Relationships among gasoline prices of eight brands at the north of Mexico City

Authors

  • Edgar I. Faustino-Cruz Universidad Panamericana
  • Francisco Ortiz-Arango Universidad Panamericana

DOI:

https://doi.org/10.29201/peipn.v17i34.86

Keywords:

gasoline prices, econometric modeling, vector error correction model, variance decomposition, Mexico City

Abstract

This document uses a vector error correction model to obtain the decomposition into permanent and transitory components of gasoline prices offered by eight brands in the north of Mexico City, through an impulse response analysis and variance decomposition, from July 1, 2018, to june 17, 2020. The main findings are that are multiple influences and interdependencies among the eight brands’ prices analyzed. In the short term, three patterns in pricing are identified: (a) prices initially explained by themselves but rapidly influenced by the rest of prices, (b) prices explained throughout the cycle mainly by their disturbances, and (c) prices that depend strongly on the rest of prices. In the long term, these patterns consequently determine that there are three cointegration vectors between all prices. The results found in the analyzed period suggest that it is perhaps still early to expect that there will be an equilibrium price vector derived from a competitive market in Mexico.

Downloads

Download data is not yet available.

References

Akinboade, O.; E. Ziramba & W. Kumo (2008). “The Demand for Gasoline in South Africa: An Empirical Analysis Using Co-integration Techniques. Energy Economics, 3222-3229. https://doi.org/10.1016/j.eneco.2008.05.002.

Bentzen, J. (1994). An empirical analysis of gasoline demand in Denmark using cointegration techniques. Energy Economics, 139-143. https://doi.org/10.1016/0140-9883(94)90008-6.

Cheung, K.-Y., & E. Thomson (2004). The demand for gasoline in China: a cointegration analysis. Journal of Applied Statistics, 533–544. https://doi.org/10.1080/02664760410001681837.

Eltony, M., & N. Mutairi (1995). Demand for gasoline in Kuwait: an empirical analysis using cointegration techniques. Energy Economics, 249–253. https://doi.org/10.1016/0140-9883(95)00006-g.

Engle, R., & C. Granger (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 251-276. https://doi.org/10.2307/1913236.

Ferrer, C., & S. Escalante (2014). Demanda de gasolina en la zona metropolitana del Valle de México: análisis empírico de la reducción del subsidio. Revista de Economía del Rosario, 89-117. https://doi.org/10.12804/rev.econ.rosario.17.01.2014.04.

Granger, C. (1980). Testing for causality: A personal viewpoint. Journal of Economic Dynamics and Control 2, 329-352.

Granger, C., & P. Newbold (1974). Spurious regressions in econometrics. Journal of Econometrics 2, 111-120. https://doi.org/10.1016/0304-4076(74)90034-7.

Ibarra Salazar, J., & L. Sotres Cervantes (2008). La demanda de gasolina en México El efecto en la frontera norte. Frontera Norte, 131-156. https://doi.org/10.2307/j.ctv26d8jg.8.

Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 231-254. https://doi.org/10.1016/0165-1889(88)90041-3.

___ (2009). Cointegration: Overview and Development. Handbook of Financial Time Series, 671-693. https://doi.org/10.1007/978-3-540-71297-8_29.

Khim, V., & S. Liew (2004). Which Lag Length Selection Criteria Should We Employ? Economics Bulletin, 1-9.

Liew, V. (2004). Which Lag Selection Criteria Should We Employ? Economics Bulletin, 1-8.

Nielsen, B. (2001). Order determination in general vector autoregressions. Economics Papers 2001-W10, Economics Group.

Rao, B., & G. Rao (2009). Cointegration and the Demand for Gasoline. Energy Policy, 3978-3983. https://doi.org/10.1016/j.enpol.2009.04.046.

Reyes, O.; R.,Escalante, & A. Matas (2010). La demanda de gasolinas en México: Efectos y alternativas ante el cambio climático. Economía teoría y práctica, 23-110. https://doi.org/10.24275/etypuam/ne/322010/reyes.

Sims, C. (1980). Macroeconomics and Reality. Econometrica, 1-48.

Wooldridge, J. (2010). Introducción a la econoemtría: un enfoque moderno. Ciudad de México: Cengage Learning.

Published

2021-12-02 — Updated on 2021-11-25

How to Cite

Faustino-Cruz, E. I., & Ortiz-Arango, F. (2021). Relationships among gasoline prices of eight brands at the north of Mexico City. Panorama Económico, 17(34), 153–184. https://doi.org/10.29201/peipn.v17i34.86

Issue

Section

Artículos

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)