Group membership and staff turnover affect outcomes in group CBT for persistent pain

The effects of two contextual factors, group membership and staff turnover, on the outcome of group cognitive behavioral therapy (CBT) for persistent pain were investigated. The data came from end of treatment and one month follow-up assessments of 3050 individuals who attended an intensive group programme over sixteen years. Intraclass correlations (ICC) showed significant intragroup effects on self-efficacy (ICC = 0.16 at end of treatment; 0.12 at one month), catastrophizing (ICC = 0.06; 0.13) and distance walked (ICC = 0.20; 0.19). This underlines the importance of modelling group membership when analyzing data from group interventions. Linear regression showed that high periods of staff turnover were significantly related to poorer outcomes on self-efficacy and distance walked at end of treatment, with the effect on self-efficacy persisting to one month follow-up. Having demonstrated significant contextual effects in an existing data set, further research is needed to explore the mechanisms by which these effects operate

Numerical estimation of densities

[Abridged] We present a novel technique, dubbed FiEstAS, to estimate the underlying density field from a discrete set of sample points in an arbitrary multidimensional space. FiEstAS assigns a volume to each point by means of a binary tree. Density is then computed by integrating over an adaptive kernel. As a first test, we construct several Monte Carlo realizations of a Hernquist profile and recover the particle density in both real and phase space. At a given point, Poisson noise causes the unsmoothed estimates to fluctuate by a factor ~2 regardless of the number of particles. This spread can be reduced to about 1 dex (~26 per cent) by our smoothing procedure. [...] We conclude that our algorithm accurately measure the phase-space density up to the limit where discreteness effects render the simulation itself unreliable. Computationally, FiEstAS is orders of magnitude faster than the method based on Delaunay tessellation that Arad et al. employed, making it practicable to recover smoothed density estimates for sets of 10^9 points in 6 dimensions.Comment: 12 pages, 18 figures, submitted to MNRAS. The code is available upon reques

Will You Still Want Me Tomorrow? The Dynamics of Families' Long-Term Care Arrangements

We estimate dynamic models of elder-care arrangements using data from the Assets and Health Dynamics Among the Oldest Old Survey. We model the use of institutional care, formal home health care, care provided by a child, and care provided by a spouse in the selection of each care arrangement, the primary arrangement, and hours in each arrangement. Our results indicate that both observed heterogeneity and true state dependence play roles in the persistence of care arrangements. We find that positive state dependence (i.e., inertia) dominates caregiver burnout, and that formal care decisions depend on the cost and quality of care.Dynamic Models, Long-Term Care, Home Health Care, Informal Care

Observing Unobservables: Identifying Information Asymmetries with a Consumer Credit Field Experiment

Information asymmetries are important in theory but difficult to identify in practice. We estimate the empirical importance of adverse selection and moral hazard in a consumer credit market using a new field experiment methodology. We randomized 58,000 direct mail offers issued by a major South African lender along three dimensions: 1) the initial "offer interest rate" appearing on direct mail solicitations; 2) a "contract interest rate" equal to or less than the offer interest rate and revealed to the over 4,000 borrowers who agreed to the initial offer rate; and 3) a dynamic repayment incentive that extends preferential pricing on future loans to borrowers who remain in good standing. These three randomizations, combined with complete knowledge of the Lender's information set, permit identification of specific types of private information problems. Specifically, our setup distinguishes adverse selection from moral hazard effects on repayment, and thereby generates unique evidence on the existence and magnitudes of specific credit market failures. We find evidence of both adverse selection (among women) and moral hazard (predominantly among men), and the findings suggest that about 20% of default is due to asymmetric information problems. This helps explain the prevalence of credit constraints even in a market that specializes in financing high-risk borrowers at very high rates.Information asymmetries, field experiment, adverse selection, moral hazard, development finance, credit markets, microfinance

Do conventions need to be common knowledge?

Do conventions need to be common knowledge? David Lewis builds this requirement into his definition of a convention. This paper explores the extent to which his approach finds support in the game theory literature. The knowledge formalism developed by Robert Aumann and others militates against Lewis’s approach, because it demonstrates that it is almost impossible for something to become common knowledge in a large society. On the other hand, Ariel Rubinstein’s Email Game suggests that coordinated action is equally hard for rational players. But an unnecessary simplifying assumption in the Email Game turns out to be doing all the work, and the paper concludes that common knowledge is better excluded from a definition of the conventions that we use to regulate our daily lives

Smoothed Income Poverty in European Countries

The purpose of this paper is to obtain by combining two longitudinal perspectives a more detailed national picture of poverty in the Member States of the European Union, using the _rst four waves (1994 - 1997) of the European Community Household Panel (ECHP). In addition to this detailed consideration of the time dimension, poverty incidence, poverty gap and poverty intensity are measured. Overall, the ranking across countries and dimensions is relatively robust. Denmark and Portugal di_er from the rest of the countries in each dimension. Other exceptions include France and Ireland, where poverty intensity is considerably lower than in the other welfare regimes. The results in terms of the di_erent subgroups of poor individuals, namely transitory, intermittently and persistently poor, emphasize the importance of a more di_erentiated perspective on poverty, in particular concerning the relationship between social and demographic characteristics and individuals' long-term income situation.smoothed income; poverty; panel data; ECHP.

Computing Optimal Policy in a Timeless-Perspective: An Application to a Small-Open Economy

Since the contribution of Kydland and Prescott (1977), it is well known that the optimal Ramsey policy is time inconsistent. In a series of recent contributions, Woodford (2003) proposes a new methodology to circumvent this problem, namely the timeless perspective solution. However, one main limitation is that it is not yet empirically implementable. In this paper, we develop a new methodology to compute initial values of the Lagrange multipliers in order to implement the timeless-perspective solution. In so doing, we also provide a generalization of the Ramsey and timeless-perspective problems. We apply our results to a small-open economy model in Canada.Monetary policy framework

Penalized Regression with Ordinal Predictors

Ordered categorial predictors are a common case in regression modeling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In this article penalized regression techniques are proposed. Based on dummy coding two types of penalization are explicitly developed; the first imposes a difference penalty, the second is a ridge type refitting procedure. A Bayesian motivation as well as alternative ways of derivation are provided. Simulation studies and real world data serve for illustration and to compare the approach to methods often seen in practice, namely linear regression on the group labels and pure dummy coding. The proposed regression techniques turn out to be highly competitive. On the basis of GLMs the concept is generalized to the case of non-normal outcomes by performing penalized likelihood estimation. The paper is a preprint of an article published in the International Statistical Review. Please use the journal version for citation