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.

Does more cycling mean more diversity in cycling?

In low-cycling countries, cycling is not evenly distributed across genders and age groups. In the UK, men are twice as likely as women to cycle to work and cycling tends to be dominated by younger adults. By contrast, in higher cycling countries and cities, gender differences are low, absent, or in the opposite direction. Such places also lack the UK's steady decline in cycling among those aged over 35 years. Over the past fifteen years some UK local areas have seen increases in cycling. This paper analyses data from the English and Welsh Census 2001 and 2011 to examine whether such increases are associated with greater diversity among cyclists. We find that in areas where cycling has increased, there has been no increase in the representation of females, and a decrease in the representation of older adults. We discuss potential causes and policy implications. Importantly, simply increasing cycling modal share has not proved sufficient to create an inclusive cycling culture. The UK's culturally specific factors limiting female take-up of cycling seem to remain in place, even where cycling has gone up. Creating a mass cycling culture may require deliberately targeting infrastructure and policies towards currently under-represented groups.