Identifying Elasticities in Autocorrelated Time Series Using Causal Mechanism Graphs
The paper uses causal mechanism time graphs to improve instrumental variable (IV) methods for estimating price elasticity in autocorrelated time series, like electricity demand. By modeling equilibrium conditions as directed acyclic graphs, researchers can systematically check estimator validity using graphical criteria. This approach helps identify structural biases and reveals complex market dynamics that simple models miss.