Evaluating Specification Tests for Markov-Switching Time-Series Models

We evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung–Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung–Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar–British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data.

The business of myth-making: Mary Poppins, P.L. Travers and the Disney effect

In just one of the many extraordinary moments during the spectacular Opening Ceremony of the 2012 London Olympic Games, thirty Mary Poppinses floated into the stadium on their umbrellas to battle a 40 foot-long inflatable Lord Voldemort. This multi-million pound extravaganza was telecast to a global audience of over one billion people, highlighting in an extremely effective manner the grandeur and eccentricities of the host nation, and featuring uniquely British icons such as Mr Bean, James Bond, The Beatles and Harry Potter, as well as those quintessential icons of Englishness, the Royal Family, double-decker red buses and the National Health Service.