北京市住房价格和租金的空间分异与相互关系

当前中国住房销售市场、住房租赁市场发展不平衡,研究住房价格、租金的空间分异与相互关系,对建立“租售并举”的住房制度具有重要参考价值。利用2016年北京市各住宅小区的住房价格、租金数据,及2006—2016年北京市逐月住房销售价格指数、住房租赁价格指数,从时空尺度剖析了住房价格、租金的空间分异与相互关系,并剖析了背后的差异机制。结果表明：① 北京市住房价格和租金的空间格局均呈多中心圈层递减结构,且南北差异明显,但租金的空间分异程度弱于住房价格。② 住房价格具有中等程度的空间相关性,受政策等随机性因素影响相对较大,而租金具有强烈的空间相关性,受区位交通等确定性因素影响相对较大。③ 住房价格和租金的价格剖面线并不相同,住房价格易受学区、大型公园等的影响,而租金更易受就业所在地、建筑年龄等的影响。售租比呈混乱斑驳、相对均质的扁平化分布特征,且小区越高档,售租比越高。④ 北京市住房销售市场和住房租赁市场基本相对独立发展,更符合双重市场的特征。产生上述差异的主要原因在于住房销售市场和住房租赁市场的市场特征、服务人群以及市场发育程度不同。     

Effect of land prices on the spatial differentiation of housing prices: Evidence from cross-county analyses in China

This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014. Multiple theoretical perspectives on housing demand, supply, and market, are combined to establish a housing price model to explore the impact of land prices on housing prices. The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique. Finally, the influencing mechanism of land prices on housing prices is discussed. The main conclusions are as follows. (1) Housing prices have a pyramid- ranked distribution in China, where higher housing prices are linked to smaller urban populations. (2) Land prices are the primary driver of housing prices, and their impacts on housing prices vary over different administrative levels. To be specific, the effect of land prices is the strongest in the urban districts of provincial capital cities. (3) The internal influence mechanisms for land prices driving housing prices are: topographic factors, urban construction level, the agglomeration degree of high-quality public service resources, and the tertiary industrial development level. The urban land supply plan (supply policies) is the intrinsic driver that determines land prices in cities; through supply and demand, cost, and market mechanisms, land prices then impact housing prices.     

农产品现货价格与期货价格关联研究

农产品现货价格无论从短期还是长期影响期货价格的统计特征都是显著的,通过建立假设,利用VEC模型,选取农产品现货月度数据,根据期货市场日数据加权计算其月度数据,进一步探析了现货影响期货的程度及其机理。逐步控制模型中的其他变量,结果验证其经济意义是历史现货价格数据影响期货价格也是显著的,但是单个农产品现货和期货价格的影响程度是不一致的,有的影响方向是相反的。从单一品种农产品价格来看,现货市场与期货市场相关度极高,对于大豆、棉花、豆粕和强麦来说,现货价格上涨1%,期货价格上涨幅度则分别为0.948%、0.836%、0.873%和0.845%,对于小麦和大豆来说,现货价格上涨1%,期货价格上涨幅度接近1%;期货价格的变动一方面直接受到现货价格的影响,另一方面还受到影响现货价格变动的因素的间接影响。拆借利率、M2、进出口总值的估计系数均显著为正,证实了农产品供求因素(生产量、进口量、出口量、世界总产量、世界总出口量)、货币政策、货币供应量、利率和汇率等的变动,都直接影响到期货价格。农产品现货价格和期货价格是具有联动影响的,因此,适度且分类引导现货价格,建立单品种农产品价格预警机制,平抑农产品期货市场上大的波动,有利于我国农产品期货市场的健康发展;同时,因为期货市场具有价格发现功能,期货价格的稳定对当前的农产品现货也具有引导作用,会促进农产品现货市场的良性发展。     

基于客源地的聚类-ARIMA模型的短期旅游需求预测--以天津欢乐谷主题公园为例

大多数旅游需求预测研究是基于目的地游客总数或消费总量开展的,尚未按不同的旅游目的或客源地细分进行预测.以天津欢乐谷主题公园为案例地,选择2014年第40周到2015年第26周为研究时段,利用通信大数据,提出了一种面向客源地的聚类-ARIMA组合预测模型.通过对不同客源地的时序数据进行聚类,选取各类别中的代表性客源地分别构建ARIMA预测模型.结果表明:对欢乐谷主题公园各客源地分别建模与聚类后通过6个代表客源地建模得到的结果一致;后者可以降低80%的预测成本.该方法具有较高的预测精度和较低的计算成本,适合面向客源地的短期旅游需求预测,可为旅游目的地提供更具针对性的旅游需求管理、分析与决策支撑.     

