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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

PrevisÃo da demanda de energia elÃtrica para o nordeste utilizando OLS dinÃmico e mudanÃa de regime / Forecast of the demand of electric energy for dynamic northeast using OLS and change of regimen

Guilherme Diniz Irffi 12 July 2007 (has links)
Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Esse estudo se propÃe estimar a demanda por energia elÃtrica para as classes residencial, comercial e industrial na regiÃo Nordeste do Brasil, no perÃodo de 1970 a 2003. Utilizando as metodologias desenvolvidas por Stock e Watson (1993) e Gregory e Hansen (1996), respectivamente, DOLS e MudanÃa de Regime para obter as elasticidades-preÃo e renda de longo prazo. A partir dos vetores de cointegraÃÃo sÃo estimados os Modelos de CorreÃÃes de Erros, os quais fornecem a base para se fazer previsÃes de longo prazo, no perÃodo de 2004 a 2010. A partir dos resultados apresentados por este estudo, sÃo feitas comparaÃÃes das elasticidades-preÃo e renda de curto e longo prazo com demais estudos para o Brasil, bem como para as previsÃes feitas pela EletrobrÃs e por Siqueira, Cordeiro Jr. e Castelar (2006). As metodologias utilizadas nesse estudo, apresentam previsÃes mais acuradas do que os demais estudos para os anos de 2004 a 2006. / The objective of this research is to estimate the residential, commercial and industrial demand for electric energy in the Northeast region of Brazil during the period of 1970 2003. Two different methodologies were used to compute the price and income elasticity of demand: i) DOLS, proposed by Stock and Watson (1993); and ii) Regime Switching by Gregory and Hansen (1996). Error Correction Models are estimated from the cointegration vectors. These models are used to perform long-run forecasts of the electricity demand for the period 2004- 2010. The results are then compared to those from other researches about Brazilianâs price and income elasticity of demand for electric energy. Furthermore, the computed forecasts are compared to those from EletrobrÃs and from Siqueira, Cordeiro Jr. e Castelar (2006). The methodologies used in this work present forecasts that are more accurate than those ones from nother works for the period 2004-2006.

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