Robust nonparametric estimation with missing data

In this paper, under a nonparametric regression model, we introduce two families of robust procedures to estimate the regression function when missing data occur in the response. The first proposal is based on a local M$M$-functional applied to the conditional distribution function estimate adapted to the presence of missing data. The second proposal imputes the missing responses using the local M$M$-smoother based on the observed sample and then estimates the regression function with the completed sample. We show that the robust procedures considered are consistent and asymptotically normally distributed. A robust procedure to select the smoothing parameter is also discussed.     

Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps

Abstract. We consider a stochastic process driven by diffusions and jumps. Given a discrete record of observations, we devise a technique for identifying the times when jumps larger than a suitably defined threshold occurred. This allows us to determine a consistent non‐parametric estimator of the integrated volatility when the infinite activity jump component is Lévy. Jump size estimation and central limit results are proved in the case of finite activity jumps. Some simulations illustrate the applicability of the methodology in finite samples and its superiority on the multipower variations especially when it is not possible to use high frequency data.     

Fluctuating capacity of policy advice in Russia: testing theory in developing country context

ABSTRACT

Theories and concepts developed and empirically tested in the context of North American and Western European countries do not always easily transfer to another political landscape. The concept of “policy advisory system” is not an exception. On the one hand, policy processes and policy styles are not unique for each country; therefore, some generalizations can be made. On the other hand, studding particularities of policy process in a specific country can enrich theories, developed for general cases. Applying existing theories to a new context also goes a long way in verification and potential falsification – the fundamental requirement for a scientific process. This article aims to contribute to the debate on the topic of policy advisory system by comparing the development of three policies in Russia, each involving policy advisors to some extent. Based on this analysis, lessons are drawn regarding the conditions under which policy advisors can impact policy changes in an environment, alternative to “western.”     

Conditional VAR and Expected Shortfall: A New Functional Approach

We estimate two well-known risk measures, the value-at-risk (VAR) and the expected shortfall, conditionally to a functional variable (i.e., a random variable valued in some semi(pseudo)-metric space). We use nonparametric kernel estimation for constructing estimators of these quantities, under general dependence conditions. Theoretical properties are stated whereas practical aspects are illustrated on simulated data: nonlinear functional and GARCH(1,1) models. Some ideas on bandwidth selection using bootstrap are introduced. Finally, an empirical example is given through data of the S&P 500 time series.     

Factor screening in nonregular two-level designs based on projection-based variable selection

In this paper, we focus on the problem of factor screening in nonregular two-level designs through gradually reducing the number of possible sets of active factors. We are particularly concerned with situations when three or four factors are active. Our proposed method works through examining fits of projection models, where variable selection techniques are used to reduce the number of terms. To examine the reliability of the methods in combination with such techniques, a panel of models consisting of three or four active factors with data generated from the 12-run and the 20-run Plackett–Burman (PB) design is used. The dependence of the procedure on the amount of noise, the number of active factors and the number of experimental factors is also investigated. For designs with few runs such as the 12-run PB design, variable selection should be done with care and default procedures in computer software may not be reliable to which we suggest improvements. A real example is included to show how we propose factor screening can be done in practice.     

Contribution analysis to analyze the effects of the health impact assessment at the local level: A case of urban revitalization

The health impact assessment (HIA) is a tool used to estimate the potential impact on health of non-health-related proposals prior to implementation. While it is increasingly used in Quebec, Canada, studies have not analyzed its medium-term impacts and potential long-term impacts. We conducted a contribution analysis using in-depth interviews with key stakeholders, as well as documents, observation and images related to HIA in order to analyze its impacts on the revitalization of road infrastructure, parks and green spaces, and residential housing. Our analysis not only reflects on the decision-making process through the adoption and implementation of HIA recommendations, but also on the link between actions implemented in the field and health outcomes.     

关于做好电视成就报道的思考

文章着重探讨了电视成就报道的创新方法,在理念上提出以个性化的受众为中心、结合电视传播特点、贴近工作实际;具体方法上则提出以四个方面为突破口,即:通过个人化的视角,贴近生活;用理性思维诠释热点;用情节化的叙述,加深人们的理解;调动多种电视表现手段,增强视觉冲击力.     

基于广义误差分布的股票收益率波动特征分析

假设股票收益率序列服从具有厚尾特征的GED分布,利用多种非对称性模型描述和检验了沪市股票日收益率序列的波动性特征,发现股票价格波动具有条件异方差性,并通过对股票市场信息影响曲线的分析,刻画了沪市股票价格波动中的显著非对称性。这说明股市波动对于不同的政策干预和信息冲击具有不同程度的反应,且非对称性的方向与以往结论有所不同,说明我国股市风险变异特征和收益状况在不断的发生变化,＂利好消息＂对股市的刺激作用需要其他市场干预的配合才能发挥出来。