Instabilities in the consumption and production for cobalt

Cobalt is obtained mainly as a byproduct of the mining and metallurgical processing of copper and nickel. The amount of minable cobalt has a characteristic supply limit, which is dependent upon demand for copper and nickel. It is considered that cobalt consumption will be affected by the amount mined in the near future, because world demand has been gradually increasing, while the production from copper sulfide ores in Zaire and Zambia, major producing countries, has decreased for political, economical and technological reasons. The world demand for cobalt has surpassed the world mine production, and cobalt sales from the National Defense Stockpile of the United States and exports from Russia and cobalt recovered from stockpiled intermediates contributed to the supply in 1994. It is concluded, from a statistical point of view, that this trend of shortage and high prices for cobalt will continue in the near future.     

Forecasting the Ethiopian Coffee Price Using Kalman Filtering Algorithm

Ethiopian coffee price is highly fluctuated and has significant effect on the economy of the country. Conducting a research on forecasting coffee price has theoretical and practical importance.This study aims at forecasting the coffee price in Ethiopia. We used daily closed price data of Ethiopian coffee recorded in the period 25 June 2008 to 5 January 2017 obtained from Ethiopia commodity exchange (ECX) market to analyse coffee prices fluctuation. Here, the nature of coffee price is non-stationary and we apply the Kalman filtering algorithm on a single linear state space model to estimate and forecast an optimal value of coffee price. The performance of the algorithm for estimating and forecasting the coffee price is evaluated by using root mean square error (RMSE). Based on the linear state space model and the Kalman filtering algorithm, the root mean square error (RMSE) is 0.000016375, which is small enough, and it indicates that the algorithm performs well.     

Efficient Generation Portfolio Construction Using Time-Varying Correlations

We constructed a procurement portfolio for the Indian power sector using two variants of the dynamic conditional correlation GARCH model to derive time-varying correlations between major coal indices. We used prices and qualities of observed cargos to adjust indices for quality gaps as well as for freight costs and power plant efficiency factors. Using the relative homogeneity of the energy content of imports from Australia, South Africa, and Indonesia, we found that the regional seaborne market is highly correlated during normal economic conditions, while suffering brief departures in correlation during demand and supply shocks. Our results show that the buying behavior of power producers is aligned with the mean-variance efficient portfolio of delivered prices using time-varying correlation estimates, but not free-on-board coal index prices. This study challenges the notion that thermal coal importers only source material with a freight price advantage and highlights the importance of coal quality gaps in power production.     

土地价格对住房价格空间分异的影响——基于中国县域单元的实证分析（英文）

This study analyzes the spatial patterns and driving forces of housing prices in China using a 2,872-county dataset of housing prices in 2014.Multiple theoretical perspectives on housing demand,supply,and market,are combined to establish a housing price model to explore the impact of land prices on housing prices.The relative impacts of land prices on housing prices at different administrative levels are then analyzed using the geographical detector technique.Finally,the influencing mechanism of land prices on housing prices is discussed.The main conclusions are as follows.(1) Housing prices have a pyramid-ranked distribution in China,where higher housing prices are linked to smaller urban populations.(2) Land prices are the primary driver of housing prices,and their impacts on housing prices vary over different administrative levels.To be specific,the effect of land prices is the strongest in the urban districts of provincial capital cities.(3) The internal influence mechanisms for land prices driving housing prices are:topographic factors,urban construction level,the agglomeration degree of high-quality public service resources,and the tertiary industrial development level.The urban land supply plan(supply policies) is the intrinsic driver that determines land prices in cities;through supply and demand,cost,and market mechanisms,land prices then impact housing prices.     

