LOS MOCHIS, MEXICO -- As part of an ongoing joint effort between the academic and commercial sectors, stemming from a Collaboration Agreement between the Autonomous University of Sinaloa (UAS) and Pacifico Mexinol (a subsidiary of Transition Industries) signed in 2024, UAS released the findings of the economic effects study of the world's largest ultra-low-carbon methanol plant, located near Topolobampo, Ahome, Sinaloa.

The Pacifico Mexinol project is aligned with the UN Sustainable Development Goals by promoting the use of clean energy, the utilization of treated wastewater, and climate change mitigation. It protects local ecosystems and will generate thousands of local jobs. The project represents more than the construction of industrial infrastructure; it is a trigger for economic growth for northern Sinaloa and Mexico.

The study estimated the direct and indirect economic effects of the project’s investment in terms of employment, income, value added, and social well-being; identified regional development opportunities; and proposed strategies to ensure the project's sustainability and its harmonious integration with the local socioeconomic environment.

The study assesses that during the four-year construction phase, the project will generate 4,500 direct jobs and 660 indirect jobs per year in Sinaloa, and around 8,000 direct and 4,000 indirect jobs nationally. During the 30-year operations phase, the facility will have approximately 1,400 direct and indirect jobs on a continuous annual basis.

The study also assesses total wage increases estimated at $3.3 billion pesos in Sinaloa and $3.2 billion pesos in the rest of the country; while Sinaloa's GDP could rise by $15 billion pesos and the rest of the country by $14 billion pesos, for a national total close to $30 billion pesos ($2 billion USD) during construction.

The UAS study not only measures the direct jobs in the sector, but also how the income of all the sectors will grow as a result of the construction of the Pacifico Mexinol facility. For every one job, there are six generated during construction and for every one job during operations, there are 11 jobs created.

The study was the effort of UAS, through the Research and Graduate Studies Directorate, the Technology Transfer Office, and the School of Economic and Social Sciences, led by Dr. Luis Armando Becerra Pérez, an economist with extensive experience in renewable energy and sustainable development.

“I believe foreign investment should complement domestic investment, and if we want to develop Mexico's regions — in this case Sinaloa specifically — we need projects of this kind to arrive… and [they] must be evaluated with a long-term perspective. If we want our regions to advance, if we want our children and grandchildren to have greater development opportunities, we need to think with that horizon in mind. Industrial districts around the world do not develop without people getting on board and sharing a vision for the future,” said Dr. Becerra.

Overall, the study represents a key tool for ensuring that industrial development translates into shared well-being and equitable growth.

“By identifying local development opportunities, social needs, and potential risks, the report contributes to the design of strategies that promote the harmonious integration of the project with its surroundings under Pacifico Mexinol’s Good Neighbor Program and the Project’s IFC-aligned Environmental and Social Impact Assessment (ESIA) for economic inclusion, community participation, and respect for the rights of local populations,” says Karin Nunan, a globally recognized human rights and socioeconomic expert who is the Global Head of Corporate Affairs for Transition Industries.

The study provides data to supplement and help visualize the economic value chain that Pacifico Mexinol has long been advocating through its Local Content Plan - which requires all contractors to maximize hiring locally within Ahome Municipality, then Sinaloa and then Mexico. The project aims for a 90% national employment rate during construction and operations.

The analysis was developed through a combination of three complementary approaches:

1) Structural econometrics, to model causal relationships between key economic variables,
2) Machine learning, to detect complex patterns in large volumes of data and simulate future scenarios, and,
3) Input-output matrices, to estimate the multiplier effects of the project on the regional economy.

Given that prior to this study, economic simulators only existed at the national level in Mexico, UAS collaborated with the National Institute of Statistics, Geography, and Informatics (INEGI) to adapt models and parameters to the local context, thus increasing the accuracy of the study.