Robust multivariate analysis for mixed-type data: Novel algorithm and its practical application in socio-economic research

We propose a novel method and algorithm for the analysis and clustering of mixed-type data using a hierarchical approach based on Forward Search. In our procedure, the identification of groups is based on the identification of similar trajectories and then linked to very intuitive two-dimensional maps. The proposed algorithm can use different measures for the calculation of distance in the case of mixed-type data, such as Gower’s metric and Related metric scaling. A key feature of our algorithm is its ability to discard redundant information from a given set of variables. The practical usefulness of the algorithm is illustrated through two applications of high relevance for empirical economic research. The first one focuses on comparing different indicators of environmental policy stringency in different countries. The second one applies our procedure to identify clusters of countries based on information regarding their institutional characteristics.     

Factor pricing of cryptocurrencies

In this paper, we study the cryptocurrency pricing factors. We review the literatures which state that the cryptocurrency market is weakly efficient. We use the Fama–MacBeth method to investigate the pricing factors. The classical equity-based risk factors including size, momentum, and value to growth from the Fama–French three factor model are studied. We use crypto-unique coin-to-token as a proxy for value-to-growth. For volatility risk factor category, we investigate realized volatility, skewness and jump. We also investigate liquidity factors including bid–ask, volume growth and Roll’s measure. The macro factors are found not to be an explanatory factor. The attention factor works sometimes. The factor model constructed by the significant factors explain most of the excess return of cryptocurrencies.     

THE MEANING OF FAILED REPLICATIONS: A REVIEW AND PROPOSAL

The welcome rise of replication tests in economics has not been accompanied by a consensus standard for determining what constitutes a replication. A discrepant replication, in current usage of the term, can signal anything from an unremarkable disagreement over methods to scientific incompetence or misconduct. This paper proposes a standard for classifying one study as a replication of some other study. It is a standard that places the burden of proof on a study to demonstrate that it should have obtained identical results to the original, a conservative standard that is already used implicitly by many researchers. It contrasts this standard with decades of unsuccessful attempts to harmonize terminology, and argues that many prominent results described as replication tests should not be described as such. Adopting a conservative standard like this one can improve incentives for researchers, encouraging more and better replication tests.     

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.     

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.     

Modeling cascade dynamics of railway networks under inclement weather

Understanding the cascade dynamics of delay propagation under inclement weather is crucial to proactive railway management. In this paper, we proposed a Switching Max-Plus System (SMPS) to model the delay propagation on railway networks, which extends the conventional MPS by incorporating multiple system matrices to capture the dynamic impacts of inclement weather. An algorithm based on the All-Paired Critical-Path (APCP) graph was developed to solve the SMPS, which calculates secondary delays without backtracking the precedent events. The proposed model and its solution algorithm were validated using discrete-time simulations on both artificial and empirical networks. The robustness of railway services was also analyzed using the concepts of vulnerability and diffusivity.     

影响自主创新的因素——基于BACE方法对中国省际数据的分析

经典估计贝叶斯平均(BACE)是最近由Sala-i-Martin等人提出的一种处理模型不确定性的方法,它可以在进行参数估计的同时给出各解释变量的稳健性指标,并且还能够按照解释能力的大小对众多的备选变量进行分类和排序.本文首次利用这一方法对可能影响中国自主创新的因素进行了全面的分析,在上百万次回归的基础上,我们得到的主要结果是:在事先列出的20个可能的解释变量中,本地区试验发展支出、人均GDP、贸易依存度、邻接地区试验发展支出对创新产出的解释能力最强,并且都具有良好的稳健性;贷款余额与GDP之比、外商直接投资与GDP之比、各地区科学研究支出、地方财政决算本级收入与GDP之比、邻接地区科学研究支出等五个变量对创新产出也有一定的解释能力.     

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     

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.     

Robustness of the air transport network

This paper presents a methodology for the detection of critical airports (those whose isolation would cause the largest losses in network connectivity) in the global air transport network (ATN), based on simulating an attack on selected ATN airports using different adaptive selection criteria. The performances of several node selection criteria are compared, together with a new criterion based on Bonacich power centrality. The results show that most critical airports can be detected with an adaptive strategy based on betweenness centrality. The detection of such airports may help the development of contingency plans to develop an appropriate response to any airport closure.