Reforming pensions: Principles, analytical errors and policy directions

This article, sets out a series of principles for pension design rooted in economic theory: pension systems have multiple objectives, analysis should consider the pension system as a whole, analysis should be framed in a second-best context, different systems share risks differently, and systems have different effects by generation and by gender. That discussion is reinforced by identification of a series of widespread analytical errors — errors that appear in World Bank work, but by no means only in World Bank work: tunnel vision, improper use of first-best analysis, improper use of steady-state analysis, incomplete analysis of implicit pension debt, incomplete analysis of the impact of funding (including excessive focus on financial flows, failure to consider how funding is generated, and improper focus on the type of asset in trust funds), and ignoring distributional effects. The second part of the article considers implications for policy: there is no single best pension design, earlier retirement does little or nothing to reduce unemployment, unsustainable pension promises need to be addressed directly, a move from pay-as-you-go towards funding in a mandatory system may or may not be welfare improving, and implementation matters — policy design that exceeds a country's capacity to implement it is bad policy design. We illustrate the ranges of designs of pension systems that fit the fiscal and institutional capacity constraints typical at different levels of economic development. The potential gains from simplicity imply that a country capable of implementing an administratively demanding plan does not necessarily gain from doing so. New Zealand has a simple pension system through choice, not constraint.     

Latent transition models with latent class predictors: attention deficit hyperactivity disorder subtypes and high school marijuana use

Summary.  Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder which is most often diagnosed in childhood with symptoms often persisting into adulthood. Elevated rates of substance use disorders have been evidenced among those with ADHD, but recent research focusing on the relationship between subtypes of ADHD and specific drugs is inconsistent. We propose a latent transition model (LTM) to guide our understanding of how drug use progresses, in particular marijuana use, while accounting for the measurement error that is often found in self-reported substance use data. We extend the LTM to include a latent class predictor to represent empirically derived ADHD subtypes that do not rely on meeting specific diagnostic criteria. We begin by fitting two separate latent class analysis (LCA) models by using second-order estimating equations: a longitudinal LCA model to define stages of marijuana use, and a cross-sectional LCA model to define ADHD subtypes. The LTM model parameters describing the probability of transitioning between the LCA-defined stages of marijuana use and the influence of the LCA-defined ADHD subtypes on these transition rates are then estimated by using a set of first-order estimating equations given the LCA parameter estimates. A robust estimate of the LTM parameter variance that accounts for the variation due to the estimation of the two sets of LCA parameters is proposed. Solving three sets of estimating equations enables us to determine the underlying latent class structures independently of the model for the transition rates and simplifying assumptions about the correlation structure at each stage reduces the computational complexity.     

Misclassification of current status data

We describe a simple method for nonparametric estimation of a distribution function based on current status data where observations of current status information are subject to misclassification. Nonparametric maximum likelihood techniques lead to use of a straightforward set of adjustments to the familiar pool-adjacent-violators estimator used when misclassification is assumed absent. The methods consider alternative misclassification models and are extended to regression models for the underlying survival time. The ideas are motivated by and applied to an example on human papilloma virus (HPV) infection status of a sample of women examined in San Francisco.     

Anglo and Latino Differences in Willingness to Pay for Urban Public Services*

Objective. This research explores Anglo and Latino differences in willingness to pay for urban public services, assuming differences will impact service delivery in local government as the Latino population increases and becomes more visible. Methods. Survey data from a probability sample of Phoenix residents, now the nation's fifth largest city, are analyzed across 28 city services using multiple mechanisms that included a logit multivariate model. Results. Latinos are substantially more likely than Anglos to report willingness to pay for urban public services. These differences cut across services and are not mitigated by Latino income levels. Conclusions. Latinos are prepared to be full partners in improving service delivery in local government, even at the expense of out‐of‐pocket payment for services. Moreover, while increases in the Latino population will carry greater demand for more and high‐quality city services by Latinos, it is unlikely to alter the menu of preferred services along class or race/ethnic lines. The fact that Latinos seem generally more willing to pay for services also raises the possibility that Latinos are interested in investing in their communities, seeking more opportunities, and perhaps remaining in those communities.     

