Testing vertical price transmission for Vietnam's Robusta coffee

Vietnam has undergone market reforms over the last three decades; and as a consequence, the coffee sector has become increasingly market‐driven. The success of the government's liberalisation policies in terms of market efficiency is investigated by examining the transmission of both positive and negative price changes for Robusta coffee between export and farmgate prices. We used a threshold vector error correction model and high‐frequency daily data. The primary result here is that of a symmetric price transmission between export and farm‐level prices. This result holds when tested with weekly price data, derived from the daily data. Farmgate prices respond faster to decreases than increases in export prices when the long‐run deviation exceeds a certain threshold. These price changes are transmitted within several days. This research also confirms the importance of transaction costs, and other price frictions mostly ignored in prior analyses for coffee.     

颠覆性创新四阶段扩散过程模型

基于颠覆性创新、创新扩散、创新模糊前端等相关理论，从全流程角度创新性地构建了颠覆性创新四阶段扩散过程模型，包括颠覆性创意产生、颠覆性创新产品开发、侵蚀非主流市场、占据主流市场4个阶段，各阶段之间相互关联、循环往复，并受到技术、市场、政策、竞争等外部环境因素影响。选取液晶电视机和山寨手机作为高端和低端两个颠覆性创新典型案例，通过对其进行验证性分析，构建具体的高端与低端颠覆性创新四阶段扩散过程模型。     

中国北方大规模生猪养殖技术效率研究

[目的]通过对我国北方地区大规模生猪养殖技术效率进行测度,以期发现影响其技术效率增长的主要因素,为我国现阶段生猪养殖业战略性区划调整"南猪北进"工作提供实践指导和理论支持。[方法]根据随机前沿分析方法 (SFA)基本原理,运用对数型柯布—道格拉斯生产函数及我国北方大规模生猪养殖数据构建中国北方大规模生猪养殖随机前沿分析模型,对我国北方大规模生猪养殖技术效率进行测度并据此提出相关建议。[结果]北方地区大规模生猪养殖技术效率值纵向上来看整体在不断下降,而从地域上来看内蒙古自治区和东北地区技术效率值较高,北京与西北地区技术效率值较低。[结论]内蒙古自治区与东北地区适宜作为大规模生猪养殖承载地,与国家政策具有一致性;华北地区与西北地区大规模生猪养殖技术效率测度值较低,存在较大改进空间;针对该现状提出构建经济效益与环境保护并重的规模生态生猪养殖体系。     

Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks

We investigate the relationship between Bitcoin and conventional financial assets from a perspective on the connectedness of asset networks. We adopt the method of measuring connectedness proposed by Diebold and Yilmaz (2009, 2012, and 2014) in a VAR system to study the dynamic interdependence between returns in Bitcoin, stocks, oil, and gold. We find that the connectedness between bitcoin and conventional assets is weak. The separation of positive and negative returns in the Bitcoin market shows the existence of an asymmetric pattern of the spillover effects between Bitcoin and conventional assets. A rolling window analysis finds that although Bitcoin prices experience a rising link to other financial assets, the magnitude is proven to be moderate. However, connectedness via negative returns is much stronger than via positive ones and exhibits a clearly increasing trend in recent periods. Our results in application are generally robust to other popular cryptocurrencies, such as ETH and Ripple. The findings presented in this paper have important implications for financial market participants, policymakers, and researchers in light of projected increases in the adoption of Bitcoin, as well as the rapid development of cryptocurrency.     

The price of going green: the role of greenness in green bond markets

In this paper, we empirically investigate how greenness information is priced in the green bond market. Our comparison of liquidity-adjusted yield premiums of green bonds versus synthetic conventional bonds indicates that, on average, there is no robust and significant yield premium or discount on green bonds. However, green bonds certified by an external reviewer enjoy a discount of about 6 bps. Furthermore, green bonds that obtain a Climate Bonds Initiative certificate show a discount of around 15 bps. The findings suggest that a universally accepted greenness measure can benefit the development of the green bond market.     

How efficient is the market for Australian firms’ earnings information?

We construct a measure of the speed with which forecasts issued by sell-side analysts accurately forecast future annual earnings. Following Marshall, we label this measure earnings information flow timeliness (EIFT). This measure avoids the aggregation problem inherent in price-based measures of information efficiency. We document large variation in EIFT across firm-years, and show that EIFT is positively associated with the extent of analyst following, consistent with increased analyst coverage improving the speed with which earnings-related information is recognised. We also find that EIFT is higher for firm-years classified as ‘bad news’ (i.e., where analysts’ forecasts at the start of the financial period exceed the reported outcome). However, when we separately consider instances where analysts appear to forecast non-GAAP (or ‘street’) earnings rather than GAAP earnings, we find that the greater timeliness of bad news is concentrated among observations where analysts forecast non-GAAP earnings, where unusual items are typically excluded. We conclude that the market for accounting information is more efficient for negative operating outcomes than for negative outcomes reflecting unusual items.     

Do news shocks increase capital utilization?

Using the workweek of capital as a measure of capital utilization, we empirically test whether news shocks actually increase capital utilization. To this end, by estimating a panel VAR on two-digit manufacturing data identifying news shocks as innovations to stock returns orthogonal to the variations in current-period TFP growth, we find the positive response of capital utilization to news shocks. Moreover, to explain the positive response of capital utilization to news shocks in terms of plant-level investment behavior, we propose a heterogeneous plant model that combines the fixed cost of capital adjustment and an endogenous capital utilization choice. With the presence of fixed costs, except for the plants that have recently adjusted capital stock, news shock shortens the effective time horizon of currently installed capital stock and increases capital utilization. When the model economy is calibrated to match the salient features of the plant-level investment rate distribution, the economy generates a news-driven positive response of capital utilization.     

Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade

This paper examines the correlation and the dependence patterns of the Qatar stock market with other markets using copula statistical theory and exploiting new datasets covering the period August 1998 to June 2018. To examine the crisis –specific change in the average degree of dependence we decomposed the data into the time periods before and after oil price shocks and the 2017 political crisis among the Gulf Cooperation Council members (i.e. the Qatari blockade). Our findings from the static copula modelling show that the correlations between the Qatari and the other stock markets significantly change after the oil price and the blockade crisis as well. The degree of change in the correlation is time varying and differs from county-group to another. Moreover, our findings reveals that the 2008 global financial crisis has a stronger impact than the price shocks and political crisis. The findings of the paper are of interest and allow for formulating a reliable and dynamic portfolio design framework for investors and risk managers.     

Bubbles for Fama

We evaluate Eugene F. Fama's claim that stock prices do not exhibit price bubbles. Based on US industry returns (1926?2014) and international sector returns (1985?2014), we present four findings (1) Fama is correct in that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward; (2) such sharp price increases predict a substantially heightened probability of a crash but not of a further price boom; (3) attributes of the price run-up, including volatility, turnover, issuance, and the price path of the run-up, help forecast an eventual crash; and (4) these attributes also help forecast future returns. Results hold similarly in US and international samples.