For a New Incomes Policy: New Possibilities and Objectives

Abstract. Moving off from the lessons of the Italian incomes policy experience of the 1980s, this paper presents a new framework to interpret the performance of incomes policy (LP) agreements and institutions, and propose new strategies for the 1990s. IP is viewed as a cooperative outcome that evolves from a non-cooperative long-term game between several players (workers, unions, firms, government, parliament, etc.), along the lines of the model drawn up by Brunetta and Carraro (1988). The paper is divided into three sections. The first summarizes the history of IP in Italy, starting from the phase of the predetermination of disinflation (1983-84). We firstly outline some of the fundamental features of recent Italian development (the “Italian model”), noting how new IP measures could be taken to create an adequate response to the new European and international deadlines. The difficulties and uncertainties that presently exist at both national and international level make the introduction of IP in new, cooperative and evolutive terms, necessary. The second section examines the various topics and new objectives of a “strategic” IP resumption, particularly relevant to the concerted action on the cost of labour, presently being discussed. The topics we consider are: the link between wage reform and IP; the recent concerted agreements reached on fiscal drag (26.1.89) and on the cost of labour (25.1 and 6.7.90); the importance of the role of productivity gain-sharing; programmed inflation and price control; indexation of gross wages and safeguarding the net wage; increase of the tax base; profit-sharing. The third and final section presents a few observations which further investigate the distribution of productivity gains between sectors and uses: how it is articulated amongst the various bargaining levels (central, sectoral or enterprise). Redistribution amongst sectors is dealt with in terms of “protected” and “unprotected” areas of the economy, showing the need of a concerted regulation at the central level. Sharing between factors and allocations presents a very different case, and is dealt with at sectoral and firm level.     

Public-Private Partnership Contractual Design: A Computational Model of the Moral Hazard with Lotteries

Public-Private Partnership (PPP) is a new model of public management which consists of the contractual relationship between public and private entities. In particular, PPPs enable risk share between public and private sectors making the asymmetric information problem in a contractual arrangement more evident. The aim of this paper was to study a moral hazard problem applied to PPP contracts. To achieve this objective, a PPP computational contractual model including the moral hazard with lotteries was developed to assess how contractual changes could affect the optimum behavior of arrangement members. Simulations indicate that projects with higher economic value should attract more qualified firms, which may be why the companies expend more effort. To deal with possible contractual contingencies and try to minimize the moral hazard problem, the government could draw up more flexible contracts in order to include possible necessary changes and punish unwanted or improper consortium behavior.     

Prediction of Human Development from Environmental Indicators

The Sustainable Development Goals (SDG) list the objectives and targets that should be addressed to solve the global issues regarding sustainable development. They encompass the social, economic and environmental dimensions and search for solutions that are able not only to monitor but also to control the operational indicators attributed to each objective. It is expected that many of these indicators are associated to each other and the accurate understanding of these correlations allows to build predictive statistical models that can improve the monitoring and controlling of variables. It would increase the rate of success in achieving the SDG. This study tested a linear multivariate model able to predict the human development index based on environmental variables which are related to SDG 3 (health), 4 (education), 8 (sustainable economic growth and decent work) and 15 (protect, restore and promote sustainable use of terrestrial ecosystems). We fitted the models using the Linear Discriminant Analysis and Best Subset Selection applied to a Linear Multivariate Regression. The model predictive ability was assessed by R² and cross-validation (CV). The results showed that exposure to unsafe sanitation, access to drinking water, tree cover loss, unsafe water quality, wastewater treatment level, and household air pollution are excellent predictors of human development index of a population, with R² = 0.94 and 10-fold CV Mean Squared Error equal to 0.0014. This tool can help stakeholders to monitor and control indicators attributed to good health and well-being, quality education, clean water and sanitation, decent work and economic growth, sustainable cities and communities and life on land sustainable development goals.     

