US Natural Gas Market Classification Using Pooled Regression

Kalashnikov, Vyacheslav V. y Pérez Valdés, Gerardo A. y Matis, Timothy I. y Kalashnykova, Nataliya I. (2014) US Natural Gas Market Classification Using Pooled Regression. Mathematical Problems in Engineering, 2014. pp. 1-9. ISSN 1024-123X

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URL o página oficial: http://doi.org/10.1155/2014/695084

Resumen

Natural gas marketing has considerably evolved since the early 1990s, when a set of liberalizing rules were passed in both the United States and the European Union that eliminated state-driven regulations in favor of open energy markets. These new rules changed many things in the business of energetics, and therefore new research opportunities arose. Econometric studies about natural gas emerged as an important area of study since natural gas may now be sold and traded in a number of stock markets, each one responding to potentially different behavioral drives. In this work, we present a method to differentiate sets of time series based on a regression model relating price, consumption, supply, and other factors. Our objective is to develop a method to classify different areas, regions, or states into groups or classes that share similar regression parameters. Once obtained, these groups may be used to make assumptions about corresponding natural gas prices in further studies.

Tipo de elemento: Article
Usuario depositante: Editor Repositorio
Creadores:
CreadorEmailORCID
Kalashnikov, Vyacheslav V.NO ESPECIFICADONO ESPECIFICADO
Pérez Valdés, Gerardo A.NO ESPECIFICADONO ESPECIFICADO
Matis, Timothy I.NO ESPECIFICADONO ESPECIFICADO
Kalashnykova, Nataliya I.NO ESPECIFICADONO ESPECIFICADO
Fecha del depósito: 29 Abr 2019 18:32
Última modificación: 29 Abr 2019 18:32
URI: http://eprints.uanl.mx/id/eprint/15252

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