基于灰色系统理论的赣州市住宅价格预测及影响因素研究
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摘要
近年来,随着商品住宅市场的发展,商品住宅价格受到各方的关注。为了能够加深对商品住宅市场的认识,本文以赣州市作为研究区域,运用灰色系统的研究方法,对商品住宅价格进行预测,并通过定性与定量分析相结合的方法研究部分商品住宅价格宏观因素,从而更好的了解未来商品住宅市场的走势,探求稳定市场价格的因素,为购房者、开发商的决策及政府的调控提供参考。
本文首先从商品住宅价格走势、居民居住现状、市场供求状况及市场存在问题等方面对赣州市的商品住宅市场进行了简单介绍。
接着介绍了灰色系统理论的基本知识和灰色系统建模方法;再接着建立了赣州市的商品住宅价格的灰色残差GM(1,1)模型,对商品住宅价格进行预测,并对模型进行了程序设计。
再其次对商品住宅价格的影响因素进行定量与定性相结合的分析,选取了地区生产总值、城市居民人均可支配收入、居民消费价格指数、房地产开发企业国内贷款、房地产开发投资额、家庭户数、房地产开发企业本年购置土地面积及一年期贷款利率8个宏观影响因素,在对影响因素进行定性分析的基础上,建立灰色GM(1,N)模型对影响因素进行定量研究。结果表明:GDP、房地产开发投资额、房地产开发企业本年购置土地面积对赣州市商品住宅价格的影响最显著,而居民消费价格指数和家庭户数对商品住宅价格影响较小。
最后结合前面的分析,为政府进行商品住宅价格的事先和事中调控提供指导,并提出商品住宅市场宏观调控的政策建议。
In recent years, with the development of commercial housing market, the price of commercial housing has attracted the attention of all circles. In order to strengthen the cognition of commercial housing market,this paper’s study area is Ganzhou, uses the research method of gray system, forecasts the price of commercial housing, and through the combining qualitative and quantitative method to researches some macro-influencing factors of commercial housing price. Accordingly, better understanding the trend of commercial housing markets, seeks the factors to stabilize the market price, makes reference for buyers、developers and government’s macro-control.
Firstly, this paper briefly introduces Ganzhou's commercial housing market form the aspects of commercial housing price trend、living present situation、market supply and demand situation and market issues and so on.
Then introduces the basic knowledge of gray system theory and gray system modeling method; and establishes grey residual error GM (1, 1) model of Ganzhou’s commercial housing price, forecasts the commercial housing price, moreover designs a program for model.
Once again, it analyses the influencing factors of commercial housing price associate with qualitatively and quantitatively method, and selects eight macro-influencing factors, which are regional gross product, per capita dispensable income of urban residents, residents consumer price index, domestic loans of real estate development enterprises, investment of real estate development, number of family households, area of land purchased this year by real estate development enterprises and one-year loan interest rate. On the basis of qualitative analysis to these influencing factors, it builds gray GM (1, N) model to quantitatively research these factors. The result indicates that GDP, investment of real estate development and area of land purchased this year by real estate development enterprises have remarkable influence to Ganzhou’s commercial housing price, but residents consumer price index and number of family households have less influence to commercial housing price.
At last, this paper associates the analysis above, provides guidance for the commercial price’s macro-control, and offers policy advices of commercial housing market’s macro-control.
本文首先从商品住宅价格走势、居民居住现状、市场供求状况及市场存在问题等方面对赣州市的商品住宅市场进行了简单介绍。
接着介绍了灰色系统理论的基本知识和灰色系统建模方法;再接着建立了赣州市的商品住宅价格的灰色残差GM(1,1)模型,对商品住宅价格进行预测,并对模型进行了程序设计。
再其次对商品住宅价格的影响因素进行定量与定性相结合的分析,选取了地区生产总值、城市居民人均可支配收入、居民消费价格指数、房地产开发企业国内贷款、房地产开发投资额、家庭户数、房地产开发企业本年购置土地面积及一年期贷款利率8个宏观影响因素,在对影响因素进行定性分析的基础上,建立灰色GM(1,N)模型对影响因素进行定量研究。结果表明:GDP、房地产开发投资额、房地产开发企业本年购置土地面积对赣州市商品住宅价格的影响最显著,而居民消费价格指数和家庭户数对商品住宅价格影响较小。
最后结合前面的分析,为政府进行商品住宅价格的事先和事中调控提供指导,并提出商品住宅市场宏观调控的政策建议。
In recent years, with the development of commercial housing market, the price of commercial housing has attracted the attention of all circles. In order to strengthen the cognition of commercial housing market,this paper’s study area is Ganzhou, uses the research method of gray system, forecasts the price of commercial housing, and through the combining qualitative and quantitative method to researches some macro-influencing factors of commercial housing price. Accordingly, better understanding the trend of commercial housing markets, seeks the factors to stabilize the market price, makes reference for buyers、developers and government’s macro-control.
