Youth earnings and labour market volatility in Europe

The authors provide new evidence on youth earnings and labour market volatility, including flows into and out of employment, across Europe during the Great Recession. EU‐SILC data for the period 2004–13 reveal large disparities in volatility levels and trends across European countries. As expected, the Great Recession increased youth labour market volatility, offsetting the trends observed over the previous years of economic prosperity. A variance decomposition exercise points to greater exposure to worker turnover in southern Europe. Fixed effects regression on labour market institutions relates higher unemployment benefits and more stringent employment protection legislation to lower earnings and labour market volatility.     

The measurement of unemployment using completed durations: evidence on the gender gap in unemployment in France

This paper examines how unemployment can be measured in a normative fashion - taking into account the mean and inequality of spell lengths - and how the extent of unemployment can be estimated from cross section data of the type found in labour force surveys. The issue is not straightforward since in these surveys completed durations of unemployed individuals are not observed yet they constitute the basis for calculating the kind of index that has been proposed to measure the extent of unemployment in a way that goes beyond the unemployment rate. The index proposed by Shorrocks has robust normative foundations and has an equivalent representation in terms of average complete duration and the density of completed durations. Building upon earlier work applied in the United States for estimating the average completed duration, we present a method that enables the index to be calculated based on an estimate of the density of completed durations. The approach is illustrated in the context of comparing male-female unemployment differences in France, where historically female unemployment has been higher than that of males.     

Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data

The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian inference highlight the potential of joint models to guide personalized risk-based screening strategies.     

Projected polynomial autoregression for prediction of stationary time series

Polynomial autoregressions are usually considered to be unrealistic models for time series. However, this paper shows that they can successfully be used when the purpose of the time series study is to provide forecasts. A projection scheme inspired from projection pursuit regression and feedforward artificial neural networks is used in order to avoid an explosion of the number of parameters when considering a large number of lags. The estimation of the parameters of the projected polynomial autoregressions is a non-linear least-squares problem. A consistency result is proved. A simulation study shows that the naive use of the common final prediction error criterion is inappropriate to identify the best projected polynomial autoregression. An explanation of this phenomenon is given and a correction to the criterion is proposed. An important feature of the polynomial predictors introduced in this paper is their simple implementation, which allows for automatic use. This is illustrated with real data for the three-month US Treasury Bill.     

THE LENDER OF LAST RESORT: A TWENTY‐FIRST CENTURY APPROACH

The classical Bagehot conception of a Lender of Last Resort (LOLR) that lends to illiquid banks has been criticized on two grounds: On the one hand, the distinction between insolvency and illiquidity is not clear‐cut; on the other, a fully collateralized repo market allows central banks to provide the adequate aggregate amount of liquidity and leave to the banks the responsibility of lending uncollateralized. The object of this paper is to analyze these issues rigorously by providing a framework in which liquidity shocks cannot be distinguished from solvency ones and then asking whether there is a need for a LOLR and how it should operate in the absence of systemic threats. Determining the optimal LOLR policy requires a careful modeling of the structure of the interbank market and of the closure policy. In our setup, the results depend upon the existence of moral hazard. If the main source of moral hazard is the banks' lack of incentives to screen loans, then the LOLR may have to intervene to improve the efficiency of an unsecured interbank market in crisis periods; if instead the main source of moral hazard is loan monitoring, then the interbank market should be secured and the LOLR should never intervene. (JEL: E58, 628)     

Selecting significant effects in factorial designs: Lenth’s method versus the Box-Meyer approach

The Lenth method is conceptually simple and probably the most common approach to analyzing the significance of the effects in factorial designs. Here, we compare it with a Bayesian approach proposed by Box and Meyer and which does not appear in the usual software packages. The comparison is made by simulating the results of 4, 8 and 16 run designs in a set of scenarios that mirror practical situations and analyzing the results provided by both methods. Although the results depend on the number of runs and the scenario considered, the use of the Box and Meyer method generally produces better results.     

Construction and application of an indicator system to assess the ergonomic performance of large and medium-sized construction companies

This article proposes a system of indicators to evaluate the performance of companies in ergonomics for buildings. The system was developed based primarily on studies related to the performance evaluation of the construction industry and on Brazilian standards of ergonomics and work safety and had also the contribution of national and international indicators related to ergonomics, work safety, quality, sustainability, quality of work life and to organizational behavior. The indicators were named, classified and their components were assigned to compose the theoretical model SIDECE--System of Performance Indicators in Ergonomics for Building Construction (as for the Portuguese acronym), serving the major goals of ergonomics: health, safety and workers' satisfaction and production efficiency. The SIDECE is being validated along with the building construction companies in the city of Natal, Brazil, whose practical results, deriving from the application of instruments to collect field data, are under process, to be presented on the occasion of the 18th World Congress on Ergonomics. It is intended that the SIDECE be used by building construction companies as a support tool for excellence management.