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