Statistical validation of geothermal development stages: A strategic benchmarking framework for energy policy and market maturity

Limiting energy-system emissions increases the strategic value of reliable renewable sources. Geothermal energy stands out for its high capacity factor and low emissions, yet its historical deployment is often described through visually defined periods rather than statistically dated regimes. This study develops a data-driven framework to statistically validate geothermal development stages and benchmark major markets against a reference pathway. Using annual cumulative installed capacity for leading countries (1945–2024), we estimate endogenous break dates with the Bai–Perron multiple structural change methodology and summarize global diffusion via a sample-aggregate series. An ACC–ACA visualization highlights long-run growth and volatility. Country trajectories are benchmarked to the U.S. reference market through correlation-based time-shift alignment and stage-by-stage similarity scores; Dynamic Time Warping distances serve as a robustness diagnostic. The U.S. series shows five statistically identified breaks over 1960–2024, including a post-2015 regime of moderated growth. The sample-aggregate series displays three breaks (1977, 1989, 2012) with accelerated expansion after 2012. Benchmarking reveals heterogeneous pathways, ranging from strong multi-stage similarity (Italy, Japan) through partial alignment with weaker late-stage recovery (Mexico, Philippines) to limited stage completion (Iceland, Türkiye). The statistically dated staging and alignment framework provides a replicable basis for interpreting geothermal deployment pathways, informing national energy strategies, and supporting policy design for accelerated clean-energy transitions under SDG 7.