Overtime Working and Contract Efficiency

We present a wage-hours contract designed to minimize costly turnover given investments in specific training combined with firm and worker information asymmetries. It may be optimal for the parties to work ‘long hours’ remunerated at premium rates for guaranteed overtime hours. Based on British plant and machine operatives, we test three predictions. First, trained workers with longer tenure are more likely to work overtime. Second, hourly overtime pay exceeds the value of marginal product while the basic hourly wage is less than the value of marginal product. Third, the basic hourly wage is negatively related to the overtime premium.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Unemployment Risk and Wage Differentials

Workers in less-secure jobs are often paid less than identical-looking workers in more secure jobs. We show that this lack of compensating differentials for unemployment risk can arise in equilibrium when all workers are identical and firms differ only in job security (i.e. the probability that the worker is not sent into unemployment). In a setting where workers search for new positions both on and off the job, the worker’s marginal willingness to pay for job security is endogenous, increasing with the rent received by a worker in his job, and depending on the behavior of all firms in the labor market. We solve for the labor market equilibrium and find that wages increase with job security for at least all firms in the risky tail of the distribution of firm-level unemployment risk. Unemployment becomes persistent for low-wage and unemployed workers, a seeming pattern of ‘unemployment scarring’ created entirely by firm heterogeneity. Higher in the wage distribution, workers can take wage cuts to move to more stable employment.

Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.