城市轨道交通对沿线周边住宅价格的影响分析——以北京地铁四号线为例

城市轨道交通是一种公益性、经济外部性都很强的大型公共基础设施,其高效的通达性促进周边住宅升值明显提升。科学地分析城市轨道交通对住宅价格的影响效应,对合理规划沿线住宅项目开发、调整城市空间布局具有重要意义。本文以北京地铁4号线周边住宅作为研究对象,对影响住宅价格的因素进行回归分析,并构建了半对数形式的特征价格模型。经过分析得出住宅距离轨道交通线路的远近、所处的位置、周边1000m范围内公交站点的数量以及住宅至市中心或中央商务区(CBD)的实际距离四个变量对住宅价格的影响比较显著,并且探讨了地铁站点与住宅距离减少,对住宅增值的作用。     

境内和离岸人民币外汇市场价格传导和波动溢出效应

］从不同经济发展阶段的视角，研究CNY、CNH和NDF市场间的价格传导机制，检验其均值溢出效应及风险溢出效应的存在性，发现并解释其异质特征，剖析CNH市场对CNY市场、NDF市场对CNH市场价格引导作用的微观机理，给出了实证证据。研究发现：这三个市场的波动丛集现象显著且逐渐趋弱；随着时间推移，当下波动对未来市场波动的影响趋缓，但风险和损失对市场冲击的持续期变长。研究还表明：境内外人民币即期汇差存在自动收敛的机制，价格将趋向一致，尽管汇差的收敛速度和波动分别随时间推移加快和收窄，但收敛缓慢、波动较大且在一段时间内保持较高水平，预期和套利机制仍不能充分发挥市场信息传导功能。CNY市场缺乏对离岸CNH市场和NDF市场的价格引导作用，人民币汇率价格从离岸向境内市场传递，离岸市场对境内市场的价格发现功能随人民币市场化和国际化发展逐渐完善，但溢出效应存在滞后性且反馈周期较长。     

中国大宗商品价格溢出网络结构及动态交互影响

研究目标：中国大宗商品价格溢出网络结构及动态交互影响。研究方法：基于中国大宗商品价格指数,采用非线性Granger因果检验方法识别大宗商品价格间溢出效应,借助SNA方法揭示其网络结构特征,并采用GIRF实证考察大宗商品价格间的非线性动态交互影响。研究发现：大宗商品价格间呈现明显的网络结构形态,在最大可能性溢出网络和稳健性溢出网络中,农产品、食糖“引领”价格波动,而牲畜、能源、橡胶则处于“跟随”地位。大宗商品价格间普遍存在正向冲击效应,但这种冲击效应存在差异,大部分商品受到冲击后的调整时间相对较短。研究创新：从非线性视角考察大宗商品价格的联动特征。研究价值：考察大宗商品价格时应注意它们之间的联动网络特征及交互影响效应。     

住宅价格波动影响因素个体固定效应模型

通过供需理论分析,住宅价格波动的影响因素有人口、收入、开发商实力、盈利能力、贷款利率及水平等,构建时间序列/截面数据的个体固定效应模型对我国除西藏外的30个省、自治区和直辖市的住宅价格进行实证研究发现,影响住宅价格波动的主要因素有人口、收入、开发商实力、销售面积、土地购置成本、建安成本,在考虑消费惯性的基础上,采用工具变量后的模型估计结果发现短期内影响住宅价格的因素主要是销售面积、土地购置成本和建安成本,且住宅价格受宏观经济影响而存在地区差异。     

制造业集聚、空间溢出与地区经济增长──基于城市面板数据的实证检验

在全国层面上,基于2002—2012年232个城市面板数据的实证检验结果表明,制造业集聚不仅可以促进本地区经济增长,而且能够通过空间溢出效应带动周边地区经济增长。东中部城市的制造业集聚都存在一定程度的区域经济增长效应和空间溢出,东部城市制造业集聚因要素成本上升等原因而使得其溢出系数小于中部;而西部城市的经济增长效应和空间溢出则不显著。这就要求合理安排我国东中西部城市层面制造业集聚的格局,从而更好地促进区域经济协调发展。     

