The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations...

This paper addresses heterogeneity in determinants of economic growth in a data-driven way. Instead of defining groups of countries with different growth characteristics a priori, based on, for example, geographical location, we use a finite mixture panel model and endogenous clustering to...

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the...

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...

This paper focuses on the role of habit formation in individual preferencesover consumption and saving. We closely relate to Alessie and Lusardi's(1997) model as we estimate a model which is based on their closed-formsolution, where saving is expressed as a function of lagged saving and...

Using Italian data, we estimate an option value model to quantify the effectof financial incentives on retirement choices. As far as we know, this isthe first empirical study to estimate the conditional multiple-years modelput forward by Stock and Wise (1990). This implies that we account...

This paper develops a Markov-Switching vector autoregressive model that allows for imperfect synchronization of cyclical regimes in multiple variables, due to phase shifts of a single common cycle. The model has three key features: (i) the amount of phase shift can be different across regimes...

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...