linearmodels.iv.results.IVResults

class IVResults(results, model)

Results from IV estimation

Parameters:

resultsdict[str, any]

A dictionary of results from the model estimation.

model{IV2SLS, IVLIML}

The model used to estimate parameters.

Attributes:

anderson_rubin

Anderson-Rubin test of overidentifying restrictions

basmann

Basmann’s test of overidentifying restrictions

basmann_f

Basmann’s F test of overidentifying restrictions

cov

Estimated covariance of parameters

cov_config

Parameter values from covariance estimator

cov_estimator

Type of covariance estimator used to compute covariance

cov_type

Covariance estimator used

debiased

Flag indicating whether covariance uses a small-sample adjustment

df_model

Model degree of freedom

df_resid

Residual degree of freedom

f_statistic

Model F-statistic

first_stage

First stage regression results

fitted_values

Fitted values

has_constant

Flag indicating the model includes a constant or equivalent

idiosyncratic

Idiosyncratic error

kappa

k-class estimator value

method

Method used to estimate model parameters

model_ss

Residual sum of squares

nobs

Number of observations

params

Estimated parameters

pvalues

Parameter p-vals.

resid_ss

Residual sum of squares

resids

Estimated residuals

rsquared

Coefficient of determination (R**2)

rsquared_adj

Sample-size adjusted coefficient of determination (R**2)

s2

Residual variance estimator

sargan

Sargan test of overidentifying restrictions

std_errors

Estimated parameter standard errors

summary

Model estimation summary.

total_ss

Total sum of squares

tstats

Parameter t-statistics

wooldridge_overid

Wooldridge’s score test of overidentification

wooldridge_regression

Wooldridge’s regression test of exogeneity

wooldridge_score

Wooldridge’s score test of exogeneity

wresids

Weighted estimated residuals

Methods

conf_int([level])	Confidence interval construction
durbin([variables])	Durbin's test of exogeneity
predict([exog, endog, data, fitted, ...])	In- and out-of-sample predictions
wald_test([restriction, value, formula])	Test linear equality constraints using a Wald test
wu_hausman([variables])	Wu-Hausman test of exogeneity

Properties

anderson_rubin	Anderson-Rubin test of overidentifying restrictions
basmann	Basmann's test of overidentifying restrictions
basmann_f	Basmann's F test of overidentifying restrictions
cov	Estimated covariance of parameters
cov_config	Parameter values from covariance estimator
cov_estimator	Type of covariance estimator used to compute covariance
cov_type	Covariance estimator used
debiased	Flag indicating whether covariance uses a small-sample adjustment
df_model	Model degree of freedom
df_resid	Residual degree of freedom
f_statistic	Model F-statistic
first_stage	First stage regression results
fitted_values	Fitted values
has_constant	Flag indicating the model includes a constant or equivalent
idiosyncratic	Idiosyncratic error
kappa	k-class estimator value
method	Method used to estimate model parameters
model_ss	Residual sum of squares
nobs	Number of observations
params	Estimated parameters
pvalues	Parameter p-vals.
resid_ss	Residual sum of squares
resids	Estimated residuals
rsquared	Coefficient of determination (R**2)
rsquared_adj	Sample-size adjusted coefficient of determination (R**2)
s2	Residual variance estimator
sargan	Sargan test of overidentifying restrictions
std_errors	Estimated parameter standard errors
summary	Model estimation summary.
total_ss	Total sum of squares
tstats	Parameter t-statistics
wooldridge_overid	Wooldridge's score test of overidentification
wooldridge_regression	Wooldridge's regression test of exogeneity
wooldridge_score	Wooldridge's score test of exogeneity
wresids	Weighted estimated residuals