城市经济对住宅价格影响研究--以35个大中城市为例

住宅市场具有很强的地域特性,不同城市由于经济发展等因素的影响,造成住宅价格具有较大的差异。将城市经济分为城市经济规模、城市产业结构和城市经济效率,以35个大中城市为例,运用静态面板数据模型研究城市经济对住宅价格的影响。结果表明,城市经济对住宅价格具有很强的正相关作用,尤其是城市经济规模和城市产业结构。城市经济规模方面,GDP、地方财政支出对住宅价格具有显著的正面影响;城市产业结构方面,第三产业增加值占GDP比重越高,住宅价格越高;城市经济效率方面,人均地方财政收入和第二、三产业增加值与建成区面积之比都对住宅价格具有显著的正相关性。因此,城市在区域经济一体化的带动下将追求创新高效率的发展,同时优化城市空间结构和产业结构,有助于住宅市场的健康发展。     

城市经济对住宅价格影响研究——以35个大中城市为例

住宅市场具有很强的地域特性,不同城市由于经济发展等因素的影响,造成住宅价格具有较大的差异。将城市经济分为城市经济规模、城市产业结构和城市经济效率,以35个大中城市为例,运用静态面板数据模型研究城市经济对住宅价格的影响。结果表明,城市经济对住宅价格具有很强的正相关作用,尤其是城市经济规模和城市产业结构。城市经济规模方面,GDP、地方财政支出对住宅价格具有显著的正面影响;城市产业结构方面,第三产业增加值占GDP比重越高,住宅价格越高;城市经济效率方面,人均地方财政收入和第二、三产业增加值与建成区面积之比都对住宅价格具有显著的正相关性。因此,城市在区域经济一体化的带动下将追求创新高效率的发展,同时优化城市空间结构和产业结构,有助于住宅市场的健康发展。     

基于修正的土地竞标租金模型的中国城市居住分异研究

城市居住分异是中国城市经济发展越来越明显的一个表现,它由市场因素与非市场因素共同作用形成。文章对阿朗索的土地竞标租金模型进行修改,加入中国城市特有的假设条件建立住宅竞标价格模型来分析中国城市居住分异现象产生的市场因素。从社会稳定、劳动力市场、城市交通及公共资源四个方面讨论了城市居住空间分异所带来的社会经济影响。最后,基于住宅竞标价格模型的分析,我们找到居住分异对策的核心是缩小不同收入家庭对住宅价格反应程度的差距。     

国际能源市场与股票市场的波动溢出效应及驱动因素研究——基于TVP-VAR-DY溢出指数分解的实证研究

随着能源金融化程度不断加深,国际能源市场和股票市场之间的联系日益密切。采用TVP-VAR-DY溢出指数分解方法探究国际能源市场和股票市场之间的时变溢出关系,在此基础上进一步探究跨市场溢出效应的主要驱动因素。研究结果表明：国际能源市场与股票市场既存在显著的市场内部溢出效应,也存在显著的跨市场溢出效应,且系统总体溢出水平的动态变化主要由后者驱动;国际能源市场对股票市场的溢出效应弱于股票市场对能源市场的溢出,即国际能源市场为溢出净接收者。国际金融危机、COVID-19等极端风险事件发生时,跨市场波动溢出效应显著增强;地缘政治风险和全球经济政策不确定性是导致跨市场波动溢出的重要因素,且分别在金融市场动荡时期、全球流动性收紧时期表现得更加明显。鉴于此,投资者应高度重视两个市场之间的波动溢出风险,当极端经济事件发生时,监管部门应采取必要的非常规政策措施,减轻溢出效应的不利影响,防范化解系统性金融风险。     

