基于面板数据的江苏省房价影响因素分析

近些年来,房价的快速上涨引起社会各界的广泛关注。江苏省作为中国的经济强省，各市房价近些年也快速上涨。为了分析江苏省不同地区房价的主要影响因素，基于2016-2020年江苏省13个地级市房价及其房价影响因素年度面板数据，使用dbscan聚类算法将江苏省房价聚类成为两大类地区，构建双固定效应面板模型对江苏省房价进行分区域分析。进一步考虑各区域房价可能存在的空间相关性，并构建相应的空间计量模型，对江苏省房价影响因素进行分析，最后给出相应的结论和建议。     

是土地供应量与房地产税赋提高了房价吗

自分税制实施后,“土地财政”成为我国地方政府获取收入以支撑财政支出的主要选择,而与此同时房价也在不断上涨。中央政府从民生角度要求地方政府对房价实施调控,地方政府则主要通过调整土地供给量和房地产税税赋来施加影响。土地供应量和税赋会影响供需双方从而影响房价,反过来房价又会影响税收收入及开发商对土地的需求,进而影响社会民生。本文对我国东、中、西部地区住房价格和土地供给量、房地产税税赋之间的关系进行分析,探讨各地区的住房价格上涨原因。通过构建住房价格和土地供给量、房地产税税赋之间的PVAR模型,利用格兰杰因果检验、脉冲分析和方差分解方法来透视地方政府行为对住房价格的影响。分析结果显示,地方政府行为和房价之间存在着联动关系,但在推动住房价格上涨的原因上存在着区域差异：在东部地区,土地供应量影响房价;中部地区,二者联合推动了房价上涨。而在西部地区,房地产税税赋对房价的影响明显。在政策建议上,对地价推动房价的地区要从丰富住房来源和数量入手,而税赋影响房价的地区则要完善相关税制改革。     

Do exchange rate arrangements and capital controls influence international capital flows and housing prices in Asia?

This paper investigates the influence of international capital flows on housing prices in eight Asian countries, including China. We focus on determining whether exchange rate arrangements and capital regulations influence capital inflows and housing prices. Our results show that an arrangement to restrain the fluctuation of the exchange rate and capital controls has the potential to raise housing prices in Asia. The strong prospect of the Chinese yuan's appreciation also pushed up housing prices in China. Another expected reason for the increase in capital inflows into Asian markets is the expansion of global liquidity. Such capital flows often have a sensitive reaction to market sentiment, and an increase in asset market volatility caused by the liquidity squeeze decreases Asian housing prices. These results suggest the need to review capital controls and future exchange rate system options for Asian countries.     

The impact of structural adjustment on housing prices in China

Studies of the factors that influence housing prices have focused on housing characteristics, governmental policies, environmental goods, macroeconomic and social fundamentals, and so on. However, the effect of industrial structural adjustment on housing prices is worthy of further investigation. In China, it would be helpful to measure this effect to coordinate housing policy and the ‘Made in China 2025’ strategy, which aims to accelerate industrial restructuring. We selected a spatial panel data model to quantify the effects of the industrial rationalisation and sophistication attributable to spatial dependence in housing prices. Estimation results show that structural adjustment has a statistically significant effect on housing prices that varies widely across regions. In descending order, the impact of industrial structure sophistication decreases in eastern, central, western, and northeastern China. This finding suggests that the government should match housing with local industry, prevent excessive real estate development in conventional agricultural areas, and pay close attention to changes in housing prices caused by increasing industrial restructuring.     

产业结构变迁对房地产价格的影响研究

以我国2004-2016 年的相关面板数据为样本数据,运用SYS-GMM 估计从产业结构合理化和产业结构高级化两个维度分析产业结构变迁对房价的影响,同时按房地产市场与经济发展水平指标对样本进行聚类分析,考察产业结构变迁对房价的区际差异化影响。研究表明：利用全国数据与分区域数据均得出产业结构变迁对房地产价格存在显著正向影响的结论,但各区域之间产业结构变迁对房价的影响存在一定的区域差异;产业结构合理化程度和高级化程度的变动对房价的影响强度在经济发达地区明显强于经济不发达地区。根据理论分析和实证结果从因城施策、租购并举、财税政策调整与人力资本提升四方面提出建议。     

