Module Reference

Instrumental Variable Estimation

IV2SLS(dependent, exog, endog, instruments, *)	Estimation of IV models using two-stage least squares
IVLIML(dependent, exog, endog, instruments, *)	Limited information ML and k-class estimation of IV models
IVGMM(dependent, exog, endog, instruments, *)	Estimation of IV models using the generalized method of moments (GMM)
IVGMMCUE(dependent, exog, endog, instruments, *)	Estimation of IV models using continuously updating GMM

Absorbing Least Squares

OLS and WLS with high-dimensional effects.

AbsorbingLS(dependent[, exog, absorb, …])	Linear regression with high-dimensional effects
AbsorbingLSResults(results, model)	Attributes
Interaction([cat, cont, nobs])	Class that simplifies specifying interactions

Estimation Results

IVResults(results, model)	Results from IV estimation
IVGMMResults(results, model)	Results from GMM estimation of IV models
OLSResults(results, model)	Results from OLS model estimation
IVModelComparison(results, *[, precision])	Comparison of multiple models
FirstStageResults(dep, exog, endog, instr, …)	First stage estimation results and diagnostics
compare(results, \*[, precision])	Compare the results of multiple models

Instrumental Variable Covariance Estimation

HomoskedasticCovariance(x, y, z, params[, …])	Covariance estimation for homoskedastic data
HeteroskedasticCovariance(x, y, z, params[, …])	Covariance estimation for heteroskedastic data
ClusteredCovariance(x, y, z, params[, …])	Covariance estimation for clustered data
KernelCovariance(x, y, z, params[, kernel, …])	Kernel weighted (HAC) covariance estimation

Kernel Weight Generators

kernel_weight_bartlett(bw, \*args)	Kernel weights from a Bartlett kernel
kernel_weight_parzen(bw, \*args)	Kernel weights from a Parzen kernel
kernel_weight_quadratic_spectral(bw, float], n)	Kernel weights from a quadratic-spectral kernel

GMM Weight and Covariance Estimation

IVGMMCovariance(x, y, z, params, w[, …])	Covariance estimation for GMM models
HomoskedasticWeightMatrix([center, debiased])	Homoskedastic (unadjusted) weight estimation
HeteroskedasticWeightMatrix([center, debiased])	Heteroskedasticity robust weight estimation
KernelWeightMatrix([kernel, bandwidth, …])	Heteroskedasticity, autocorrelation robust weight estimation
OneWayClusteredWeightMatrix(clusters[, …])	Clustered (one-way) weight estimation

IV Data Structures

IVData(x[, var_name, nobs, convert_dummies, …])

Simple class to abstract different input data formats