Working Paper: NBER ID: w16421
Authors: James J. Heckman; Daniel A. Schmierer
Abstract: This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971, 1974), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model.
Keywords: correlated random coefficient model; instrumental variables; causal inference; microeconometrics
JEL Codes: C31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| choice indicator (d_i) (C25) | outcome (y_i) (C29) |
| cov(d_i, i) ≠ 0 (C10) | marginal returns differ from average returns (D29) |
| i independent of d_i given x_i (C29) | valid instruments identify the same estimand (C36) |
| selection on unobservables (C52) | bias in causal estimates from standard IV methods (C36) |