Are REITs more resilient than non-REITs? Evidence from natural experiments

REITs draw attention from investors around the world, yet our understanding of the various risks associated with such securities is limited. Using the introduction of Arrowhead, a low-latency high-frequency trading platform, to the Tokyo Stock Exchange and the financial crisis of 2008 as natural experiments, we compare the resilience of REITs and equities in terms of liquidity and volatility. The results indicate that the introduction of Arrowhead improved the quality of the Japanese REIT market but also increased the probability of flash crashes. We also find that although the financial crisis significantly deteriorated overall equity market quality, the Japanese REIT market was resilient. Finally, using a difference-in-differences regression model, we show that the higher transparency and better price discovery of REITs, compared to non-REITS, protected them from the negative effects of the financial crisis and the introduction of Arrowhead. Overall, our analysis shows that REITs are more resilient than non-REITs.     

A truly global crisis? Evidence from contagion dependence across international REIT markets

This study examines the global nature of the recent crisis under bivariate Markov-switching models for pre- and post-crisis periods using the breakpoint of August 9, 2007. It quantifies international synchronization of boom-bust regime switches to investigate contagion-type dynamic comovements of Real Estate Investment Trusts (REITs). Global REIT markets display persistent bust regimes from September 2008 to May 2009, whereas the regime-switching patterns are not significant in the pre-crisis period. The results provide new evidence for global REIT contagion phenomena and suggest greater difficulties in diversifying risks across global REIT markets during the post-crisis period.     

人民币跨境流动自由度的测算——基于资本项目名义开放指数的借鉴

长期以来,人们只看重货币国际化结果,以占全球贸易计价结算比重、外汇交易比重、国际债券比重、外汇储备比重等相关指标衡量一国货币的国际化程度,而忽视货币跨境流动放松过程,即一国货币的跨境流动自由化程度。货币国际化是一个过程又是一种结果,包含进程和结果两个层面,在货币国际化进程中,过早过快放松本币流出入会引发经济金融风险,某些情形下进程比结果更值得关注。构建人民币跨境自由度指数涉及强度赋值、项目设置和权重确定三方面内容。在梳理2019年第2季度前我国货币政策基础上,对2008年至2019年经常项目下的人民币跨境流动自由度、证券投资项目下的人民币跨境流动自由度以及资本项目下的人民币跨境流动自由度进行评估,并以美国近5年各项目下的资金流动平均占比为权重,构建了人民币跨境流动自由化指数,考察2008—2019年人民币跨境流动自由化程度,结果显示人民币国际化进展较快,跨境流动已得到很大程度放松,而且人民币流入自由程度显著高于流出自由度。我国人民币国际化进程应持续遵循先经常项目后资本项目、先流入后流出、先机构后个人、先大额后小额、先风险小项目后风险大项目的次序,提高人民币跨境流动的稳定性,降低无序流动的投机风险;严格管控证券投资、其他投资、衍生品项目下人民币跨境流动,并依据我国利率市场化程度、金融市场发达程度及审慎监管能力进行调整;大力提升经常项目的人民币结算比重,发展人民币离岸市场,提高非居民间的人民币使用频率和使用规模;充分评估各项目下人民币跨境流动和本外币兑换自由度,提高两者的协同匹配程度,降低因两者不匹配而产生的负面影响。     

全国煤炭交易中心运营模式研究

全国煤炭交易中心的设立对规范我国煤炭交易市场规则、实施能源宏观调控、提升我国煤炭国际定价话语权具有重要意义。在分析全国煤炭交易中心功能定位和业务的基础上,设计中长期合同邀约、现货挂牌、现货竞价、现货招投标4种交易模式及业务流程,提出依托国家重大战略争取政策支持、加强各方沟通完善综合物流体系、建立银企合作机制与信用体系、完善煤炭交易中心协调机制、增强信息服务与风险防控能力等对策建议。研究成果对优化煤炭供给结构、规范煤炭交易市场和保障国家煤炭能源安全提供了支撑。     

