2859 1049
KK 923
强积金是香港的强制性公积金计划，旨在为居民提供基本的退休保障。在过去25年里，强积金对香港普惠金融的发展起了重要的推动作用，成功鼓励了家庭参与证券市场。然而，其年化回报率偏低的问题一直备受批评。随着积金易平台即将推出，不同强积金计划将可以整合到统一数码制度中，这正好提供一个有利的契机，以对香港的主要退休储蓄制度作出重大改进。 关颖伦教授、Thomas Maurer教授及太明珠教授分析了导致强积金表现欠佳的三个主要原因：资产配置过于保守，限制了收益潜力；部分强积金产品质量不高，管理或投资策略存在缺陷；以及高昂的费用，直接侵蚀了投资者的回报。针对这些问题，他们向政府提出了以下建议：首先，政府可以修订预设投资策略以进一步降低费率，同时积金局亦可以邀请收费较低的新服务供应商进入市场。其次，政府应积极监察资产配置，透过采取规定性措施、推广理财教育及筛选强积金资讯，协助市场参与者了解强积金复杂的投资产品空间。第三，政府可以开拓强积金的产品空间，引入更多元化的投资选择。最后，积金局应提高数据透明度，并善用其数据资源进行分析。
Innovative firms must trade off disclosing to investors and maintaining secrecy from competitors. We study this trade-off in a sample of IP licenses mandatorily disclosed by US public firms, whose contents can be temporarily redacted. Hand classifying the redacted information, we find that firms with valuable IP in competitive markets redact IP information more often. Markets react positively to the redaction of IP information, consistent with theoretical predictions rationalizing a separating equilibrium in which nondisclosure signals more valuable IP. Our results suggest that credible nondisclosure partially resolves information frictions for innovative public firms when facilitated by sophisticated investors.
基于种种社会经济问题，香港有数十万劳动人口及其家庭已经移居海外。与此同时，受香港政府积极进取的人才计划所吸引，过去一年也有数十万人从外地来港。人口流动对香港的劳动力和人才库有何影响？关颖伦博士、邓希炜教授和王柏林博士通过分析领英（LinkedIn）社交数据和政府统计数据评估香港的劳动力市场和经济前景。
The Dodd-Frank Act shifted regulatory jurisdiction over “midsize” investment advisers from the SEC to state-securities regulators. Client complaints against midsize advisers increased relative to those continuing under SEC oversight by 30 to 40 percent of the unconditional probability. Complaints increasingly cited fiduciary violations and rose more where state regulators had fewer resources. Advisers responding more to weaker oversight had past complaints, were located farther from regulators, faced less competition, had more conflicts of interest, and served primarily less-sophisticated clients. Our results inform optimal regulatory design in markets with informational asymmetries and search frictions.
