Deaf and disabled? (Un)Employment of deaf people in Belgium: a comparison of eighteenth-century and nineteenth-century cohorts

In this article, the employment characteristics of pre-industrial and industrial cohorts of deaf men and women are compared with each other, as well as with a cohort of non-disabled siblings. The aim is to determine the extent to which the employment patterns of deaf persons lined up with those of non-disabled people and to see how nineteenth-century industrialization processes influenced their employment opportunities. This article challenges the widely held assumption that the nineteenth century constituted a definitive break by arguing that the professional lives of deaf people were not necessarily better before industrialization. Moreover, I demonstrate that the development of deaf schools in the course of the nineteenth century opened a new range of career opportunities for deaf individuals.     

Risk Analysis: Celebrating the Accomplishments and Embracing Ongoing Challenges

As part of the celebration of the 40th anniversary of the Society for Risk Analysis and Risk Analysis: An International Journal, this essay reviews the 10 most important accomplishments of risk analysis from 1980 to 2010, outlines major accomplishments in three major categories from 2011 to 2019, discusses how editors circulate authors’ accomplishments, and proposes 10 major risk-related challenges for 2020–2030. Authors conclude that the next decade will severely test the field of risk analysis.     

China’s Choice of Analytical Models for Its Anti-Monopoly Law

Modern analytical models for anti-monopoly laws are a core element of the application of those laws. Since the Anti-Monopoly Law of the People’s Republic of China was promulgated in 2008, law enforcement and judicial authorities have applied different analytical models, leading to divergent legal and regulatory outcomes as similar cases receive different verdicts. To select a suitable analytical model for China’s Anti-Monopoly Law, we need to consider the possible contribution of both economic analysis and legal formalism and to learn from the mature systems and experience of foreign countries. It is also necessary to take into account such binding constraints as the current composition of China’s anti-monopoly legal system, the ability of implementing agencies and the supply of economic analysis, in order to ensure complementarity between the analytical model chosen and the complexity of economic analysis and between the professionalism of implementing agencies and the cost of compliance for participants in economic activities. In terms of institutional design, the models should provide a considered explanation of the legislative aims of the law’s provisions. It is necessary, therefore, to establish a processing model of behavioral classification that is based on China’s national conditions, applies analytical models using normative comprehensive analysis, makes use of the distribution rule of burden of proof, improves supporting systems related to analytical models and enhances the ability of public authorities to implement the law.     

Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

Analyzing multiple vector autoregressions through matrix-variate normal distribution with two covariance matrices

Abstract

This article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method.     

Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

Hierarchical Bayesian Modeling of Post-Earthquake Ignition Probabilities Considering Inter-Earthquake Heterogeneity

Post-earthquake fires are high-consequence events with extensive damage potential. They are also low-frequency events, so their nature remains underinvestigated. One difficulty in modeling post-earthquake ignition probabilities is reducing the model uncertainty attributed to the scarce source data. The data scarcity problem has been resolved by pooling the data indiscriminately collected from multiple earthquakes. However, this approach neglects the inter-earthquake heterogeneity in the regional and seasonal characteristics, which is indispensable for risk assessment of future post-earthquake fires. Thus, the present study analyzes the post-earthquake ignition probabilities of five major earthquakes in Japan from 1995 to 2016 (1995 Kobe, 2003 Tokachi-oki, 2004 Niigata–Chuetsu, 2011 Tohoku, and 2016 Kumamoto earthquakes) by a hierarchical Bayesian approach. As the ignition causes of earthquakes share a certain commonality, common prior distributions were assigned to the parameters, and samples were drawn from the target posterior distribution of the parameters by a Markov chain Monte Carlo simulation. The results of the hierarchical model were comparatively analyzed with those of pooled and independent models. Although the pooled and hierarchical models were both robust in comparison with the independent model, the pooled model underestimated the ignition probabilities of earthquakes with few data samples. Among the tested models, the hierarchical model was least affected by the source-to-source variability in the data. The heterogeneity of post-earthquake ignitions with different regional and seasonal characteristics has long been desired in the modeling of post-earthquake ignition probabilities but has not been properly considered in the existing approaches. The presented hierarchical Bayesian approach provides a systematic and rational framework to effectively cope with this problem, which consequently enhances the statistical reliability and stability of estimating post-earthquake ignition probabilities.     

Juvenile Delinquency Under Conditions of Rapid Social Change

Increased juvenile delinquency can be seen as an indicator for a deteriorating social fabric under conditions of rapid social change. Criminological theories suggest, however, that such conditions do not per se produce delinquency: They force youth into prodelinquent leisure activities with peers, leading to an endorsement of delinquent behavior and offering the infrastructure for it. Resources acquired in family and public life, however, may prevent youth from drifting into such prodelinquent leisure activities and indirectly from delinquent behavior. Empirical tests of these hypotheses have to employ simultaneous analyses of societal-level and individual-level data. On the basis of an international youth study, the paper undertakes such an analysis: In the years 1992–95, data from 42 independent samples of seventh graders from East and West Germany, Poland, Russia, Bulgaria, Slovakia, Hungary, Czechia, and Greece were surveyed. Data on deviant school behavior, delinquent drift, nurturant parenting, and subjective feelings of justice in public were obtained from 7282 thirteen- to fourteen-year-olds. Processes of rapid social change were incorporated as data on changes in GNP in the years proceeding the surveys. Analyses show that delinquent drift is a valid predictor of deviant school behavior only on the individual level. The extent to which adolescents engage in prodelinquent peer activities depends more on the cultural context in which adolescents live than on their personal experience in the family and in public. Nurturant parenting does, however, covary negatively with deviant school behavior irrespective of level of analysis.