https://github.com/beniaminogreen/cragg
Test for weak IV instruments in R.
https://github.com/beniaminogreen/cragg
instrumental-variable iv ivreg2 r regression weak-instruments
Last synced: 11 months ago
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Test for weak IV instruments in R.
- Host: GitHub
- URL: https://github.com/beniaminogreen/cragg
- Owner: beniaminogreen
- License: gpl-3.0
- Created: 2020-12-31T02:02:33.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2021-08-26T14:51:48.000Z (almost 5 years ago)
- Last Synced: 2023-07-15T02:29:02.532Z (almost 3 years ago)
- Topics: instrumental-variable, iv, ivreg2, r, regression, weak-instruments
- Language: R
- Homepage:
- Size: 992 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Cragg
[](https://travis-ci.com/beniaminogreen/cragg)
[](https://www.gnu.org/licenses/gpl-3.0.en.html)
An R package to implement the Cragg-Donald test for weak instruments.
## Overview
The Cragg-Donald (1993) test is a common way to test for weak
instruments in an IV regression but has never been implemented in R. The
cragg package provides an implementation of the Cragg-Donald test in R
and provides access to the critical values for the Cragg-Donald
statistic developed in Stock and Yogo (Stock 2005). These tests quantify
the degree to which weak instruments can undermine regression estimates
for models with multiple endogenous variables / treatments.
### Main Features
- Calculates Cragg-Donald statistics for weak instruments.
- Recommends critical values for the Cragg-Donald Statistic based on
the largest allowable bias relative to regular OLS or the maximum
allowable size distortion of the Wald test statistic.
## Installation
``` r
install.packages("cragg")
library(cragg)
```
## Usage
The cragg package has two main functions `cragg_donald()`, and
`stock_yogo_test()`.
`cragg_donald()` implements the Cragg-Donald test for weak instruments
in R. It can be thought of as the matrix-equivalent of the first-stage
F-test for weak instruments, and is used to evaluate models with
multiple endogenous variables. This function has been tested against the
results from STATA’s ivreg2 package (Baum, Mark, Stillman 2002) to
ensure accuracy.
The syntax is show below:
``` r
library(cragg)
#Cragg-Donald Test
cragg_donald(
~X1+X2+X3, #Controls
~D1 + D2, #Treatments
~Z1 + Z2 + Z3, #Instruments
data =example_data
)
#> Cragg-Donald test for weak instruments:
#>
#> Data: example_data
#> Controls: ~X1 + X2 + X3
#> Treatments: ~D1 + D2
#> Instruments: ~Z1 + Z2 + Z3
#>
#> Cragg-Donald Statistic: 186.1346
#> Df: 993
```
`stock_yogo_test()` implements the Stock and Yogo test for weak
instruments. The test developed by Stock and Yogo (2005) is a decision
rule meant to ensure that weak instruments do not pose a problem. Stock
and Yogo suggest two methods to select the critical values: one based on
maximum allowable bias relative to normal OLS and another based on the
maximum size of a Wald test on all of the instruments. Both of these
decision rules are implemented.
``` r
stock_yogo_test(
~X1+X2+X3, #Controls
~D1, #Treatments
~Z1 + Z2, #Instruments
B=.1, #Maximum Allowable Size Distortion
size_bias="size", #Calculate critical value for size distortions
data =example_data
)
#> Results of Stock and Yogo test for weak instruments:
#>
#> Null Hypothesis: Instruments are weak
#> Alternative Hypothesis: Instruments are not weak
#>
#> Data: example_data
#> Controls: ~X1 + X2 + X3
#> Treatments: ~D1
#> Instruments: ~Z1 + Z2
#>
#> Alpha: 0.05
#> Acceptable level of bias: 10% Wald test distortion.
#> Critical Value: 19.93
#>
#> Cragg-Donald Statistic: 360.5978
#> Df: 994
```
# References
Baum, Christopher F, Mark E Schaffer, and Steven Stillman. 2002. “IVREG2: Stata module for extended instrumental
variables/2SLS and GMM estimation.” Statistical Software
Components, Boston College Department of Economics.
Cragg, John G., and Stephen G. Donald. 1993. “Testing Identifiability
and Specification in Instrumental Variable Models.” *Econometric Theory*
9 (2): 222–40. .
Stock, James H., and Motohiro Yogo. 2005. “Testing for Weak Instruments
in Linear IV Regression.” In *Identification and Inference for
Econometric Models*, 80–108. Cambridge University Press.
.