Firstly, this paper briefly introduces Ganzhou's commercial housing market form the aspects of commercial housing price trend、living present situation、market supply and demand situation and market issues and so on.
Then introduces the basic knowledge of gray system theory and gray system modeling method; and establishes grey residual error GM (1, 1) model of Ganzhou’s commercial housing price, forecasts the commercial housing price, moreover designs a program for model.
Once again, it analyses the influencing factors of commercial housing price associate with qualitatively and quantitatively method, and selects eight macro-influencing factors, which are regional gross product, per capita dispensable income of urban residents, residents consumer price index, domestic loans of real estate development enterprises, investment of real estate development, number of family households, area of land purchased this year by real estate development enterprises and one-year loan interest rate. On the basis of qualitative analysis to these influencing factors, it builds gray GM (1, N) model to quantitatively research these factors. The result indicates that GDP, investment of real estate development and area of land purchased this year by real estate development enterprises have remarkable influence to Ganzhou’s commercial housing price, but residents consumer price index and number of family households have less influence to commercial housing price.
At last, this paper associates the analysis above, provides guidance for the commercial price’s macro-control, and offers policy advices of commercial housing market’s macro-control.
引文
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[2] Poterba J.M.House Price Dynamics:The Role of Tax Policy and Demograpy. Brookings Papers on Economic Activity,1991(2):143-148
[3] Potepan,M.J.Explaining Intermetropolitan Variation in Housing Prices,Rents and Land Prices.Real Estate Economic,l996(24):219-245
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[5] Quigley.J.Real Estate Prices and Economic Cycles.International Real Estate Review,1999(1):1-20
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[7]沈悦,刘洪玉.房地产价格与宏观经济指标关系的研究.价格理论与实践,2002(08):30-32
[8]钟昌宝.基于灰色-马尔柯夫模型预测房地产价格.统计与决策,2005(1):120-121
[9]刘润秋,蒋永穆.论房价决定定价-兼论当前房地产宏观调控政策.社会科学研究,2005(6):44-48
[10]刘翎,杨大蓉.商品住宅价格的决定:上海市场的计量模型研究.科学经济社会,2006(1):26-29
[11]周仁.北京和上海商品住宅价格决定因素对比分析.价格理论与实践,2007(08):43-44
[12]惠彦涛.基于BP人工神经网络的商品住宅价格研究.决策参与,2007(08):39-40
[13]孔煜.利率与房价关系的认识.建筑经济,2007(9):86-89
[14]徐滇庆.价格宏观调控论.北京:机械工业出版社,2006
[15]邓聚龙.灰理论基础.武汉:华中科技大学出版社,2002
[16]傅立.灰色系统理论及其应用.北京:科学技术文献出版社,1992:185-197
[17]邓聚龙.灰色系统基本方法.武汉:华中工学院出版社,1987
[18]熊和金,徐华中.灰色控制.北京:国防工业出版社,2005
[19]刘洪玉,马亚男.住房价格与政府调控.建筑经济,2005(6):49-52.
[20]王人已.房地产估价.上海:上海财经大学出版社,2002
[21]胡伟艳,王钰.武汉市商品住宅需求影响因素及预测.工业技术经济,2007(5):86-89
[22]姚远.我国房地产价格波动率的影响因素及实证研究.当代经济,2006(9):24-25
