THE ESTIMATION OF HUMAN CAPITAL BY ADMINISTRATIVE ARCHIVES IN A STATIC AND LONGITUDINAL PERSPECTIVE: THE CASE OF MILAN

Abstract This paper focuses on the estimation of the latent variable human capital (HC) at disaggregated level (worker) by available routinely institutional data flows. In particular we utilize the Lombardy region administrative archive ‘Employment Centers of the Province of Milan’, collecting information about careers of workers in the private sector of the Milan area, and administrative flows collecting mandatory workers' individual income tax returns, filed with the National Internal Revenue Service. First, we propose and empirically estimate HC scores in a static (referred to 2004) framework, by means of a realistic measurement model within causal relationships among endogenous and exogenous (investment) HC indicators. Furthermore, the model also specifies a set of (concomitant) indicators that, not belonging to HC investment indicators, have causal impact on endogenous variables and on HC scores, too. Second, we propose a longitudinal analysis (period 2000–2004) aimed to investigate how workers' earned income growth rates vary over workers' educational levels and other personal characteristics. The empirical results of both analyses confirm the characteristics of the Italian job market, denoted by marked inequalities, and knowledge regarding the process of school to work transition, characterized by a weak incidence of education on longitudinal trajectories of earned income.     

A century of equity premium predictability and the consumption–wealth ratio: An international perspective

This paper re-examines the predictive ability of the consumption–wealth ratio (cay) on the equity premium using hand-collected annual data spanning one century for four major economies. In addition to statistical tests of out-of-sample forecast accuracy, we measure the economic value of the predictive information in cay in a stylized asset allocation strategy. We find that cay does not contain predictive power prior to World War II, when a structural break occurs for all countries. In the postwar period, while statistical tests provide mixed evidence, economic criteria uncover substantial predictive power in cay, further enhanced when allowing for economically meaningful restrictions.     

The out-of-sample success of term structure models as exchange rate predictors: a step beyond

A large literature suggests that standard exchange rate models cannot outperform a random walk forecast and that the forward rate is not an optimal predictor of the spot rate. However, there is evidence that the term structure of forward premia contains valuable information for forecasting future spot exchange rates and that exchange rate dynamics display nonlinearities. This paper proposes a term-structure forecasting model of exchange rates based on a regime-switching vector equilibrium correction model which is novel in this context. Our model significantly outperforms both a random walk and, to a lesser extent, a linear term-structure vector equilibrium correction model for four major dollar rates across a range of horizons.     

HUMAN CAPITAL MEASUREMENT: A SURVEY

Abstract After a short history of the concept of human capital (henceforth HC) in economic thought ( Section 1 ), this study presents the two main methods for estimating the value of the stock of HC – the retrospective and prospective one – with a review of the models proposed ( Section 2 ). These methods are linked both to the theory of HC investment as a rational choice ( Section 3 ), the literature analysing the contribution of HC investment to economic growth and the HC estimating method through educational attainment ( Section 4 ). The more recent literature on HC as a latent variable is also assessed ( Section 5 ) and a new method of estimation where HC is seen both as an unknown function of formative indicators and as a ‘latent effect’ underlying earned income is proposed ( Section 6 ). Section 7 concludes.     

Quality risk aversion, conjectures, and new product diffusion

In this paper, we provide a generalization of the standard models of the diffusion of a new product. Consumers are heterogeneous and risk averse, and the firm is uncertain about the demand curve: both learn from past observations. The attitude towards risk has important effects with regard to the diffusion pattern. In our model, downward-biased signals to consumers can prevent the success of the product, even if its objective quality is high: a “lock-in” result. We show, in addition, that the standard logistic pattern can be derived from the model. Finally, we discuss the steady states of the learning dynamics, with regard to the multiplicity and the local stability of equilibria, and to their welfare properties.     

Model building and estimation strategies for implementing the Balanced Scorecard in Health sector

Over last two decades, the concept of the Balanced Scorecard has had broad application by the health sector internationally, including Hospitals systems and national healthcare systems or organizations. However, the lack of literature on causal-effect relationships between different types of dimensions and indicators poses difficulty in conceptualising and implementing a quality evaluation system based on Balanced Scorecard. Methodologically, the most natural context for Balanced Scorecard conceptualization and estimation deals with Structural Equation Models with latent variables. Partial Least Squares Path Modelling has found increased applications, thanks to its ability to handle complex models. However, the lack of a global optimization criterion makes it difficult to evaluate this procedure. The aim of this article is to propose a methodological conceptualization of the Balanced Scorecard in a new context, as the Health sector, using a suitable statistical approach to estimate causal relationships among specified latent dimensions, together with a model building strategy, a necessary step when expert knowledge is too weak to build a robust and well suited model. Specifically, within the Structural Equation Models framework a two-step model building strategy is presented; the first step build the measurement models based on a clustering (around latent variables) technique and the second step build the structural model based on partial correlations and a procedure that selects the best model in terms of predictive power, measured by the mean of the R ² for the endogenous latent variables. Finally, an application based on administrative archives of Lombardy region (Italy) illustrates the presented methodology.     

Indirect estimation of large conditionally heteroskedastic factor models,with an application to the Dow 30 stocks

We derive indirect estimators of conditionally heteroskedastic factor models in which the volatilities of common and idiosyncratic factors depend on their past unobserved values by calibrating the score of a Kalman-filter approximation with inequality constraints on the auxiliary model parameters. We also propose alternative indirect estimators for large-scale models, and explain how to apply our procedures to many other dynamic latent variable models. We analyse the small sample behaviour of our indirect estimators and several likelihood-based procedures through an extensive Monte Carlo experiment with empirically realistic designs. Finally, we apply our procedures to weekly returns on the Dow 30 stocks.     

On inferior inputs and marginal returns

An input is inferior if and only if an increase in its price raises all marginal productivities. A sufficient condition for input inferiority under quasi-concavity of the production function is then that there are increasing marginal returns with respect to the other input and a non-positive marginal productivity cross derivative. Thus, contrary to widespread opinion, input “competitiveness” is not needed. We discuss these facts and illustrate them by introducing a class of simple production function functional forms. Our results suggest that the existence of inferior inputs is naturally associated with increasing returns, and possibly strengthen the case for inferiority considerably.