Module Reference¶
Models for Panel Data¶
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 | One- and two-way fixed effects estimator for panel data | 
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 | One-way Random Effects model for panel data | 
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 | Between estimator for panel data | 
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 | First difference model for panel data | 
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 | Pooled coefficient estimator for panel data | 
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 | Pooled coefficient estimator for panel data | 
Estimation Results¶
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 | Results container for Fama MacBeth panel data models | 
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 | Results container for panel data models that do not include effects | 
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 | Results container for panel data models that include effects | 
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 | Results container for random effect panel data models | 
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 | Comparison of multiple models | 
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 | Compare the results of multiple models | 
Panel Model Covariance Estimators¶
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 | Homoskedastic covariance estimation | 
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 | Covariance estimation using White estimator | 
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 | One-way (Rogers) or two-way clustered covariance estimation | 
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 | Driscoll-Kraay heteroskedasticity-autocorrelation robust covariance estimation | 
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 | Autocorrelation robust covariance estimation | 
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 | HAC estimator for Fama-MacBeth estimator | 
Panel Data Structures¶
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 | Abstraction to handle alternative formats for panel data | 
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 | Convert a MI DataFrame to a 3-d structure where columns are items. | 
Test Data Generation¶
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 | Simulate panel data for testing | 
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 | Typed namedtuple to hold simulated panel data |