Asymptotic distributions in affiliation networks with an increasing sequence

A central limit theorem for a linear combination of all the maximum likelihood estimators with an increasing dimension for affiliation networks has been established. Simulation studies are provided to illustrate the asymptotic results.     

Generalized method of moments for an extended gamma process

In reliability theory, a widely used process to model the phenomena of the cumulative deterioration of a system over time is the standard gamma process (SGP). Based on several restrictions, such as a constant variance-to-mean ratio, this process is not always a suitable choice to describe the deterioration. A way to overcome these restrictions is to use an extended version of the gamma process introduced by Cinlar (1980), which is characterized by shape and scale functions. In this article, the aim is to propose statistical methods to estimate the unknown parameters of parametric forms of the shape and scale functions. We here develop two generalized methods of moments (Hansen 1982 Hansen, L. P. 1982. Large sample properties of generalized method of moments estimators. Econometrica 50 (4):1029–54.[Crossref], [Web of Science ®] , [Google Scholar]), based either on the moments or on the Laplace transform of an extended gamma process. Asymptotic properties are provided and a Wald-type test is derived, which allows to test SGPs against extended ones with a specific parametric shape function. Also, the performance of the proposed estimation methods is illustrated on simulated and real data.     

A review of backtesting for value at risk

There have been many backtesting methods proposed for value at risk. Yet they have rarely been applied in practice. Here, we provide a comprehensive review of all of the recent backtesting methods for VaR. This review could encourage applications and also the development of further backtesting methods.     

WLAD-LASSO method for robust estimation and variable selection in partially linear models

This paper focuses on robust estimation and variable selection for partially linear models. We combine the weighted least absolute deviation (WLAD) regression with the adaptive least absolute shrinkage and selection operator (LASSO) to achieve simultaneous robust estimation and variable selection for partially linear models. Compared with the LAD-LASSO method, the WLAD-LASSO method will resist to the heavy-tailed errors and outliers in the parametric components. In addition, we estimate the unknown smooth function by a robust local linear regression. Under some regular conditions, the theoretical properties of the proposed estimators are established. We further examine finite-sample performance of the proposed procedure by simulation studies and a real data example.     

Strong and weak consistency of LS estimators in the EV regression model with negatively superadditive-dependent errors

In this paper, the strong laws of large numbers for partial sums and weighted sums of negatively superadditive-dependent (NSD, in short) random variables are presented, especially the Marcinkiewicz–Zygmund type strong law of large numbers. Using these strong laws of large numbers, we further investigate the strong consistency and weak consistency of the LS estimators in the EV regression model with NSD errors, which generalize and improve the corresponding ones for negatively associated random variables. Finally, a simulation is carried out to study the numerical performance of the strong consistency result that we established.     

Emergent models and strategies of social enterprises in China

Abstract

Many nonprofits are turning to commercial strategies to enhance their income. While previous research identified challenges social enterprises face in balancing commercial and social missions, little is known about how Chinese social enterprises respond to similar challenges in meeting the double bottom line. Using 16 cases studies, this study identified different types of social enterprises extant in the Chinese context, and examined the strategies they adopt. We found that the fee-for-service is the most common operational model, and that despite attempts of heavy state influence, Chinese SEs were able to demonstrate their resilience by diversifying their operational models. Implications for China’s social work development are discussed.     

突发事件中的国家-社会关系——上海基层社区“抗非”考察

对中国城市基层治理的探讨,大多得出“强国家、弱社会”的结论,其议题亦无涉居民切身利益,无法为“强势国家”提供有力佐证。本研究以上海社区“抗非”动员为背景,观察突发事件中的国家-社会关系。调查发现,上海的“抗非”工作几乎都由国家主导,居民仅被动配合,自发参与度极其有限。在具体策略上,国家一方面透过主流媒体的调控,掌握“议题建构”渠道;另一方面则借助社区建设的配合,节制“社会参与”渠道,从而在因对突发事件的过程中,强化了国家的合法性和掌控力,构筑了“国强社弱”的制度格局。     

Assessing a minimum pension guarantee for the voluntary IPS in Turkey

The returns from individual account pension plans are subject to fluctuations in capital markets. This increases income uncertainty for the beneficiary and exposes individuals to the risk of fluctuations in the economy in general and the stock market in particular. A minimum pension guarantee is a way to avoid this pitfall by providing a minimum annuity regardless of the actual investment performance of individual accounts. In this article, we present a cost analysis of a minimum benefit guarantee mechanism for the voluntary Individual Pension System in Turkey. We examine the cost estimates and the probability of providing guaranteed payments under various economic and demographic assumptions.     

收入风险、金融教育与家庭金融市场参与

运用中国城市居民消费金融调查数据,基于因果推断的分析框架,采用倾向分值匹配法研究了收入风险、金融教育对家庭金融市场参与的影响。研究发现,收入越稳定,家庭开展金融教育的概率越高;金融教育显著提高了家庭的金融市场参与;按收入风险将样本分组后,上述结论依然稳健,且金融教育对不同家庭金融市场参与的影响具有非对称性。在对家庭收入稳定性分类的基础上,有针对性地增加金融教育的供给,提升家庭整体的金融教育水平,有利于提高家庭金融市场参与度,优化家庭金融资产配置,进而改善家庭金融福利。     

Likelihood estimation for longitudinal zero-inflated power series regression models

In this paper, a zero-inflated power series regression model for longitudinal count data with excess zeros is presented. We demonstrate how to calculate the likelihood for such data when it is assumed that the increment in the cumulative total follows a discrete distribution with a location parameter that depends on a linear function of explanatory variables. Simulation studies indicate that this method can provide improvements in obtaining standard errors of the estimates. We also calculate the dispersion index for this model. The influence of a small perturbation of the dispersion index of the zero-inflated model on likelihood displacement is also studied. The zero-inflated negative binomial regression model is illustrated on data regarding joint damage in psoriatic arthritis.