Measuring and Predicting Heterogeneous Recessions

This paper conducts an empirical analysis of the heterogeneity of recessions in monthly U.S. coincident and leading indicator variables. Univariate Markovswitching models indicate that it is appropriate to allow for two distinct recession regimes, corresponding with ‘mild’ and ‘severe’ recessions. All downturns start with a mild decline in the level of economic activity. Contractions that develop into severe recessions mostly correspond with periods of substantial credit squeezes as suggested by the ‘financial accelerator’ theory. Multivariate Markov-switching models that allow for phase shifts between the cyclical regimes of industrial production and the Conference Board Leading Economic Index confirm these findings.Business cycle, phase shifts, regime-switching models, Bayesian analysis

Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only include valuation ratios and interest rate related variables, and possibly individual macro variables, as well as the historical average excess return. The improvements in out-of-sample forecast accuracy are both statistically and economically significant. The factor-augmented predictive regressions have superior market timing ability and volatility timing ability, while a mean-variance investor would be willing to pay an annual performance fee of several hundreds of basis points to switch from the predictions offered by the benchmark models to those of the factor-augmented models. An important reason for the superior performance of the factor-augmented predictive regressions is the stability of their forecast accuracy, whereas the benchmark models suffer from a forecast breakdown during the 1990s

Modeling and Estimation of Synchronization in Multistate Markov-Switching Models

This paper develops a Markov-Switching vector autoregressive model that allows for imperfect synchronization of cyclical regimes in multiple variables, due to phase shifts of a single common cycle. The model has three key features: (i) the amount of phase shift can be different across regimes (as well as across variables), (ii) it allows the cycle to consist of any number of regimes J is larger than or equal to 2, and (iii) it allows for regime-dependent volatilities and correlations. In an empirical application to monthly returns on size-based stock portfolios, a three-regime model with asymmetric phase shifts and regime-dependent heteroscedasticity is found to characterize the joint distribution of returns most adequately. While large- and small-cap portfolios switch contemporaneously into boom and crash regimes, the large-cap portfolio leads the small-cap portfolio for switches to a moderate regime by a month

Home-School Relationships: The Communication and Engagement Practices of Schools and the Role of the Community Educational Psychologist

Paper One: Developing positive relationships between schools and families has become an increasing priority within education in order to best support children and young people’s learning and development. Despite an increasing focus on seeking the parental ‘voice’, the views and experiences of school staff, parents and children appear to have limited prominence within the literature. This paper presents a piece of illuminative Community Psychology research that explored home-school relationships from the perspectives of school staff, parents and children from four Primary schools in a local community. A mixed-methods approach to data collection involved twenty-eight staff and sixty-four parent questionnaires, a focus group with eight children, and semi-structured research interviews with six staff and five parents. The importance of effective communication to encourage home and school to ‘work together’ is highlighted along with the need to provide support tailored to local needs focused around developing parental knowledge and skills to support children’s learning. The findings offer valuable insights into the views and experiences of parents, school staff and children around the current communication and engagement practices of schools in a local community. There are also implications for educational practice, including within Educational Psychology, in developing more effective home-school relationships in the future. Paper Two: With an increasing focus on supporting parental involvement within education, the development of effective ‘partnerships’ between schools and families is widening. Despite the wealth of information and advice around engaging parents in education (DfE, 2011), there appears limited training and ongoing support for school staff on how to foster and maintain these positive interactions and how to tackle ‘real life’ issues faced within home-school relationships. This research explored the role of a Community Educational Psychologist working with school staff to develop and maintain positive home-school relationships. Through support and facilitation from a Trainee Community Educational Psychologist, a series of education and supervision sessions were developed with a group of school staff to increase knowledge and confidence around the applications of psychology within education and the influential factors in home-school interactions. A model of reflection was introduced through the supervision sessions to assist the creation of a sustainable support network for staff within school concerning their work with families. The findings highlighted a ‘need to’ and ‘desire for’ developing school staff knowledge and confidence and the significant impacts of the education/supervision sessions in achieving this. Factors enabling and preventing progress through these sessions were noted along with the value of ‘sharing’ within supervision. The necessity of continued practice in order to embed supervision into teaching practice was acknowledged, and the positive impact of a Community Educational Psychologist facilitating these groups was found. Implications for educational practice, including within Educational Psychology, in supporting school staff with home-school relationships are discussed

Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with Non-filtered Data

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended Phillips Curve (PC) models. It is shown that mechanical removal or modeling of simple low frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic PC models are extended to include structural time series models that describe typical time varying patterns in levels and volatilities. Forward as well as backward looking expectation mechanisms for inflation are incorporated and their relative importance evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long run stability between inflation and marginal costs. Backward-looking inflation appears stronger than forward-looking one. Levels and volatilities of inflation are estimated more precisely using rich PC models. Estimated inflation expectations track nicely the observed long run inflation from the survey data. The extended PC structures compare favorably with existing basic Bayesian Vector Autoregressive and Stochastic Volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of disinflation in recent years

Modeling and Estimation of Synchronization in Multistate Markov-Switching Models

This paper develops a Markov-Switching vector autoregressive model that allows for imperfect synchronization of cyclical regimes in multiple variables, due to phase shifts of a single common cycle. The model has three key features: (i) the amount of phase shift can be different across regimes (as well as across variables), (ii) it allows the cycle to consist of any number of regimes J ≥ 2, and (iii) it allows for regime-dependent volatilities and correlations. In an empirical application to monthly returns on size-based stock portfolios, a three-regime model with asymmetric phase shifts and regime-dependent heteroscedasticity is found to characterize the joint distribution of returns most adequately. While large- and small-cap portfolios switch contemporaneously into boom and crash regimes, the large-cap portfolio leads the small-cap portfolio for switches to a moderate regime by a month