When data sets are multilevel (group nesting or repeated measures), different sources of variations must be identified. In the framework of unsupervised analyses, multilevel simultaneous component analysis (MSCA) has recently been proposed as the most satisfactory option for analyzing multilevel...

Purpose – The purpose of this paper is to propose a practical conceptualization of the balanced scorecard (BSC) to describe the mechanism producing creation of monetary value for hospitals in the territorial context of Lombardy region (Italy). Design/methodology/approach – The authors...

Dagum and Slottje (2000) estimated household human capital (HC) as a latent variable (LV) and proposed its monetary estimation by means of an actuarial approach. This paper introduces an improved method for the estimation of household HC as an LV by means of formative and reflective indicators...

In this paper we propose a methodology for measuring the ‘relative effectiveness’ of healthcare services (i.e. the effect of hospital care on patients) under general conditions, in which: a) a healthcare outcome underlies qualitative and quantitative observable indicators; ß) we are...

A new approach for the estimation and the validation of a Structural Equation Model with a formative-reflective scheme is presented. The basis of the paper is a proposal for overcoming a potential deficiency of PLS Path Modeling. In the PLS approach the reflective scheme assumed for the...

In this paper we analyze the effects of some distortions induced by the prospective payment system, i.e. upcoding, cream skimming and readmissions, on hospitals' technical efficiency. We estimate a production function using a population-based dataset composed by all active hospitals in an...

In this paper, we propose a new least-squares based procedure to extract exogenous and endogenous latent variables in formative-reflective structural equation models. The procedure is a valuable alternative to PLS-PM and Lisrel; it is fully consistent with the causal structure of...

Cluster Weighted Modeling (CWM) is a mixture approach regarding the modelisation of the joint probability of data coming from a heterogeneous population. Under Gaussian assumptions, we investigate statistical properties of CWM from both the theoretical and numerical point of view; in particular,...

This paper presents a new stochastic frontier model for panel data. The model takes into account firm unobservable heterogeneity and short-run and long-run sources of inefficiency. Each of these features is modeled by a specific random effect. In this way, firms’ latent heterogeneity is not...