Short-Term Causal Relationships between the Oil Sector and Economic Growth in the Mexican Economy: FG-ARDL Approach

Abstract

This research aims to analyze the short-term causal relationships between the oil sector and economic growth, using two methodologies, the ARDL model and the proposal based on fuzzy logic, the FG-ARDL, Fuzzy Gaussian Autoregressive Distributed Lag. For this purpose, 59 variables of the oil sector and their relationship with the Global Economic Activity Indicator, and the corresponding indicator of primary, secondary, and tertiary activities, were analyzed in monthly format between January 1997 and December 2019. The FG-ARDL model achieved better estimates, identifying the influence of variables derived from the oil industry on economic growth with better precision. The main recommendation is to evaluate other economic relationships to verify the efficiency of the new methodology, in which the primordial limitation is its dependence to the ARDL method, so it does not provide new causal relationships. Originality was the proposed time series and fuzzy theory approach to economic modeling. The most important conclusion is that the internal consumption of fuel and PEMEX Diesel are the key variables that drive short-term economic growth, this result is better observed in the proposed model.