Although many studies on the directional accuracy of forecasts by international organizations and professional forecasters have been scrutinized, little attention has been paid to forecasts by business leaders. In order to address this gap, we use directional tests to investigate whether...

A maximal overlap discrete wavelet transform is used to obtain time scale decompositions of economic forecasts and their errors. The generated time scale components can be used in loss measures and tests for comparing forecast accuracy to evaluate whether the forecasts accurately capture the...

Accurate and timely information on GDP is important to gauge the overall state of the economy and is thus essential for economic policymaking. A single-index dynamic factor model is estimated using mixed-frequency data on GDP, industrial production, employment, private consumption and exports to...

Professional forecasters can rely on an econometric model to create their forecasts. It is usually unknown to what extent they adjust an econometric model-based forecast. In this paper we show, while making just two simple assumptions, that it is possible to estimate the persistence and variance...

This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS Predictive Accuracy (KSPA) test. The KSPA test...

This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS Predictive Accuracy (KSPA) test. The KSPA test...

Our main goal in this paper is to evaluate the point forecasting accuracy of several time series econometric models when applied to a small Spanish region. The variable of interest is the sectoral GVA of the Basque Country. The results support the use of causal models, which outperform...

This paper uses two-types of large-scale models, namely the Dynamic Factor Model (DFM) and Bayesian Vector Autoregressive (BVAR) Models based on alternative hyperparameters specifying the prior, which accommodates 267 macroeconomic time series, to forecast key macroeconomic variables of a small...

It is not uncommon to observe the published forecasts of economic commentators closely bunched together over long periods of time. In our case, the phenomenon is observed for eight national panels of economists who report monthly forecasts. A framework is developed that conveniently nests within...

This paper presents evidence linking in-sample tests of predictive content and out-of-sample forecast accuracy. Our approach focuses on the negative effect that finite-sample estimation error has on forecast accuracy despite the presence of significant population-level predictive content. We...