收入差距、房价与消费变动——基于面板数据联立方程模型的分析

正确理清收入差距与房地产价格的关系,探知其对消费的影响,是实现我国扩大内需战略所面临的重要问题。本文基于我国的2000-2008年31个省、市(自治区)的面板数据,构造联立方程模型,深入探讨了收入差距、房地产价格与消费的关系,结果发现,收入差距与房价之间存在着正向的互动关系,但是对消费的影响却呈现出一定的区域差异,在东中部地区,收入差距与房价之间这种相互强化的关系,使得代表消费主体的广大中低收入群体的住房负担加重,不得不减少消费。但是在西部地区,由于住房负担相对较轻,能正向发挥财富效应,所以收入差距与房价之间的互动影响,反而促进了消费。这种差异正好折射出我国区域经济发展的不平衡性。因此,有必要通过对收入分配的合理调整,实施稳健的货币政策和有效的住房保障政策来科学调控房价,进而切实促进消费。     

住房贷款与房地产价格关系的实证研究——来自深圳的证据

本文围绕住房贷款与住房价格的关系展开研究,将住房贷款与住房价格视为内生变量,将购买住房成本、二手住房价格、住房供求缺口、收入住房价格比视为外生变量,采用深圳市2006年1月至2008年5月的月度数据估计了包括2个内生变量、4个外生变量的VECM模型。实证结果表明：深圳住房贷款与住房价格之间存在长期均衡关系,中央银行信贷数量调控效果要优于利率价格调控效果,银行业住房信贷政策整体上讲是稳健的,基于此并针对有关结论提出了政策建议。     

Impact of Monetary Supply on Chinese Nonferrous Metal Price Movement*

Employing both classical vector autoregressive methodology and regression models utilizing shock factors constructed with the Hodrick–Prescott filtering method, this paper empirically studies the influence of monetary factors on the price of nonferrous metals and their expectation formation in the Chinese market. Monetary factors are found to significantly positively influence Chinese nonferrous metal prices, and further empirical research reveals that a structural change occurred near August 2006. There is an expectation formation mechanism of lagged futures prices on spot metal prices, and the risk originating primarily from international market is transmitted to Chinese markets.     

"货币幻觉"与房价虚涨实涨——质疑"房价虚涨论"

在房价不断上涨的现象面前,房价上涨源于货币幻觉的观点具有一定影响。通过对房价上涨是虚涨还是实涨的分析,从而说明房价虚涨论的片面性。实际情况是,货币幻觉对房价上涨的影响是短暂的;收入的增长幅度低于房价的上涨幅度等因素,决定了房价是实涨而非虚涨。房价虚涨论的危害在于,如果房价上涨被房价虚涨论所误导,将会影响政府抑制房价过快上涨政策措施的制定和实施,也将对居民的住房投资和消费产生负面影响。     

垃圾处理设施对住宅价格影响的Meta分析

基于16篇垃圾处理设施对住宅价格影响的实证研究进行Meta分析,探讨垃圾处理设施引起周边住宅价格波动的影响因素,并分析这些因素具体影响作用和方向。研究结果显示：整体上,垃圾处理设施对周围住宅存在贬值效应,住宅平均贬值幅度为10.4%;距离变量、建筑变量、区位特征、邻里特征和方法变量对垃圾处理设施对周边住宅价格波动幅度具有显著影响。通过研究为垃圾处理设施负外部性的管理提供理论依据。     

基于需求角度房地产价格影响因素的实证分析

本文从需求角度分析影响房价的各因素,包括经济发展水平、城镇化水平、城镇居民收入水平和通货膨胀等,并选取一系列房地产价格的影响指标在2001-2010年的十年数据,建立31个省市房价的多种面板数据模型。对不同模型间进行选择和比较,得出最佳模型为个体固定效应模型,力图揭示各选取因素是否能够对房地产价格产生显著影响,从而确定需求层面上房价的影响因素,以及得出相应建议。     

