ivmodel (version 1.9.1)

ivmodel-package: tools:::Rd_package_title("ivmodel")

Description

The package fits an instrumental variables (IV) model of the following type. Let \(Y\), \(D\), \(X\), and \(Z\) represent the outcome, endogenous variable, p dimensional exogenous covariates, and L dimensional instruments, respectively; note that the intercept can be considered as a vector of ones and a part of the exogenous covariates \(X\).The package assumes the following IV model $$ Y = X \alpha + D \beta + \epsilon, E(\epsilon | X, Z) = 0$$ It carries out several IV regressions, diagnostics, and tests associated with the parameter \(\beta\) in the IV model. Also, if there is only one instrument, the package runs a sensitivity analysis discussed in Jiang et al. (2015).

The package is robust to most data formats, including factor and character data, and can handle very large IV models efficiently using a sparse QR decomposition.

Author

tools:::Rd_package_author("ivmodel")

Maintainer: tools:::Rd_package_maintainer("ivmodel")

Details

Supply the outcome \(Y\), the endogenous variable \(D\), and a data frame and/or matrix of instruments \(Z\), and a data frame and/or matrix of exogenous covariates \(X\) (optional) and run ivmodel. Alternatively, one can supply a formula. ivmodel will generate all the relevant statistics for the parameter \(\beta\).

The DESCRIPTION file: tools:::Rd_package_DESCRIPTION("ivmodel") tools:::Rd_package_indices("ivmodel")

References

Anderson, T. W. and Rubin, H. (1949). Estimation of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics 20, 46-63.

Andrews, D. W. K., Moreira, M. J., and Stock, J. H. (2006). Optimal two-side invariant similar tests for instrumental variables regression. Econometrica 74, 715-752.

Card, D. Using Geographic Variation in College Proximity to Estimate the Return to Schooling. In Aspects of Labor Market Behavior: Essays in Honor of John Vanderkamp, eds. L.N. Christophides, E.K. Grant and R. Swidinsky. 201-222. National Longitudinal Survey of Young Men: https://www.nlsinfo.org/investigator/pages/login.jsp

Fuller, W. (1977). Some properties of a modification of the limited information estimator. Econometrica, 45, 939-953.

Moreira, M. J. (2003). A conditional likelihood ratio test for structural models. Econometrica 71, 1027-1048.

Sargan, J. D. (1958). The estimation of economic relationships using instrumental variables. Econometrica , 393-415.

Wang, X., Jiang, Y., Small, D. and Zhang, N. (2017), Sensitivity analysis and power for instrumental variable studies. Biometrics 74(4), 1150-1160.

Examples

data(card.data)
# One instrument #
Y=card.data[,"lwage"]
D=card.data[,"educ"]
Z=card.data[,"nearc4"]
Xname=c("exper", "expersq", "black", "south", "smsa", "reg661", 
        "reg662", "reg663", "reg664", "reg665", "reg666", "reg667", 
		"reg668", "smsa66")
X=card.data[,Xname]
card.model1IV = ivmodel(Y=Y,D=D,Z=Z,X=X)
card.model1IV

# Multiple instruments
Z = card.data[,c("nearc4","nearc2")]
card.model2IV = ivmodel(Y=Y,D=D,Z=Z,X=X)
card.model2IV