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)

Results from IV estimation

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, …)

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, 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, …])

Type abstraction for use in univariate models.