Non-compliance in randomized control trials without exclusion restrictions
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This study presents a method to identify treatment effects without exclusion restrictions for randomized experiments with non-compliance. It exploits a baseline survey that is commonly available in randomized control trials. I show the identification of the average treatment effect on the treated (ATT) and the local average treatment effect (LATE), assuming that a baseline variable maintains similar rank orders to the control outcome. I apply this strategy to a microcredit experiment with one-sided non-compliance to identify the ATT. I find that the instrumental variable (IV) estimate of log revenue is 2.2 times larger than my preferred estimate of log revenue.
New Economics Papers: this item is included in nep-ecm, nep-exp and nep-mfd
Date: 2019-10, Revised 2019-10
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1910.03204
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