Effect of COVID-19 lockdowns on city-center and suburban housing markets: Evidence from Hangzhou,China

In 2020, governments worldwide enforced lockdowns to contain the spread of COVID-19, severely impeding aspects of daily life such as work, school, and tourism. Consequently, numerous economic activities were affected. Before the COVID-19 outbreak, city-center housing markets in areas surrounding popular tourist attractions performed better than did suburban housing markets because of the output of the tourism industry. This study examines the changes in the performance of city-center and suburban housing markets in regions with popular tourist attractions after the lockdown. Specifically, the dynamics of city-center and suburban housing markets in Hangzhou, where West Lake is located, and the changes in the information transfer between these housing markets after the lockdown are explored. Transaction data from January 1, 2019 to September 30, 2020 are used to perform analysis, in which adjusted housing prices and asking prices are employed to measure market performance and sellers’ pricing strategies, and transaction volume and time on the market are used to measure market liquidity and transaction frequency. The results reveal that the effects of lockdowns differ between city-center and suburban housing markets. After the lockdown, a substantial structural change is observed in the suburban housing market; the volatility risk of housing prices decreases substantially, causing an increase in transaction premiums. Housing prices and transaction volume increase in the city-center housing market after the lockdown; this is possibly because of the influence from the overall housing market booms. In addition, because sellers raise their asking prices and the transaction time is extended, the sellers in the city-center housing market are particularly influenced by the disposition effect. This leads to a reversal in the lead–lag relationship between the city center and suburban housing markets in terms of informativeness. Specifically, before the lockdown, the city-center market transfers information to the suburban market, but after the lockdown, the suburban market transfers information to the city-center market. The COVID-19 pandemic has changed the world in many aspects; this paper finds that it will also change the development pattern of the real estate market in different locations.     

Time-varying inter-urban housing price spillovers in China: Causes and consequences

The spatial spillovers of housing prices across regions are well documented by a large body of previous studies. This paper tries to investigate the dynamic (time-varying) evolution of spatial interactions and their underlying driving factors intensively. Using a recently developed Generalized Autoregressive Score (GAS) model, this paper examines the time-varying spatial spillovers of housing prices in 70 major and median cities of China from 2006 to 2019. We find that the GAS model can well capture the impact of time-varying critical events of Chinese real estate market on the whole. However, different regions display heterogeneous variation patterns over time. Further investigation shows that inter-regional labor mobility and trades are two major channels, accounting for 1.25% and 2.58% of the monthly standard deviations of spatial spillover effects from one city to another, respectively. We also characterize and distinguish between three time-varying patterns of spatial spillovers within different regions of China. Our results shed lights on the understanding of spatial spillovers across regional real estate markets across different city network structures within China.     

Does local governments’ budget deficit push up housing prices in China?

Budget deficit has been a common fiscal pressure facing Chinese cities since the 1994 fiscal reform. Meanwhile, land lease sales have become a significant off-budgetary revenue to local governments since 2003. This paper investigates whether financing budget deficit is an important driving force of the recent soaring housing prices when local governments function as the monopoly supplier of urban land. A conceptual framework is developed to illustrate a transmission mechanism from budget deficit to housing prices. This leads to an empirical model consisting of two simultaneous structural equations for housing prices and land prices. Using data for the 35 major Chinese cities from 2003 to 2011, an empirical exercise shows that although budget deficit has a positive effect on land prices, it is the factors from demand side, such as amenities, income and the user cost of housing capital, that have been pulling up the housing prices.     

“大水漫灌”还是“精准滴灌”:基于时-频域动态视角下房价调控机制研究

基于时-频域动态视角采用小波分析模型,文章结合高频序列和低频数据在同一框架内研究总量货币政策、结构性信贷政策和房价波动三者之间不同时期的动态影响关系,并进一步甄别供需调控对房价的异质性影响。实证发现,作为房价调控的手段,结构性信贷要优于总量货币政策,而结构性信贷的影响机制是,中期时供给端调控存在非对称性,长期和超长期需求端优于供给端调控,这表明需求结构性信贷政策+总量货币政策工具的调控效果更佳。因此,应用价值体现在遏制房价的过程中,政府应该让"大水漫灌"式的总量货币政策用于"事前预防",而让"精准滴灌"式的结构性信贷政策用于"事后控制",在不同的时-频域中以前者为辅后者为主交替或协调使用,以此防止房地产市场泡沫累积而爆发风险。     

