影响四川省房地产业发展的因素分析.doc

影响四川省房地产业发展的因素分析 “民以食为天，以住为地”，房地产在国民经济生活中起着重要的作用.房地产业的发展对国民经济发展有着巨大而深刻的影响.因此，审慎分析房地产市场的现状及其基本走势,深入探讨影响房地产业发展的主要因素，对促进房地产业事业持续重要. 一、对房地产市场的基本判断 年间，我国房地产投资连续四年增幅在以上，年房地产投资增长率高达，投资规模首次突破万亿元，占全社会固定资产投资的占的。 在投资规模不断增长的同时，商品房的销售率也在稳步上涨。然而，在总体看好的情况下，局部地区投资增长过快、供求结构失衡的问题仍十分突出。除区域性问题外，投资结构也不容忽视。近几年，全国普通住宅销售率连续四年在以上，且不断走高，但高档住宅、经济适用房、办公楼宇和商厦的销售率却都比较低，导致办公楼和商厦的大量闲置。简言之，此轮房地产投资热，有合理的因素，如中国经济的高速增长、城市化进程的加快、居民收入水平的提高、消费的升级换代、大量外资的进入和劳动力的流动形成的市场有效需求等，但是，政府人为造市、无视地区市场环境的盲目大干快上，导致奢靡之风、非理性投资泛滥，由此引发的投资热和结构失衡，对房地产业来说则是贻害长远。 二、选定变量进行计量经济学的分析我们选定四川省房地产开发总值(单位:亿元)作为被解释变量,同时一共选定了八个解释变量:1四川省每年税收总额(单位:万元)2四川省每年储蓄存款总额(单位:亿元)3四川省建筑材料工业品出厂价格指数(单位:)4四川省原材料燃料和动力购进价格指数(建筑材料类)(单位:)5四川省每人每年可支配收入(单位:元)6四川省(单位:亿元)7货币供应量(单位:亿元)8贷款利率(3年-5年期)(单位:)年份yx1x2x3x4x5x6x7x819005.18 256513 698.15101.21001862.36890.9515293.411.7%19916.09 323350 813.4796.4118.22132.561016.3119349.911.7%199214.19486213904.6892.4139.32988.211177.2725402.211.7%199334.87658821988.1787.2168.53422.171486.0834879.811.7%199450.578694511024.2198.5215.13846.222001.4146923.511.7%199579.9610520131148.59103.7273.34002.912504.9560750.511.7%199690.6212984071521.97140.5294.44406.092985.1576094.911.7%1997100.2615257921841.2297.0354.64763.263320.1190995.39.9%1998120.6016602861984.5495.3417.25127.083580.26104498.57.65%1999142.5017789792351.2194.0417.25477.893711.61119897.96.03%2000195.9719463192693.1794.7444.75894.274010.25134610.36.03%2001268.1521814663123.3997.3470.76360.474421.76158301.96.03%构造模型: （数据见下页）0+11+22+33+44+55+66+77+88对数据进行分析:dependent variable: ymethod: least squaresdate: 12/22/04 time: 16:40sample: 1990 2002included observations: 13variablecoefficientstd. errort-statisticprob. c9.50619061.473400.1546390.8846x1-0.0001080.000146-0.7371200.5019x2-1.32e-061.34e-06-0.9817610.3818x30.5152790.8940200.5763620.5952x4-1.0198000.958646-1.0637930.3474x5-0.0194620.037130-0.5241620.6279x6-0.1540270.062463-2.4659140.0692x70.0079940.0011546.9251130.0023x89.8308403.2403013.0339290.0386r-squared0.995226 mean dependent var115.8538adjusted r-squared0.985677 s.d. dependent var114.4145s.e. of regression13.69309 akaike info criterion8.277619sum squared resid750.0024 schwarz criterion8.668738log likelihood-44.80453 f-statistic104.2251durbin-watson stat3.388729 prob(f-statistic)0.000226对数据的多重共线性进行分析:x1x2x3x4x5x6x7x8x1 1.000000 0.992449-0.490698-0.579667 0.926422 0.942814 0.985242-0.808622x2 0.992449 1.000000-0.482882-0.568568 0.920679 0.932850 0.975851-0.819597x3-0.490698-0.482882 1.000000 0.900281-0.486587-0.511065-0.489324 0.424923x4-0.579667-0.568568 0.900281 1.000000-0.638015-0.648189-0.604672 0.455466x5 0.926422 0.920679-0.486587-0.638015 1.000000 0.995972 0.969636-0.620918x6 0.942814 0.932850-0.511065-0.648189 0.995972 1.000000 0.981303-0.655603x7 0.985242 0.975851-0.489324-0.604672 0.969636 0.981303 1.000000-0.749205x8-0.808622-0.819597 0.424923 0.455466-0.620918-0.655603-0.749205 1.000000可见解释变量间存在多重共线性,对此我们进行修正,采用逐步回归：y与x7的拟合效果最好dependent variable: ymethod: least squaresdate: 12/22/04 time: 16:54sample: 1990 2002included observations: 13variablecoefficientstd. errort-statisticprob. c-47.5999617.42865-2.7311330.0195x70.0019820.00017811.158270.0000r-squared0.918823 mean dependent var115.8538adjusted r-squared0.911444 