全球智库信息集成服务系统(G2TT): Multi-Period Corporate Failure Prediction with Stochastic Covariates

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w10743
来源ID	Working Paper 10743
	Multi-Period Corporate Failure Prediction with Stochastic Covariates
	Darrell Duffie; Ke Wang
发表日期	2004-09-06
出版年	2004
语种	英语
摘要	We provide maximum likelihood estimators of term structures of conditional probabilities of bankruptcy over relatively long time horizons, incorporating the dynamics of firm-specific and macroeconomic covariates. We find evidence in the U.S. industrial machinery and instruments sector, based on over 28,000 firm-quarters of data spanning 1971 to 2001, of significant dependence of the level and shape of the term structure of conditional future bankruptcy probabilities on a firm's distance to default (a volatility-adjusted measure of leverage) and on U.S. personal income growth, among other covariates.Variation in a firm's distance to default has a greater relative effect on the term structure of future failure hazard rates than does a comparatively sized change in U.S. personal income growth, especially at dates more than a year into the future.
主题	Econometrics ; Estimation Methods ; Financial Economics ; Corporate Finance ; Macroeconomics ; Money and Interest Rates
URL	https://www.nber.org/papers/w10743
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/568375
推荐引用方式 GB/T 7714	Darrell Duffie,Ke Wang. Multi-Period Corporate Failure Prediction with Stochastic Covariates. 2004.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
w10743.pdf（363KB）	智库出版物		限制开放	CC BY-NC-SA	浏览