A panel data approach to economic forecasting: the bias-corrected average forecast

• Autor(a) principal: Lima, Luiz Renato Regis de Oliveira
• Data de Publicação: 2008
• Outros Autores: Issler, João Victor
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
• Texto Completo: http://hdl.handle.net/10438/731
• topic: Forecast combination; Forecast-combination puzzle; Common features; Panel data; Bias-corrected average forecast; Economia; Economia; Previsão econômica - Modelos econométricos

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 panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.