Labor Productivity Trends in Mexico's Maquiladora Manufacturing Sector: Increase in Remuneration per Worker and Contraction in Employment (2020–2025)

Abstract

The Manufacturing, Maquiladora, and Export Services Industry Program (IMMEX) is one of the cornerstones of Mexico's manufacturing economy. This article analyzes the official monthly time series published by INEGI (2020–2025) corresponding to employed personnel, wages, hours worked, and foreign income in the manufacturing sector. Using data mining techniques—implicit productivity calculation (wages/employed personnel), STL decomposition, and trend analysis—a sustained increase in productivity per worker of +104.3% was identified between 2020 and 2025, while the number of employed workers first remained relatively stable and then declined moderately in recent years. Three predictive models were compared on the productivity series: simple linear regression, exponential smoothing (Holt-Winters), and ARIMA. The ARIMA and exponential smoothing models obtained the best predictive performance (lowest RMSE and AIC in the validation set). The complete Python code (Pandas, statsmodels, and matplotlib) is included in the Methods section to ensure full replicability with the original Excel file. The results show a clear decoupling between employment volume  and value generated per worker, signaling a transition toward greater labor efficiency in the Mexican maquiladora sector.