Unobserved components models with correlated disturbances

The paper deals with the decomposition of a time series process admitting an ARIMA representation into permanent and transitory components, with the intent of investigating whether the introduction of correlated disturbances provides meaningful extensions of the admissible parameter range. The main points are illustrated with reference to ARIMA(2,1,0) and IMA(2,2) models. It is argued that there is very little reason for such extensions, and that the restrictions implied by the assumption of uncorrelated components are sound.This research was supported by the MURST Cofin2000. The paper was presented at the XL Scientific Meeting of the Italian Statistical Society (Florence 2000), ISF 2000 (Lisbon), and at the Europaeisches Heimbildungswerk workshop, Helenau-Bernau (Berlin). I thank participants for their comments and in particular Jörg Breitung for very stimulating discussion. I also wish to thank the associate editor and the referee for their comments.     

Transform orders and stochastic monotonicity of statistical functionals

In some inferential statistical methods, such as tests and confidence intervals, it is important to describe the stochastic behavior of statistical functionals, aside from their large sample properties. We study such a behavior in terms of the usual stochastic order. For this purpose, we introduce a generalized family of stochastic orders, which is referred to as transform orders, showing that it provides a flexible framework for deriving stochastic monotonicity results. Given that our general definition makes it possible to obtain some well known ordering relations as particular cases, we can easily apply our method to different families of functionals. These include some prominent inequality measures, such as the generalized entropy, the Gini index, and its generalizations. We also illustrate the applicability of our approach by determining the least favorable distribution, and the behavior of some bootstrap statistics, in some goodness-of-fit testing procedures.     

Is the Preference for Children so Low,or is the Price of Time so High? A simultaneous model of fertility and participation in Italy with cohort effects

ABSTRACT: This paper presents a simultaneous model of fertility and female participation in Italy, estimated with a sequence of cross-sections of micro data. Cohort dummies are used to capture permanent effects, including cohort changes in preferences. The cohort effects turn out to be not very significant, the point estimates suggesting a decreasing trend in participation and an increasing trend in fertility. The wage effects are instead rather strong and significant. The model produces simulations which are close to actual trends, which would seem largely explained by wage incentives. The explanation for a particularly high elasticity of fertility with respect to female wage should ultimately be searched for in the specific differences which characterize the Italian social and institutional environment.