This study proposes a reproducible exploratory framework to link long-term territorial development with electricity demand in data-scarce contexts, and applies it to Ecuador’s Costa region. The pipeline combines three commonly available input streams: periodic census microdata, an official demand series, and macroeconomic aggregates. Socioeconomic heterogeneity across five non-uniform census rounds (1974, 1982, 1990, 2001, 2010) is summarized through Principal Component Analysis (PCA), and territorial indicators are projected to the demand horizon using low-order polynomial functions. Eleven regression specifications are compared on a log-transformed demand variable, and a rollingorigin backtesting scheme plus a 2020–2024 holdout are used for validation. The selected Trend OLS log model attains R2 = 0.551 and MAPE = 6.08%, and projects a regional demand of approximately 6,940 MW by 2050, equivalent to a compound annual growth rate of 3.45%. Beyond the Ecuadorian case, the results show that transparent, low-data pipelines based on harmonized census information, macroeconomic drivers and simple regression models can provide defensible medium- and long-term demand signals for planners in other emerging economies with limited high-frequency data.