The Women’s Empowerment in Livestock Index

Social Indicators Research - The empowerment of women in the livestock sector is fundamental to achieve gender equality. It also is instrumental for increased household productivity and improved...     

Testing Fair Wage Theory

Fairness considerations often are invoked to explain wage differences that appear unrelated to worker characteristics or job conditions, but non-experimental tests of fair wage models are rare because market data rarely permit researchers to measure individual workers’ productivity and its value. We use data from the baseball labor market to address this problem, and find no support for fair wage theory. We do find, however, that fairness premia can be illusory: Wages appear to incorporate fairness premia in regressions that control for variation in individuals’ physical output, but such premia evaporate when the value of that output is held constant.

Failings in U.K. transport planning

This discussion of British Government policy on transport, highlights the absence of a coherent strategic plan as a guideline for individual decision-making. Without this framework and a recognition of the close connection between transport and land use planning, conventional methods of project appraisal produce an unsatisfactory piecemeal transport system. As an example, the 1973 Channel Tunnel proposals are examined and found inappropriate for either of the main possible directions of progress sketched out.     

On the multilateral index number system based on the factorial approach

This paper examines what of the Eichhorn-Voeller axioms are satisfied by the multilateral index numbers based on the factorial approach. Finally, concerning the overall performance of the system, a pertinent observation is made strengthening its dependability as a practical guide.     

基于价值链的中国企业社会责任对财务价值的影响

为了支持企业持续地将履行社会责任作为一种长期的战略,探讨企业社会责任与业务相结合对财务绩效的影响以及如何选择既造福社会又有利于商业的社会责任项目.基于价值链视角,采用利益相关者理论和归因理论,用实证方法,选择中国公司社会责任披露的数据,采用因子分析法划分企业社会责任活动,采用面板数据回归分析每种社会责任活动及其交互作用对企业财务绩效的影响.研究结果表明,把社会责任活动分为与价值链基本活动相关的社会责任、与价值链支持活动相关的社会责任和一般性社会责任(与价值链活动无关),与价值链基本活动相关的社会责任和与价值链支持活动相关的社会责任对财务绩效有积极影响,与价值链活动无关的一般性社会责任对财务绩效有消极影响,他们的交互作用对财务绩效也有方向不同的显著影响,即基本活动与支持活动的交互作用对财务绩效有积极影响,基本活动与一般性活动的交互作用对财务绩效有积极影响,而支持活动与一般性活动的交互作用对财务绩效有消极影响.研究结果对企业将履行社会责任与价值创造相结合、实现社会效益和经济效益双赢提供具体的参考.     

HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.     

A tolerance interval approach for assessment of agreement in method comparison studies with repeated measurements

This paper generalizes the tolerance interval approach for assessing agreement between two methods of continuous measurement for repeated measurement data—a common scenario in applications. The repeated measurements may be longitudinal or they may be replicates of the same underlying measurement. Our approach is to first model the data using a mixed model and then construct a relevant asymptotic tolerance interval (or band) for the distribution of appropriately defined differences. We present the methodology in the general context of a mixed model that can incorporate covariates, heteroscedasticity and serial correlation in the errors. Simulation for the no-covariate case shows good small-sample performance of the proposed methodology. For the longitudinal data, we also describe an extension for the case when the observed time profiles are modelled nonparametrically through penalized splines. Two real data applications are presented.     

Point and confidence interval estimates for a global maximum via extreme value theory

The aim of this paper is to provide some practical aspects of point and interval estimates of the global maximum of a function using extreme value theory. Consider a real-valued function f:D→? defined on a bounded interval D such that f is either not known analytically or is known analytically but has rather a complicated analytic form. We assume that f possesses a global maximum attained, say, at u*∈D with maximal value x*=max _u  f(u)?f(u*). The problem of seeking the optimum of a function which is more or less unknown to the observer has resulted in the development of a large variety of search techniques. In this paper we use the extreme-value approach as appears in Dekkers et al. [A moment estimator for the index of an extreme-value distribution, Ann. Statist. 17 (1989), pp. 1833–1855] and de Haan [Estimation of the minimum of a function using order statistics, J. Amer. Statist. Assoc. 76 (1981), pp. 467–469]. We impose some Lipschitz conditions on the functions being investigated and through repeated simulation-based samplings, we provide various practical interpretations of the parameters involved as well as point and interval estimates for x*.