Re-employment hazard of displaced German workers: evidence from the GSOEP

This study investigates the re-employment hazard of displaced German workers using the first fourteen sweeps of the German Socio-Economic Panel (GSOEP) data. As well as parametric and non-parametric discrete-time specifications for the baseline hazard, the study employs alternative mixing distributions to account for unobserved heterogeneity. Findings of the study suggest negative duration dependence, even after accounting for unobserved heterogeneity. In terms of covariate effects, those at the lower end of the skills ladder, those who had been working in manufacturing and those with previous experience of non-employment are found to have lower hazard of exit via reemployment.

Forecasting overseas visitors into the United Kingdom using continuous time and autoregressive fractional integrated moving average models with discrete data

This paper applies Gaussian estimation methods to continuous time models for modelling overseas visitors into the UK. The use of continuous time modelling is widely used in economics and finance but not in tourism forecasting. Using monthly data for 1986–2010, various continuous time models are estimated and compared to autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models. Dynamic forecasts are obtained over different periods. The empirical results show that the ARIMA model performs very well, but that the constant elasticity of variance (CEV) continuous time model has the lowest root mean squared error (RMSE) over a short period.

Volatility and VaR Forecasting in the Madrid Stock Exchange

This paper provides an empirical study to assess the forecasting performance of a wide range of models for predicting volatility and VaR in the Madrid Stock Exchange. The models performance was measured by using different loss functions and criteria. The results show that FIAPARCH processes capture and forecast more accurately the dynamics of IBEX-35 returns volatility. It is also observed that assuming a heavy-tailed distribution does not improve models ability for predicting volatility. However, when the aim is forecasting VaR, we find evidence of that the Student’s t FIAPARCH outperforms the models it nests the lower the target quantile.

Blacklisting and its legacy in the UK construction industry: employment relations in the aftermath of exposure of the Consulting Association

This paper explores responses to the exposure of blacklisting in the UK construction industry in the period following the closure of the Consulting Association (CA) in 2009. It asks whether employer collusion to blacklist in this way has been terminated and concludes that it is now largely of historical interest although other forms of anti-union activity continue. It highlights particularly the historic and continuing importance of ‘double breasting’ and reports on divergent employer paths in the aftermath of the exposure and subsequent closure of the activities of the CA.