南京市城市土地价格空间分布特征

城市土地供给是城市扩张的重要支撑,分析城市不同类型的土地价格空间分布特征对于城市土地的合理开发具有重要意义,并已成为学者们研究城市扩张过程的重要视角。采用传统统计学与地统计学方法,以住宅、工业、商服三种不同土地利用类型的出让价格为样本,分析了南京市2001-2010年土地交易价格的统计特征及空间分布特征。结果表明,土地用途不同,其出让价格的空间分布特征也不同。商服用地对商服繁华度要求较高,价格高值区集聚在市中心,以新街口、夫子庙等商贸商务区为中心,向外围价格逐渐降低,为典型的单中心布局模式;住宅用地对环境质量要求较高,价格高值区相对商服用地集聚度有所下降,并呈现出由市中心向外迁移的趋势,圈层布局态势明显;工业用地由于有较高的对外交通条件要求,以及环境成本约束和政策导向,除部分对研发及基础设施等条件要求较高的高新技术等工业外,大多布局在远离市中心,区位条件良好的沿江产业园区及工业区内,呈现多中心发展格局。     

Spatial analysis of residential fuel prices: Local variations in the price of heating oil in Northern Ireland

Spatial disparities in the price of residential heating fuel may have considerable impacts on social well-being. Dependence on relatively expensive fuels in off-gas grid contexts may be linked to high rates of fuel poverty, making it a key policy issue. However, fuel prices in the off-grid sector have received relatively little research attention. This study investigates pricing structures within the heating oil market in Northern Ireland, a region with high rates of fuel poverty, using applied spatial analysis. The results indicate significant spatial variations in the price of heating oil at local level. High prices occur in remote rural areas and urban areas with high rates of gas heating. Prices appear to arise from a complex set of interacting factors related to local market structures, supply costs, market competitiveness and socio-economic factors which affect demand. This study makes a significant contribution to the literature on off-gas residential heating. Although further research is needed, the results presented here suggest that policy responses such as price regulation may have only limited impacts on fuel poverty levels, emphasizing the importance of maximising access to more affordable fuels (e.g. mains gas or renewables) as part of a sustainable energy solution.     

用水计划与水价对华北工业企业用水的影响--以河北省为例

工业是仅次于农业的用水大户,其用水的规模、方式和效率直接影响着华北地区总的用水需求。在对华北地区工业企业问卷调查的基础上,就影响企业效益的主要因素、用水计划对企业用水的影响、水费占总成本的比例、企业对目前和未来水价的看法、企业对提高水价的意愿、企业应对水价上涨的策略、企业对节水的态度和采取的节水措施等问题进行了分析。结果表明:用水计划对限制企业的用水有明显的作用;提高水价也有明显促进企业节水的效应。并选择了两个万元产值耗水量差别大的典型企业,对其13年来的用水情况进行了分析,验证了用水计划和水价对企业用水行为的影响效果。     

全球石油供应下新地缘政治经济格局分析

本文选取1994年1月到2011年12月的时间序列数据,从地缘政治视角研究国际石油供给的格局及石油价格波动主导权。首先通过ArcGIS分类来展现石油供给的地缘政治格局总体面貌;其次对国际石油价格波动主导权进行实证分析,结果显示石油存储量与石油价格之间并非简单的线性关系,且在金融危机时期呈现负相关关系,在地缘政治事件频发时期呈现正相关关系;进一步对主导权量化估算,结果表明,国际石油价格波动主导权更多的掌控在OECD需求方,即金融业主导国家。随着时间的推移,NonOECD需求方与石油供给方对国际石油价格主导权逐渐增加,同时,金融因素对国际油价波动的主导权不容忽视。     

中国城市住宅价格的空间分异格局及影响因素

分别研究2009年中国286个地级以上城市住宅均价和房价收入比的空间分异格局、总体趋势、空间异质性和相关性;根据供需理论和城市特征价格理论建立了影响中国城市住宅价格空间分异的初选因素,并根据半对数模型分析主要影响因素。结果表明：① 中国城市住宅价格空间分异显著,呈现出空间集聚性分异（东南沿海三大城市群与内陆城市之间）和行政等级性分异（省会与地级市之间）的双重格局;② 房价收入比较高的城市数量更多,分布范围更广,购房难度较大的城市已超过一半;③ 住宅均价的总体分异趋势和空间异质性都强于房价收入比;④ 城市居民收入与财富水平和城市区位与行政等级特征是住宅价格空间分异的两大核心影响因素。     

