Appraisal-Based Real Estate Returns under Alternative Market Regimes

In this article we use Monte Carlo simulation to study the statistical properties of real estate returns. We set up a model where transactions prices are noisy signals of true prices. We then consider a number of appraisal rules, derived from Bayesian and non-Bayesian theory, to estimate the current true price and rate of return. The class of exponential smoothing and Kalman filter rules perform well at both the disaggregate (returns on an individual property) and aggregate (returns on a real property portfolio) levels. A special case of exponential smoothing (α= 1.0) places all weight on current market data. Since this case eliminates smoothing, our results suggest that appraisers should place all weight on current data (no weight on past data) provided that they want to estimate returns rather than values. However, these results should be used with caution if sales prices are very noisy.     

Estimating Returns on Commercial Real Estate: A New Methodology Using Latent-Variable Models

Despite their widespreao use as benchmarks of U.S. commercial real estate returns, indexes produced by the National Council of Real Estate Investment Fiduciaries (NCREIF) are subject to measurement problems that severely impair their ability to capture the true risk–return characteristics–especially volatility–of privately held commercial real estate. We utilize latent-variable statistical methods to estimate an alternative index of privately held (unsecuritized) commercial real estate returns. Latent-variable methods have been extensively applied in the behavioral sciences and, more recently, in finance and economics. Unlike factor analysis or other unconditional statistical approaches, latent variable models allow us to extract interpretable common information about unobserved private real estate returns using the information contained in various competing measures of returns that are measured with error. We find that our latent-variable real estate return series is approximately twice as volatile as the aggregate NCREIF total return index, but less than half as volatile as the NAREIT equity index. Overall, our results strongly support the use of latent-variable statistical models in the construction of return series for commercial real estate.     

改进的SWOT技术在房地产企业发展战略中应用

SWOT技术主要是通过对企业所面临的内、外部因素进行分析,从而制定企业发展战略.传统的SWOT技术,侧重于对企业进行定性分析.在与层次分析法结合后对传统的SWOT技术进行了改进,侧重于对企业定量分析,提高了企业制定发展战略的科学性和准确性.以房地产企业为例,进行了详细的定量分析.     

A Different Look at Commercial Real Estate Returns

Commercial real estate makes up a relatively small percentage of most institutional portfolios, even though the existing literature has consistently reported attractive risk-return characteristics that would suggest much larger allocations. This discrepancy has been explained by a perceived lack of comparability between return series calculated for real estate and those calculated for other asset classes. Just as investors actively involved in the futures markets do not consider individual common stocks to be traded continuously, those active in the stock market do not consider real estate to be traded continuously. In both cases, adjustments to reported returns are necessary to achieve a degree of comparability. This study makes such adjustments, using sales data from properties that help comprise the National Council of Real Estate Investment Fiduciaries / Frank Russell Company (NCREIF/FRC) Index to generate a "transaction-driven" commercial real estate return series. Examination of the risk-return characteristics of this series shows that it is quite different from traditionally reported real estate return series and far more consistent with risk-return characteristics that have been reported for other asset classes.     

Do Common Risk Factors in the Returns on Stocks and Bonds Explain Returns on REITs?

The monthly returns on equity and mortgage real estate investment trusts (REITs) are analyzed over the period July 1976 to December 1992. The results indicate that risk premiums on equity REITs are significantly related to risk premiums on a market portfolio of stocks as well as to the returns on mimicking portfolios for size and book-to-market equity factors in common stock returns. Mortgage REIT risk premiums are significantly related to the three stock market factors and two bond market factors in returns. Also, mortgage REIT shares underperform by an average of 6.8% per year.     

The Motivation for Institutional Real Estate Sales and Implications for Asset Class Returns

Since real estate assets are sold infrequently, analyses that use samples of exclusively sold properties to estimate pricing models may be seriously in error. This paper uses data on samples of sold and unsold properties and an appropriate statistical methodology to evaluate the extent of this bias. The results clearly show that it is important to control for sales motivations and that pricing equations that ignore this source of bias may be misleading.     

