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1、多元时间序列理论之面板数据案例一、问题的提出在进行经济分析时经常会遇到时间序列和横截面两者相结合的数据。例如，在企业投资需求分析中，我们会遇到多个企业的若干指标的阅读或极度时间序列；在城镇居民消费分析中，我们会遇到不同省市地区的反映居民消费和居民收入的年度时间序列。这种具有三维（个体、时间、指标）信息的数据结构称为时间序列/截面数据。时间序列/截面数据中，往往横截面中观测值个数相对较少，而依时期序列的观测值较多。例如1999-2001年25个主要城市每日天气情况（包括降水量、湿度、平均气温）的数据；西方七国1960-1990年各月经济总量指标等。这些数据时间跨度往往很长，因此可以在随机过程的背
2、景中研究扰动项，侧重于时间序列分析。另一种截面时间序列数据则具有相反的数据，即横截面包含很多的观测值，但依时间序列的观测值相对很少。典型的例子是对全国数十万家庭进行为期10年的年收入调查。此类数据被称为面板（panel）数据。它们通常是宽而短的，更适用于横截面分析。二、方法选择研究面板数据的第一步是确定模型的形式（变截距或变斜率），广泛使用的检验是协方差分析检验。如果是变截距模型，则使用SAS软件的Hausman检验是采用随机影响模型还是固定影响模型。模型的估计采用SAS软件的FGLS方法。三、统计指标和数据收集本案例的样本数据来自中国统计出版社出版的中国统计年鉴，数据年限为19912005年
3、。第一个表格是城镇每年居民可支配收入，第二个表格是城镇居民每年消费性支出。表61 19912005城镇居民可支配收入YEAR19911992199319941995199619971998北京2040.432556.123546.785084.706235.007332.017813.168472.00天津1844.982238.382769.263982.134929.535967.716608.397110.50河北1489.321872.002334.323177.293921.354442.814958.675084.60山西1410.201622.841957.482565.6733
4、05.983702.693989.924098.70内蒙古1294.681494.921893.172498.292863.033431.813944.674353.00辽宁1705.601948.942314.223062.893706.514207.234518.104617.20吉林1395.361636.971953.102561.083174.833805.534190.584206.60黑龙江1389.001630.281959.612596.903375.213768.314090.724268.50上海2486.003026.584297.335889.137191.77817
5、8.488438.898773.10江苏1622.932138.342773.773778.874634.425185.795765.206017.90浙江2143.002619.163625.995066.326221.366955.797358.727836.80安徽1485.101807.842247.943047.663795.384512.774599.274770.50福建1952.502282.822839.233672.554506.995172.936143.646485.60江西1295.401528.301918.822773.073376.513780.204071.3
6、24251.40山东1687.561974.492515.113444.424264.084890.285190.795380.10河南1249.501608.031962.752618.553299.463755.444093.624219.40湖北1592.911883.112450.253356.074028.634364.044673.154826.40湖南1783.242094.412687.803887.644699.235052.125209.745434.30广东2752.183476.704632.376367.027438.708157.818561.718839.70广西
7、1613.642103.832895.333981.094791.875033.335110.295412.20海南1848.002318.123071.633920.154770.414926.434849.934852.90四川1691.002001.292420.683310.724002.924482.704763.265127.10贵州1593.541899.632312.803220.493931.464221.244441.914565.40云南1703.202075.902652.903452.194085.114977.955558.296042.80陕西1498.00171
8、7.762101.692684.023309.683809.644001.304220.20甘肃1368.801707.782002.502658.133152.523353.943592.434009.60青海1325.15806.482127.312812.753319.853834.213999.364240.10宁夏1565.111820.702170.612985.863382.813612.123836.544112.40新疆1494.481951.902422.973170.274163.444649.864844.725000.80YEAR1999200020012002200
9、320042005北京9182.8010349.7011577.8012463.9013882.6215637.8417652.95天津7649.808140.508958.709337.6010312.9111467.1612638.55河北5365.005661.205984.806679.707239.067951.319107.09山西4342.604724.105391.106234.407005.037902.868913.91内蒙古4770.505129.105535.906051.007012.908122.999136.79辽宁4898.605357.805797.00652
10、4.507240.588007.569107.55吉林4480.004810.005340.506260.207005.177840.618690.62黑龙江4595.104912.905425.906100.606678.907470.718272.51上海10931.6011718.0012883.5013249.8014867.4916682.8218645.03江苏6538.206800.207375.108177.609262.4610481.9312318.57浙江8428.009279.2010464.7011715.6013179.5314546.3816293.77安徽506
11、4.605293.605668.806032.406778.037511.438470.68福建6859.807432.308313.109189.409999.5411175.3712321.31江西4720.605103.605506.006335.606901.427559.648619.66山东5809.006490.007101.107614.408399.919437.8010744.79河南4532.404766.305267.406245.406926.127704.908667.97湖北5212.805524.505856.006788.507321.988022.75878
12、5.94湖南5815.406218.706780.606958.607674.208617.489523.97广东9125.909761.6010415.2011137.2012380.4313627.6514769.94广西5619.505834.406665.707315.307785.048689.999286.70海南5338.305358.305838.806822.707259.257735.788123.94四川5477.905894.306360.506610.807041.877709.878385.96贵州4934.005122.205451.905944.106569.2
13、37322.058151.13云南6178.706324.606797.707240.607643.578870.889265.90陕西4654.105124.205483.706330.806806.357492.478272.02甘肃4475.204916.305382.906151.406657.247376.748086.82青海4703.405170.005853.706170.506745.327319.678057.85宁夏4472.904912.405544.206067.406530.487217.878093.64新疆5319.805644.906395.006899.60
