An Unbalance Adjustment Method for Development Indicators

This paper analyzes some aggregation aspects of the procedure for constructing a composite index on a multidimensional socio-economic phenomenon such as development, the main focus being on the unbalance among individual dimensions. First a theoretical framework is set up for the unbalance adjustment of the index. Then an aggregation function is proposed that takes unbalance among development dimensions into account; a separate index is also introduced that measures the unbalance itself. Finally the dataset of the Index of African Governance for the year 2007 is used to test this method and compare it against the weighted arithmetic mean of variables with relation to the measured values of unbalance, yielding significantly different results for ratings and rankings, which in addition show negative correlations with the unbalance adjustment values. The changes ensuing from the adjustment are commented for some countries.     

Higher Moments and Prediction‐Based Estimation for the COGARCH(1,1) Model

COGARCH models are continuous time versions of the well‐known GARCH models of financial returns. The first aim of this paper is to show how the method of prediction‐based estimating functions can be applied to draw statistical inference from observations of a COGARCH(1,1) model if the higher‐order structure of the process is clarified. A second aim of the paper is to provide recursive expressions for the joint moments of any fixed order of the process. Asymptotic results are given, and a simulation study shows that the method of prediction‐based estimating function outperforms the other available estimation methods.     

Optimal Maintenance Time for Repairable Systems Under Two Types of Failures

Determination of preventive maintenance is an important issue for systems under degradation. A typical maintenance policy calls for complete preventive repair actions at pre-scheduled times and minimal repair actions whenever a failure occurs. Under minimal repair, failures are modeled according to a non homogeneous Poisson process. A perfect preventive maintenance restores the system to the as good as new condition. The motivation for this article was a maintenance data set related to power switch disconnectors. Two different types of failures could be observed for these systems according to their causes. The major difference between these types of failures is their costs. Assuming that the system will be in operation for an infinite time, we find the expected cost per unit of time for each preventive maintenance policy and hence obtain the optimal strategy as a function of the processes intensities. Assuming a parametrical form for the intensity function, large sample estimates for the optimal maintenance check points are obtained and discussed.     

Disability and work intensity in Italian households

Review of Economics of the Household - The 2030 Agenda of the United Nations clearly sets the inclusion of persons with disabilities in the labour market as a main goal. However, especially in care...     

Deriving Harsanyi’s Utilitarianism from De Finetti’s Book-Making Argument

The book-making argument was introduced by de Finetti as a principle to prove the existence and uniqueness of subjective probabilities. It has subsequently been accepted as a principle of rationality for decisions under uncertainty. This note shows that the book-making argument has relevant applications to welfare: it gives a new foundation for utilitarianism that is alternative to Harsanyi’s, it generalizes foundations based on the theorem of the alternative, and it avoids arguments based on expected utility.     

A Computational Framework for Prime Implicants Identification in Noncoherent Dynamic Systems

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time‐dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple‐valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases.     

RELATIONSHIP LENDING DURING A FINANCIAL CRISIS

This paper studies whether relationship lending mitigates the transmission of the Lehman default shock to the supply of credit in Italy. Exploiting the presence of multiple banking relationships, we control for banks' and firms' unobserved characteristics. Results show that the growth of credit itself is higher and its cost lower the shorter the distance between the bank and the firm, the longer the relationship, and the higher the share of credit held by the bank. Credit growth by relationship lenders is 4.6% higher than that by transactional lenders; the increase in the cost of credit is 50 basis points lower. The positive effect of relationship lending on credit supply increased during the crisis, compared to a pre‐crisis period. The beneficial effect of relationship lending is weaker if the relationship lender is more exposed to the financial crisis, especially when lending to weaker borrowers.     

Asymptotic relative efficiency of score tests in Weibull models with measurement errors

The main object of this paper is to discuss properties of the score statistics for testing the null hypothesis of no association in Weibull model with measurement errors. Three different score statistics are considered. The efficient score statistics, a naive score statistics obtained by replacing the unobserved true covariate with the observed one and a score statistics based on the corrected score statistics. It is shown that corrected and naive score statistics are equivalent and the asymptotic relative efficiency between naive and efficient score statistics is derived.     

Bayesian inference for power law processes with applications in repairable systems

Statistical models for recurrent events are of great interest in repairable systems reliability and maintenance. The adopted model under minimal repair maintenance is frequently a nonhomogeneous Poisson process with the power law process (PLP) intensity function. Although inference for the PLP is generally based on maximum likelihood theory, some advantages of the Bayesian approach have been reported in the literature. In this paper it is proposed that the PLP intensity be reparametrized in terms of (β,η), where β is the elasticity of the mean number of events with respect to time and η is the mean number of events for the period in which the system was actually observed. It is shown that β and η are orthogonal and that the likelihood becomes proportional to a product of gamma densities. Therefore, the family of natural conjugate priors is also a product of gammas. The idea is extended to the case that several realizations of the same PLP are observed along overlapping periods of time. Some Monte Carlo simulations are provided to study the frequentist behavior of the Bayesian estimates and to compare them with the maximum likelihood estimates. The results are applied to a real problem concerning the determination of the optimal periodicity of preventive maintenance for a set of power transformers. Prior distributions are elicited for β and η based on their operational interpretation and engineering expertise.