上海市住房价格梯度及其影响因素分析

选择从上海市中心区至宝山区的一条南北向区段,通过采集沿线内环以内、内环和中环之间、中环和外环之间以及外环以外四个区间内二手房、新房的价格样本,分析其价格梯度差,发现二手房价格一般要高于新房价格,但其价格递减速度比新房更快。根据实际情况,提取繁华程度、市场供求比例、地理区位、交通条件、人口状况、基础设施、环境质量七个影响住房价格的主要因子,运用多元回归分析方法对样本区域的房地产价格进行分析,得出了多元线性回归方程,并进行了回归分析效果检验;最后分别运用偏相关系数分析法和单项因子权重度量法来估算各因子的影响程度。结果表明,二手房市场和新房市场具有明显差异,市场供求是影响二手房价格的最主要因子,而环境质量则是影响新开楼盘价格的首要因子;繁华程度和交通条件的重要影响作用在本次回归模型中没有得到验证。     

Dynamics Behind Cycles and Co-movements in Metal Prices: An Empirical Study Using Band-Pass Filters

After living one of the most intense metal price cycles, several ongoing macroeconomic phenomena with the potential of structurally redefining the long-run supply and demand for metals, and raising divergency regarding where the metal prices are trending, it is suitable to evaluate the dynamics in the metal prices, especially focus on the long cyclical components. This article studies in detail the cyclical components of the real prices of base metals, iron ore, and gold, applying band-pass filters and a novel decomposition over time series with length as far as 1800. The main findings are: (1) the long cyclical components in real prices are highly correlated among them and with the proposed long economic cycles, (2) short and medium cyclical components are more relevant in explaining the price deviations from their trend, but the long cyclical component is not negligible, (3) co-movement in base metals is strong for all the cyclical components, but decreasing as cyclical frequency increases, and (4) prices are either sideways or upward-trending depending on the assumptions for correction of the US Consumer Price Index, which suggests that the supply side of these industries, in the best case, only offset the cost increases by depletion.

     

基于高铁网络的中国省会城市经济可达性

基于列车时刻表中的省会城市间交通时间以及相应票价数据和各省市城镇居民家庭人均收入数据,以铁路服务价格、城镇居民消费铁路服务能力两方面为突破口,分析高铁网络对中国省会城市经济可达性的影响。结果表明：① 高铁网络不同程度地提升了省会城市铁路服务价格,降低了铁路服务价格与时间可达性的相关性,同时改变了铁路服务价格的分布格局。② 城镇居民消费铁路服务能力等级差异明显,其中收入水平发挥着决定性作用,而铁路服务价格的影响也不容忽视。③ 高铁网络缩小了“所有城市”铁路服务价格、铁路服务消费能力分布的不公平性,但扩大了“高铁城市”铁路服务价格、铁路服务消费能力分布的不公平性;铁路服务消费能力分布的不公平程度高于铁路服务价格分布的不公平程度。     

Commercial Possibilities for Stranded Conventional Gas from Alaska’s North Slope

Stranded gas resources are defined for this study as gas resources in discrete accumulations that are not currently commercially producible, or producible at full potential, for either physical or economic reasons. Approximately 35 trillion cubic feet (TCF) of stranded gas was identified on Alaska’s North Slope. The commercialization of this resource requires facilities to transport gas to markets where sales revenue will be sufficient to offset the cost of constructing and operating a gas delivery system. With the advent of the shale gas revolution, plans for a gas pipeline to the conterminous US have been shelved (at least temporarily) and the State and resource owners are considering a liquefied natural gas (LNG) export project that targets Asian markets. This paper focuses on competitive conditions for Asian gas import markets by estimating delivered costs of competing supplies from central Asia, Russia, Indonesia, Malaysia, and Australia in the context of a range of import gas demand projections for the period from 2020 to 2040. These suppliers’ costs are based on the cost of developing, producing, and delivering to markets tranches of the nearly 600 TCF of recoverable gas from their own conventional stranded gas fields. The results of these analyses imply that Alaska’s gas exports to Asia will likely encounter substantial competitive challenges. The sustainability of Asia’s oil-indexed LNG pricing is also discussed in light of a potentially intense level of competition.     

