Claudia Pigini, Alessandro Pionati, Francesco Valentini
arXiv 10 Feb 2025 · Econometrics
arXiv:2502.06446 · PDF · DOI · OpenAlex · Extracted main text
We study the application of the Grouped Fixed Effects (GFE) estimator (Bonhomme et al., ECMTA 90(2):625-643, 2022) to binary choice models for network and panel data. This approach discretizes unobserved heterogeneity via k-means clustering and performs maximum likelihood estimation, reducing the number of fixed effects in finite samples. This regularization helps analyze small/sparse networks and rare events by mitigating complete separation, which can lead to data loss. We focus on dynamic models with few state transitions and network formation models for sparse networks. The effectiveness of this method is demonstrated through simulations and real data applications.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Dhaene, Geert and Jochmans, Koen Split-panel jackknife estimation of fixed-effect models | 1.000 | 14 | 4 | 100% |
| 2 | Bonhomme, Stéphane and Lamadon, Thibaut and Manresa, Elena (2022) Discretizing unobserved heterogeneity | 1.000 | 14 | 3 | 100% |
| 3 | Fernández-Val, Iván (2009) Fixed effects estimation of structural parameters and marginal effects in panel probit models | 0.969 | 11 | 5 | 91% |
| 4 | Hahn, Jinyong and Kuersteiner, Guido (2011) Bias reduction for dynamic nonlinear panel models with fixed effects | 0.737 | 3 | 2 | 100% |
| 5 | Laeven, Mr Luc and Valencia, Mr Fabian (2018) Systemic banking crises revisited | 0.737 | 3 | 2 | 100% |
| 6 | Pigini, Claudia (2021) Penalized maximum likelihood estimation of logit-based early warning systems self | 0.644 | 2 | 2 | 100% |
| 7 | Bonhomme, Stéphane and Lamadon, Thibaut and Manresa, Elena (2022) Supplement to “Discretizing unobserved heterogeneity” | 0.585 | 3 | 1 | 100% |
| 8 | Cook, Scott J and Hays, Jude C and Franzese, Robert J (2018) Fixed effects in rare events data: A penalized maximum likelihood solution | 0.511 | 2 | 1 | 100% |
| 9 | Firth, David (1993) Bias reduction of maximum likelihood estimates | 0.511 | 2 | 1 | 100% |
| 10 | Kunz, Johannes S and Staub, Kevin E and Winkelmann, Rainer (2021) Predicting individual effects in fixed effects panel probit models | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 37 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Estimating Long Run Welfare Outcome in Rotating Panel with Grouped Fixed Effects: Application to Poverty Dynamics in Peru | 0.405 | 1 | 1 |