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Working Paper
ivcrc: An Instrumental Variables Estimator for the Correlated Random Coefficients Model
We present the ivcrc command, which implements an instrumental variables (IV) estimator for the linear correlated random coefficients (CRC) model. This model is a natural generalization of the standard linear IV model that allows for endogenous, multivalued treatments and unobserved heterogeneity in treatment effects. The proposed estimator uses recent semiparametric identification results that allow for flexible functional forms and permit instruments that may be binary, discrete, or continuous. The command also allows for the estimation of varying coefficients regressions, which are ...
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Latent Heterogeneity in the Marginal Propensity to Consume
We estimate the unconditional distribution of the marginal propensity to consume (MPC) using clustering regression and the 2008 stimulus payments. Since we do not measure heterogeneity as the variation of MPCs with observables, we can recover the full distribution of MPCs. Households spent at least one quarter of the rebate, and individual households used rebates for different goods. While many observables are individually correlated with our estimated MPCs, these relationships disappear when tested jointly, except for nonsalary income and the average propensity to consume. Household ...
Working Paper
ivcrc: An Instrumental Variables Estimator for the Correlated Random Coefficients Model
We discuss the ivcrc module, which implements an instrumental variables (IV) estimator for the linear correlated random coefficients (CRC) model. The CRC model is a natural generalization of the standard linear IV model that allows for endogenous, multivalued treatments and unobserved heterogeneity in treatment effects. The estimator implemented by ivcrc uses recent semiparametric identification results that allow for flexible functional forms and permit instruments that may be binary, discrete, or continuous. The ivcrc module also allows for the estimation of varying coefficients ...
Working Paper
Modeling Event Studies with Heterogeneous Treatment Effects
This paper develops a simple approach to overcome the shortcomings of using a standard, single treatment–effect event study to assess the ability of an empirical model to measure heterogeneous treatment effects. Equally as important, we discuss how the standard errors reported in a typical event-study analysis for the posttreatment event-time effects are, without additional information, of limited use for assessing posttreatment variations in the treatment effects. The simple reformulation of the standard event—study approach described and illustrated with artificially constructed data in ...