Investigation of institutional changes in the UK housing market using structural break tests and time-varying parameter models

This paper investigates the effects of institutional changes within the UK housing market in recent decades using structural break tests and time-varying parameter models. This approach is motivated by models of institutional change drawn from the political science literature which focus on the existence of both fast-moving and slow-moving institutional changes and the interactions between them as drivers of the dynamics of asset prices. As a methodological contribution, we use several time-varying parameter models for the first time in investigations of institutional change. Our findings support the existence of both structural breaks and continuous variance in parameters. This contributes to our understanding of the housing market in two respects. Firstly, the dates of structural breaks appear to better match unexpected market shocks rather than remarkable political events, and this supports prior institutional theory. Secondly, assessment of the effect of slow-moving institutional changes shows that people’s biased expectations rather than the economic fundamentals have increasingly played an important role in driving housing prices in the short run although fundamentals continue to drive house prices to converge to their long-run equilibrium

A general approach to handling missing values in Procrustes analysis

General Procrustes analysis is concerned with transforming a set of given configuration matrices to closest agreement. This paper introduces an approach useful for handling missing values in the configuration matrices in the context of general linear transformations. Centring and/or standardisation are allowed. Simplifications occur in the important case where the transformations are orthogonal. In the most general case, an interesting quadratic constrained optimisation problem appears

Mobile phone conversations, listening to music and quiet (electric) cars: Are traffic sounds important for safe cycling?

Listening to music or talking on the phone while cycling as well as the growing number of quiet (electric) cars on the road can make the use of auditory cues challenging for cyclists. The present study examined to what extent and in which traffic situations traffic sounds are important for safe cycling. Furthermore, the study investigated the potential safety implications of limited auditory information caused by quiet (electric) cars and by cyclists listening to music or talking on the phone. An Internet survey among 2249 cyclists in three age groups (16–18, 30–40 and 65–70 year old) was carried out to collect information on the following aspects: 1) the auditory perception of traffic sounds, including the sounds of quiet (electric) cars; 2) the possible compensatory behaviours of cyclists who listen to music or talk on their mobile phones; 3) the possible contribution of listening to music and talking on the phone to cycling crashes and incidents. Age differences with respect to those three aspects were analysed. Results show that listening to music and talking on the phone negatively affects perception of sounds crucial for safe cycling. However, taking into account the influence of confounding variables, no relationship was found between the frequency of listening to music or talking on the phone and the frequency of incidents among teenage cyclists. This may be due to cyclists’ compensating for the use of portable devices. Listening to music or talking on the phone whilst cycling may still pose a risk in the absence of compensatory behaviour or in a traffic environment with less extensive and less safe cycling infrastructure than the Dutch setting. With the increasing number of quiet (electric) cars on the road, cyclists in the future may also need to compensate for the limited auditory input of these cars.Transport and PlanningTransport and Logistic

Pattern recognition based on color-coded quantum mechanical surfaces for molecular alignment

A pattern recognition algorithm for the alignment of drug-like molecules has been implemented. The method is based on the calculation of quantum mechanical derived local properties defined on a molecular surface. This approach has been shown to be very useful in attempting to derive generalized, non-atom based representations of molecular structure. The visualization of these surfaces is described together with details of the methodology developed for their use in molecular overlay and similarity calculations. In addition, this paper also introduces an additional local property, the local curvature (C L), which can be used together with the quantum mechanical properties to describe the local shape. The method is exemplified using some problems representing common tasks encountered in molecular similarity

Unfolding Incomplete Data: Guidelines for Unfolding Row-Conditional Rank Order Data with Random Missings

Unfolding, Incomplete data, Missing data, BIBD, PREFSCAL,