PyFixest Function Reference
Estimation
User-facing estimation functions. Everything in this reference is available under the pf. namespace after import pyfixest as pf.
| feols | Estimate a linear regression model with fixed effects using fixest formula syntax. |
| fepois | Estimate Poisson regression model with fixed effects using the ppmlhdfe algorithm. |
| feglm | Estimate GLM regression models with fixed effects. |
| quantreg | Fit a quantile regression model using the interior point algorithm from Portnoy and Koenker (1997). |
Difference-in-Differences
Difference-in-differences and event-study estimators, plus panel treatment visualization.
| event_study | Estimate Event Study Model. |
| did2s | Estimate a Difference-in-Differences model using Gardner’s two-step DID2S estimator. |
| lpdid | Local projections approach to estimation. |
| SaturatedEventStudy | Saturated event study with cohort-specific effect curves. |
| panelview | Generate a panel view of the treatment variable over time for each unit. |
Multiple Hypothesis Testing
Family-wise error-rate corrections for multiple hypothesis testing.
| bonferroni | Compute Bonferroni adjusted p-values for multiple hypothesis testing. |
| rwolf | Compute Romano-Wolf adjusted p-values for multiple hypothesis testing. |
| wyoung | Compute the Westfall-Young adjusted p-values for multiple hypothesis testing. |
Estimation Classes
Fitted-model classes returned by the estimation functions. Users do not construct these directly; they are the objects feols(), fepois(), feglm(), and quantreg() return.
| Feols | Non user-facing class to estimate a linear regression via OLS. |
| Fepois | Estimate a Poisson regression model. |
| Feiv | Non user-facing class to estimate an IV model using a 2SLS estimator. |
| Feglm | Base class for the estimation of a fixed-effects GLM model. |
| FixestMulti | Results container holding every model fitted by one public-API call. |
| Quantreg | Quantile regression model. |
Post-Estimation Methods
Methods available on a fitted model object, e.g. the result of a call to feols(). Defined on Feols and shared by Fepois, Feglm, Feiv, and Quantreg through inheritance.
| Feols.tidy | Tidy model outputs. |
| Feols.coef | Estimated coefficients as a pandas Series. |
| Feols.se | Coefficient standard errors as a pandas Series. |
| Feols.tstat | Coefficient t-statistics as a pandas Series. |
| Feols.pvalue | Coefficient p-values as a pandas Series. |
| Feols.confint | Fitted model confidence intervals. |
| Feols.resid | Fitted model residuals. |
| Feols.vcov | Compute covariance matrices for an estimated regression model. |
| Feols.predict | Predict values of the model on new data. |
| Feols.fixef | Compute the coefficients of (swept out) fixed effects for a regression model. |
| Feols.get_performance | Get Goodness-of-Fit measures. |
| Feols.wald_test | Conduct Wald test. |
| Feols.wildboottest | Run a wild cluster bootstrap based on an object of type “Feols”. |
| Feols.ritest | Conduct Randomization Inference (RI) test against a null hypothesis of |
| Feols.ccv | Compute the Causal Cluster Variance following Abadie et al (QJE 2023). |
| Feols.decompose | Implement the Gelbach (2016) decomposition method for mediation analysis. |
| Feols.update | Update coefficients for new observations using Sherman-Morrison formula. |
| Feols.evalue | Compute coefficient-wise SAVI e-values. |
| Feols.pvalue_savi | Compute coefficient-wise SAVI sequential p-values. |
Summarize and Visualize
Summary tables and coefficient plots for fitted models.
| summary | Print a summary of estimation results for each estimated model. |
| etable | Generate a table summarizing the results of multiple regression models. |
| coefplot | Plot model coefficients with confidence intervals. |
| iplot | Plot model coefficients for variables interacted via “i()” syntax, with |
| qplot | Plot regression quantiles. |
Data Sets
Synthetic data generators used throughout the documentation and tests.
| get_data | Create a random example data set. |
| get_ivf_data | Synthetic data for the motherhood penalty IV application (IVF instrument). |
| get_bartik_data | Synthetic data for a Bartik (shift-share) IV application on immigration and wages. |
| get_encouragement_data | Synthetic data for an A/B encouragement design IV application. |
| get_twin_data | Generate twin study data for returns to education. |
| get_worker_panel | Generate a worker-firm panel dataset with two-way fixed effects. |
| get_motherhood_event_study_data | Generate a fertility-timing panel for motherhood-penalty event studies. |
Formula Parsing & Model Matrix
Internal APIs for formula parsing and model matrix construction.
| Formula | A formulaic-compliant formula. |
| ModelMatrix | A wrapper around formulaic.ModelMatrix for the specification of PyFixest models. |
| factor_interaction | Fixest-style i() operator for categorical encoding with interactions. |
Demeaning
Fixed-effects demeaning: the demean() workhorse and the configurable backends. See the Choosing a Demeaner Backend guide for how to pick one.
| demean | Demean an array. |
| BaseDemeaner | Base configuration shared by all fixed-effects demeaners. |
| MapDemeaner | Method of Alternating Projections (MAP) demeaner. |
| LsmrDemeaner | Sparse LSMR demeaner. |
| Preconditioner |
Misc / Utilities
Other PyFixest internals and utilities.
| detect_singletons | Detect singleton fixed effects in a dataset. |
| ssc | Set the small sample correction factor applied in get_ssc(). |
| get_ssc | Compute small sample adjustment factors. |
| optimal_mixture_precision | Compute the mixture precision that minimizes SAVI sequence width |
| model_matrix_fixest | Create model matrices for fixed effects estimation. |