奖励型众筹模式下考虑银行融资的企业最优运作策略研究

本文研究了企业在奖励型众筹模式下的最优运作策略,同时考虑了众筹融资不足时,企业继续向银行贷款的情况。通过分析众筹项目的运作机制,我们构建了企业在奖励型众筹模式下的决策模型,并研究得到了关于企业研发投入成本,产品生产量及众筹融资目标的最优策略及相关性质。最后,利用Kickstarter众筹平台上的实际数据进行数值实验,本文验证了相关的研究结论。研究表明:1)只有在众筹融资额达到一定阈值的前提下,企业才愿意投入研发成本,此时企业的研发投入成本及产品生产量都将随众筹投资者的需求增大;2)为保证投资者和银行对众筹项目具有投资意愿,同时也为确保众筹成功的项目具有盈利性,存在关于融资目标的可行域,使企业在启动众筹项目时需要将融资目标设置在该可行域内;3)企业通过众筹平台获得的期望融资额不会随融资目标增加,且企业的最优融资目标为融资目标在其可行域中的下界;4)此外,我们通过数值实验还发现最优众筹目标不会随企业的研发效率而增加。     

融资融券约束与股市波动

本文从融资约束和融券约束的视角出发，研究我国股票市场融资机制和融券机制对标的股票波动率的影响。相比于融资融券交易量，约束可以更好地识别融资融券机制的作用，因为它可以从交易渠道、信息渠道、公司治理渠道对股价产生影响。我们利用融资融券机制推进过程中标的证券名单的变化识别融资融券约束放松后的总体效果，然后合理构造子样本识别融资约束的作用，最后利用转融通的实施识别融券约束的作用。研究结果显示融资约束和融券约束的放松显著降低了标的股票的波动率，表明融资融券机制可以发挥稳定股票市场的作用。     

A model selection criterion for clustered survival analysis with informative cluster size

We propose a model selection criterion for correlated survival data when the cluster size is informative to the outcome. This approach, called Resampling Cluster Survival Information Criterion (RCSIC), uses the Cox proportional hazards model that is weighted with the inverse of the cluster size. The RCSIC based on the within-cluster resampling idea takes into account the possible variability of the within-cluster subsampling and the possible informativeness of cluster sizes. The RCSIC allows for easy execution for the within-cluster resampling idea without a large number of resamples of the data. In contrast with the traditional model selection method in survival analysis, the RCSIC has an additional penalization for the within-cluster subsampling variability. Our simulations show the satisfactory results where the RCSIC provides a more robust power for variable selection in terms of clustered survival analysis, regardless of whether informative cluster size exists or not. Applying the RCSIC method to a periodontal disease studies, we identify the tooth loss in patients associated with the risk factors, Age, Filled Tooth, Molar, Crown, Decayed Tooth, and Smoking Status, respectively.     

民营企业跨所有制并购与资本结构调整速度

民营企业混合所有制改革是助推经济高质量发展的重要途径,是拓宽融资渠道、缓解融资约 束、优化企业资本结构的重要抓手,但相关研究相对不足。 利用 2014—2018 年民营上市公司的并购数 据,检验跨所有制并购对资本结构调整速度的作用机理。 研究发现:民营企业跨所有制并购对资本结构 调整速度具有促进作用,且主要是通过降低企业的融资约束、削弱代理成本而实现,融资约束和代理成本 发挥了部分中介效应。 研究结论不仅为缓解企业融资约束及代理问题提供了新的思路和方法,也为保护 关注非公有制企业的发展与融合,促使其发挥民间资本的优势,在混合所有制经济的建设过程中贡献力 量具有积极意义。     

