Person-centered Treatment (PeT) Effects: Individualized Treatment Effects Using Instrumental Variables

I describe a command, petiv, that uses a local instrumental-variables (LIV) approach to estimate person-centered treatment effects for a variety of specifications for the LIV estimand as outlined in Basu (2014, Journal of Applied Econometrics 29: 671–691). The petiv command creates a new variable in the dataset that contains the person-centered treatment effects for each individual in the dataset. However, the command takes the validity of the instrumental variables and the specification of the LIV estimand as given. Appropriateness of these features of an LIV analysis should be determined before running the petiv command. The individual effects can be used to answer distributional questions and can also be easily aggregated to obtain mean treatment-effects estimates.

[1]  Markus Frölich,et al.  Quantile Treatment Effects in the Regression Discontinuity Design: Process Results and Gini Coefficient , 2010, SSRN Electronic Journal.

[2]  J. Angrist,et al.  Identification and Estimation of Local Average Treatment Effects , 1995 .

[3]  J. Newhouse,et al.  Econometrics in outcomes research: the use of instrumental variables. , 1998, Annual review of public health.

[4]  Edward Vytlacil,et al.  Local Instrumental Variables , 2000 .

[5]  J. Heckman,et al.  Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients. , 2007, Health economics.

[6]  A. Basu Estimating Decision-Relevant Comparative Effects Using Instrumental Variables , 2011, Statistics in biosciences.

[7]  J J Heckman,et al.  Local instrumental variables and latent variable models for identifying and bounding treatment effects. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[8]  E. Vytlacil,et al.  Partial Identification in Triangular Systems of Equations With Binary Dependent Variables , 2011 .

[9]  E. Vytlacil Independence, Monotonicity, and Latent Index Models: An Equivalence Result , 2002 .

[10]  Markus Frölich,et al.  Unconditional Quantile Treatment Effects Under Endogeneity , 2013 .

[11]  James J Heckman,et al.  Understanding Instrumental Variables in Models with Essential Heterogeneity , 2006, The Review of Economics and Statistics.

[12]  Estimating Person-Centered Treatment (Pet) Effects Using Instrumental Variables , 2012, Journal of applied econometrics.