Unemployment insurance benefits and income smoothing

Labor unemployment insurance reduces unemployment concerns. We argue that these benefits moderate incentives to smooth earnings to reduce employees’ concerns about unemployment risk. Using exogenous variations in unemployment insurance benefits, we find evidence consistent with this argument. We also find that the link between unemployment insurance benefits and income smoothing is stronger when there is higher unemployment risk and when the firm is likely to employ more low-wage workers, who find unemployment insurance benefits especially useful. Our paper contributes to the literature by showing that public policy decisions such as unemployment insurance have significant, albeit probably unintended, externalities on corporate financial reporting.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.     

延迟退休年龄下隔代抚育与劳动参与的抉择*——基于工资收入随机性假定的研究

隔代抚育会对延迟退休年龄政策在促进劳动力供给上产生挤出效应。为了对此进行验证，本文在工资收入随机性的假定及延迟退休5年的情景下，模拟了面临孙辈照护需求的女性临近退休者提前退休所产生的福利变化。进一步，本文采用CHIP和CHARLS的微观调查数据，对不同群组的收入增长率和收入风险进行了估计，继而分析了当面临孙辈照护需求时这些收入特征对退休决策者制度退休和退休后劳动参与抉择产生的影响。总体上，在延迟退休年龄政策下，隔代抚育将对女性劳动力供给产生挤出效应。当面临孙辈照护需求时，女性临近退休者的制度退休抉择主要受自身收入增长率和收入风险的影响，收入增长率越低，或收入风险越高，她们提前退休的意愿就越强烈；制度退休后的劳动参与则更多地受子女收入增长率的影响，子女收入增长率越高，劳动参与的概率越低。     

Audit Firm Attributes and Auditor Litigation Risk

This study examines the association between auditors' litigation risk and audit firm attributes. Using professional liability insurance premiums as a proxy for auditors' litigation risk, we present evidence that the risk is lower in audit firms having: (1) separate non-audit and audit divisions; (2) a higher proportion of partners; and (3) a higher annual growth in number of CPAs employed. Additionally, we find that the risk is higher in audit firms having: (1) operating losses; and (2) high revenue growth. Our results are consistent with the idea that audit firms' financial condition and organizational structure affect their independence/ expertise, and, in turn, their litigation risk. Our results are broadly supportive of the PCAOB's (2015) and US Department of Treasury's (2008) views that investors, audit committees, management, and other regulators could benefit from having access to financial and organizational information about audit firms.     

The Local Whittle Estimator of Long-Memory Stochastic Volatility

We propose a new semiparametric estimator of the degree of persistencein volatility for long memory stochastic volatility (LMSV) models.The estimator uses the periodogram of the log squared returnsin a local Whittle criterion which explicitly accounts for thenoise term in the LMSV model. Finite-sample and asymptotic standarderrors for the estimator are provided. An extensive simulationstudy reveals that the local Whittle estimator is much lessbiased and that the finite-sample standard errors yield moreaccurate confidence intervals than the widely-used GPH estimator.The estimator is also found to be robust against possible leverageeffects. In an empirical analysis of the daily Deutsche Mark/USDollar exchange rate, the new estimator indicates stronger persistencein volatility than the GPH estimator, provided that a largenumber of frequencies is used.     

Time Inhomogeneous Multiple Volatility Modeling

Price variations at speculative markets exhibit positive autocorrelationand cross correlation. Due to large parameter spaces necessaryfor joint modeling of variances and covariances, multivariateparametric volatility models become easily intractable in practice.We propose an adaptive procedure that identifies periods ofsecond-order homogeneity for each moment in time. To overcomethe high dimensionality of the problem we transform the multivariateseries into a set of univariate processes. We discuss thoroughlythe implementation of the adaptive technique. Theoretical andMonte Carlo results are given. We provide two applications ofthe new method. For a bivariate exchange rate series we comparethe multivariate GARCH approach with our method and find thelatter to be more in line with the underlying assumption ofindependently distributed innovations. Analyzing a 23-dimensionalvector of asset returns we underscore the case for adaptivemodeling in high-dimensional systems.     

The Impact of Institutional Differences on Derivatives Usage: a Comparative Study of US and Dutch Firms

This paper examines the influence of institutional differences on corporate risk management practices in the USA and the Netherlands. We compare results to surveys in each country using a strategy that corrects for differences over industry and size classes across the Dutch and US samples. We document several differences in the firms’ uses and attitudes towards derivatives and attempt to attribute them to the differences in the institutional environments between the USA and the Netherlands. We find that institutional differences appear to have an important impact on risk management practices and derivatives use across US and Dutch firms.     

Is Volatility the Best Predictor of Market Crashes?

The objective of this paper is to determine the best predictor of equity market crashes by focusing particularly on volatility and market liquidity. In finance, volatility has traditionally been regarded as the best measure of market risk. However, this paper shows that the forecast value of market liquidity, in particular our modified calculated market depth, predicts equity market crashes much more accurately than does the forecast values of EGARCH or Implied Volatility.