How influential is ballot design in elections?

We exploit an original dataset from a referendum in Peru to study the influence of voting "arrangements" on electoral outcomes. The relative importance of these arrangements (e.g., ballot design) with respect to the fundamentals (e.g., ideology, candidates' quality) has not been measured. After controlling for a comprehensive set of politicians' characteristics, we estimate unbiased ballot order effects making use of the within party variation in outcomes. We estimate a non-linear probability model and we create counterfactuals to conclude that ballot design not only may have changed the electoral results but also has a greater importance than candidates' ideology, education, experience and party affiliation

Deciding for others: local public good contributions with intermediaries

Given that pure public goods' broader use is often limited by distance, congestion, or borders, local public goods are prevalent. The decision for the provision of these local public goods is often made by individuals who do not get to consume them. It is, therefore, not clear whether the classic free-riding problem result holds in this framework. We study the provision of a local public good where the public good contribution decisions are made by non-local intermediaries who neither contribute from their own endowment nor directly benefit from the local public good. Each intermediary decides for only one public good beneficiary. Intermediaries make decisions under two compensation mechanisms where their incentives are either non-aligned (fixed), or aligned (variable), with those of the beneficiaries they represent. We find that the use of intermediaries, regardless of the compensation mechanism, significantly increases contributions to the provision of the public good

The binding constraint on firms'growth in developing countries

Firms in developing countries face numerous and serious constraints on their growth, ranging from corruption to lack of infrastructure to inability to access finance. Countries lack the resources to remove all the constraints at once and so would be better off removing the most binding one first. This paper uses data from World Bank Enterprise Surveys in 2006-10 to identify the most binding constraints on firm operations in developing countries. While each country faces a different set of constraints, these constraints also vary by firm characteristics, especially firm size. Across all countries, access to finance is among the most binding constraints; other obstacles appear to matter much less. This result is robust for all regions. Smaller firms must rely more on their own funds to invest and would grow significantly faster if they had greater access to external funds. As a result, a low level of financial development skews the firm size distribution by increasing the relative share of small firms. The results suggest that financing constraints play a significant part in explaining the"missing middle"-- the failure of small firms in developing countries to grow into medium-size or large firms.Access to Finance,Environmental Economics&Policies,Microfinance,Debt Markets,Banks&Banking Reform

The Promotion of Eating Behaviour Change through Digital Interventions.

Diet-related chronic disease is a global health epidemic giving rise to a high incidence of morbidity and mortality. With the rise of the digital revolution, there has been increased interest in using digital technology for eating behavioural change as a mean of diet-related chronic disease prevention. However, evidence on digital dietary behaviour change is relatively scarce. To address this problem, this review considers the digital interventions currently being used in dietary behaviour change studies. A literature search was conducted in databases like PubMed, Cochrane Library, CINAHL, Medline, and PsycInfo. Among 119 articles screened, 15 were selected for the study as they met all the inclusion criteria according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) search strategy. Four primary digital intervention methods were noted: use of personal digital assistants, use of the internet as an educational tool, use of video games and use of mobile phone applications. The efficiency of all the interventions increased when coupled with tailored feedback and counselling. It was established that the scalable and sustainable properties of digital interventions have the potential to bring about adequate changes in the eating behaviour of individuals. Further research should concentrate on the appropriate personalisation of the interventions, according to the requirements of the individuals, and proper integration of behaviour change techniques to motivate long-term adherence

Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials

Objective: To evaluate differences in downstream testing, coronary revascularisation, and clinical outcomes following non-invasive diagnostic modalities used to detect coronary artery disease. Design: Systematic review and network meta-analysis. Data sources: Medline, Medline in process, Embase, Cochrane Library for clinical trials, PubMed, Web of Science, SCOPUS, WHO International Clinical Trials Registry Platform, and Clinicaltrials.gov. Eligibility criteria for selecting studies: Diagnostic randomised controlled trials comparing non-invasive diagnostic modalities in patients presenting with symptoms suggestive of low risk acute coronary syndrome or stable coronary artery disease. Data synthesis: A random effects network meta-analysis synthesised available evidence from trials evaluating the effect of non-invasive diagnostic modalities on downstream testing and patient oriented outcomes in patients with suspected coronary artery disease. Modalities included exercise electrocardiograms, stress echocardiography, single photon emission computed tomography-myocardial perfusion imaging, real time myocardial contrast echocardiography, coronary computed tomographic angiography, and cardiovascular magnetic resonance. Unpublished outcome data were obtained from 11 trials. Results: 18 trials of patients with low risk acute coronary syndrome (n=11 329) and 12 trials of those with suspected stable coronary artery disease (n=22 062) were included. Among patients with low risk acute coronary syndrome, stress echocardiography, cardiovascular magnetic resonance, and exercise electrocardiograms resulted in fewer invasive referrals for coronary angiography than coronary computed tomographic angiography (odds ratio 0.28 (95% confidence interval 0.14 to 0.57), 0.32 (0.15 to 0.71), and 0.53 (0.28 to 1.00), respectively). There was no effect on the subsequent risk of myocardial infarction, but estimates were imprecise. Heterogeneity and inconsistency were low. In patients with suspected stable coronary artery disease, an initial diagnostic strategy of stress echocardiography or single photon emission computed tomography-myocardial perfusion imaging resulted in fewer downstream tests than coronary computed tomographic angiography (0.24 (0.08 to 0.74) and 0.57 (0.37 to 0.87), respectively). However, exercise electrocardiograms yielded the highest downstream testing rate. Estimates for death and myocardial infarction were imprecise without clear discrimination between strategies. Conclusions: For patients with low risk acute coronary syndrome, an initial diagnostic strategy of stress echocardiography or cardiovascular magnetic resonance is associated with fewer referrals for invasive coronary angiography and revascularisation procedures than non-invasive anatomical testing, without apparent impact on the future risk of myocardial infarction. For suspected stable coronary artery disease, there was no clear discrimination between diagnostic strategies regarding the subsequent need for invasive coronary angiography, and differences in the risk of myocardial infarction cannot be ruled out. Systematic review registration: PROSPERO registry no CRD42016049442

Heteropolyacids supported on zirconia-doped γ, θ and α alumina: A physicochemical assessment and characterisation of supported solid acids

In this paper we carry out a surface study of promising supported solid acid catalysts commonly used for the production of high value chemicals derived from glycerol. In particular, γ, θ and α alumina (Al2O3) were modified by (i) grafting with 5 wt% zirconia, (ii) doping with 30 wt% silicotungstic acid (STA), and (iii) using both zirconia and STA. The aim is to rationalise the effect of these different parameters on structural properties and surface adsorption through a comprehensive multi-technique approach, including recently developed NMR relaxation techniques. XRD and laser Raman spectroscopy confirmed a strong interaction between STA and the γ-/θ-Al2O3 resulting in a distortion of the supported STA Keggin structure relative to that of bulk STA. Conversely, a much weaker interaction between the supported STA and α-Al2O3 was measured. NMR relaxation demonstrated that the STA doping increases the adsorption properties of the catalyst, particularly for γ-/θ-Al2O3. For catalysts based on α-Al2O3, such effect was negligible. Thermogravimetric/differential thermogravimetry (TGA/DTG) analysis suggested that zirconia-grafted and non-grafted θ-Al2O3 and γ-Al2O3 are suitable materials for increasing the thermal stability of STA whereas α-Al2O3 (both grafted and non-grafted) does not improve the thermal stability of STA

Incorporating dose effects in network meta-analysis

Systematic reviews with network meta-analysis that ignore potential dose effects could limit the applicability and validity of review findings. This article aims to help content experts (eg, clinicians), methodologists, and statisticians better understand how to incorporate dose effects in network meta-analysis. Three models are described that make different clinical and statistical assumptions about how to model dose effects. This article also illustrates the importance of dose effects in understanding the potential risk of harm in people with dementia from cerebrovascular events associated with atypical antipsychotic drug use (quetiapine, olanzapine, and risperidone) and the potential risk of harm in people with nausea and headache associated with cholinesterase inhibitor use (donepezil, galantamine, and rivastigmine). Finally, important considerations when choosing between different network meta-analysis models incorporating dose effects are discussed

Bayesian models for aggregate and individual patient data component network meta-analysis.

Network meta-analysis can synthesize evidence from studies comparing multiple treatments for the same disease. Sometimes the treatments of a network are complex interventions, comprising several independent components in different combinations. A component network meta-analysis (CNMA) can be used to analyze such data and can in principle disentangle the individual effect of each component. However, components may interact with each other, either synergistically or antagonistically. Deciding which interactions, if any, to include in a CNMA model may be difficult, especially for large networks with many components. In this article, we present two Bayesian CNMA models that can be used to identify prominent interactions between components. Our models utilize Bayesian variable selection methods, namely the stochastic search variable selection and the Bayesian LASSO, and can benefit from the inclusion of prior information about important interactions. Moreover, we extend these models to combine data from studies providing aggregate information and studies providing individual patient data (IPD). We illustrate our models in practice using three real datasets, from studies in panic disorder, depression, and multiple myeloma. Finally, we describe methods for developing web-applications that can utilize results from an IPD-CNMA, to allow for personalized estimates of relative treatment effects given a patient's characteristics