Contracting and Reporting Conservatism around a Change in Fiduciary Duties*

We exploit an influential 1991 Delaware court ruling to examine simultaneously two types of conservatism that play important roles in resolving creditor–owner agency conflicts: contracting conservatism and reporting conservatism. The ruling expanded managerial fiduciary duties in favor of creditors for Delaware-incorporated firms in the vicinity of insolvency. In those firms, following the ruling, debt contracts are less likely to include conservative adjustments to accounting numbers used for covenant compliance (i.e., contracting conservatism decreases), while public financial reporting becomes more conservative (i.e., reporting conservatism increases). The decrease in contracting conservatism is concentrated in firms that exhibit a greater increase in reporting conservatism, suggesting that reporting conservatism is more cost-effective in resolving agency conflicts. In addition, the substitution effect is more pronounced in firms facing greater business uncertainty and firms with greater board independence.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Policy induced increases in private healthcare financing provide short-term relief of total healthcare expenditure growth: Evidence from OECD countries

Healthcare reforms have long been advocated as a cure to the increasing healthcare expenditures in advanced economies. Nevertheless, it has not been established whether a market solution via private financing, rather than public financing, curb aggregate healthcare expenditures. To our knowledge, this paper is the first that quantifies the impact of reforms that significantly increases (decreases) the private (public) share of healthcare financing on total healthcare expenditures relative to income in 20 OECD countries. Our reform measure is based on structural break testing of the private share of total expenditures, and verification using evidence of policy reforms. To quantify the effect of these reforms we apply Propensity Score Matching and Inverse Probability Weighted regression analysis. Over a 5-year evaluation period the reforms lead to an accumulated cost saving 0.45 percentage points of GDP. The yearly effects of the reforms are largest in the first years in the post-reform period and decreases in size as a function of time since the reform. Our findings suggest that the investigated healthcare reforms have a relatively short-lived effect on aggregate health spending relative to GDP. The findings are robust to various sensitivity tests.     

Some Potential Linkages for Input-Output Analysis with Flow-of-Funds

Three major, interrelated accounting statements, at the frontiers of quantitative economic analysis, are three interrelated systems, namely: (1) National income and product accounts (NIPA), (2) The input-output tableaux, (IO), and (3) flow-of- funds accounts (FF). The third-mentioned system is somewhat less available and used in only limited areas of macroeconomic analysis. This paper is mainly concerned with use of FF accounting systems. This system shows where financial resources originate, and where they go in support of real capital formation. In this respect, interest rates and other market-based financial rates are of key importance. While much macroeconomic analysis is based on the rates that fit the yield curve, showing the interest rate structure over various maturities of debt associated with a given degree of risk. In contrast, the FF accounts throw light on the whole spectrum of interest rates, across maturities and debt qualities. For example, in analysis of the real estate market and funding of capital formation there, it is important to have a full understanding of the course of mortgage rates of different maturities and qualities. In short, it is necessary to develop a full appreciation of supply and demand forces in the mortgage market, which often is not obviously related to movements of the operative rate for monetary policy, such as very short-term inter bank rates or call money rates. This paper attempts to provide material from the flow-of-funds accounts that would make it possible to analyze the movement of relevant mortgage rates or whatever other rates are needed to understand the financing of capital formation in real estate.     

民营企业发展的金融支持

文章首先回顾了民营企业融资研究的有关成果.其次,详细分析了目前我国民营企业存在的金融约束.最后,尝试给出了一些建议以加强对民营企业的金融支持.     

The financing decisions of REITs: The case of warrant extensions

In this paper, we examine the warrant price and stock price reactions to the announcement of warrant life extensions by REITs. As predicted by option pricing theory, warrant prices increase in response to these extensions. The stocks of REITs making the extension announcements experience average abnormal returns that are not significantly different from zero. Thus, total firm value appears to increase, with the gains accruing primarily to the warrantholders.     

我国国债的风险评估与防范

从国债的可持续性、国债的货币扩张效应、国债对经济增长的影响三个层面评估了我国当前的国债风险，并针对我国的国债特点，提出了防范国债风险的措施。     

Debtor-in-possession financing

Several recent papers have documented the benefits of debtor-in-possession (DIP) financing in the restructuring of firms in Chapter 11. However, the view on benefits is not unanimous and some legal scholars have raised doubts about DIP financing's effects on debt-holders and the possibility of expropriative wealth transfers. In this paper we address this issue by analyzing both stock and bond price data for a comprehensive sample of DIP loans and find significant positive abnormal stock and bond returns at the announcement of DIP loans. Also, we do not find evidence of wealth transfers from junior to senior debt-holders. Further, we examine the DIP loan process in detail and we document important institutional features of DIP loans such as maturity, covenants, fees and interest charges. We find evidence of intense monitoring using covenants. We also find higher fees and charges associated with DIP loans. We argue that overall the results are consistent with the information processing role of financial intermediaries.     

城市轨道交通项目融资的偿债能力分析

城市轨道交通项目融资的贷款人并不是项目所有者,不可能从项目的投资中获得股本收益。因此,当贷款人在考察是否为采用项目融资方式建设的城市轨道交通项目提供融资时,所关心的重点是项目未来的偿债能力。本文在分析偿债资金来源的基础上,构造城市轨道交通项目的现金流模型,并从贷款偿还期、债务覆盖率、利息覆盖率、债务承受比率等方面,对城市轨道交通项目融资的偿债能力进行分析。     

国债规模的均衡数量及优化

笔者基于世代交叠模型,假定政府执行赤字预算体制,在市场结清的均衡状态下得到了确定国债规模与私人资本规模之比值的解析式。通过模拟发现税率、基本财政支出率、产出关于私人资本的弹性等是决定该比值大小的主要因素。