“I Pay Enough Taxes Already!” Applying Economic Voting Models to Environmental Referendums*

Objectives. Models of economic voting have rarely been applied to referendum votes. We fill this gap by testing citizens' voting behavior on environmental policy in relation to their perception of the business cycle and general orientation toward politics. Thus, the study examines the personal, institutional, and economic determinants of vote choice on 36 environmental bills from 1983 to 2004 in Switzerland. Methods. We apply a logistic hierarchical model, where individual characteristics on Level 1 are nested within contextual determinants situated on Level 2. Results. We confirm the crucial importance of the individual‐level variables education, political affinity, car ownership, and urbanity. Classifying the electorate into five groups, using open‐ended survey questions about respondents' reasons for approval or dismissal of the bills, allows for finer hypotheses testing. We show that the individuals' positive perception of their personal current economic condition has a positive effect on the likelihood of supporting the proposals. In turn, we prove the negative, constraining effect of deteriorating macroeconomic conditions on approval rates. Conclusions. By applying economic voting models to referendum analyses we advance the understanding of citizens' vote choice on environmental ballots, we show the role of context, and we propose an original typology of voters' general orientation toward politics.     

Weight-preserving simulated tempering

Statistics and Computing - Simulated tempering is a popular method of allowing MCMC algorithms to move between modes of a multimodal target density $$\pi $$. One problem with simulated tempering...     

Evaluating Potential Distribution of High‐Risk Aquatic Invasive Species in the Water Garden and Aquarium Trade at a Global Scale Based on Current Established Populations

Aquatic non‐native invasive species are commonly traded in the worldwide water garden and aquarium markets, and some of these species pose major threats to the economy, the environment, and human health. Understanding the potential suitable habitat for these species at a global scale and at regional scales can inform risk assessments and predict future potential establishment. Typically, global habitat suitability models are fit for freshwater species with only climate variables, which provides little information about suitable terrestrial conditions for aquatic species. Remotely sensed data including topography and land cover data have the potential to improve our understanding of suitable habitat for aquatic species. In this study, we fit species distribution models using five different model algorithms for three non‐native aquatic invasive species with bioclimatic, topographic, and remotely sensed covariates to evaluate potential suitable habitat beyond simple climate matches. The species examined included a frog (Xenopus laevis), toad (Bombina orientalis), and snail (Pomacea spp.). Using a unique modeling approach for each species including background point selection based on known established populations resulted in robust ensemble habitat suitability models. All models for all species had test area under the receiver operating characteristic curve values greater than 0.70 and percent correctly classified values greater than 0.65. Importantly, we employed multivariate environmental similarity surface maps to evaluate potential extrapolation beyond observed conditions when applying models globally. These global models provide necessary forecasts of where these aquatic invasive species have the potential for establishment outside their native range, a key component in risk analyses.     

Are You A Terrorist? Comparing Security Screening for Iraqi Asylum Seekers in the United States and Sweden

How can countries balance demands for national security while remaining committed to humanitarian protection? In 2016, the United States and European Union agreed to resettle significant numbers of refugees. Some politicians, including President Trump, argued that refugees are a security threat, even though there are few refugees connected to terrorism. This article investigates how the United States and Sweden screened for terrorism with Iraqi asylum seekers from 2003‐2013, in order to discover how states balance protection and security. This study finds significant policy convergence in three areas (security checks and databases, interagency cooperation, and safety valve programmes), but retains different definitions of terrorism. Policy convergence was driven by international law, UNHCR guidance notes, and international conferences. The study concludes by discussing the policy implications for “extreme vetting” and the use of future safety valve programmes.

Policy Implications

• From 2003‐2013, both the US and Sweden added new security checks, databases, and interagency cooperation. One lesson is that in response to perceived security threats, states often add new layers of bureaucracy and technologies, resulting in slower, more burdensome processes.
• To overcome these barriers, both the US and Sweden created safety value immigration programmes to relieve the pressure from overwhelming demand from Iraqi asylum‐seekers. Policymakers should consider the strategic use of safety valve programmes to speed up processing, allocate additional resources, and provide temporary protection without revising the wider immigration systems.

     

Global Warming Risk Perceptions in India

Few studies have focused on global warming risk perceptions among people in poor and developing countries, who are disproportionately impacted by climate change. This analysis conducts a comprehensive assessment of global warming risk perceptions in India using a national sample survey. Consistent with cultural theory, egalitarianism was positively associated with global warming risk perceptions. In addition, perceived vulnerability and resilience to extreme weather events were also two of the strongest factors associated with global warming risk perceptions. While worry was positively associated with risk perceptions, it accounted for only a small proportion of the variance, unlike studies in developed countries. Finally, the study also collected global warming affective images. The most common responses were “don't know” or “can't say” (25%), followed by “pollution” (21%), “heat” (20%), and “nature” (16%). The study finds that the predictors of global warming risk perceptions among the Indian public are both similar and different than those in developed countries, which has important implications for climate change communication in India.