ivmte

Instrumental Variables: Extrapolation by Marginal Treatment Effects

CRAN Package

The marginal treatment effect was introduced by Heckman and Vytlacil (2005) doi:10.1111/j.1468-0262.2005.00594.x to provide a choice-theoretic interpretation to instrumental variables models that maintain the monotonicity condition of Imbens and Angrist (1994) doi:10.2307/2951620. This interpretation can be used to extrapolate from the compliers to estimate treatment effects for other subpopulations. This package provides a flexible set of methods for conducting this extrapolation. It allows for parametric or nonparametric sieve estimation, and allows the user to maintain shape restrictions such as monotonicity. The package operates in the general framework developed by Mogstad, Santos and Torgovitsky (2018) doi:10.3982/ECTA15463, and accommodates either point identification or partial identification (bounds). In the partially identified case, bounds are computed using either linear programming or quadratically constrained quadratic programming. Support for four solvers is provided. Gurobi and the Gurobi R API can be obtained from http://www.gurobi.com/index. CPLEX can be obtained from https://www.ibm.com/analytics/cplex-optimizer. CPLEX R APIs 'Rcplex' and 'cplexAPI' are available from CRAN. MOSEK and the MOSEK R API can be obtained from https://www.mosek.com/. The lp_solve library is freely available from http://lpsolve.sourceforge.net/5.5/, and is included when installing its API 'lpSolveAPI', which is available from CRAN.


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