Inflation and the stock market: Understanding the “Fed Model”

The so-called Fed model postulates that the dividend or earnings yield on stocks should equal the yield on nominal Treasury bonds, or at least that the two should be highly correlated. In US data there is indeed a strikingly high time series correlation between the yield on nominal bonds and the dividend yield on equities. This positive correlation is often attributed to the fact that both bond and equity yields comove strongly and positively with expected inflation. Contrary to some of the extant literature, we show that this effect is consistent with modern asset pricing theory incorporating uncertainty about real growth prospects and habit-based risk aversion. In the US, high expected inflation has tended to coincide with periods of heightened uncertainty about real economic growth and unusually high risk aversion, both of which rationally raise equity yields.     

中国FDI区位决定因素研究(1986—2009)

关于中国和其他经济体的外商直接投资(FDI)区位决定,绝大部分研究仅仅关注决定因素的选择,而忽略了决定因素及其重要性可能会随一个国家或地区FDI的特性的变化而变化。而且,这类研究也几乎不考虑空间数据的特征。文章以中国为对象,顾及省域变量的空间特征,采用空间面板数据分析方法,并通过分阶段方式来捕捉FDI决定因素及其重要性,研究结果表明,空间特征确实在中国省域引进FDI中具有影响作用,FDI决定因素及其重要性会随时期动态变化。上述发现对中国各级政府以及跨国公司都具有重要政策和决策意义。     

中美股市价格收益波动关联性的研究

随着经济和资本市场的全球化，各国股市之间的相互影响变得越来越大。为了研究中美股市自金融危机爆发后价格收益波动的关联性，可以选取上证综指和标准普尔500作为研究样本，绘出中美股市的走势图，研究两者的联动性，运用协整检验对上证综指和标准普尔500进行实证检验和分析。结果表明，中美股市价格收益波动存在一定程度的关联性。     

Tourism water footprint: an empirical analysis of Mount Huangshan

Water is an important factor for the sustainable development of tourism. We constructed a comprehensive model of the tourism water footprint (TWF), including tourism sewage and water for management, and used the world heritage Mount Huangshan as an example. The results showed that the total TWF, which included green, blue and grey water of Mount Huangshan in 2012, was about 10.19 million m³/year, approximately per tourist 3.39?m³/day or 3387?L/day. Tourism sewage and food were the main factors of water consumption. The spatial transfer of TWF led the spillover of tourism environmental impact, not only affecting Mount Huangshan but the Huangshan City and even nationwide. Tourist flow and temperature had a highly significant positive correlation with the TWF. Quantifying the TWF can reflect the pressure of tourists on water resources, and provide an effective decision-making basis for rational use of water resources.     

Residential Enclosure,Power and Relationality: Rethinking Sociopolitical Relations in Southeast Asian Cities

As in many other areas around the globe, enclosed residential spaces have proliferated in Southeast Asia since the 1990s. Recent publications have presented such gated communities as ‘porous enclaves', implying multiple socio‐spatial dynamics of movements through gates and walls. However, the enclave model does not suffice for analyzing the relational dynamics generated by enclosed residential estates. The concept of ‘ecotonal space' and social geography are used to show, in the case of Cambodia's capital Phnom Penh, that the enclosure and its borders are producers and products of multiple social, spatial, economic and political relations, both symbolic and material. Property developers assert their position as an emerging elite in the city's society and politics, a process based on different types of everyday relations they have with the inhabitants of their residential estates and territorial institutions. The enclosed residential estate can serve as a resource for deploying new power relations. Consubstantial with the neopatrimonial nature of the Cambodian economy and politics, this process is a response to the opacity and uncertainty of real estate markets and urban development.     

2004-2008年福建省制造业空间结构及变化分析

基于2008年和2004年福建省制造业产值，以县域为基本研究单元，采用K均值聚类法对66个研究单元进行聚类、合并，根据制造业集聚程度将福建省划分为核心区、中间区和外围区3个区域；并测算制造业空间结构的集中度以及产业结构调整对区域集中度变动的贡献率α和产业空间分布变动对制造业空间结构变化的贡献率β，结果表明：核心区制造业高集聚，但集中度呈下降趋势，中间区和外围区的制造业集中度有所上升，但相对缓慢；各产业类型的空间结构及变化均有较大的差异，集中度区域变动较为显著的产业主要有食品加工业、烟草加工业本地资源依赖型行业和皮革、毛皮、羽绒及其制品业等外向度高的行业；本地资源依赖型的木草加工、饮料食品业和原有发展基础影响大的设备制造业等行业的变化是影响福建省制造业空间结构变化的主要原因。     

Prices,policies, and place: What drives greenfield development?

While the recent global financial crisis heightened awareness of the linkages between global financial capital and urban spatial pattern, the timing of urban development – largely thought to be market driven – is not fully understood. Parcel-level studies of urban land-use change, which often use hazard models to investigate if and when development occurs, offer an opportunity to juxtapose the extent to which decisions to develop individual plots of farmland into housing are driven by market forces, the unique characteristics of the land and its intraurban location, or policies such as transportation infrastructure and municipal annexation. Using residential completion data in the Phoenix, Arizona region from 1992 to 2014, a period of dramatic commodity, fuel, and home price swings, and land cover imagery, we develop a parcel-level hazard model to gauge the relative impacts of market, policy, and place-based drivers of land change. We find limited evidence of induced development associated with freeway planning, that annexation and development are closely linked and moreso during economic booms, high fuel prices spur development in the region's core, and agricultural and urban land rents affect the timing of development. This study advances our understanding of development decision- making, policy impacts, and urban land-use change modeling and provides an empirical connection between local and global drivers of Greenfield development.     

GRAPHICAL MODELS FOR CORRELATED DEFAULTS

A simple graphical model for correlated defaults is proposed, with explicit formulas for the loss distribution. Algebraic geometry techniques are employed to show that this model is well posed for default dependence: it represents any given marginal distribution for single firms and pairwise correlation matrix. These techniques also provide a calibration algorithm based on maximum likelihood estimation. Finally, the model is compared with standard normal copula model in terms of tails of the loss distribution and implied correlation smile.     

Correlations between stock returns and bond returns: income and substitution effects

We attempt to better understand the varying correlations between stock and bond returns across countries and over sample periods using international data. The observation is that there are two forces that affect the correlation between stock and bond returns. The force that drives a positive correlation is identified as the income effect. The force that drives a negative correlation is identified as the substitution effect. In combination, the two effects help determine the actual correlation between stock and bond returns. We contribute to the literature by proposing an empirical method, the structural vector autoregression (VAR) identification method, to identify the two—income and substitution—effects and to measure the relative importance of the two effects that determine the actual net relation between the two asset returns. We further provide some evidence that the income and substitution effects are related to, among other things, the size of the financial market, the growth and volatility (risk) of the economy, and the business cycle over time. In addition, the framework of the income and substitution effects helps us better understand the automatic stabilizing effects of the dynamic optimal asset allocation during business cycles.