypothesis: LSA has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic based on SIC, MAXLAG=13)t-StatisticProb.*Augmented Dickey-Fuller test statistic-3.2957650.0711Test critical values:1% level-4.0225865% level-3.44111110% level
