A result characterizing the effect of temporal aggregation in the frequency domain is known for arbitrary stationary processes and generalized for difference-stationary processes here. Temporal aggregation includes cumulation of flow variables as well as systematic (or skip) sampling of stock...

A result characterizing the effect of temporal aggregation in the frequency domain is known for arbitrary stationary processes and generalized for difference-stationary processes here. Temporal aggregation includes cumulation of flow variables as well as systematic (or skip) sampling of stock...

We propose a new nonparametric density forecast based on time- and state‐domain smoothing. We analyze some of its asymptotic properties and provide an empirical illustration. Copyright (C) 2010 John Wiley & Sons, Ltd.

Bayesian networks are graphical models that represent the joint distributionof a set of variables using directed acyclic graphs. When the dependence structure is unknown (or partially known) the network can be learnt from data. In this paper, we propose a constraint-based method to perform...

By using a sample of 77 countries our analysis applies several nonparametric techniques in order to reveal the link between national culture and corruption. Based on Hofstede’s cultural dimensions and the corruption perception index, the results reveal that countries with higher levels of...

The aim of the paper is twofold: i) to propose a methodology to compute the growth rate volatility of an economy, and ii) to investigate the relationship between growth volatility and economic development through the lenses of the structural characteristics of an economy. We study a large...

We develop a novel approach to build checks of parametric regression models when many regressors are present, based on a class of sufficiently rich semiparametric alternatives, namely single-index models. We propose an omnibus test based on the kernel method that performs against a sequence of...

Total Factor Productivity (TFP) accounts for a sizeable proportion of the income and growth differences across countries. Two challenges remain to researchers aiming to explain these differences: on the one hand, TFP growth is hard to measure; on the other hand, model uncertainty hampers...

Conditional quantile curves provide a comprehensive picture of a response contingent on explanatory variables. Quantile regression is a technique to estimate such curves. In a flexible modeling framework, a specific form of the quantile is not a priori fixed. Indeed, the majority of applications...