Learning from others: conditioning versus averaging

How should we revise our beliefs in response to the expressed probabilistic opinions of experts on some proposition when these experts are in disagreement? In this paper I examine the suggestion that in such circumstances we should adopt a linear average of the experts’ opinions and consider whether such a belief revision policy is compatible with Bayesian conditionalisation. By looking at situations in which full or partial deference to the expressed opinions of others is required by Bayesianism I show that only in trivial circumstances are the requirements imposed by linear averaging compatible with it.     

USING THE PARETO DISTRIBUTION TO IMPROVE ESTIMATES OF TOPCODED EARNINGS

Inconsistent censoring in the public‐use March Current Population Survey (CPS) limits its usefulness in measuring labor earnings trends, as previous approaches for imputing topcoded earnings systematically understate top earnings. Using Pareto estimation methods with less‐censored internal data, we create an enhanced cell‐mean series to capture top earnings in the public‐use data. Annual earnings inequality trends since 1963 using our series largely mirror those found by Kopczuk, Saez, and Song using social security administration data for commerce and industry workers. When we extend our analysis to 2013 and consider all workers, earnings inequality levels are higher but its growth is more modest. (JEL C81, D31, J01)     

Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

Seasonal fractional ARIMA (ARFISMA) model with infinite variance innovations is used in the analysis of seasonal long-memory time series with large fluctuations (heavy-tailed distributions). Two methods, which are the empirical characteristic function (ECF) procedure developed by Knight and Yu [The empirical characteristic function in time series estimation. Econometric Theory. 2002;18:691–721] and the Two-Step method (TSM) are proposed to estimate the parameters of stable ARFISMA model. The ECF method estimates simultaneously all the parameters, while the TSM considers in the first step the Markov Chains Monte Carlo–Whittle approach introduced by Ndongo et al. [Estimation of long-memory parameters for seasonal fractional ARIMA with stable innovations. Stat Methodol. 2010;7:141–151], combined with the maximum likelihood estimation method developed by Alvarez and Olivares [Méthodes d'estimation pour des lois stables avec des applications en finance. Journal de la Société Française de Statistique. 2005;1(4):23–54] in the second step. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques.     

Bayesian estimation of reliability using time-to-failure distribution of parametric degradation models

This paper focusses on computing the Bayesian reliability of components whose performance characteristics (degradation – fatigue and cracks) are observed during a specified period of time. Depending upon the nature of degradation data collected, we fit a monotone increasing or decreasing function for the data. Since the components are supposed to have different lifetimes, the rate of degradation is assumed to be a random variable. At a critical level of degradation, the time to failure distribution is obtained. The exponential and power degradation models are studied and exponential density function is assumed for the random variable representing the rate of degradation. The maximum likelihood estimator and Bayesian estimator of the parameter of exponential density function, predictive distribution, hierarchical Bayes approach and robustness of the posterior mean are presented. The Gibbs sampling algorithm is used to obtain the Bayesian estimates of the parameter. Illustrations are provided for the train wheel degradation data.     

Measuring stakeholder identification with nonprofit causes: the development and validation of the identification with social causes scale

Nonprofit organizations (NPOs) achieve desired outcomes by fostering organizational identification. However, little research has explored how identification with the cause or the recipients of support relates to identification with the NPO. This study developed the Identification with Social Causes Scale as a mechanism for distinguishing organizational identification from identification with a social group or cause. Data were collected using two groups: the homeless (n = 318) and HIV positive (n = 314) individuals. Exploratory factor analysis and multigroup confirmatory factor analysis yielded a 9-item scale measuring two dimensions: attachment and consubstantiality. Initial construct validity of the scale was established.     

Social-ecological innovation: adaptive responses to urban environmental conditions

Novel approaches to natural resource management, particularly those which promote stakeholder participation, have been put forward as fundamental ingredients for establishing resilient, polycentric forms of environmental governance. This is nowhere more pertinent than in the case of the complex adaptive systems associated with urban areas. Decentralisation of urban green space management has been posited as an element thereof which, according to resilience thinking, should contribute to the adaptive capacity of cities and the ecosystem services upon which they rely. Implicit in this move towards increased adaptive capacity is the ability to manage through innovation. Although the importance of innovation towards system adaptability has been acknowledged, little work has thus far been carried out which demonstrates that innovative use of urban green space represents a form of adaptive response to environmental conditions. The current paper reports on research which maps examples of organised social-ecological innovation (OSEI) in an urban study area and evaluates them as adaptive responses to local environmental conditions which may contribute to system resilience. The results present OSEI as a coherent body of responses to local social and environmental deprivation, exhibiting diversity and adaptability according to individual contexts. The study therefore provides evidence for the importance of local stakeholder-led innovation as in the building of adaptive capacity in urban social-ecological systems.     

The beta generalized linear exponential distribution

In this paper, a new five-parameter lifetime distribution called beta generalized linear exponential distribution (BGLED) is introduced. It includes at least 17 popular sub-models as special cases such as the beta linear exponential, the beta generalized exponential, and the exponentiated generalized linear distributions. Mathematical and statistical properties of the proposed distribution are discussed in details. In particular, explicit expression for the density function, moments, asymptotics distributions for sample extreme statistics, and other statistical measures are obtained. The estimation of the parameters by the method of maximum-likelihood is discussed and the finite sample properties of the maximum-likelihood estimators (MLEs) are investigated numerically. A real data set is used to demonstrate its superior performance fit over several existing popular lifetime models.