庚子赔款的债务化偿付及其影响

庚子赔款是中国近代史上最大一笔赔款,也是以长期债务形式体现的赔款。本文对庚子赔款的债务化偿付安排、利率水平、支付流程及经济影响等进行比较分析。发现:(1)庚子赔款本金4.5亿两,是清政府 1903 年财政收入的 4.33倍,但通过债务化偿付,每年支付赔款占财政收入比重逐步下降;(2)按购买力折算,庚子赔款本金约占1900年中国GDP的2.1%;(3)与当时主要国家长期债务利率相比,庚子赔款4%的利率属于中等水平;(4)将庚子赔款与德国“一战”赔款进行比较,发现赔款本金和占经济总量比重,中国低于德国,但中国每年支付赔款的财政压力高于德国;(5)庚子赔款偿付对近代中国的财税金融产生深刻影响,外籍海关税务司借机成为独立于中国政府的“第二财政”,外商银行藉此强化其“隐性中央银行” 地位,赔款还催生了货币流通的“新周期” 和“新危机”。总体上,赔款的债务化偿付安排不仅受政治外交形势主导,也与金融机构特别是银行跨国经营存在密切联系。赔款的经济影响不仅取决于偿付总量,也取决于经济治理能力和财税金融制度。国家财税金融制度落后,则受到冲击较大。     

Is it still economic to build a new coal-fired power plant in the U.S.? A real option analysis

In the U.S., virtually no new coal-fired power plants have been built in recent years. Both industry experts and academics seem to believe that no rational firm will build a new coal-fired plant. Will such a trend continue in the future? To provide insights into this question, we investigate the optimal decision of an electricity company with an irreversible and deferrable opportunity to build either a new coal-fired or natural gas-fired power plant as its new base-load resource. According to our real option analysis, the optimal decision depends on the location. In the case of the eastern U.S., it is optimal to choose a natural gas plant if a firm is given a choice among a new natural gas plant, a new coal plant and deferring the investment. However, contrary to the common sentiment in the industry and academia, building a new coal plant in the western U.S. is still more economical than building a new natural gas plant in the absence of emission pricing. Furthermore, introducing carbon pricing to western U.S. states, as California did, can substantially increase the probability that a firm will optimally choose a natural gas plant over a coal plant.     

Cryptocurrencies and Cagan’s model of hyperinflation

The drivers of the prices of Bitcoin and Ethereum are studied within a framework based on Cagan’s model of hyperinflation. In the model, the prices of the cryptocurrencies are driven by stochastic adoption and velocity shocks as well as endogenous expectations of future prices. The model is estimated with data for prices, transaction volumes, and money supplies. A majority of price fluctuations in both currencies can be attributed to shocks in adoption, velocity shocks are much less important. The money demand sensitivity to expected price changes is estimated to be larger for Bitcoin than for Ethereum, and both have higher sensitivity than fiat currencies during episodes of hyperinflation.     

Characteristics and implications of Chinese macroeconomic data revisions

The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.     

What determines the long-term correlation between oil prices and exchange rates?

In this study, we obtain the long-term correlation between oil prices and exchange rates by employing the dynamic conditional correlation-mixed data sampling (DCC-MIDAS) model. We then identify the factors that influence the long-term correlation using panel data analysis. We find that the long-run correlations between oil prices and exchange rates are negative for all oil-exchange rate markets except Japan. We also find that both inflation and term spread have negative effects, while the risk-free interest rate has a positive effect on the long-term correlation between oil prices and exchange rates. Importantly, the empirical results show that an increase in inflation will significantly damage the real value of the currency itself.     

On credit and output: Is the supply of credit relevant?

The consensus that changes in the supply of credit were irrelevant to making monetary policy decisions existed among macroeconomists during the second half of the twentieth century. Transmission of shocks to the real economy through changes in the supply of credit, however, played an important role in the recent U.S. financial crisis. This paper explores the extent to which policymakers should consider changes in the supply of credit when making forecasts and monetary policy decisions. More specifically, it considers whether a measure of real credit balances offers consistent and stable information, beyond that of a real interest rate and real money balances, about future output gaps during the U.S. post-war era. Results yield evidence that changes in real credit balances are the only variable, among those considered, to provide consistent and stable information about future output gaps over the entire sample period. Each information variable, however, provides relatively little value added for forecasting future output gaps, beyond a simple autoregressive model. To improve upon forecasts and monetary policy decisions, policymakers therefore should consider a broader range of information variables and occasionally reassess the relative weightings assigned to each.