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Title: Tests for Weak Instruments in R
Version: 0.0.1
Description: Implements Cragg-Donald (1993) <doi:10.1017/S0266466600007519> and Stock and Yogo (2005) <doi:10.1017/CBO9780511614491.006> tests for weak instruments in R.
License: GPL (≥ 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: expm (≥ 0.999)
Suggests: testthat (≥ 3.0.0), knitr, MASS, rmarkdown
Config/testthat/edition: 3
Depends: R (≥ 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-05 20:31:53 UTC; beniamino
Author: Beniamino Green [aut, cre]
Maintainer: Beniamino Green <ben@greendalba.com>
Repository: CRAN
Date/Publication: 2021-01-08 08:40:03 UTC

Calculate the Cragg-Donald statistic for a given model.

Description

Calculate the Cragg-Donald statistic for a given model.

Usage

cragg_donald(X, D, Z, data = data.frame())

Arguments

X

(formula). A one-sided formula of control variables.

D

(formula). A one-sided formula of endogenous variables (treatments)

Z

(formula). A one-sided formula of instruments

data

(dataframe). An optional dataframe, list, or environment containing the variables used in the model. As with many of the base R functions, if the variables are not found here, they may be searched for in the environment cragg_donald() was called.

Value

(cd_test) results object of class "cd_test"

Examples

#Obtain the Cragg-Donald statistic for a model that instruments
#Sepal Width on Petal Length, Petal Width, and Species, while controlling
#for Sepal.Length (a toy example).
cragg_donald(X=~Sepal.Length, D=~Sepal.Width,
			Z=~Petal.Length + Petal.Width + Species, data = iris)

Recommend a critical value for the Cragg-Donald test given a maximum allowable bias/size distortion

Description

Recommend a critical value for the Cragg-Donald test given a maximum allowable bias/size distortion

Usage

stock_yogo_reccomender(K, N, B, size_bias)

Arguments

K

(int). The number of instruments.

N

(int). The number of endogenous variables (treatments)

B

One of [.05, .1, .15, .2, .25, .3]. The maximum size of allowable bias relative to the normal OLS or the maximum Wald test size distortion.

size_bias

Either "bias" or "size". Whether to use a critical value based on the maximum allowable bias relative to regular OLS (bias), or maximum Wald test size distortion.

Value

(float) the recommended critical value.

Examples

#To reccomend a critical value for a test with 2 endogenous variables
#and four instruments based on a 5% maximum allowable bias relative to OLS

stock_yogo_reccomender(4,2,.05,"bias")


Perform the Stock and Yogo test for weak instruments

Description

Perform the Stock and Yogo test for weak instruments

Usage

stock_yogo_test(X, D, Z, data, B = 0.05, size_bias = "bias")

Arguments

X

(formula). A one-sided formula of control variables.

D

(formula). A one-sided formula of endogenous variables (treatments)

Z

(formula). A one-sided formula of instruments

data

(dataframe). An optional dataframe, list, or environment containing the variables used in the model. As with many of the base R functions, if the variables are not found here, they may be searched for in the environment cragg_donald() was called.

B

One of [.05, .1, .15, .2, .25, .3]. The maximum size of allowable bias relative

size_bias

Either "bias" or "size". Whether to use a critical value based on the maximum allowable bias relative to regular OLS (bias), or maximum Wald test size distortion (size).

Value

(sy_test) the results of the stock and yogo test.

Examples

#Perform the Stock and Yogo test on a model that instruments
#Sepal Width on Petal Length, Petal Width, and Species, while controlling
#for Sepal.Length (a toy example).

stock_yogo_test(X=~Sepal.Length, D=~Sepal.Width,
	Z=~Petal.Length + Petal.Width + Species,
	size_bias="bias",data = iris)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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