Experimental evidence on the effect of incentives and domain in risk aversion and discounting tasks

Journal of Risk and Uncertainty - Environmental policy evaluation is often criticised for employing discount rates that have little grounding in research. Yet, experimental research aimed at...     

From social workers to socio-therapists: the transformative journey of substance abuse therapists

ABSTRACT

The efficiency of interventions in addiction is associated with the processes of practitioners’ professional development. Identity formation is studied extensively for clinical professions but little research focuses on social workers working in addiction settings. This study examined the experience of social workers working in a community treatment network in Greece. Fifteen interviews were conducted with 11 women and 4 men, ranging between 29 and 47 years οf age, who worked in different centers within the network. Data were analyzed following the guidelines of Interpretative Phenomenological Analysis, offering in-depth examinations of people’s lived experience. The results delineate a series of transformations in professional identity comprising a process of biographization. The participants highlighted intrapersonal and relational factors that influence this process which leads to self-understanding and engagement with the therapeutic community. The results contribute to deciphering the factors that influence social workers’ experience in their professional identity formation in substance abuse treatment contexts.     

Who cares and how much: exploring the determinants of co-residential informal care

The importance of informal care provided inside the household (co-residential care) is widely acknowledged in policy circles. However, the factors that determine the likelihood and scale of provision are not fully understood. A two-part model (2PM) is used to investigate both participation and levels of provision. Random effects dynamic panel specifications are employed. Results show that co-residential informal care competes with other time demanding activities, such as childcare and employment. Wealthier individuals are less likely to be caregivers, whereas wealthier households have a higher tendency towards caregiving. Evidence of both substitution and complementarity is found between formal and informal care. Informal care and health status are significantly related, with carers more likely to report worse General Health Questionnaire scores than non-carers. Finally, significant dynamic effects are observed with the continuance of the provision of informal care being more likely than the initiation of such activity, while heavy commitment in the past increases the hours provided in the current period.

QUANTITATIVE EASING AND THE UK STOCK MARKET: DOES THE BANK OF ENGLAND INFORMATION DISSEMINATION STRATEGY MATTER?

We use intraday aggregate stock market data and an event‐study framework to assess the UK's equity market reaction to the unexpected element of the Bank of England Monetary Policy Committee's (MPC) asset purchase announcements for the 2009–2017 period. We assess the reactions of equity returns and their volatility over various time frames, both preceding and following the MPC announcements. Our results show that the UK unconventional monetary policy shocks have a significant impact on domestic equity returns and volatilities. The strength of this impact depends on the Bank's information dissemination through inflation reports and the publication of the MPC's voting records. (JEL G14, E44, E52)     

Valuing Informal Care Experience: Does Choice of Measure Matter?

Well-being equations are often estimated to generate monetary values for non-marketed activities. In such studies, utility is often approximated by either life satisfaction or General Health Questionnaire scores. We estimate and compare monetary valuations of informal care for the first time in the UK employing both measures, using longitudinal data on well-being and informal care provision. The choice of well-being measure has some effect on the estimated parameters and resulting monetary valuations, but any differences are not statistically significant. Further research is needed to confirm the comparability of these measures if researchers are to continue to use them interchangeably.     

Nonparametric Tree‐Based Predictive Modeling of Storm Outages on an Electric Distribution Network

This article compares two nonparametric tree‐based models, quantile regression forests (QRF) and Bayesian additive regression trees (BART), for predicting storm outages on an electric distribution network in Connecticut, USA. We evaluated point estimates and prediction intervals of outage predictions for both models using high‐resolution weather, infrastructure, and land use data for 89 storm events (including hurricanes, blizzards, and thunderstorms). We found that spatially BART predicted more accurate point estimates than QRF. However, QRF produced better prediction intervals for high spatial resolutions (2‐km grid cells and towns), while BART predictions aggregated to coarser resolutions (divisions and service territory) more effectively. We also found that the predictive accuracy was dependent on the season (e.g., tree‐leaf condition, storm characteristics), and that the predictions were most accurate for winter storms. Given the merits of each individual model, we suggest that BART and QRF be implemented together to show the complete picture of a storm's potential impact on the electric distribution network, which would allow for a utility to make better decisions about allocating prestorm resources.     

A real survival analysis application via variable selection methods for Cox's proportional hazards model

Variable selection is fundamental to high-dimensional statistical modeling in diverse fields of sciences. In our health study, different statistical methods are applied to analyze trauma annual data, collected by 30 General Hospitals in Greece. The dataset consists of 6334 observations and 111 factors that include demographic, transport, and clinical data. The statistical methods employed in this work are the nonconcave penalized likelihood methods, Smoothly Clipped Absolute Deviation, Least Absolute Shrinkage and Selection Operator, and Hard, the maximum partial likelihood estimation method, and the best subset variable selection, adjusted to Cox's proportional hazards model and used to detect possible risk factors, which affect the length of stay in a hospital. A variety of different statistical models are considered, with respect to the combinations of factors while censored observations are present. A comparative survey reveals several differences between results and execution times of each method. Finally, we provide useful biological justification of our results.     

Fiscal deficits under financial pressure and insolvency: Evidence for Italy,Greece and Spain

This article attempts to re-evaluate the sustainability of the fiscal deficit as well as the long-run macroeconomic relationship between government spending and revenues for three South-European economies under financial market pressure and insolvency; Italy, Greece and Spain. The empirical analysis uses annual data from 1970 to 2010 and employs various cointegration techniques to account for possible linear and nonlinear effects in fiscal policy actions. The evidence for all three countries suggests that, allowing for structural break, (i) the fiscal deficits are weakly sustainable in the long-run, (ii) the spend-and-tax hypothesis is supported and (iii) the budgetary adjustment process is asymmetric in Italy and Spain.     

The poor,the rich and the happy: Exploring the link between income and subjective well-being

The relationship between income and subjective well-being (SWB) is investigated using eight waves of the British Household Panel Survey and an estimation strategy that allows us to relax some assumptions typically made in the literature. First, we use a random effects generalised ordered probit model to investigate whether income effects are heterogeneous across SWB categories, and, second, we discretise (absolute and relative) income variables to allow for the income effects to vary across income groups. We find that higher absolute income increases SWB but up to a certain level, while low income is significantly correlated with low scores in the SWB ladder. Our results are consistent with the Easterlin Paradox that has been reported in the literature. We find that high-income groups are less likely to belong in the highest SWB level, which could be partly explained by the fact that the relative income status (rather than the absolute one) is more important in determining (the highest level of) SWB.