DOES MOTHER'S EDUCATION MATTER IN CHILD'S HEALTH? EVIDENCE FROM SOUTH AFRICA1

Using the 1993 South Africa Integrated Household Survey, this paper studies the effect that mother's education through the knowledge channel has on children's health using height for age Z‐scores as health measure. Under a two‐stage least square methodology we find that an increase in 4 years on mother's education (approximately 1 standard deviation) will lead to an increase of 0.6 standard deviations on her child's height for age Z‐score. We also find, as the medical literature suggests, support for the hypothesis that mother's education is more important for children older than 24 months of age.     

The ever‐declining role of gender equality in the European Employment Strategy

This article analyses the changing position of gender in the European Employment Strategy (EES) since its 2005 relaunch. Overall, we find a picture of mixed progress towards gender equality goals across Member States. There is evidence of the EU soft law approach leading to positive developments as the use of targets in conjunction with Country‐Specific Recommendations and Points‐to‐Watch have had some influence in promoting gender equality policies among Member States. However, the weakened position of gender mainstreaming in European‐level initiatives has led to gender being marginalised or ignored in national and EU policy responses to the crisis. The prominence of gender has declined further in the 2010 revision of the EES under the 2020 banner. This introduces new risks as the emphasis on gender equality falls further down the list of priorities in the streamlining of the Lisbon Process.     

The impact of Nepal's earthquake on the health status of rural children

We study the impact of Nepal's 2015 earthquake on the health status of children aged 0–5 years. Using a difference-in-differences approach we find that the earthquake decreased height-for-age z-scores (HAZ) and that this effect is largely driven by females, who experienced an average decline of −0.763 standard deviations in their HAZ. Further, we find that females in the 0–3 years age group and in the least wealthy households are the most vulnerable. This is particularly unfortunate, as the first 3 years of life can impact long-term health and well-being, and female undernutrition contributes to the intergenerational transmission of poverty and ill health.     

Assessing the needs of international markets against an emerging market company's capabilities: A tool for internationalization

Senior managers in emerging markets often strive to ensure that their companies develop sufficient capabilities to confront the needs they encounter in international markets. However, extant research and practice remain unclear as to how senior managers in emerging market companies can approach assessing the needs of their international markets against their own company's capabilities, to aim for a balance between both. This article offers an innovative approach for assessing the needs of international markets against an emerging market company's capabilities. Based on the assessments of 100 senior managers leading emerging market companies, we explain how this approach can provide two key insights. First, evidence of a balance between the needs of international markets and an emerging market company's capabilities, that indicates the company's competitive position is focused; or evidence of an imbalance between the needs of international markets and an emerging market company's capabilities, that indicates the company's competitive position is either vulnerable or overqualified. Second, an understanding of where the gaps between the needs of international markets and an emerging market company's capabilities are, that enables improving the company's competitive position by closing these gaps. Drawing on this approach, we offer an open access tool that allows senior managers in emerging markets to identify and improve their own company's competitive position for internationalization. Using this tool, senior managers can lead their emerging market companies toward a focused competitive position in international markets, providing better chances of successfully capturing potential benefits.     

The Editorial Boards of Italian Economics Journals: Women,Gender, and Social Networking

In Italy, women's advancement in economics has been curtailed by the structure of editorial boards of Italian economics journals. In this paper, we examine the presence of men and women economists on the editorial boards of thirty-six Italian economics journals published since 1970 and analyze the gender distribution across different kinds of boards, roles, and fields. Because boards are hierarchically ordered, women work mostly in the lower positions, and the increase in women's participation has led only to more "editorial secretaries." Since men and women tend to have different scientific interests and men's standards of academic value prevail, women economists cannot build publication records as strong as those of their male colleagues, which, in turn, affects women's hiring, promotion, and wages, as well as the shape of the discipline.     

Growth in transition countries

This study analyzes the impact of the speed of transition reforms on economic growth in transition countries in the context of the debate on ‘big‐bang vs. gradualist approach’. It builds a new indicator for the speed of transition reforms based on a three‐way principal component analysis. It shows that: (i) the speed of transition reforms Granger‐causes economic growth and there is no reverse causation; (ii) the impact of contemporaneous speed of transition reforms on economic growth is negative, but becomes positive in the longer horizon; and (iii) other factors, such as initial conditions and macroeconomic stabilization programmes, also drive economic growth. Although the first two results are robust to different estimators, the impact of control variables depends on the econometric specification.     

