Instrumental Variables: Extrapolation by Marginal Treatment Effects
Obtaining IV-like estimands
Parsing marginal treatment response formulas
Function to multiply polynomials
Calulating population mean
Print results
(Alternative) Defining single splines basis functions, with interactio...
Auxiliary function: extract arguments from function in string form
Audit procedure
Obtaining TE bounds
Construct confidence intervals for treatment effects under partial ide...
Construct p-values for treatment effects under partial identification
Spline basis function of order 1
Check polynomial form of the u-term
Auxiliary function: test if object is a formula
Auxiliary function: test if object is a list
Combining the boundedness and monotonicity constraint objects
Construct constant function
Minimizing violation of observational equivalence
Generating design matrices
Auxiliary function: extracting columns by component names
Format result for display
Evaluate a particular function
Generate basis matrix for splines
Generating the constraint matrix
Generate test distribution 1
Generate test distribution 1 with errors
Generate test distribution 2
Generate test distribution 3
Generate test distribution 3 with errors
Generate test distribution 4
Generate test distribution 5 (has errors and a covariate)
Generate test distribution 6 (has errors and a covariate)
Generate basic data set for testing
Generate test data set with covariates
Generate mosquito data set
Generate test data set with splines
Auxiliary function: generating basis vectors
Estimating expectations of terms in the MTR (gamma objects)
Generate Gamma moments for splines
Generating the Gamma moments for splines, for 'testthat'
Function to generate gamma moments for 'testthat'
Generating the grid for the audit procedure
Generate components of the monotonicity constraints
Generating monotonicity and boundedness constraints
Generating moments/data for IV-like estimands
Generating target MTR moments
Generating list of target weight functions
Auxiliary function: extract X and Z covariates from a formula
GMM estimate of TE under point identification
Update splines object with list of interactions
Auxiliary function: check if string is command
Obtaining IV-like specifications
Instrumental Variables: Extrapolation by Marginal Treatment Effects
Single iteration of estimation procedure from Mogstad, Torgovitsky, Sa...
Listing subsets and components
Constructing LP problem
Configure LP environment for obtaining the bounds
Configure LP environment for minimizing the criterion
Configure LP environment for specification testing
Generate equality constraints
Configure LP environment for diagnostics
Configure LP environment to be compatible with solvers
Check magnitude of real number
Convert matrix into triplet form
Function to generate integral of m0 and m1
Auxiliary function: modifying calls
Construct pre-meaned moment matrix
Integrating and evaluating monomials
Check if custom weights are negations of each other
OLS weights
Function to parse options for CPLEX
Function to parse a single set of options for CPLEX
Function to extract feasibility tolerance from CPLEX options
Function to parse options for Gurobi
Function to parse options for lp_solve
Function to parse options for Gurobi
Correct boolean expressions in terms lists
Auxiliary function: generate all permutations of a vector
Auxiliary function: generate all permutation orderings
Estimating propensity scores
Constructing QCQP problem
Constructing QCQP problem for bounding
Configure QCQP problem to find minimum criterion
Configure QP environment for diagnostics
Separating splines from MTR formulas
Function to implement rescaling procedure
Auxiliary function that converts an expression of variable names into ...
Generate Halton sequence
Running cplexAPI solver
Running Gurobi solver
Running lpSolveAPI
Running Rmosek
Select points from audit grid to add to the constraint grid
IV-like weighting function, OLS specification 1
IV-like weighting function, OLS specification 2
IV-like weighting function, OLS specification 3
IV-like weighting function, OLS specifications
Integrating splines
Evaluating splines basis functions
Constructing higher order splines
Convert status code to string
IV-like weighting function, TSLS specification
IV-like weighting function, TSLS specification
Auxiliary function: remove extraneous spaces
Summarize results
IV-like weighting function, Wald specification
Generate symmetric matrix
TSLS weights, with controls
Auxiliary function that converts a vector of strings into an expressio...
Spline basis function
Integrated splines
Auxiliary function: extracting elements from strings
Target weight for ATE
Target weight for ATT
Target weighting function, for ATT
Target weight for ATU
Generating splines weights
Target weight for generalized LATE
Auxiliary function: which
for lists
Target weight for LATE
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.