数字经济对城市经济绩效的驱动效应——机制识别与空间效应检验

探讨数字经济与城市经济绩效之间的内在逻辑关系,并利用2011～2018年中国287个地级市面板数据,在构建与测度数字经济与城市经济绩效指标的基础上,从多个维度细致剖析数字经济对城市经济绩效的影响效应及作用机制。研究发现：数字经济对城市经济绩效具有显著促进作用,且技术创新效应、产业结构升级效应以及资本错配缓解效应是其有效作用机制;数字经济对东部、中心城市经济绩效的影响主要通过技术创新效应和资本错配缓解效应来实现,而产业结构升级效应则是数字经济驱动中西部、非中心城市经济绩效提升的作用路径;数字经济对城市经济绩效存在显著的正向空间溢出效应。研究结论可为未来如何依托数字经济驱动城市经济绩效提升提供经验证据和政策支撑。     

The spillover effects of infill developments on local housing prices

This paper examines the spillover effects of infill developments, which involve developing vacant or under-used parcels within existing urban areas that are largely developed, on local housing prices. Employing a difference-in-difference specification on a sample of 275 new developments and 55,887 sale transactions of houses in Singapore, we find that infill developments have a positive and persistent impact on local housing prices. The contagion effect is larger for infill developments that are built on teardown sites. The spillover effect can also be traced to the overpricing of new homes by developers. Overall, the evidence indicates that developers act as price leaders and contribute significantly to price discovery in the local housing market.     

Supply constraints and housing market dynamics

Although the volatility of house prices is often ascribed to demand-side factors, constraints on housing supply have important and little-studied implications for housing dynamics. I illustrate the strong relationship between the volatility of house prices and the regulation of new housing supply. I then employ a dynamic structural model of housing investment to investigate the mechanisms underlying this relationship. I find that supply constraints increase volatility through two channels: First, regulation lowers the elasticity of new housing supply by increasing lags in the permit process and adding to the cost of supplying new houses on the margin. Second, geographic limitations on the area available for building houses, such as steep slopes and water bodies, lead to less investment on average relative to the size of the existing housing stock, leaving less scope for the supply response to attenuate the effects of a demand shock. My estimates and simulations confirm that regulation and geographic constraints play critical and complementary roles in decreasing the responsiveness of investment to demand shocks, which in turn amplifies house price volatility.     

Risk shocks and housing supply: A quantitative analysis

This paper analyzes the role of stochastic uncertainty in a multi-sector housing model with financial frictions. We include time varying uncertainty (i.e. risk shocks) in the technology shocks that affect housing production and provide estimates of the time-series properties of risk shocks by using firm level productivity data. The analysis demonstrates that risk shocks to the housing production sector are a quantitatively important impulse mechanism for understanding housing price movements. Specifically, the model can match the volatility of housing prices observed in the data. It is also demonstrated that adjustment costs are important in replicating the contemporaneous correlation of housing prices with GDP and residential investment. Critically, bankruptcy costs act as an endogenous markup factor in housing prices and are an important determinant of house price volatility. However, in comparison to housing demand shocks, risk shocks have low explanatory power for real quantities.     

Spillover effects of human service facilities in a racially segmented housing market

Previous studies of human service facility spillovers on residential property values have been inconclusive, and have failed to take into account the effects of racial segmentation of housing markets. Likewise, studies of racial discrimination in urban housing markets and price differentials between white and nonwhite areas of the city have failed to consider the impacts of service facilities on prices. This study develops an hedonic price model of housing services in a racially segmented housing market, which considers a variety of human service facilities and their spillover effects. Model results for Oakland, California in 1976 indicate that facilities significantly affect housing prices both positively and negatively, and that these effects vary by racial submarket. Implications of these findings for the interpretation of past discrimination studies, facility impact studies, and social policy are considered.     