[23]国家统计局网站http://www.stats.gov.cn/tjzs/t20070924_402434339.htm
[24]张正东.基于人工神经元网络的商品住宅价格研究:[硕士学位论文].西安:西安建筑科技大学,2005
[25]阳辉.城市商品住宅价格模型研究:[硕士学位论文].大连:大连理工大学,2005
[26]刘维新.中国房地产宏观调控的回顾与展望.城市开发,2006(7):6-8
[27]陈柳钦.房地产宏观调控回顾及2008年展望.改革与开放,2008(2):6-8
[28]中国房地信息.房地特别策划.中国房地信息,2008(1):61-62
[29]廖英敏.2006年1季度:房地产市场矛盾突出,宏观调控须有的放矢.价格理论与实践,2006(5):42-43
[30]陈伯庚,顾志敏.激活需求,稳定房市.上海房地,2006(5):7-12
[31]贾晶.房地产市场宏观调控的回顾分析.武汉商业服务学院学报,2007(3):63-64
[32]黄石松,郭建民,陈红梅.对当前我国房地产宏观调控中几个问题的思考.生态经济,2007(8):101-105
[33]周旭.宏观调控政策对稳定房价的经济学分析.集团经济研究,2006(11):33-34
[34]王菲.论房地产宏观调控与房地产价格:[硕士学位论文].上海:华东师范大学,2006
[35]李舟.90年代以来房地产宏观调控政策分析:[硕士学位论文].成都:西南财经大学,2006
[36]周旭.宏观调控政策对稳定房价的经济学分析.集团经济研究,2006(32):33-34
[37]苗万青.非均衡市场条件下房地产业的宏观调控研究:[硕士学位论文].重庆:重庆大学,2006
[38]倪红日,陈全伟.关于宏观调控政策选择的几点认识.宏观经济管理,2000(4):19-21
[2] Poterba J.M.House Price Dynamics:The Role of Tax Policy and Demograpy. Brookings Papers on Economic Activity,1991(2):143-148
[3] Potepan,M.J.Explaining Intermetropolitan Variation in Housing Prices,Rents and Land Prices.Real Estate Economic,l996(24):219-245
[4] Meen G,Andrew M.Modelling Regional House Prices:A Review of the Literature,prepared for the Department of the Environment,Transport and the Regions. ISBN 0 7049 1305 4.1998
[5] Quigley.J.Real Estate Prices and Economic Cycles.International Real Estate Review,1999(1):1-20
[6] Marco Del Negro,Christopher Otrok.Monetary Policy and the House Price Boom across US States.Working Paper series,2005(24)
[7]沈悦,刘洪玉.房地产价格与宏观经济指标关系的研究.价格理论与实践,2002(08):30-32
[8]钟昌宝.基于灰色-马尔柯夫模型预测房地产价格.统计与决策,2005(1):120-121
[9]刘润秋,蒋永穆.论房价决定定价-兼论当前房地产宏观调控政策.社会科学研究,2005(6):44-48
[10]刘翎,杨大蓉.商品住宅价格的决定:上海市场的计量模型研究.科学经济社会,2006(1):26-29
[11]周仁.北京和上海商品住宅价格决定因素对比分析.价格理论与实践,2007(08):43-44
[12]惠彦涛.基于BP人工神经网络的商品住宅价格研究.决策参与,2007(08):39-40
[13]孔煜.利率与房价关系的认识.建筑经济,2007(9):86-89
[14]徐滇庆.价格宏观调控论.北京:机械工业出版社,2006
[15]邓聚龙.灰理论基础.武汉:华中科技大学出版社,2002
[16]傅立.灰色系统理论及其应用.北京:科学技术文献出版社,1992:185-197
[17]邓聚龙.灰色系统基本方法.武汉:华中工学院出版社,1987
[18]熊和金,徐华中.灰色控制.北京:国防工业出版社,2005
[19]刘洪玉,马亚男.住房价格与政府调控.建筑经济,2005(6):49-52.
[20]王人已.房地产估价.上海:上海财经大学出版社,2002
[21]胡伟艳,王钰.武汉市商品住宅需求影响因素及预测.工业技术经济,2007(5):86-89
[22]姚远.我国房地产价格波动率的影响因素及实证研究.当代经济,2006(9):24-25
[23]国家统计局网站http://www.stats.gov.cn/tjzs/t20070924_402434339.htm
[24]张正东.基于人工神经元网络的商品住宅价格研究:[硕士学位论文].西安:西安建筑科技大学,2005
[25]阳辉.城市商品住宅价格模型研究:[硕士学位论文].大连:大连理工大学,2005
[26]刘维新.中国房地产宏观调控的回顾与展望.城市开发,2006(7):6-8
[27]陈柳钦.房地产宏观调控回顾及2008年展望.改革与开放,2008(2):6-8
[28]中国房地信息.房地特别策划.中国房地信息,2008(1):61-62
[29]廖英敏.2006年1季度:房地产市场矛盾突出,宏观调控须有的放矢.价格理论与实践,2006(5):42-43
[30]陈伯庚,顾志敏.激活需求,稳定房市.上海房地,2006(5):7-12
[31]贾晶.房地产市场宏观调控的回顾分析.武汉商业服务学院学报,2007(3):63-64
[32]黄石松,郭建民,陈红梅.对当前我国房地产宏观调控中几个问题的思考.生态经济,2007(8):101-105
[33]周旭.宏观调控政策对稳定房价的经济学分析.集团经济研究,2006(11):33-34
[34]王菲.论房地产宏观调控与房地产价格:[硕士学位论文].上海:华东师范大学,2006
[35]李舟.90年代以来房地产宏观调控政策分析:[硕士学位论文].成都:西南财经大学,2006
[36]周旭.宏观调控政策对稳定房价的经济学分析.集团经济研究,2006(32):33-34
[37]苗万青.非均衡市场条件下房地产业的宏观调控研究:[硕士学位论文].重庆:重庆大学,2006
[38]倪红日,陈全伟.关于宏观调控政策选择的几点认识.宏观经济管理,2000(4):19-21