An extended peer communities’ knowledge sharing approach for environmental governance

This paper is devoted to propose an approach to implement the idea of extended peer knowledge to environmental governance by means of engaging the «extended peer communities». Socially robust knowledge relies on transparency and citizen participation. These two underlying elements take the form of both assessment and post-assessment decision support systems. Initially, during the assessment process citizens and stakeholders are engaged in the framing, proposal of alternatives, and evaluation criteria. Then the analysts assessed the alternatives proposed by means of DSS. Then, in a second stage, the analysts inspired in the idea of transparency, gave back the assessment result to the «extended peer community» who were able to give their opinion regarding the results and suggest potential parametric changes that were used for sensitivity analyses. The authors explore the proposed extended peer communities’ knowledge sharing for environmental governance assessment using a case study applied to a sustainable mobility planning process carried out in Tenerife (Canary Islands). The results gathered highlight that this approach is of use for guaranteeing the robustness of complex environmental decisions under high levels of uncertainty.     

Robustness checks and robustness tests in applied economics

A common exercise in empirical studies is a “robustness check”, where the researcher examines how certain “core” regression coefficient estimates behave when the regression specification is modified by adding or removing regressors. If the coefficients are plausible and robust, this is commonly interpreted as evidence of structural validity. Here, we study when and how one can infer structural validity from coefficient robustness and plausibility. As we show, there are numerous pitfalls, as commonly implemented robustness checks give neither necessary nor sufficient evidence for structural validity. Indeed, if not conducted properly, robustness checks can be completely uninformative or entirely misleading. We discuss how critical and non-critical core variables can be properly specified and how non-core variables for the comparison regression can be chosen to ensure that robustness checks are indeed structurally informative. We provide a straightforward new Hausman (1978) type test of robustness for the critical core coefficients, additional diagnostics that can help explain why robustness test rejection occurs, and a new estimator, the Feasible Optimally combined GLS (FOGLeSs) estimator, that makes relatively efficient use of the robustness check regressions. A new procedure for Matlab, testrob, embodies these methods.     

汇率与股价变动关系:基于汇改后数据的实证研究

研究我国2005年7月汇率制度改革后汇率与股市的关系及其传导机制,有助于深刻认识金融市场联动特征,对于防范金融市场风险和完善我国资本市场、外汇市场等的改革具有重要的理论和实践意义。本文实证发现了汇率和股价存在着长期均衡的协整关系;从长期来看,两者关系符合流量导向模型,上证指数受到汇率长期影响,从短期来看,股市和汇市存在着交互影响,汇率变化影响股指变动有时滞。运用滚动窗口的Granger检验和加入其他重要宏观变量的多变量协整检验,本文证明了这种长期关系具有较强的稳健性。进一步从板块指数与汇率的关系来看,房地产、金融、民航、石化、钢铁指数均与汇率存在着长期的协整关系,汇率变化是这些板块指数的Granger原因。最后,本文对实证结果做出分析并指出了相应的政策含义。     

Maxbias curves of robust scale estimators based on subranges

A maxbias curve is a powerful tool to describe the robustness of an estimator. It is an asymptotic concept which tells how much an estimator can change due to a given fraction of contamination. In this paper, maxbias curves are computed for some univariate scale estimators based on subranges: trimmed standard deviations, interquantile ranges and the univariate Minimum Volume Ellipsoid (MVE) and Minimum Covariance Determinant (MCD) scale estimators. These estimators are intuitively appealing and easy to calculate. Since the bias behavior of scale estimators may differ depending on the type of contamination (outliers or inliers), expressions for both explosion and implosion maxbias curves are given. On the basis of robustness and efficiency arguments, the MCD scale estimator with 25% breakdown point can be recommended for practical use. Received: February 2000     

Bounds for Ratios of Posterior Expectations: Applications in the Collective Risk Model

This paper considers the collective risk model for the insurance claims process. We will adopt a Bayesian point of view, where uncertainty concerning the specification of the prior distribution is a common question. The robust Bayesian approach uses a class of prior distributions which model uncertainty about the prior, instead of a single distribution. Relatively little research has dealt with robustness with respect to ratios of posterior expectations as occurs with the Esscher and Variance premium principles. Appropriate techniques are developed in this paper to solve this problem using the k -contamination class in the collective risk model.     

How to improve the performances of DEA/FDH estimators in the presence of noise?

In frontier analysis, most nonparametric approaches (DEA, FDH) are based on envelopment ideas which assume that with probability one, all observed units belong to the attainable set. In these “deterministic” frontier models, statistical inference is now possible, by using bootstrap procedures. In the presence of noise, envelopment estimators could behave dramatically since they are very sensitive to extreme observations that might result only from noise. DEA/FDH techniques would provide estimators with an error of the order of the standard deviation of the noise. This paper adapts some recent results on detecting change points [Hall P, Simar L (2002) J Am Stat Assoc 97:523–534] to improve the performances of the classical DEA/FDH estimators in the presence of noise. We show by simulated examples that the procedure works well, and better than the standard DEA/FDH estimators, when the noise is of moderate size in term of signal to noise ratio. It turns out that the procedure is also robust to outliers. The paper can be seen as a first attempt to formalize stochastic DEA/FDH estimators.      

The robustness of optimal equilibrium among overlapping generations

Summary. We combine and strengthen optimality and robustness theorems for the overlapping-generations model of money. Roughly, we find a Pareto-optimal monetary equilibrium of a generic stationary economy that is near an optimal monetary equilibrium of each nearby non-stationary economy. Since the nearby equilibria are monetary, the general problem of macroeconomic stabilization reduces to maintaining the money supply. And since the nearby equilibria are optimal, stabilization is socially desirable. Received: October 27, 1997; revised version: March 25, 1998