Housing markets and the economy: the assessment

Housing markets have multiple interactions with the rest ofthe economy and these are surveyed in this paper. The driversof house prices include income, the housing stock, demography,credit availability, interest rates, and lagged appreciation,the latter a potential mechanism for overshooting. There israther less agreement on the determinants of new construction,though planning constraints are widely seen as a major issueand one of the causes of the UK housing affordability problem.The paper argues that housing collateral and downpayment constraintsare the key to understanding the role of house-price variationsin explaining medium-term consumption fluctuations. Institutionalvariations between countries and over time account for majordifferences in linkages between house prices and economic activity.This illuminates debates about how monetary and other policyshould react to house-price variations. The paper also discussesthe role of housing markets in explaining regional migrationand location decisions, intergenerational inequality, and restrictingaccess of the less affluent to public goods, such as good schools,which are capitalized in local house prices.     

房产信贷约束下中国房价波动与非住房消费的门槛效应分析

针对城镇居民非住房消费不足与高房价并存的典型现象,运用面板门槛模型对31个省区市2005—2019年的数据进行研究,探讨房价波动对非住房消费的影响并揭示空间差异。结果表明：房价波动对家庭非住房消费既有挤出效应也有财富效应,其中随着房产信贷约束的放松,挤出效应减弱,而财富效应增强;东部、中部、西部和东北部之间的门槛效应是异质的;各地区住房信贷约束水平存在明显差异,对房价与非住房消费之间的异质性关联起着至关重要的作用;房价波动和房产信贷约束并不是导致低消费的综合因素,无法负担的房价以及家庭抚养负担的增加是低消费的综合因素。因此,稳定房价仍是当务之急,房产信贷政策应与房地产市场的发展相适应,以促进消费。     

华东地区住宅价格空间格局及其演化研究

住宅价格空间格局不论对于学界还是决策层来说都是一个重要课题。文章运用探索性空间分析方法,对华东地区2005-2011年间区域住宅价格空间格局及其时空演化进行了研究,得到了以下结论：总体上,华东地区房价水平区域之间的分异程度较高,空间相对与绝对差异都不断增长;华东地区住宅价格的空间相关性以长三角地区为核心,逐层衰减分布;同时,沿海地区的空间相关性往往高于内陆。住宅价格趋同现象较为显著的除了长三角地区之外,还有江西省、山东南部与安徽北部,但前者是高高聚集,后者是低低聚集;整个华东地区住宅价格的重心主要向长三角地区偏移。导致华东地区住宅价格变化的主要原因为居民收入水平、住房的供需、货币投放量。但其中供需机制与传统供需理论呈现反向作用趋势。     

人口老龄化与房价——基于中国省级面板数据的分析

文章采用2002-2011年的省级面板数据分析了中国人口年龄结构变化对住房价格的影响及其区域差异。结果发现:老龄化所导致的房价波动滞后于老龄化进程,各年龄阶段人口比例对房价均产生正向影响,但不同年龄阶段在不同区域的解释力度不尽相同。对此实证检验结果,文章认为可以从我国居民的改善性住房需求与投资渠道匮乏、人口家庭结构小型化以及城市集聚效应等方面进行解释,并以前瞻性政策加以应对。     

我国不同发展层次城市房价影响因素的差异分析及对策研究

本文利用2000～2009年"北上广深"4个一线城市以及其他14个二三线城市的房地产数据来实证检验导致我国一线城市和二三线城市房价快速上涨的影响因素,并分别定量分析了这些因素对两类城市房价的影响程度。研究结果表明,由于房地产市场发展阶段不同,我国一线城市和二三线城市的房价影响因素存在较大差异,全国统一的房地产调控政策难以满足不同城市稳定房价和保障房地产市场健康发展的需要。就房地产调控重点而言,一线城市应重在抑制投机型需求,二三线城市应重在增加保障性住房供给。