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.     

Inflation projections for monetary policy decision making

Many central banks set inflation targets over the medium term and inflation projections are a key input for monetary policy decision making. In this paper, we present the procedures used by the Spanish Central Bank staff to project consumer price inflation. We also provide some illustrations of their policy uses, such as fan charts, deflation probabilities and the monitoring of inflation targets.     

人民政协在利益协调机制中的独特地位和作用

人民政协是发扬社会主义民主的重要形式,这就决定了它在完善社会利益协调机制中具有重要的地位。作为中国上层建筑的重要组成部分,人民政协必须也可以适应经济基础的发展,在完善利益诉求表达机制、利益政策整合机制、利益观念引导机制、利益冲突化解机制、利益实现与保障机制中,发挥独特作用。     

Non-tariff barrier on chicken imports into Russia: Impact on production,trade and prices

We analyze the Russian restriction on chicken imports as an example of a non-tariff barrier (NTB). Cointegration test results support the hypothesis that the NTB limited trade. We calibrate an equilibrium market model to cointegration results to assess the market impact. The tariff equivalent of the Russian chicken NTB is estimated to be 30 − 40% depending on the representation of consumer demand. Removing the NTB decreases domestic production by 4–5% and domestic price by 27%–34%, while imports increase by 326–423 thousand tons annually in 2015–2019.     

Central tendency bias in belief elicitation

We conduct an experiment in which subjects participate in a first-price auction against an automaton that bids randomly in a given range. The subjects first place a bid in the auction. They are then given an incentivized elicitation of their beliefs of the opponent’s bid. Despite having been told that the bid of the opponent is drawn from a uniform distribution, we find that a majority of subjects report beliefs that have a peak in the interior of the range. This result is robust across seven different experimental treatments. While not expected at the outset, these single-peaked beliefs have precedence in the experimental psychology judgments literature. Our results suggest that an elicitation of probability beliefs can result in responses that are more concentrated than the objectively known or induced truth. We provide indicative evidence that such individual belief reports can be rationalized by well-defined subjective beliefs that differ from the objective truth. Our findings offer an explanation for the conservatism and overprecision biases in Bayesian updating. Finally, our findings suggest that probabilistic forecasts of uncertain events might have less variance than the actual events.     

青少年道德判断能力研究

道德教育重要组成部分的道德判断能力,在规范人际关系上发挥着法律所无法起到的作用,对此进行研究为中国学校道德教育提供有效的评估工具和手段．使道德教育更具科学性和可操作性。德国道德心理学家林德设计的“道德判断测验（MJT）”界定了道德认知和情感。对湖北省青少年的研究发现,青少年道德判断能力的总体相对偏低。在政治面貌这一特征上出现了显著差异,而性别职业学历、是否为独生子女、家住农村或城镇等方面的不同不会带来显著差异。具体到各特征内部,出现了年龄、政治面貌等值得进一步关注的问题。     

Enabling robust assessment of QTc prolongation in early phase clinical trials

Since the implementation of the International Conference on Harmonization (ICH) E14 guideline in 2005, regulators have required a “thorough QTc” (TQT) study for evaluating the effects of investigational drugs on delayed cardiac repolarization as manifested by a prolonged QTc interval. However, TQT studies have increasingly been viewed unfavorably because of their low cost effectiveness. Several researchers have noted that a robust drug concentration‐QTc (conc‐QTc) modeling assessment in early phase development should, in most cases, obviate the need for a subsequent TQT study. In December 2015, ICH released an “E14 Q&As (R3)” document supporting the use of conc‐QTc modeling for regulatory decisions. In this article, we propose a simple improvement of two popular conc‐QTc assessment methods for typical first‐in‐human crossover‐like single ascending dose clinical pharmacology trials. The improvement is achieved, in part, by leveraging routinely encountered (and expected) intrasubject correlation patterns encountered in such trials. A real example involving a single ascending dose and corresponding TQT trial, along with results from a simulation study, illustrate the strong performance of the proposed method. The improved conc‐QTc assessment will further enable highly reliable go/no‐go decisions in early phase clinical development and deliver results that support subsequent TQT study waivers by regulators.     

Inference of non-centrality parameter of a truncated non-central chi-squared distribution

Non-central chi-squared distribution plays a vital role in statistical testing procedures. Estimation of the non-centrality parameter provides valuable information for the power calculation of the associated test. We are interested in the statistical inference property of the non-centrality parameter estimate based on one observation (usually a summary statistic) from a truncated chi-squared distribution. This work is motivated by the application of the flexible two-stage design in case–control studies, where the sample size needed for the second stage of a two-stage study can be determined adaptively by the results of the first stage. We first study the moment estimate for the truncated distribution and prove its existence, uniqueness, and inadmissibility and convergence properties. We then define a new class of estimates that includes the moment estimate as a special case. Among this class of estimates, we recommend to use one member that outperforms the moment estimate in a wide range of scenarios. We also present two methods for constructing confidence intervals. Simulation studies are conducted to evaluate the performance of the proposed point and interval estimates.     

Models for the analysis of C-reactive protein in statin trials

Elevation in C-reactive protein (CRP) is an independent risk factor for cardiovascular disease progression and levels are reduced by treatment with statins. However, on-treatment CRP, given baseline CRP and treatment, is not normally distributed and outliers exist even when transformations are applied. Although classical non-parametric tests address some of these issues, they do not enable straightforward inclusion of covariate information. The aims of this study were to produce a model that improved efficiency and accuracy of analysis of CRP data. Estimation of treatment effects and identification of outliers were addressed using controlled trials of rosuvastatin. The robust statistical technique of MM-estimation was used to fit models to data in the presence of outliers and was compared with least-squares estimation. To develop the model, appropriate transformations of the response and baseline variables were selected. The model was used to investigate how on-treatment CRP related to baseline CRP and estimated treatment effects with rosuvastatin. On comparing least-squares and MM-estimation, MM-estimation was superior to least-squares estimation in that parameter estimates were more efficient and outliers were clearly identified. Relative reductions in CRP were higher at higher baseline CRP levels. There was also evidence of a dose-response relationship between CRP reductions from baseline and rosuvastatin. Several large outliers were identified, although there did not appear to be any relationships between the incidence of outliers and treatments. In conclusion, using robust estimation to model CRP data is superior to least-squares estimation and non-parametric tests in terms of efficiency, outlier identification and the ability to include covariate information.     

Exponentially weighted moving average charts for correlated multivariate Poisson processes

In this article, we study exponentially weighted moving average (EWMA) control schemes to monitor the multivariate Poisson distribution with a general covariance structure, so that the practitioner can simultaneously monitor multiple correlated attribute processes more effectively. The statistical performance of the charts is assessed in terms of the run length properties and compared against other mainstream attribute control schemes. The application of the proposed methods to real-life and simulated datasets is demonstrated.