Starting from the Cholesky-GARCH model, recently proposed by Darolles, Francq, and Laurent (2018), the paper introduces the Block-Cholesky GARCH (BC-GARCH). This new model adapts in a natural way to the asset pricing framework. After deriving conditions for stationarity, uniform invertibility...

This paper derives a sufficient condition for noncausality at all forecast horizons (infinitestep noncausality). We propose a test procedure for this sufficient condition. Our procedure presents two main advantages. First, our infinite-step Granger causality analysis is conducted in a more...

This paper shows that indicators and tests of government solvency should not be used alternatively. We present a simple and intuitive procedure to integrate simultaneously the results from the two approaches to fiscal sustainability. An application to U.S. post-World War II data demonstrates the...

The literature on heteroskedasticity and autocorrelation robust (HAR) inference is extensive but its usefulness relies on stationarity of the relevant process, say Vt, usually a function of the data and estimated model residuals. Yet, a large body of work shows widespread evidence of various...

The aim of this research is to investigate the relationship between obesity and wages, using data for nine countries from the European Community Household Panel (ECHP) over the period 1998-2001. We improve upon the existing literature by adopting an Instrumental Variable Quantile Regression...

This paper introduces the notion of common noncausal features and proposes tools to detect them in multivariate time series models. We argue that the existence of co-movements might not be detected using the conventional stationary vector autoregressive (VAR) model as the common dynamics are...

A common problem in applied regression analysis is that covariate values may be missing for some observations but imputed values may be available. This situation generates a trade-off between bias and precision: the complete cases are often disarmingly few, but replacing the missing observations...

The formulation of unobserved components models raises some relevant interpretative issues, owing to the existence of alternative observationally equivalent specifi cations, differing for the timing of the disturbances and their covariance matrix. We illustrate them with reference to unobserved...

This paper examines the relationship between economic growth and carbon dioxide emissions in Italy considering the developments in a 150-year time span. Using several statistical techniques, we find that GDP growth and carbon dioxide emissions are strongly interrelated, with a dramatic change of...

We consider the problem of estimating the high-dimensional autocovariance matrix of a stationary random process, with the purpose of out of sample prediction and feature extraction. This problem has received several solutions. In the nonparametric framework, the literature has concentrated on...