Metadata-Version: 2.4
Name: weak_instruments
Version: 0.0.1
Summary: A package for weak instruments in an instrumental variables regression.
Project-URL: Homepage, https://github.com/pypa/weak_instruments
Project-URL: Issues, https://github.com/pypa/weak_instruments/issues
Author-email: Jonathan Hyatt <hyatt.jonathan99@gmail.com>, Jacob Hutchings <jacobhutchings1@gmail.com>
License-Expression: MIT
License-File: LICENSE
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# Solutions to Weak Instruments

## JIVE1 and JIVE2 estimates based on Angrist, Imbens, and Krueger (1999)
We use the following formula for estimation of JIVE1:

$\[\frac{Z_i \hat{\pi} - h_i X_i}{1-h_i}\]$

where $h_i$ is the leverage for observation $i$.

We use the following formula for estimation of JIVE2:

$\[\frac{Z_i \hat{\pi} - h_i X_i}{1-(\frac{1}{N})}\]$

## Weak identification with many instruments (Mikushueva and Sun)





## Lim et al.




## Jacknife Anderson-Rubin tests for many weak IV inference



## Lagrange Multiplier



## HFUL



Each file should check for:
- Multicollinearity
- Perfect collinearity
- Dimensions of variables (Single column of controls etc)
    - Check to see if dimensions are the same for all variables
- Constant columns
- Y and Z must be one dimensional vectors