Semiparametric Bayesian analysis for longitudinal mixed effects models with non-normal AR(1) errors

Statistics and Computing - This paper studies Bayesian inference on longitudinal mixed effects models with non-normal AR(1) errors. We model the nonparametric zero-mean noise in the autoregression...     

SIMEX estimation for single-index model with covariate measurement error

AStA Advances in Statistical Analysis - In this paper, we consider the single-index measurement error model with mismeasured covariates in the nonparametric part. To solve the problem, we develop a...     

Diana Fu: Mobilizing Without the Masses: Control and Contention in China

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Bayesian nonparametric modelling of the link function in the single-index model using a Bernstein–Dirichlet process prior

This paper proposes the use of the Bernstein–Dirichlet process prior for a new nonparametric approach to estimating the link function in the single-index model (SIM). The Bernstein–Dirichlet process prior has so far mainly been used for nonparametric density estimation. Here we modify this approach to allow for an approximation of the unknown link function. Instead of the usual Gaussian distribution, the error term is assumed to be asymmetric Laplace distributed which increases the flexibility and robustness of the SIM. To automatically identify truly active predictors, spike-and-slab priors are used for Bayesian variable selection. Posterior computations are performed via a Metropolis-Hastings-within-Gibbs sampler using a truncation-based algorithm for stick-breaking priors. We compare the efficiency of the proposed approach with well-established techniques in an extensive simulation study and illustrate its practical performance by an application to nonparametric modelling of the power consumption in a sewage treatment plant.     

A misspecification test for the higher order co-moments of the factor model

The traditional estimation of higher order co-moments of non-normal random variables by the sample analog of the expectation faces a curse of dimensionality, as the number of parameters increases steeply when the dimension increases. Imposing a factor structure on the process solves this problem; however, it leads to the challenging task of selecting an appropriate factor model. This paper contributes by proposing a test that exploits the following feature: when the factor model is correctly specified, the higher order co-moments of the unexplained return variation are sparse. It recommends a general to specific approach for selecting the factor model by choosing the most parsimonious specification for which the sparsity assumption is satisfied. This approach uses a Wald or Gumbel test statistic for testing the joint statistical significance of the co-moments that are zero when the factor model is correctly specified. The asymptotic distribution of the test is derived. An extensive simulation study confirms the good finite sample properties of the approach. This paper illustrates the practical usefulness of factor selection on daily returns of random subsets of S&P 100 constituents.     

The quest for legitimacy and the communication of strategic cross-sectoral partnership on Facebook: A big data study

Nowadays, many wicked problems such as environmental issues require organizations from multiple sectors to form cross-sectoral alliances. Cross-sectoral alliance networks can transfer resources and signal affiliations and value alignment between strategic partners. The communication of cross-sectoral alliances is a form of CSR communication that serves organizations’ strategic goals and objectives. Drawing on the literature on digital CSR communication and legitimacy theory, this article examines which legitimacy needs shape the formation of cross-sectoral ties on Facebook in addressing environmental and sustainable development issues in the United States. Combining data-mining, text-mining, social network analysis, and exponential graph modeling, this research investigates the structure of a network among 3071 organizations across multiple sectors. Findings show that organizations’ cross-sectoral tie formation is mainly driven by social legitimacy and alliance legitimacy needs.     

Online crisis communication in a post-truth Chinese society: Evidence from interdisciplinary literature

Through a thematic content analysis of 118 journal articles from interdisciplinary fields, this study reviews the research trends of online crisis communication literature in a Chinese post-truth society, where objective facts play a diminishing role, and Chinese people are losing their trust, despite the best efforts of organizations to deal with fake news in crises. Results of this study disclose some unique crisis communication strategies (e.g., strategic distraction, rumor-rebuttal, fabrication, acting cute, and content censorship) in crises of China. Influential contextual factors such as the political system, cultural values, and media features are identified as well. Theoretical and practical implications of this study are discussed, and a greater picture of online crisis communication in contexts is posited for future research.     

The laws of large numbers for Pareto-type random variables with infinite means

In this paper, we consider the laws of large numbers for NSD random variables satisfying Pareto-type distributions with infinite means. Based on the Pareto-Zipf distributions, some weak laws of large numbers for weighted sums of NSD random variables are obtained. Meanwhile, we show that a weak law for Pareto-Zipf distributions cannot be extended to a strong law. Furthermore, based on the two tailed Pareto distribution, a strong law of large numbers for weighed NSD random variables is presented. Our results extend the corresponding earlier ones.     

Lower bound of average centered L2-discrepancy for U-type designs

Uniform designs are widely used in various scientific investigations and industrial applications. By considering all possible level permutation of the factors, a connection between average centered L₂-discrepancy and generalized wordlength pattern for asymmetrical fractional factorial designs is derived. Moreover, we present new lower bounds to the average centered L₂-discrepancy for symmetrical and asymmetrical U-type designs. For illustration of the theoretical results, the lower bounds for symmetrical and asymmetrical U-type designs are tabulated, and numerical results indicate that our lower bounds behave well and can be recommended for use in practice.     

环境信息不对称、机构投资者实地调研与企业环境治理

基于信息不对称理论,本文以2013-2016年深交所重污染行业上市公司为研究样本,分析了机构投资者实地调研对企业环境治理的影响及其作用机制。研究发现,机构投资者实地调研对企业环境治理具有积极的推动作用;在环境信息披露较差以及本地子公司较多的企业中,机构投资者实地调研的环境治理作用更为明显。进一步考察实地调研对企业环境治理的影响路径发现,机构投资者实地调研推动了企业环境治理的资本市场监督和媒体监督。本文的研究验证了信息不对称理论在环境治理中的作用,拓宽了实地调研经济后果的研究领域,对于深入理解并推动我国企业环境治理具有重要的现实意义。