When direct cause-and-effect analysis is tricky, instrumental variables step in as a powerful statistical tool. They isolate true causal impact by using a third "instrument" related to the treatment but not the outcome. Economists, epidemiologists, and data scientists benefit, gaining unbiased insights from messy observational data to guide policy and research.
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