The Impact of Market Imperfections on Real Estate Returns and Optimal Investor Portfolios

This study investigates the consequences of several imperfections associated with real estate markets on pricing and optimal investor portfolios from a CAPM context. CAPM assumptions are relaxed to recognize illiquidity, the consumption and investment attributes of owner-occupied housing, and a mildly segmented market structure. The study finds that relaxing the CAPM assumptions lead to a separate pricing paradigm for financial assets, income-producing real estate and owner-occupied housing respectively, that a "dividend effect" arises for real estate as the result of illiquidity, and that illiquidity reduces the extent to which investors hold real estate in their portfolios.     

Gains From Diversifying Into Real Estate: Three Decades of Portfolio Returns Based on the Dynamic Investment Model

This paper compares the investment policies and returns for portfolios of stocks and bonds with and without up to three categories of real estate. Both domestic and global settings are examined, with and without the possibility of leverage. The portfolios were generated via the dynamic investment model based on the empirical probability assessment approach applied to past (joint) realizations of returns, both with and without correction for "smoothing" in the real estate data series. Our principal findings are: (1) the gains from adding real estate, on a semi-passive (equal-weighted) basis, to portfolios of either U.S. or global financial assets were relatively modest; in contrast, (2) the gains from adding real estate to the universe of U.S. financial assets under an active strategy were rather large (in some cases highly statistically significant), especially for the very risk-averse strategies; (3) the gains from adding U.S. real estate to a universe of global financial assets under an active strategy were mixed, although generally favorable for the highly risk-averse strategies; (4) correcting for second-moment smoothing in the real estate returns series had a relatively small impact for the more risk-tolerant strategies; and (5) there was some evidence that desmoothing resulted in improved probability estimates.     

The Effects of Rate Regulation on Mean Returns and Non-Diversifiable Risk: The Case of Cable Television

Anticipated effects of rate controls are best observed in abnormalreturns in sectors providing complements and substitutes to the sector targeted for regulation. Further, risk may rise in response to rate controls, increasing the cost of capital and lowering investment. We examine stock price movements during events tied to the 1992 Cable Act, which reinstituted price controls on U.S. cable TV operators. We find strong evidence that controls were not anticipated to lower quality-adjusted cable rates. In addition, the uncertaintyof the policy led to substantially increased stock betas in some sectors.     

房地产上市公司财务风险识别及处置措施研究

论文以我国沪深两市8家房地产上市公司为研究样本,采用上市公司发生财务危机前2年的实际财务数据,选用主成分分析方法建立了财务风险识别模型,进行财务风险识别,并提出了房地产企业财务风险控制以及财务风险处置措施,如降低资产负债率、合理安排收款计划、加快房地产的变现等,为房地产企业进行财务风险管理提供参考。针对该类公司财务风险管理方面存在的一些问题提出了相应的解决对策,即调整资产负债结构、加强对外担保管理等。     

基于ISM的临港产业集群风险系统分析

在分析临港产业集群面临的基础设施风险、产业关联风险、持续稳定风险、公共管理风险和不可抗力风险、物流项目风险等因素及多重关联影响的基础上,应用解释结构建模方法(ISM)建立了临港产业集群风险系统的结构模型。文章结合宁波临港产业集群的具体实例,并着重探讨了方法的应用和结果的分析。     

商业模式的系统分析与启示

商业模式是企业保持竞争优势的重要方式,本文从系统角度分析了商业模式的本质,以系统思考理论为基础构建了商业模式的系统循环图,分析了商业模式系统的结构、行为和性能之间的内在联系,并对企业如何实现企业商业模式创新提出了建议.     

Cost and benefits from infrastructure competition. Estimating welfare effects from broadband access competition

Competition between parallel infrastructures incorporates opposing welfare effects. The gain from reduced deadweight loss might be outweighed by the inefficient duplication of an existing infrastructure. Using data from broadband Internet access for western Europe 2000–04, this paper investigates which effect prevails empirically. Infrastructure competition between DSL and cable TV had a significant and positive impact on the broadband penetration. However, comparing the additional social surplus attributable to cable competition with the cable investments, it can be concluded that, in the absence of significant positive externalities, infrastructure competition has probably not been welfare enhancing.     