s.d. dependent var114.4145s.e. of regression34.04795 akaike info criterion10.03406sum squared resid12751.89 schwarz criterion10.12097log likelihood-63.22136 f-statistic124.5069durbin-watson stat0.631549 prob(f-statistic)0.000000将其余变量逐一引入的如下几个模型:引入6:dependent variable: ymethod: least squaresdate: 12/22/04 time: 17:01sample: 1990 2002included observations: 13variablecoefficientstd. errort-statisticprob. c24.2790625.195100.9636420.3579x6-0.0907270.027503-3.2987890.0080x70.0041510.0006706.1961140.0001r-squared0.961126 mean dependent var115.8538adjusted r-squared0.953351 s.d. dependent var114.4145s.e. of regression24.71162 akaike info criterion9.451598sum squared resid6106.641 schwarz criterion9.581971log likelihood-58.43539 f-statistic123.6208durbin-watson stat0.917644 prob(f-statistic)0.0000006通过检验,引入：dependent variable: ymethod: least squaresdate: 12/22/04 time: 17:05sample: 1990 2002included observations: 13variablecoefficientstd. errort-statisticprob. c-80.2639534.93053-2.2978160.0472x6-0.1432060.024342-5.8829980.0002x70.0058510.0006768.6556460.0000x811.172183.2356693.4528190.0072r-squared0.983278 mean dependent var115.8538adjusted r-squared0.977703 s.d. dependent var114.4145s.e. of regression17.08441 akaike info criterion8.761870sum squared resid2626.894 schwarz criterion8.935700log likelihood-52.95215 f-statistic176.3999durbin-watson stat1.513796 prob(f-statistic)0.0000008通过检验,引入2:dependent variable: ymethod: least squaresdate: 12/22/04 time: 17:07sample: 1990 2002included observations: 13variablecoefficientstd. errort-statisticprob. c-50.8081526.01905-1.9527290.0866x2-2.24e-066.92e-07-3.2373780.0119x6-0.1627520.018028-9.0275450.0000x70.0074020.00067311.007200.0000x88.1099102.4481403.3126830.0107r-squared0.992761 mean dependent var115.8538adjusted r-squared0.989142 s.d. dependent var114.4145s.e. of regression11.92238 akaike info criterion8.078435sum squared resid1137.146 schwarz criterion8.295723log likelihood-47.50983 f-statistic274.2850durbin-watson stat2.434411 prob(f-statistic)0.0000002通过各项检验,而其他变量未能通过各项检验,以上变量模型拟合度良好:利用arch检验是否存在异方差arch test:f-statistic0.444405 probability0.730040obs*r-squared1.818050 probability0.611015test equation:dependent variable: resid2method: least squaresdate: 12/22/04 time: 17:18sample(adjusted): 1993 2002included observations: 10 after adjusting endpointsvariablecoefficientstd. errort-statisticprob. c197.6702116.59791.6953150.1409resid2(-1)-0.3897540.411792-0.9464810.3804resid2(-2)-0.4030480.444113-0.9075350.3991resid2(-3)-0.0912190.421512-0.2164100.8358r-squared0.181805 mean dependent var103.1534adjusted r-squared-0.227292 s.d. dependent var136.2191s.e. of regression150.9079 akaike info criterion13.16039sum squared resid136639.2 schwarz criterion13.28143log likelihood-61.80196 f-statistic0.444405durbin-watson stat1.941317 prob(f-statistic)0.730040obs*r-squared=1.8180507.81=x2 0.05(3)所以不存在异方差利用cochrane-orcutt迭代法检验dependent variable: ymethod: least squaresdate: 12/22/04 time: 17:36sample(adjusted): 1991 2002included observations: 12 after adjusting endpointsconvergence achieved after 10 iterationsvariablecoefficientstd. errort-statisticprob. c-46.5320127.88659-1.6686160.1462x2-2.54e-069.14e-07-2.7756200.0322x6-0.1678690.018630-9.010