{"blocks": [{"key": "8f814097", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "6755ee40", "text": "Marketing analytics team wants to measure the causal impact of campaigns.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "5880b651", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "8043bd86", "text": "Explain how you would use Propensity Score Matching (PSM) and Difference-in-Differences (DiD) to estimate treatment effect. When is a synthetic control method preferable to DiD? Describe the Double Machine Learning (DML) framework for causal inference and why it helps with high-dimensional covariates.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "d69b5579", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "6d80a7d8", "text": "Cover identification assumptions, overlap, parallel trends, cross-fitting, and robustness checks.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}