系统科学视角下的乔布斯

创新型人才是建设创新型国家的关键。系统科学视角下的美国最富代表性的创新人物史蒂夫·乔布斯的成长过程具有耗散性、混沌性和协同性等系统特征。鼓励创新、宽容失败、尊重个人价值的系统环境以及创新教育、快速发展的风险投资业和不断交汇的人文与科技等系统要素是史蒂夫.乔布斯成长的关键。因此,我们应该采取加强创新创业教育、推广通识教育、鼓励风险投资业发展等措施,改善创新环境,这对于我们成功实现＂十二五＂规划和《国家中长期人才发展规划纲要》以及十七届六中全会的要求,具有重要的现实意义。     

Inferring an Investment Return Series for Real Estate from Observations on Sales

Accurate measurement of the returns to real estate investment are essential to sound analysis. This paper improves upon the traditionally employed method—collecting comparable sales data. A dynamic model of real estate appraisal is developed in which agents have incomplete information, heterogeneous search costs, and varying expectations. Various types of simulation analysis of the model indicate it performs best in the sense that the return estimate converges to the true value faster than other simpler rules.     

Estimating obsolescence risk from demand data to enhance inventory control—A case study

In this paper obsolescence of service parts is analyzed in a practical environment. Based on the analysis, we propose a method that can be used to estimate the risk of obsolescence of service parts, which is subsequently used to enhance inventory control for those parts. The method distinguishes groups of service parts. For these groups, the risk of obsolescence is estimated using the behavior of similar groups of service parts in the past. The method uses demand data as main information source, and can therefore be applied without the use of an expert's opinion. We will give numerical values for the risk of obsolescence obtained with the method, and the effects of these values on inventory control will be examined.     

The Disciplining Effect of Concern for Referrals: Evidence from Real Estate Agents

Real estate agents rely on clients for referrals to generate future business; this article examines whether concern for referrals disciplines agents. We compare results for sellers who move to another area (and are less likely to provide referrals) with results for sellers who remain in the area (and are more likely to provide referrals). We find that moving‐away sellers’ houses have a higher sale rate, sell faster and sell for less (even after controlling for moving‐away sellers’ greater impatience). We also provide evidence that the disciplining effect of concern for referrals is stronger for agents who place a greater value on reputation. Finally, among sellers who are better at evaluating and monitoring agents, we see less of the high sell rate, low sale‐price effect.     

Estimating willingness-to-pay for broadband attributes among low-income consumers: Results from two FCC lifeline pilot projects

Recent studies have confirmed that broadband adoption (as opposed to simply having access to broadband infrastructure) is positively linked with economic growth. In light of this, federal policy efforts have switched from focusing mainly on the provision of infrastructure to more explicit adoption-oriented efforts. One of those efforts was the Federal Communications Commission’s (FCC’s) Low-income Broadband Lifeline Pilot Projects, which ran from 2013 to 2014. The program worked with 14 private telecommunications firms to subsidize household broadband adoption for low-income households by providing discounted monthly and equipment costs. Low-income households are an important component of the broadband adoption puzzle: between 2003 and 2013, the adoption gap between low-income and high-income households actually increased by 5% points. This paper focuses on two specific FCC Broadband Lifeline Pilot projects that allowed consumers to make choices among different options, such as data allowance, speed, and wireless vs. wired connections. Conditional logit models are used to develop estimates of consumer’s willingness-to-pay for specific broadband attributes. The results indicate that low-income consumers have a preference for smartphone connections (versus aircards) – and that this effect is even more pronounced for those households earning less than $20,000; that low-income consumers have a preference for wired connections (versus wireless); and that there is evidence that low-income consumers are willing to pay for an extra GB of data each month – but not for the speed of their connection.     

Estimating the adoption of Bt eggplant in India: Who Benefits from public–private partnership?

The study analyzes ex ante the adoption of insect-resistant Bt eggplant technology in India. Farmers’ willingness to pay (WTP) is estimated using the contingent valuation method. Given the economic importance of insect pests in eggplant cultivation, the average WTP for Bt hybrids is more than four times the current price of conventional hybrid seeds. Since the private innovating firm has also shared its technology with the public sector, proprietary hybrids will likely get competition through public open-pollinated Bt varieties after a small time lag. This will reduce farmers’ WTP for Bt hybrids by about 35%, thus decreasing the scope for corporate pricing policies. Nonetheless, ample private profit potential remains. Analysis of factors influencing farmers’ adoption decisions demonstrates that public Bt varieties will particularly improve technology access for resource-poor eggplant producers. The results suggest that public–private partnership can be beneficial for all parties involved.