An empirical estimate of the electricity supply curve from market outcomes

Researchers and electricity sector practitioners frequently require the supply curve of electricity markets and the price elasticity of supply for purposes such as price forecasting, policy analyses or market power assessment. It is common practice to construct supply curves from engineering data such as installed capacity and fuel prices. In this study, we propose a data-driven methodology to estimate the supply curve of electricity market empirically, i.e. from observed prices and quantities without further modeling assumptions. Due to the massive swings in fuel prices during the European energy crisis, a central task is detecting periods of stable supply curves. To this end, we implement two alternative clustering methods, one based on the fundamental drivers of electricity supply and the other directly on observed market outcomes. We apply our methods to the German electricity market between 2019 and 2024. We find that both approaches identify almost identical regimes shifts, supporting the idea of stable supply regimes stemming from stable drivers. Supply conditions are often stable for extended periods, but evolved rapidly during the energy crisis, triggering a rapid succession of regimes. Fuel prices were the dominant drivers of regime shifts, while conventional plant availability and the nuclear phase-out play a comparatively minor role. Our approach produces empirical supply curves suitable for causal inference and counterfactual analysis of market outcomes.