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.

Should I stay or should I go? Sibling effects in household formation

This paper analyzes peer effects among siblings in the decision to leave parental home. Estimating peer effects is challenging because of problems of refection, endogenous group formation, and correlated unobservables. We overcome these issues using the exogenous variation in siblings' household formation implied by the eligibility rules for a Spanish rental subsidy. Our results show that sibling effects are negative and that these effects can be explained by the presence of old or ill parents. Sibling effects turn positive from older to younger close-in-age siblings, when imitation is more likely to prevail. Our findings indicate that policy makers who aim at fostering household formation should target the household rather than the individual and combine policies for young adults with policies for the elderly.