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.     

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.     

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。     

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。     

西方现代股利政策理论及实证研究回顾

本文对西方现代公司股利政策方面的理论和实证研究进行了一个综合性的回顾和分析。其中包括主流的股利行为模型、股利的信息内涵、代理成本、追随者效应,也包括国内研究中较少涉及的债务约束、声誉学说、成长机会和交易成本问题,以期对国内相对落后的股利政策研究和随意性较强的股利政策制定带来一定的借鉴意义。     

A consumer education programme based on the Transtheoretical Model of Change

MONEY 2000? is a successful consumer education programme that was implemented by Cooperative Extension personnel in over two dozen states of the USA between 1996 and 2002. One of the unique features of this programme is that it was based on the Transtheoretical Model of Change (TTM), a framework that has been widely used to study health‐related behaviour changes such as smoking cessation. This paper first describes how the MONEY 2000? programme was developed around major constructs contained within the TTM. Findings are reported from a survey conducted with participants in the first two states that delivered the programme. The findings suggest that several change processes used by MONEY 2000? participants are associated with specific stages of change. In addition, there may be differences in behavioural changes between participants who increased their savings and those who reduced their debts.     

Foreign debt and economic growth

This paper empirically examines the relationship between government foreign debt and the growth rate of per capita GDP based on a total sample of 77 countries, as well as sub‐samples of various regions. Cross‐sectional estimates of the coefficient of foreign debt based on the total sample have a negative sign, but are not always statistically significant. Available data from African countries indicate that foreign debt and the growth rate of per capita GDP were negatively related at a high level of significance. For industrialized and Latin American sub‐samples, this relationship is negative but statistically insignificant. The sub‐sample Asian and other developing countries show a positive but insignificant relationship. JEL classification: F34, H6, O23.     

Credit risk and sustainable debt: a model and estimations of why the Euro is stable in the long-run

Sustainable debt has become the key issue in rating of private as well as sovereign debtors. The problem of how to estimate sustainable debt has also been at the center of the debate over the Asian 1997–1998 financial crisis. If the external value of the currency depends on the external debt of a country, it is necessary to estimate the creditworthiness of the country. This paper studies credit risk and sustainable debt in the context of a dynamic model. For a dynamic growth model with an additional equation for the evolution of debt, we demonstrate of how to compute sustainable debt and creditworthiness. The model is estimated by employing time series data for the core countries of the Euro-area. The computations show that the Euro-area has large external assets. Using time series methods, the sustainability of external debt (assets) is estimated for those core countries of the Euro-area. Those estimations show that the Euro will be a stable currency in the long-run.