Poverty and educational achievement in the US: A less-biased estimate using PISA 2012 data

In the current paper, we employ the most recent Programme for International Student Assessment (PISA) data to calculate a less-biased estimate of poverty on US achievement. The PISA was specifically chosen as it is an assessment removed from a specific curriculum and instead focuses on concepts that students should know in order to participate in a global economy. Using a propensity score matching approach, our findings suggest that US students in poverty have notable educational attainment deficiencies compared to a matched group of students who are not in poverty. In other words, when we select two students who have a great deal in common but for the fact that one comes from a poverty background, the student in poverty is expected to perform nearly 28 points, or about a quarter of a standard deviation lower, on the PISA assessment. In real terms, this puts math achievement for children not in poverty on-par with the Organisation for Economic Co-operation and Development (OECD) average, while children in poverty are well below the OECD average.     

Multivariate Return Decomposition: Theory and Implications

In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method.     

New calibration estimator based on two auxiliary variables in stratified sampling

In recent years, calibration estimation has become an important field of research in survey sampling. This paper proposes a new calibration estimator for the population mean in the presence of two auxiliary variables in stratified sampling. The theory of new calibration estimator is given and optimum calibration weights are derived. A simulation study is carried out to performance of the proposed calibration estimator over other existing calibration estimators. The results reveal that the proposed calibration estimators are more efficient than other existing calibration estimators in stratified sampling.     

参加医疗保险对农村居民健康的影响——基于CHARLS 2015数据的实证分析

基于CHARLS 2015数据,采用倾向得分匹配法实证分析参加医疗保险对农村居民健康的影响。研究发现:参加医疗保险对农村居民的日常活动能力和自评健康影响不显著,参加医疗保险对农村居民认知能力具有显著的正向影响。据此提出,应进一步提升社会医疗保险保障水平、扩大社会医疗保险保障范围、促进商业医疗保险有序发展、推进"三医"高效协同联动等,以充分发挥医疗保险的健康保障功能,从而进一步提升参加医疗保险对农村居民健康的正向影响。     

Identifying Systemically Important Banks: A temporal approach for macroprudential policies

Contrary to the general belief, systemic risk does not only regard the risk posed by balance sheet relationships and interdependencies among institutions. It also features a temporal dimension related to the inappropriate responses of financial market participants to changes in risk over time. This paper proposes a method to simultaneously address the cross-sectional and the time dimension in which systemic risk materializes. The method is based on the TOPHITS algorithm. It provides three scores, namely borrowing, lending and time scores: the first two represent the systemic importance of the borrowing and the lending activity associated with each financial institution,while the third represents an empirical Early Warning Signal of the financial crisis. Our findings reveal that the identification of the time score as an indicator for an incoming market distress could be relevant to design macro prudential policies.     

Investment communities: Behavioral attitudes and economic dynamics

Using a real-world data set encompassing the daily portfolio holdings and exposures of complex investment funds, we derive a set of quantitative attributes to capture essential behavioral features of fund managers. We find the existence and stability of three investment attitudes, namely the conservative, the reactive, and the pro-active profiles, defining communities that respond differently when facing external shocks. The conservative community has behavioral similarities that tend to decrease due to external shocks, the reactive community members greatly increase their activity level especially during turmoil phases, while delegated investors in the pro-active community are more resilient to turbulence and counterbalance the impact of the events by adjusting their portfolio exposures in advance. We show that exogenous shocks only temporarily perturb the behavioral traits of the communities which then go back to their original states once the distress is embedded.     

Latin American convergence and divergence towards the mortality profiles of developed countries

It is uncertain whether Latin America and Caribbean (LAC) countries are approaching a single mortality regime. Over the last three decades, LAC has experienced major public health interventions and the highest number of homicides in the world. However, these interventions and homicide rates are not evenly shared across countries. This study documents trends in life expectancy and lifespan variability for 20 LAC countries, 2000–14. By extending a previous method, we decompose differences in lifespan variability between LAC and a developed world benchmark into cause-specific effects. For both sexes, dispersion of amenable diseases through the age span makes the largest contribution to the gap between LAC and the benchmark. Additionally, for males, the concentration of homicides, accidents, and suicides in mid-life further impedes mortality convergence. Great disparity exists in the region: while some countries are rapidly approaching the developed regime, others remain far behind and suffer a clear disadvantage in population health.     

A propensity score matching analysis of the relationship between victim sex and capital juror decision-making in North Carolina

A small body of prior research has examined the impact of victim sex on jury death penalty decision-making and the majority of this research has demonstrated some evidence of a “female victim effect” such that cases involving a female victim are more likely to receive the death penalty than similarly situated cases with a male victim. However, within this line of research studies have suggested that victim sex may work in conjunction with other case characteristics. In order to further explore this phenomenon, the current study examines a near-population of death penalty cases from North Carolina (n = 1069) from 1977–2009 using propensity score matching. Results demonstrate that once cases are matched on more than 50 legal and extralegal case characteristics, there is no statistically significant or substantive link between victim sex and death penalty decision-making. Findings suggest that it is concrete differences in the legal and extralegal factors observed in cases with female victims compared to male victims that shape jury death sentence decisions rather than a direct effect of victim sex (before matching: OR = 1.53; 95% CI = 1.20–1.95; p < .001/after matching: OR = 0.90; 95% CI = 0.66–1.24; p = .52). Study limitations and implications are also discussed.     

Noninformative priors for linear combinations of normal means with unequal variances

For normal populations with unequal variances, we develop matching priors and reference priors for a linear combination of the means. Here, we find three second-order matching priors: a highest posterior density (HPD) matching prior, a cumulative distribution function (CDF) matching prior, and a likelihood ratio (LR) matching prior. Furthermore, we show that the reference priors are all first-order matching priors, but that they do not satisfy the second-order matching criterion that establishes the symmetry and the unimodality of the posterior under the developed priors. The results of a simulation indicate that the second-order matching prior outperforms the reference priors in terms of matching the target coverage probabilities, in a frequentist sense. Finally, we compare the Bayesian credible intervals based on the developed priors with the confidence intervals derived from real data.     

Macroeconomic performance of inflation targeting in European and Asian emerging economies

The macroeconomic performance resulting from adopting an inflation targeting policy in emerging economies of Europe and Central Asia are examined. The research includes 26 countries in the period 1997–2019, with a special focus on the period 2008–2019. Our econometric analysis consists of two approaches: dynamic panel modeling and propensity score matching. The results suggest that macroeconomic performance has improved due to the inflation targeting monetary framework. We find that a policy of inflation targeting has been effective in reducing the inflation rate, inflation volatility, and GDP volatility. The results are particularly robust for the subperiod that started in 2008. Econometric results suggest that inflation targeting policy did not affect inflation persistence or GDP growth. Our results suggest that inflation targeting improves the macroeconomic performance of developing countries even when they only partially meet the standard requirements for its implementation.