Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

Comparative probability for conditional events: A new look through coherence

We study, from the standpoint of coherence, comparative probabilities on an arbitrary familyE of conditional events. Given a binary relation ·, coherence conditions on · are related to de Finetti's coherent betting system: we consider their connections to the usual properties of comparative probability and to the possibility of numerical representations of ·. In this context, the numerical reference frame is that of de Finetti's coherent subjective conditional probability, which is not introduced (as in Kolmogoroff's approach) through a ratio between probability measures.Another relevant feature of our approach is that the family & need not have any particular algebraic structure, so that the ordering can be initially given for a few conditional events of interest and then possibly extended by a step-by-step procedure, preserving coherence.     

Social forecasting: An integral part of corporate planning?

The increasing need for business to monitor the social dimensions of its environment and, hopefully make some forecasts of future trends has met with some constructive response from academics and consultants although not as yet on a very liberal scale. The published literature does not indicate to what extent companies in general attemp social forecasting and, where they do, the degree of integration which exists within their corporate planning systems. The authors, therefore, decided to survey a sample of British organizations to see if they could shed some light on these issues and thereby add some information to the excellent accounts of individual cases of social forecasting in, they suspect, the more advanced and atypical companies. The survey suggests a general picture of: awareness of the value of social forecasting; fairly widespread ignorance of the techniques which do exist, primitive though these may largely be; successful integration of social forecasting into the corporate planning systems of a substantial number of organizations but not in the majority.     

Multidimensional Analysis of Deprivation and Fragility Patterns of Migrants in Lombardy,Using Partially Ordered Sets and Self-Organizing Maps

Social Indicators Research - In this paper, we present a multidimensional fuzzy analysis of the levels and the patterns of poverty and social fragility of migrants’ families, in the Italian...     

Lessons from Nigeria for improved thinking and working politically in the extractives sector

Despite the wealth that comes from being the biggest oil producer in Africa, Nigeria has some of the worst development indicators in the world. From 2011 to mid‐2016, the DFID‐funded Facility for Oil Sector Transparency and Reform (FOSTER) programme's unique design aimed to reduce incentives for the capture of oil revenue by elites and international oil companies, restoring the potential of those revenues to accelerate economic and social development. This article asks what lessons FOSTER's successes and failures offer for improved “thinking and working politically” (TWP). It examines the outcomes from five “clusters” of interventions: three viewed by the FOSTER team as successes and two as failures. The article identifies factors for successful TWP‐based programming, including the need for local ownership rooted in staff with a combination of technical expertise, a deep knowledge of the local political context and excellent networking abilities. The research used a qualitative and inductive approach. Field research was undertaken with 44 semi‐structured qualitative interviews during one month of fieldwork in Abuja and Lagos. The research also included reviews of FOSTER's internal documentation and evaluation frameworks, as well as analysis of newspaper articles and grey literature on the oil sector in Nigeria. The project offers important lessons for politically informed programming about how interventions were implemented (process), what was actually done (content) and how the project responded to changes in context that created or blocked opportunities for reform (responsiveness). The article identifies factors for successful TWP‐based programming, including the need for local ownership rooted in staff with a combination of technical expertise, a deep knowledge of the local political context and excellent networking abilities. The findings have important implications for programme design. They demonstrate the value of built‐in flexibility that allows staff to choose and switch the partners they work with and the channels they work through. They also show that a key aspect of TWP‐based programming is implicit acceptance that some failure may be unavoidable, since this permits staff to balance risk against opportunities. Finally, a better understanding of FOSTER's failures reveals the challenges of a TWP‐based approach and the trade‐offs it demands.     

How to Foster Toddlers' Mental‐State Talk,Emotion Understanding,and Prosocial Behavior: A Conversation‐Based Intervention at Nursery School

Recent years have seen the development and implementation of a range of training programs aimed at improving children's socio‐emotional skills. Nevertheless, few studies have been conducted with toddlers attending nursery school. In this study, we adopted observational and experimental paradigms to examine the efficacy of an intervention based on conversing about emotions with small groups of 2‐ to 3‐year‐old children. The intervention was designed to promote toddlers' mental‐state talk, emotion understanding (EU), and prosocial behavior. The training group significantly outperformed the control group in the use of mental‐state language, especially emotional‐state lexicon, EU, and prosocial behavior toward peers. There was also a significant Group × Age interaction, with the older training group participants displaying greater gains in EU than the younger ones. We discuss the theoretical and practical implications of these findings.     

Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets

We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time‐varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset‐specific instruments. The estimator uses simple weighted two‐pass cross‐sectional regressions, and we show its consistency and asymptotic normality under increasing cross‐sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no‐arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi‐period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousand U.S. stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time‐invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four‐factor model capturing market, size, value, and momentum effects.     

Measuring ambiguity preferences: A new ambiguity preference survey module

Journal of Risk and Uncertainty - Ambiguity preferences are important to explain human decision-making in many areas in economics and finance. To measure individual ambiguity preferences, the...     

Assessment of Composite Indicators Using the ANOVA Model Combined with Multivariate Methods

The synthesis of a number of single observed indicators into a unique composite indicator involves various subjective choices related, for instance, to the type of combination (linear, non-linear) and to the aggregation method (simple average, geometric average) used in its construction. Thus, it is clearly important to analyse the variability of a composite indicator according to all possible alternatives before employing it in any decision-making process. Within such a framework, in this paper, we present a new approach based on a combination of explorative and confirmative analyses aiming to investigate the impact of different subjective choices on the variability of composite indicators. This new approach also allows the analysis of the related individual differences among the statistical units and the use of external information on the same units to enhance the interpretation of the final results.