数字普惠金融、金融素养与农户创业

在“大众创业、万众创新”的战略背景下，探究数字普惠金融与农户创业的关系对双创具有重要意义。首先，梳理数字普惠金融影响农户创业的直接和间接作用机制，得出数字普惠金融缓解金融约束促进创业是直接机制、提高农户的金融素养促进创业是间接机制的结论。其次，基于中国家庭追踪调查(CFPS)数据，探究数字普惠金融是否有效促进农户创业。结果表明，数字普惠金融发展能显著促进农户创业，且覆盖更广。数字普惠金融对东中部地区农户创业的促进作用更显著，尤其是社会网络维度广的农户。最后，基于研究结论就进一步发展数字普惠金融促进农户创业提出相应建议。     

企业战略差异度与融资约束 ——基于信息不对称视角的研究

融资约束问题一直是学术界和实务界关注的焦点,企业经营战略的实施会对融资风险产生重要影响.基于2007—2018年中国A股非金融类上市公司数据,从信息不对称这一视角实证检验了企业战略差异度对融资约束的影响.研究发现:(1)企业战略差异度与融资约束显著正相关,即战略差异度越大,企业所面临的融资约束越严重;(2)信息不对称在战略差异度和融资约束之间发挥着中介作用;(3)战略差异度与融资约束的正相关关系在非国有企业、未被"四大"审计的企业、分析师关注度较低的企业以及在经济政策不确定性较高的情况下更加显著.研究结论表明,对于战略差异度较大的企业,要充分重视可能带来的融资约束问题,尤其是在经济政策不确定性较高之时.企业可通过聘请高质量审计机构、吸引更多分析师关注等外部治理手段缓解战略差异度对融资约束的不利影响.     

Incorporating historical information to improve dose optimization design with toxicity and efficacy endpoints: iBOIN-ET

In modern oncology drug development, adaptive designs have been proposed to identify the recommended phase 2 dose. The conventional dose finding designs focus on the identification of maximum tolerated dose (MTD). However, designs ignoring efficacy could put patients under risk by pushing to the MTD. Especially in immuno-oncology and cell therapy, the complex dose-toxicity and dose-efficacy relationships make such MTD driven designs more questionable. Additionally, it is not uncommon to have data available from other studies that target on similar mechanism of action and patient population. Due to the high variability from phase I trial, it is beneficial to borrow historical study information into the design when available. This will help to increase the model efficiency and accuracy and provide dose specific recommendation rules to avoid toxic dose level and increase the chance of patient allocation at potential efficacious dose levels. In this paper, we propose iBOIN-ET design that uses prior distribution extracted from historical studies to minimize the probability of decision error. The proposed design utilizes the concept of skeleton from both toxicity and efficacy data, coupled with prior effective sample size to control the amount of historical information to be incorporated. Extensive simulation studies across a variety of realistic settings are reported including a comparison of iBOIN-ET design to other model based and assisted approaches. The proposed novel design demonstrates the superior performances in percentage of selecting the correct optimal dose (OD), average number of patients allocated to the correct OD, and overdosing control during dose escalation process.     

Efficiency,Equilibrium, and Asset Pricing with Risk of Default

We introduce a new equilibrium concept and study its efficiency and asset pricing implications for the environment analyzed by Kehoe and Levine (1993) and Kocherlakota (1996). Our equilibrium concept has complete markets and endogenous solvency constraints. These solvency constraints prevent default at the cost of reducing risk sharing. We show versions of the welfare theorems. We characterize the preferences and endowments that lead to equilibria with incomplete risk sharing. We compare the resulting pricing kernel with the one for economies without participation constraints: interest rates are lower and risk premia depend on the covariance of the idiosyncratic and aggregate shocks. Additionally, we show that asset prices depend only on the valuation of agents with substantial idiosyncratic risk.     

Approximate exchangeability and de Finetti priors in 2022

This is a review paper, beginning with de Finetti's work on partial exchangeability, continuing with his approach to approximate exchangeability, and then his (surprising) approach to assigning informative priors in nonstandard situations. Recent progress on Markov chain Monte Carlo methods for drawing conclusions is supplemented by a review of work by Gerencsér and Ottolini on getting honest bounds for rates of convergence. The paper concludes with a speculative approach to combining classical asymptotics with Monte Carlo. This promises real speed-ups and makes a nice example of how theory and computation can interact.