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• W1967993709 abstract "Abstract Two-stage least squares (TSLS) is widely used in econometrics to estimate parameters in systems of linear simultaneous equations and to solve problems of omitted-variables bias in single-equation estimation. We show here that TSLS can also be used to estimate the average causal effect of variable treatments such as drug dosage, hours of exam preparation, cigarette smoking, and years of schooling. The average causal effect in which we are interested is a conditional expectation of the difference between the outcomes of the treated and what these outcomes would have been in the absence of treatment. Given mild regularity assumptions, the probability limit of TSLS is a weighted average of per-unit average causal effects along the length of an appropriately defined causal response function. The weighting function is illustrated in an empirical example based on the relationship between schooling and earnings." @default.
• W1967993709 created "2016-06-24" @default.
• W1967993709 creator A5027614993 @default.
• W1967993709 creator A5052726702 @default.
• W1967993709 date "1995-06-01" @default.
• W1967993709 modified "2023-10-18" @default.
• W1967993709 title "Two-Stage Least Squares Estimation of Average Causal Effects in Models with Variable Treatment Intensity" @default.
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• W1967993709 doi "https://doi.org/10.2307/2291054" @default.
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