Introduction | Why interactive fixed effects? | The IFE model | What xtife provides | Balanced Panel IFE | Data | Quick start | Estimation algorithm | Standard error types | Comparison with TWFE | Factor number selection | Asymptotic bias correction (balanced panel) | Static regressors — Bai (2009) | Dynamic regressors — Moon and Weidner (2017) | Unbalanced Panel IFE | Motivation | The unbalanced IFE model | Identification | Additive fixed effects via force | Quick start with unbalanced data | Outer alternating-maximisation (AM) loop | EM inner loop (Bai 2009, Appendix B) — used within each AM iteration | Initialisation | Analytical standard errors | Analytical bias correction | Strictly exogenous regressors (exog = "strict") | Weakly exogenous regressors (exog = "weak") | Balanced vs unbalanced on the same data | Input validation and common errors | Quick reference: argument tables | ife() — balanced panel | ife_unbalanced() — unbalanced panel | References
This package is considered a duplicate. The official version of this package is found at:https://rickchen0910.r-universe.dev/xtife
Package: xtife 0.1.4
Binzhi Chen
xtife: Interactive Fixed Effects Estimator for Panel Data
Implements the interactive fixed effects ('IFE') panel estimator of Bai (2009) <doi:10.3982/ECTA6135> for balanced and unbalanced panels, with optional additive unit and/or time fixed effects. Provides analytical standard errors ('homoskedastic', 'HC1' heteroskedasticity-robust, cluster-robust by unit, and heteroskedasticity- and autocorrelation- consistent), together with asymptotic incidental-parameter bias correction for large panels, including a dynamic extension for predetermined (lagged-dependent) regressors following Moon and Weidner (2017) <doi:10.1017/S0266466615000328>. The number of factors is chosen by information criteria (Bai and Ng 2002 <doi:10.1111/1468-0262.00273>) or by singular value thresholding. Unbalanced panels are handled by an expectation-maximisation algorithm with nuclear-norm-regularised initialisation, with estimation, analytical inference, and bias correction following Su, Wang and Wang (2025) <doi:10.2139/ssrn.5177283> and building on the matrix-completion and missing-data factor analysis of Bai and Ng (2021) <doi:10.1080/01621459.2021.1967163>. All computations use base R only, with no external dependencies.
Authors:
xtife_0.1.4.tar.gz
xtife_0.1.4.zip(r-4.7-any)
xtife_0.1.4.tar.gz(r-4.7-any)xtife_0.1.4.tar.gz(r-4.6-any)
xtife_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
xtife/json (API)
| # Install 'xtife' in R: |
| install.packages('xtife', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rickchen0910/xtife/issues
Datasets:
- cigar - Dataset on US Cigarette Demand Panel
Last updated from:e20022ec89. Checks:5 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 125 | ||
| source / vignettes | OK | 237 | ||
| linux-release-x86_64 | OK | 137 | ||
| windows-devel-x86_64 | OK | 96 | ||
| wasm-release | OK | 92 |
Exports:ifeife_select_rife_select_r_unbife_unbalanced
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Dataset on US Cigarette Demand Panel | cigar |
| Estimate Interactive Fixed Effects Model (Bai 2009) | ife |
| Select the Number of Factors via Information Criteria | ife_select_r |
| Factor Number Selection for Unbalanced Panel IFE via SVT | ife_select_r_unb |
| Unbalanced Panel Interactive Fixed Effects Estimator | ife_unbalanced |
| Print an IFE Model Summary | print.ife |