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A panel data approach to economic forecasting: the bias-corrected average forecast
(Escola de Pós-Graduação em Economia da FGV, 2008-01-01)
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using ...
A panel data approach to economic forecasting: the bias-corrected average forecast
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2007-09-01)
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using ...
A panel data approach to economic forecasting: the bias-corrected average forecast
(Escola de Pós-Graduação em Economia da FGV, 2007-01-01)
In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data ...
Empirical analysis of systematic errors in chilean GDP forecasts
(Wiley, 2001)
This paper presents a statistical comparison between the actual and predicted
evolution of the Chilean GDP for the period 0875Ð0887 made by several
forecasters[ We show that the forecasters systematically underestimate ...
A New Methodology for Neural Network Training Ensures Error Reduction in Time Series Forecasting
(Science publications, 2017-06-30)
Artificial Neural Networks (ANN) consists of some components,
such as architecture and learning algorithm. These components have a
significant effect on the performance of the ANN, but finding good
parameters is a ...
Time series forecasting based on ensemble learning methods applied to agribusiness, epidemiology, energy demand, and renewable energy
(Pontifícia Universidade Católica do ParanáPato BrancoBrasilPrograma de Pós-Graduação em Egenharia de Produção e SistemasPUCPR, 2021-12-03)
Time series forecasting and analysis are helpful in the decision-making process. However, exogenous factors, nonlinearities, and seasonality make developing efficient forecasting models challenging. In this context, the ...
Comparative study of continuous hourly energy consumption forecasting strategies with small data sets to support demand management decisions in buildings
(2022)
Buildings are one of the largest consumers of electrical energy, making it important to develop different strategies to help to reduce electricity consumption. Building energy consumption forecasting strategies are widely ...