Outlier Robust Two-Stage Least Squares Inference and Testing
Calculates a Hausman test on the difference between robust and full sa...
Calculates the correction factor for inference under H0 of no outliers
Calculates valid se for coefficients under H0 of no outliers
Conducts a t-test on the difference between robust and full sample est...
Calculates the asymptotic variance of the difference between robust an...
Uses nonparametric case resampling for standard errors of parameters a...
Calculate constants across estimation
L2 norm between two most recent estimates
Counts the number of times each index was sampled
Count test
Estimation of moments of the data
Estimation of moments of the data
Evaluate bootstrap results
Extracts bootstrap results for a specific iteration
Extract the elements of ivreg formula
Asymptotic variance of gauge
Asymptotic covariance of gauge
Random data of 2SLS model (Monte Carlo)
Parameters of 2SLS model (Monte Carlo)
Global test correcting for multiple hypothesis testing
Impulse Indicator Saturation (IIS initial estimator)
Monte Carlo simulations parameter grid
Creates a vector of the centered FODR across different cut-offs
Multiple models, varying cut-off
Multivariate normal supremum simulation
Constructor of robust2sls class
Determine which observations can be used for estimation
Nonparametric resampling from a data frame
Create indices for nonparametric bootstrap
Outlier detection algorithms
Outlier history of single observation
Proportion of outliers
Number of outliers
Plotting of standardised residuals and outliers
Helper of robust2sls class
Proportion test
robust2sls: A package for outlier robust 2SLS inference and testing
Robustified 2SLS (full sample initial estimator)
Saturated 2SLS (split-sample initial estimator)
Create selection (non-outlying) vector from IIS model
Create selection (non-outlying) vector from model
Simes (1986) procedure for multiple testing
Scaling sum proportion test across different cut-offs
Supremum proportion test across different cut-offs
Critical and p-value for test statistic relative to simulated distribu...
Append new iteration results to "robust2sls" object
User-specified initial estimator
Validator of robust2sls class
Calculate varrho coefficients
An implementation of easy tools for outlier robust inference in two-stage least squares (2SLS) models. The user specifies a reference distribution against which observations are classified as outliers or not. After removing the outliers, adjusted standard errors are automatically provided. Furthermore, several statistical tests for the false outlier detection rate can be calculated. The outlier removing algorithm can be iterated a fixed number of times or until the procedure converges. The algorithms and robust inference are described in more detail in Jiao (2019) <https://drive.google.com/file/d/1qPxDJnLlzLqdk94X9wwVASptf1MPpI2w/view>.