Resources for business resilience in a COVID-19 world: A community-centric approach

COVID-19 has drawn renewed focus on the importance of resilience, both among practitioners and in academia, as companies struggle to cope with the rapid swings, changing patterns, and disruptions in supply and demand. This article identifies and delineates a way forward for companies to support resilience, particularly recognizing the wider communities they are nested in and the resources that exist there. To identify such productive resources, known as capitals, we provide a novel and actionable integrated capitals framework (ICF). ICF integrates 10 existing frameworks drawn from both practice and academia and is comprised of nine different forms of capital that businesses can leverage and contribute toward supporting resilience. We provide insights into how businesses can use this framework to achieve resilience through this useful, yet underutilized, path.     

Capital Flows to Latin America (2003–17): A Critical Survey from Prebisch’s Business Cycle Theory

ABSTRACT

The economic literature on capital flows to developing countries has shared two important commonalities since the 1990s. Published works (whether they focus on the external situation or stress the domestic determinants of capital flows) tend to assume a beneficial effect of capital inflows, which leads to an improvement of peripheral institutions, whose deficiencies are ostensibly the main cause of economic turmoil and/or failure in attracting capital flows, in continuity with New Institutional Economics. In doing so, mainstream economists deliberately overlook the asymmetric characteristics of the international monetary system and the persisting hegemony of dollar. Raul Prebisch’s pioneering work on business cycles in Latin America provide an alternative view, one capable of amending the existing mainstream literature. On the one hand, Prebisch stressed the destabilizing role of capital inflows on Latin American economies, particularly short-term speculative capital. On the other hand, Prebisch designed a set of counter cyclical monetary policies in order to contrast capital volatility, particularly during downturns. An analysis of stylized facts shows that, when correctly updated, Prebisch’s theory has remarkable explanatory potential when applied to Latin America’s current economic and financial situation.     

技术创业型企业孵化资本投入的风险管控——来自多案例对比

待孵化的技术创业型企业同时具有概念性技术向差异化产品转化的高风险与产品异质性被认同后溢价评估的高收益特点，导致其投资者多处于隔岸观火却欲罢不能的的孵化投资矛盾中。对孵化资本实施有效的风险管控，成为吸引外部资本投入的关键。基于此，选择在可创概念选育与技术创业孵化领域探索出高成功率路径的概念证明中心、YCombinator和创新工场为研究案例，分析其在创业项目筛选、孵化资金运营等关键环节的风险管控方式，以期完善我国孵化资本管控理论、助力我国商业孵化器提高资金风险管控能力、促进外部资本投入。     

基于状态空间模型的政产学研资协同创新四螺旋影响因素实证研究

在三螺旋理论框架下，搭建政府、产业、大学、研究机构和资本部门四螺旋模型，运用文献归纳法选取多元主体协同创新6类影响因素，以主体间协同程度测度结果为因变量基础，利用状态空间模型动态分析这些因素影响方向、大小和趋势。实证结果表明，中国经济因素表现为促进作用持续提升；中国技术市场规模和创新产业规模表现为先抑制后促进，且促进作用不断提升；中国产品市场需求和创新投入表现为抑制作用持续提升；中国创新产出在时间上表现为促进作用先提升后下降并最终稳定的状态。最后，提出不同政策建议，以促进中国政产学研资协同创新体系后续发展。     

Farm Capital Investment and Deviations from the Optimal Path

We identify farms’ optimal investment path in capital assets and compare it with their actual investment to assess the direction and extent of deviation from the optimal investment. A probit model is further used to investigate the determinants of the probability that a farmer over‐ or under‐invests in capital assets. We use a panel dataset of Dutch dairy farms over the period 2003–2013, and find that most farms under‐invest in capital assets during the study period. Although the number of farms that had over‐invested in capital assets is relatively small, these farms account for the biggest share of total investment in capital assets. The probit results show that liquidity, agricultural support payments, age, land tenure and standard output size are important variables explaining the likelihood of over‐and under‐investment.     

Central bank disclosure as a macroprudential tool for financial stability

The Basel Capital Accord (pillar 3) states that disclosure of information (transparency) is essential to financial stability. This study analyzes, through inflation reports, the disclosure of information from the Central Bank of Brazil concerning the credit market. We consider credit risk and capital buffers as measures of financial stability in this analysis. Furthermore, in order to measure the perception of the monetary authority on the credit market, we built two indices based on the central bank’s communication on credit development. We performed a panel data analysis based on a sample of 125 banks for the period from June 1999 to September 2014 (7000 observations). The findings suggest that central bank communication regarding expectations concerning the credit market contributes to financial stability. Therefore, this kind of communication of central banks (about credit development) may constitute an important macroprudential tool to improve financial stability.     

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。     

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.