A New Interpretation of the Logistic Model in Estimating Seasonal and Yearly Natural Gas Consumption

Ahmet Goncu


The logistic type model, which requires the use of an optimization routine for the estimation of model parameters, is one of a number of widely used methods in modeling natural gas consumption. In this study, we derive a regression model by considering the Euler discretization of the logistic type model and show that this regression based approach offers a simpler estimation procedure, in addition to better modeling natural gas consumption data. For comparison, the regression model derived from the logistic model is fitted to the same dataset published in Forouzanfar et al. (2010). Furthermore, in the regression approach, confidence intervals for point forecasts can be obtained, whereas the logistic function model is a deterministic function of time that does not provide confidence intervals.

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DOI: https://doi.org/10.5296/rae.v5i4.4156

Copyright (c) 2013 Ahmet Goncu

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Research in Applied Economics ISSN 1948-5433

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