LAND PRICE INFLATION AND AFFORDABLE HOUSING

Prices for standard lots and acreage were collected for 1975 and 1980 in 30 metropolitan areas and then analyzed, using multiple regression, to identify factors which would explain variations among metropolitan areas. Extreme price variations were observed. For example, from 1975 to 1980, the price of a standard residential lot increased as little as 31% in one area, while the price rose 1 76% in another. Over 80% of the variation in lot price increases was explainable by a model combining land supply and demand factors. In their order of importance, the factors were: (1) an index of regulatory restriction, (2) population increases, (3) per-capita income increases, and (4) job increases. The analysis suggests that public regulatory, infrastructure and tax policies can significantly affect land supply and demand and, in turn, prices. Communities that choose to manage growth must monitor land supply and demand and adjust their policies to ensure competitive noninflationary land markets. Otherwise major increases in land prices for housing and businesses may result.     

中国风电减排CO2的成本测算及其时空分异

以风电并网利用为主的风能资源快速开发和利用已产生了显著的能源替代、CO₂减排和推动地区经济发展等良性效应,开展中国风电减排CO₂成本测算及其时空分异的探究对于准确认识风能在能源系统中地位、明确风电发展方向和制定应对气候变化对策具有重要作用。在明确风电电价测算方法和构建风电减排CO₂成本测算模型的基础上,通过对当前中国典型风电项目技术经济数据的收集和分析以及通过学习曲线模型分析,测算了不同风能等级区、不同省份不同时期的中国风电减排CO₂成本。结果表明,在当前水平下,中国在风能极丰富区、丰富区、较丰富区、一般区、贫乏区风电减排CO₂的成本分别为120元/t、182元/t、243元/t、367元/t、737元/t;不同省份减排成本差异很大,最高值和最低值分别为783元/t和39元/t,且呈现出沿海省份减排成本低于内陆省份,减排成本空间分布与风能资源存在一定错位的现象。在2008~2050年期间,中国风电减排CO₂成本呈持续下降趋势,预计在2020年风电开始具备与常规火电竞争的能力。     

北京市景观可达性与住宅价格空间关联

随着城市居民对住宅环境要求的不断提高,城市景观对城市住宅价格分异影响日趋显著。分析景观对住宅价格分异格局的影响,可为城市住宅空间结构的规划提供依据,为规划与管理部门提供决策参考。以北京城区二手房小区为样本,基于ArcGIS空间分析方法和特征价格模型,探讨景观因素对北京市住宅价格空间分异格局的影响。以主流房地产交易网站二手商品房报价资料为基础数据,共采集到2012 年1 月北京市城六区有效住宅小区样本3174 个,对住宅样点进行空间化处理,并建立住宅空间信息数据库。运用密度分析、空间插值等方法,分析北京市住宅空间分布特征与价格空间分异格局。核密度分布图显示：北京市住宅空间分布呈现显著的向心化与离心化并存现象,总体上以天安门为中心向周边呈衰减趋势,在地铁转换站点形成了多个集聚次中心。在此基础上,从住宅属性、交通因素、区位特征等方面选择主要解释变量,构建地理加权回归模型,对住宅价格影响因素进行分析,重点探讨景观可达性（如绿地、水景、山景等）与住宅价格的关联。结果表明：次中心与住宅价格关联最为显著,绿地、水景、山景与住宅价格存在一定程度关联。其中,山景和高绿化率对住宅价格增效明显;由于水质较差,北京城六区内河流与住宅价格存在负相关;污水处理以及丧葬场所等污染源与住宅价格也存在显著负相关。远离污染源、靠近宜人景观、低容积率、高绿化率是居民选择住宅的需求。