OpenBB/website/content/sdk/reference/econometrics/panel.md

title, description, keywords

title	description	keywords
panel	Tutorial on how to use OpenBB Terminal's econometric functions with focus on running panel regression models. This includes choosing the type of regression, setting entity and time effects, and interacting with the Python SDK. Provides examples using the 'openbb.econometrics.panel' function, which allows selection of OLS or pooled OLS models, and demonstrates how to read and interpret the model summary. Also explains the 'openbb.econometrics.panel_chart' function, which visualizes regression outcomes.	Docusaurus Econometrics Panel Regression Fixed Effects Python SDK OLS Regression Regression Model Pooled OLS Regression Chart

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Based on the regression type, this function decides what regression to run.

Source Code: [link]

openbb.econometrics.panel(Y: pd.DataFrame, X: pd.DataFrame, regression_type: str = "OLS", entity_effects: bool = False, time_effects: bool = False)

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Parameters

Name	Type	Description	Default	Optional
Y	pd.DataFrame	Dataframe containing the dependent variable.	None	False
X	pd.DataFrame	Dataframe containing the independent variables.	None	False
regression_type	str	The type of regression you wish to execute.	OLS	True
entity_effects	bool	Whether to apply Fixed Effects on entities.	False	True
time_effects	bool	Whether to apply Fixed Effects on time.	False	True

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Returns

Type	Description
Any	A regression model

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Examples

from openbb_terminal.sdk import openbb
df = openbb.econometrics.load("wage_panel")
df = df.set_index(["nr","year"])
X = df[["exper","educ","union"]]
Y = df["lwage"]
pooled_ols_model = openbb.econometrics.panel(Y,X,"POLS")
print(pooled_ols_model.summary)

PooledOLS Estimation Summary
================================================================================
Dep. Variable:                  lwage   R-squared:                        0.1634
Estimator:                  PooledOLS   R-squared (Between):              0.1686
No. Observations:                4360   R-squared (Within):               0.1575
Date:                Sun, Nov 13 2022   R-squared (Overall):              0.1634
Time:                        13:04:02   Log-likelihood                   -3050.4
Cov. Estimator:            Unadjusted
                                        F-statistic:                      283.68
Entities:                         545   P-value                           0.0000
Avg Obs:                       8.0000   Distribution:                  F(3,4356)
Min Obs:                       8.0000
Max Obs:                       8.0000   F-statistic (robust):             283.68
                                        P-value                           0.0000
Time periods:                       8   Distribution:                  F(3,4356)
Avg Obs:                       545.00
Min Obs:                       545.00
Max Obs:                       545.00
                            Parameter Estimates
==============================================================================
            Parameter  Std. Err.     T-stat    P-value    Lower CI    Upper CI
------------------------------------------------------------------------------
const         -0.0308     0.0620    -0.4965     0.6196     -0.1523      0.0908
exper          0.0561     0.0028     20.220     0.0000      0.0507      0.0616
educ           0.1080     0.0045     24.034     0.0000      0.0992      0.1168
union          0.1777     0.0172     10.344     0.0000      0.1441      0.2114
==============================================================================

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Based on the regression type, this function decides what regression to run.

Source Code: [link]

openbb.econometrics.panel_chart(Y: pd.DataFrame, X: pd.DataFrame, regression_type: str = "OLS", entity_effects: bool = False, time_effects: bool = False, export: str = "")

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Parameters

Name	Type	Description	Default	Optional
data	dict	A dictionary containing the datasets.	None	True
regression_variables	list	The regressions variables entered where the first variable is the dependent variable. each column/dataset combination.	None	True
regression_type	str	The type of regression you wish to execute. Choose from: OLS, POLS, RE, BOLS, FE	OLS	True
entity_effects	bool	Whether to apply Fixed Effects on entities.	False	True
time_effects	bool	Whether to apply Fixed Effects on time.	False	True
export	str	Format to export data		True

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Returns

Type	Description
The dataset used, the dependent variable, the independent variable and

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