Part–Time Work During Post–Compulsory Education And Examination Performance: Help Or Hindrance?

This paper examines the effects on examination performance of having a part–time job whilst in full–time post–sixteen education, using new data on young people in Northern Ireland. Around 35% engaged in part time employment during their education spell, compared to over 60% found by recent GB studies. This may be related to Northern Ireland's comparatively slack youth labour market and might reflect part–time employment levels in other peripheral regions. Our estimations suggest working part–time per se is not detrimental to examination performance, although working long hours is. Policy makers might improve educational performance by reducing incentives to work long hours.     

Adding Value to Agricultural Data: A Golden Opportunity

Agricultural decision makers rely on information provided by public and private entities. Data is a valuable asset and represents a tremendous investment of resources. However, difficulty locating sources and/or interpreting values may compromise its usefulness. The Florida citrus industry serves as an example of the data problem faced by many users; over 50 publications produced by 13 agencies are identified as official sources of citrus data. An indication of the potential for lost value and the dilemma facing modern agriculture is provided. This paper draws on corporate information management techniques as a framework for adding value to agricultural data.     

A review and validation of overall survival extrapolation in health technology assessments of cancer immunotherapy by the National Institute for Health and Care Excellence: how did the initial best estimate compare to trial data subsequently made available?

Background: Validation of overall survival (OS) extrapolations of immune-checkpoint inhibitors (ICIs) during the National Institute for Health and Care Excellence (NICE) Single Technology Assessment (STA) process is limited due to data still maturing at the time of submission. Inaccurate extrapolation may lead to inappropriate decision-making. The availability of more mature trial data facilitates a retrospective analysis of the plausibility and validity of initial extrapolations. This study compares these extrapolations to subsequently available longer-term data.

Methods: A systematic search of completed NICE appraisals of ICIs from March 2000 to December 2017 was performed. A targeted search was also undertaken to procure published OS data from the pivotal clinical trials for each identified STA made available post-submission to NICE. Initial Kaplan-Meier curves and associated extrapolations from NICE documentation were extracted to compare the accuracy of OS projections versus the most mature data.

Results: The review identified 11 STAs, of which 10 provided OS data upon submission to NICE. The extrapolations undertaken considered parametric or piecewise survival models. Additional data cut-offs provided a mean of 18 months of OS beyond the end of the original data. Initial extrapolations typically under-estimated OS from the most mature data cut-off by 0.4–2.7%, depending on the choice of assessment method and use of the manufacturer- or ERG-preferred extrapolation.

Conclusion: Long-term extrapolation of OS is required for NICE STAs based on initial immature OS data. The results of this study demonstrate that the initial OS extrapolations employed by manufacturers and ERGs generally predicted OS reasonably well when compared to more mature data (when available), although on average they appeared to underestimate OS. This review and validation shows that, while the choice of OS extrapolation is uncertain, the methods adopted are generally aligned with later-published follow-up data and appear appropriate for informing HTA decisions.     

Behavioural Microsimulation with Labour Supply Responses

This paper provides a technical survey of recent developments in behavioural microsimulation. We discuss the criteria by which models of labour supply may be chosen for application to behavioural microsimulation, and consider how such models may be augmented to control for fixed costs, child–related work costs, preference heterogeneity and endogeneity in wages. We describe methods by which non–linear budget constraints may be accommodated in estimation, policy simulations and welfare analysis, and discuss how stochastic terms may be factored into the simulation of behavioural responses to a policy shock.     

Life histories in housing research: the case of Pakistanis in Glasgow

The discussion centers on three key criticisms of life history techniques, which are reviewed and evaluated with reference to data from research on Pakistani housing histories in Glasgow. Firstly, the problem of bias is reframed as an issue of reflexivity, which enhances research findings. Secondly, awareness of the cultural construction of life histories allows greater depth of analysis. And thirdly the problem of the relationship between the life history and wider social forces is argued to increase awareness and understanding of social actor agency. In conclusion, we argue that life history techniques can develop research on housing careers, particularly of Pakistanis, provided certain of their properties are recognised in the process of analysis.     

Testing Alternative Regression Frameworks for Predictive Modeling of Health Care Costs

Predictive models of health care costs have become mainstream in much health care actuarial work. The Affordable Care Act requires the use of predictive modeling-based risk-adjuster models to transfer revenue between different health exchange participants. Although the predictive accuracy of these models has been investigated in a number of studies, the accuracy and use of models for applications other than risk adjustment have not been the subject of much investigation. We investigate predictive modeling of future health care costs using several statistical techniques. Our analysis was performed based on a dataset of 30,000 insureds containing claims information from two contiguous years. The dataset contains more than 100 covariates for each insured, including detailed breakdown of past costs and causes encoded via coexisting condition flags. We discuss statistical models for the relationship between next-year costs and medical and cost information to predict the mean and quantiles of future cost, ranking risks and identifying most predictive covariates. A comparison of multiple models is presented, including (in addition to the traditional linear regression model underlying risk adjusters) Lasso GLM, multivariate adaptive regression splines, random forests, decision trees, and boosted trees. A detailed performance analysis shows that the traditional regression approach does not perform well and that more accurate models are possible.     

Where are the best opportunities for reducing greenhouse gas emissions in the food system (including the food chain)?

This paper reviews estimates of food related greenhouse gas (GHG) emissions at the global, regional and national levels, highlighting both GHG-intensive stages in the food chain, and GHG-intensive food types. It examines approaches that have been proposed for mitigating emissions at each stage in the chain and looks at how these sit within wider discussions of sustainability. It finds that efficiency-focused technological measures, while important, may not only be insufficient in reducing GHGs to the level required but may also give rise to other environmental and ethical concerns. It gives evidence showing that in addition to technological mitigation it will also be necessary to shift patterns of consumption, and in particular away from diets rich in GHG-intensive meat and dairy foods. This will be necessary not just in the developed but also, in the longer term, in the developing world. This move, while potentially beneficial for food secure, wealthier populations, raises potentially serious nutritional questions for the world’s poorest. A priority for decision makers is to develop policies that explicitly seek to integrate agricultural, environmental and nutritional objectives.     

Personal income tax mimicry: evidence from international panel data

This paper investigates personal income tax (PIT) mimicry at the international level. It is the first to empirically investigate the extent to which PIT mimicry varies along the tax schedule and the first to include nations which are not part of the OECD. We use data on international personal income tax schedules from the world tax indicators to estimate marginal and average tax rates at various multiples of per capita gross domestic product (GDP). These tax rates are then used to estimate the extent to which countries respond to their neighbors’ PIT policy. We find evidence of PIT mimicry using a balanced panel of 53 countries over 24 years. This finding is strongest for tax rates at lower multiples of per capita GDP and survives several robustness checks.     

Unequal inequalities: Do progressive taxes reduce income inequality?

This paper analyzes the effect of changes in the structural progressivity of national income tax systems on observed and actual income inequality. Using several unique measures of progressivity over the 1981–2005 period for a large panel of countries, we find that progressivity reduces inequality in observed income, but has a significantly smaller impact on actual inequality, approximated by consumption-based Ginis. An empirical comparative analysis shows that the differential effect on observed versus actual inequality is much larger in countries with weaker legal institutions. We also find that structural progressivity has a greater equalizing effect in environments that support pro-poor redistribution. Substantial differences in inequality response to changes in top versus bottom rates are also uncovered.