The information content of implied volatility, skewness and kurtosis: empirical evidence from long-term CAC 40 options

Implied standard deviation is widely believed to be the best available forecast of the volatility of returns over the remaining contract life (Jorion, 1995 ). In this paper, we take this result two steps further to the higher moments of the distribution (skewness and kurtosis) based on a Gram–Charlier series expansion of the normal distribution (Corrado and Su, 1996 ) using long-term CAC 40 option prices contract, named PXL. First, we found that implied first moments contain a substantial amount of information for future moments of CAC 40 returns although this amount decreases with respect to the moment's order. Secondly, we found that the different shapes of the volatility smile are consistent with different distribution of the underlying returns. Based on these results, we also observed that including other implied moments significantly improves the out-of-sample pricing performance of the Black–Scholes, (1973) model.     

Estimated burden of cardiovascular disease and value-based price range for evolocumab in a high-risk,secondary-prevention population in the US payer context

Aim: To estimate real-world cardiovascular disease (CVD) burden and value-based price range of evolocumab for a US-context, high-risk, secondary-prevention population.

Materials and methods: Burden of CVD was assessed using the UK-based Clinical Practice Research Datalink (CPRD) in order to capture complete CV burden including CV mortality. Patients on standard of care (SOC; high-intensity statins) in CPRD were selected based on eligibility criteria of FOURIER, a phase 3 CV outcomes trial of evolocumab, and categorized into four cohorts: high-risk prevalent atherosclerotic CVD (ASCVD) cohort (n?=?1448), acute coronary syndrome (ACS) (n?=?602), ischemic stroke (IS) (n?=?151), and heart failure (HF) (n?=?291) incident cohorts. The value-based price range for evolocumab was assessed using a previously published economic model. The model incorporated CPRD CV event rates and considered CV event reduction rate ratios per 1?mmol/L reduction in low-density lipoprotein-cholesterol (LDL-C) from a meta-analysis of statin trials by the Cholesterol Treatment Trialists Collaboration (CTTC), i.e. CTTC relationship.

Results: Multiple-event rates of composite CV events (ACS, IS, or coronary revascularization) per 100 patient-years were 12.3 for the high-risk prevalent ASCVD cohort, and 25.7, 13.3, and 23.3, respectively, for incident ACS, IS, and HF cohorts. Approximately one-half (42%) of the high-risk ASCVD patients with a new CV event during follow-up had a subsequent CV event. Combining these real-world event rates and the CTTC relationship in the economic model, the value-based price range (credible interval) under a willingness-to-pay threshold of $150,000/quality-adjusted life-year gained for evolocumab was $11,990 ($9,341–$14,833) to $16,856 ($12,903–$20,678) in ASCVD patients with baseline LDL-C levels ≥70?mg/dL and ≥100?mg/dL, respectively.

Conclusion: Real-world CVD burden is substantial. Using the observed CVD burden in CPRD and the CTTC relationship, the cost-effectiveness analysis showed that, accounting for uncertainties, the expected value-based price for evolocumab is higher than its current annual cost, as long as the payer discount off list price is greater than 20%.     

A continuous time Bayesian network classifier for intraday FX prediction

Abstract

Prediction of foreign exchange (FX) rates is addressed as a binary classification problem in which a continuous time Bayesian network classifier (CTBNC) is developed and used to solve it. An exact algorithm for inference on CTBNC is introduced. The performance of an instance of these classifiers is analysed and compared to that of dynamic Bayesian network by using real tick by tick FX rates. Performance analysis and comparison, based on different metrics such as accuracy, precision, recall and Brier score, evince a predictive power of these models for FX rates at high frequencies. The achieved results also show that the proposed CTBNC is more effective and more efficient than dynamic Bayesian network classifier. In particular, it allows to perform high frequency prediction of FX rates in cases where dynamic Bayesian networks-based models are computationally intractable.