Penalized maximum likelihood estimation in the modified extended Weibull distribution

We address the issue of performing inference on the parameters that index the modified extended Weibull (MEW) distribution. We show that numerical maximization of the MEW log-likelihood function can be problematic. It is even possible to encounter maximum likelihood estimates that are not finite, that is, it is possible to encounter monotonic likelihood functions. We consider different penalization schemes to improve maximum likelihood point estimation. A penalization scheme based on the Jeffreys’ invariant prior is shown to be particularly useful. Simulation results on point estimation, interval estimation, and hypothesis testing inference are presented. Two empirical applications are presented and discussed.     

The emergence of modern emotional power: governing passions in the French Grand Siècle

Theory and Society - This article aims to analyse the governmental rationalities that took passions as an object in the French seventeenth century, unleashing the modern transformation in emotional...     

Interval-censored data with misclassification: a Bayesian approach

Survival data involving silent events are often subject to interval censoring (the event is known to occur within a time interval) and classification errors if a test with no perfect sensitivity and specificity is applied. Considering the nature of this data plays an important role in estimating the time distribution until the occurrence of the event. In this context, we incorporate validation subsets into the parametric proportional hazard model, and show that this additional data, combined with Bayesian inference, compensate the lack of knowledge about test sensitivity and specificity improving the parameter estimates. The proposed model is evaluated through simulation studies, and Bayesian analysis is conducted within a Gibbs sampling procedure. The posterior estimates obtained under validation subset models present lower bias and standard deviation compared to the scenario with no validation subset or the model that assumes perfect sensitivity and specificity. Finally, we illustrate the usefulness of the new methodology with an analysis of real data about HIV acquisition in female sex workers that have been discussed in the literature.     

Dynamic structural models with covariates for short-term forecasting of time series with complex seasonal patterns

This work presents a framework of dynamic structural models with covariates for short-term forecasting of time series with complex seasonal patterns. The framework is based on the multiple sources of randomness formulation. A noise model is formulated to allow the incorporation of randomness into the seasonal component and to propagate this same randomness in the coefficients of the variant trigonometric terms over time. A unique, recursive and systematic computational procedure based on the maximum likelihood estimation under the hypothesis of Gaussian errors is introduced. The referred procedure combines the Kalman filter with recursive adjustment of the covariance matrices and the selection method of harmonics number in the trigonometric terms. A key feature of this method is that it allows estimating not only the states of the system but also allows obtaining the standard errors of the estimated parameters and the prediction intervals. In addition, this work also presents a non-parametric bootstrap approach to improve the forecasting method based on Kalman filter recursions. The proposed framework is empirically explored with two real time series.     

The influence of familiarization sessions on the stability of ramp and ballistic isometric torque in older adults

Ramp isometric contractions determine peak torque (PT) and neuromuscular activation (NA), and ballistic contractions can be used to evaluate rate of torque development (RTD) and electrical mechanical delay (EMD). The purposes of this study were to assess the number of sessions required to stabilize ramp and ballistic PT and to compare PT and NA between contractions in older adults. Thirty-five older men and women (age 63.7 ± 3.7 yr, body mass 64.3 ± 10.7 kg, height 159.2 ± 6.6 cm) performed 4 sessions of unilateral ramp and ballistic isometric knee extension, 48 hr apart. PT significantly increased (main time effect p < .05) from the first to the third session, with no further improvements thereafter. There was a trend toward higher PT in ballistic than in ramp contractions. No difference between contraction types on EMG values was observed. Therefore, the authors suggest that 3 familiarization sessions be performed to correctly assess PT. In addition, PT, NA, RTD, and EMD can be assessed with ballistic contraction in older adults.     

Corporate governance,family ownership and performance

Using a sample of 56 Italian IPOs issued between 1999 and 2005, several hypotheses are tested on the interplay between corporate governance, family ownership and performance. Specifically tested is which approach among all agency, stewardship, and contingency theory is most appropriate for Italian family firms. Findings suggest that board independence increases with family disinvestment at IPO, presence of venture capitalists, establishment of large and active boards, and existence of appointment and compensation committees. At the same time, results indicate that the presence of independent directors affects performance positively but with little statistical significance, while family involvement and the presence of execution committees negatively impact share performance.