Transparency and trust in the European pharmaceutical sector: outcomes from an experimental study

Many European pharmaceutical regulators have committed to a more open, inclusive, and transparent model of regulatory decision-making in recent years. Yet, based on little empirical evidence, they have overwhelmingly adopted ‘fishbowl’ transparency measures, ‘the full disclosure of information without explanatory information or contextualization’ (e.g. heightening access to raw data). This paper conveys recent findings from an open-ended questionnaire with 200 face-to-face interviews carried out in the UK and the Netherlands. The study provides evidence on how members of the public are likely to react to ‘fishbowl’ transparency policies and receiving decontextualized data. After showing respondents raw data from a periodic safety update report that regulators are proposing to proactively release, the survey found they were shocked, concerned, and more worried, while many said they would reconsider taking their medicines and seek further advice. Based on these findings, the authors argue that enhancing ‘transparency’ needs to be integrated with effective, evidence- and science-based benefit/risk communication.     

Hospitalized fall-related injury trends in Sweden between 2001 and 2010

Previous studies have indicated increasing trends of hospitalized fall-related injuries amongst elderly. Whether this is true also in Sweden is unknown though it is important to study considering the potential societal impact. Data were obtained regarding hospitalized injuries with falls as external cause among those aged 65 years and above with information on injury type, gender and age, on a yearly basis, from 2001 to 2010. Age- and sex-specific incidence rates were calculated (per 100,000 population) for all fall-related injuries, and for each injury type and trend lines were drawn. Linear regression analyses and percentage change were calculated for the types of fall-related injuries. A decreasing incidence was observed in the younger age groups (65–79 years) with greater decreases amongst women (women: ?14.6%, men 65–79 years: ?10.5%). However, increasing rates were observed in the older age group (80 years and above), with greater increases amongst men (women: 4.3%, men: 11.4%). Superficial injuries showed greater increases than fractures amongst those aged 80 years and above. This study indicates that older elderly in Sweden are increasingly being hospitalized for less serious injuries. This changing injury panorama is important to include in the future planning of both health care and fall-related prevention.     

MOSES: Model for studying the economy of Sweden

MOSES is an aggregate econometric model for Sweden, estimated on quarterly data, and intended for policy simulations and short-term forecasting. After a presentation of qualitative model properties, the econometric methodology is summarized. The model properties, within sample simulations, and forecast evaluations are presented. We also address methodology and practical issues relating to building and maintaining a macro model of this type. The detailed econometric equations are reported in Appendix A.“I think it should be generally agreed that a model that does not generate many properties of actual data cannot be claimed to have any ‘policy implications’…”Clive.W. J. Granger (1992, p. 4).     

On the epidemiology of injury in developing countries: A one-year emergency room-based surveillance experience from León,Nicaragua

Background Regularly available data has been shown to be inadequate for developing, implementing, and evaluating injury prevention and control programs in Nicaragua. A specific prevention-oriented local injury surveillance system has therefore been set up in the city of León. Objectives The aim of this paper is to describe the epidemiology of fatal and non-fatal injuries over a one-year period in a well-defined local population in Nicaragua, as emerging from the perspective of emergency room and inpatient treatments over a one-year period. Methods A hospital-based injury surveillance system was established to collect data for different levels of severity. All treated unintentional and intentional injuries were registered, including information on the external causes according to the ICD-9. Results Of all emergency room visits, 15.9% (9,970) were injuries. For every death due to injuries, there were 31 hospital admissions and 253 emergency room visits. Home and street/roads were the main arenas for the accidents. The estimated underreporting rate was about 6%, and in 20.3% of the cases, no E-code was assigned. The overall incidence and mortality rates were 56.2 per 1,000 and 20 per 100,000 inhabitants, respectively. However, comparison with a parallel household survey showed that the reporting rate of the surveillance system is only about 9%. The overall ratio of male to female injury rates was 2.1 to 1. The main causes of non-fatal injuries were falls, whereas the main cause of death was traffic accidents. Conclusions Hospital discharge and emergency room data systems are effective and feasible means for collecting the data needed to prevent injuries. However, in a country like Nicaragua with limited access to hospital health services, it is necessary to supplement such a system with additional sources of information in order to gain a more comprehensive picture of injury occurrence.     

Stochastic Production and Heterogeneous Risk Preferences: Commercial Fishers' Gear Choices

We present a model of fishers' gear choice, which allows for heterogeneity both in production technology and risk preferences and apply it on a panel of Swedish trawlers. Stochastic revenue functions are estimated and used to predict the mean and standard deviation of revenue for each trip. In a random-parameters logit model, we test if these predicted values explain gear choice. A majority of fishers respond positively to increased mean and negatively to increased variability of expected landing values, indicating risk aversion, but also show a strong tendency to choose the same gear used on the previous trip.     

Model Selection for Monetary Policy Analysis: How Important is Empirical Validity?*

We investigate the economic significance of trading off empirical validity of models against other desirable model properties. Our investigation is based on three alternative econometric systems of the supply side, in a model that can be used to discuss optimal monetary policy in Norway. Our results caution against compromising empirical validity when selecting a model for policy analysis. We also find large costs from basing policies on the robust model, or on a suite of models, even when it contains the valid model. This confirms an important role for econometric modelling and evaluation in model choice for policy analysis.     

Cursed by Resources or Institutions?

Natural resource‐abundant countries constitute both growth losers and growth winners, and the main difference between the success cases and the cases of failure lies in the quality of institutions. With grabber‐friendly institutions more natural resources push aggregate income down, while with producer‐friendly institutions more natural resources increase income. Such a theory finds strong support in data. A key question we also discuss is if resources in addition alter the quality of institutions. When that is the case, countries with bad institutions suffer a double resource curse – as the deterioration of institutions strengthens the negative effect of more natural resources.     

Poverty and crime in 19th century Germany

We estimate the impact of poverty on crime in 19th century Bavaria, Germany. Rainfall is used as an instrumental variable for grain (rye) prices to address econometric identification problems in the existing literature. The rye price was a major determinant of living standards during this period. The rye price has a positive effect on property crime: a one standard deviation increased property crime by 8%. OLS estimates are twice as large as instrumental variable estimates, highlighting the value of our empirical approach. Higher rye prices lead to significantly less violent crime, though, and we argue that higher beer prices, caused by the higher rye prices, are a likely explanation.     

Learning lessons: how to practice nudging around the world

Abstract

The aim of this article is to cover three things: (1) to introduce the context behind why a report prepared by the Organisation for Economic Co-operation and Development (OECD) in 2017 would be of such importance to researchers in various academic disciplines and public policy, (2) to present the details of a simple classification system that was applied to all 111 case studies of behavioural interventions (better known as nudges) referred to in the OECD (2017a OECD. 2017a. Behavioural Insights and Public Policy Lessons from Around the World.1-408 pp. OeCD Publishing. https://read.oecd-ilibrary.org/governance/behavioural-insights-and-public-policy_9789264270480-en. doi:10.1787/9789264270480-en.[Crossref] , [Google Scholar]) report, and (3) to discuss what needs to be done to help advance practitioners’ pursuit of effective behavioural interventions. This article aims to highlight the importance of accurately cataloguing the types of behavioural interventions that have been trialled/implemented across the world. By adopting an agreed classification system, researchers and practitioners can benefit from knowing what can work, and where it can work, as well as what does not work, in order to be better armed when considering the use of behavioural interventions to solve social policy issues.