We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to...

We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to...

We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to...

The primary objective of this paper is to propose two nonlinear extensions for macroeconomic forecasting using large datasets. First, we propose an alternative technique for factor estimation, i.e., kernel principal component analysis, which allows the factors to have a nonlinear relationship to...

We investigate the relationship between Corporate Social Responsibility (hereafter CSR) and I/B/E/S analysts' earnings per share (EPS) forecasts using a large sample of US firms for the 1992-2011 period. Based on literature findings we decompose the CSR effect into four factors: accounting...

This paper aims to introduce a nonlinear model to forecast macroeconomic time series using a large number of predictors. The technique used to summarize the predictors in a small number of variables is Principal Component Analysis (PC), while the method used to capture nonlinearity is artificial...

We investigate the relationship between corporate social responsibility (CSR) and I/B/E/S analysts’ earnings per share (EPS) forecasts using a large sample of US firms for 1992–2011. Based on literature findings, we decompose the CSR effect into four factors: accounting opacity, corporate...

In this work we use a measure of predictability of a time series following a stationary ARMA process to develop a test of equal predictability of two or more time series. The test is derived by a set of propositions which links the structure of the AR and MA coefficients to the predictability...

In this paper an expression is obtained for the determinant of a particular patterned matrix. The result is then used to derive the partial autocorrelation function of a first order non-invertible moving average process.