Linear and nonlinear dynamic relationships between housing prices and trading volumes

This study applied linear and nonlinear causality tests and estimation models to investigate the efficiency of housing prices and volumes in the United States and its four major regions. The results of this study confirm that housing volumes can function as a price-discovery indicator. According to the nonlinear volatility of housing prices, this study verified numerous hypotheses. Housing returns can also influence housing volume. The results of this study imply that housing price efficiency can vary based on market conditions. Consequently, estimating the behavior of housing prices through a linear model can result in underestimating the information reflected by housing returns.     

Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data

In this paper we investigate housing price volatility within a spatial econometrics setting. We propose an extended spatial regression model of the real estate market that includes the effects of both conditional heteroskedasticity and spatial autocorrelation. Our suggested model has features similar to those of autoregressive conditional heteroskedasticity (ARCH) in the time-series context. We utilize the spatial ARCH (SARCH) model to analyze Boston housing price data used by Harrison and Rubinfeld (1978) and Gilley and Pace (1996). We show that measuring the variability of housing prices is an important issue and our SARCH model captures the conditional spatial variability of Boston housing prices. We argue that there is a different source of spatial variation, which is independent of traditional housing and neighborhood characteristics, and is captured by the SARCH model.     

Housing and the Korean economy

This paper explores the nexus between housing and the Korean economy. It starts with an overview of the size, growth, and volatility of residential investment in conjunction with long-term resource allocation and short-term macroeconomic fluctuations. Then, the evolution of housing finance and its implications for recent house price run-up are discussed. The relationships among housing price, consumer spending, and inflation are also investigated. Particular attention is paid to the debate over house price bubbles, housing wealth effects on consumption, and the causality between house price and inflation. The paper concludes with a brief assessment of government intervention to stabilize house prices.     

教育资本化视角下“学区房”空间布局研究——以天津市中心城区为例

当前各地积极推行义务教育学校“学区”制,旨在破解择校难题,追求公平教育。已有研究与实践经验表明学区制背景下教育资源“资本化”现象确实存在,并带来教育资源的内生性,强化了“学区房”空间分布的不均衡。基于此,阐述“学区房”内涵以及基础教育资本化实证经验,结合天津市中心城区“学区房”空间分布特征,探讨“学区房”不均衡分布的溢出效应,进而提出改善“学区房”不均衡布局的对策。     

Spatial spillover effects and risk contagion around G20 stock markets based on volatility network

Employing the spatial econometric model as well as the complex network theory, this study investigates the spatial spillovers of volatility among G20 stock markets and explores the influential factors of financial risk. To achieve this objective, we use GARCH-BEKK model to construct the volatility network of G20 stock markets, and calculate the Bonacich centrality to capture the most active and influential nodes. Finally, we innovatively use the volatility network matrix as spatial weight matrix and establish spatial Durbin model to measure the direct and spatial spillover effects. We highlight several key observations: there are significant spatial spillover effects in global stock markets; volatility spillover network exists aggregation effects, hierarchical structure and dynamic evolution features; the risk contagion capability of traditional financial power countries falls, while that of “financial small countries” rises; stock market volatility, government debt and inflation are positively correlated with systemic risk, while current account and macroeconomic performance are negatively correlated; the indirect spillover effects of all explanatory variables on systemic risk are greater than the direct spillover effects.     

住房流动性对房价指数的影响及其定量分析

目前中国城市住房市场不稳定程度较高,这不仅体现为房价的迅速变化,而且反映在交易量的大幅波动上,后者就是住房流动性的变化。有学者研究指出,以实际交易价格为基础的房价指数可能会低估住房市场的波动程度。为了更准确地把握住房市场的运行状态,本文借鉴美国MIT的相关技术,分析了住房流动性（交易活跃程度）对房价指数的影响,并尝试将流动性信息引入房价指数当中。我们发现,住房流动性对于房价指数有较大影响,且符合人们对于市场走势的直观判断,能够较好地反映市场转折点。