arXiv 21 Jul 2023 · Econometrics · publishedRevue économique (2024)
arXiv:2307.11484 · PDF · DOI · OpenAlex · Extracted main text
Economic interactions often occur in networks where heterogeneous agents (such as workers or firms) sort and produce. However, most existing estimation approaches either require the network to be dense, which is at odds with many empirical networks, or they require restricting the form of heterogeneity and the network formation process. We show how the functional differencing approach introduced by Bonhomme (2012) in the context of panel data, can be applied in network settings to derive moment restrictions on model parameters and average effects. Those restrictions are valid irrespective of the form of heterogeneity, and they hold in both dense and sparse networks. We illustrate the analysis with linear and nonlinear models of matched employer-employee data, in the spirit of the model introduced by Abowd, Kramarz, and Margolis (1999).
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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 | Graham (2017) An econometric model of network formation with degree heterogeneity | 1.000 | 9 | 5 | 100% |
| 2 | Abowd, Kramarz, and Margolis (1999) High wage workers and high wage firms | 1.000 | 8 | 5 | 100% |
| 3 | Bonhomme (2012) Functional differencing self | 1.000 | 7 | 4 | 100% |
| 4 | Andrews, Gill, Schank, and Upward (2008) High wage workers and low wage firms: negative assortative matching or limited mobility bias? | 0.928 | 4 | 3 | 100% |
| 5 | Dobronyi, Gu, and Kim (2021) Identification of dynamic panel logit models with fixed effects | 0.928 | 4 | 3 | 100% |
| 6 | Lentz, Piyapromdee, and Robin (2022) The Anatomy of Sorting-Evidence from Danish Data | 0.874 | 5 | 2 | 100% |
| 7 | Bonhomme, Lamadon, and Manresa (2019) A distributional framework for matched employer employee data | 0.811 | 4 | 2 | 100% |
| 8 | Bonhomme, Holzheu, Lamadon, Manresa, Mogstad, and Setzler (2023) How much should we trust estimates of firm effects and worker sorting? | 0.737 | 3 | 2 | 100% |
| 9 | Chernozhukov, Fernández-Val, Hahn, and Newey (2013) Average and quantile effects in nonseparable panel models | 0.737 | 3 | 2 | 100% |
| 10 | Kline, Saggio, and Slvsten (2020) Leave-out estimation of variance components | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 51 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Debiased Machine Learning for Unobserved Heterogeneity: High-Dimensional Panels and Measurement Error Models | 0.511 | 2 | 1 |
| 2 | Triadic Network Formation | 0.405 | 1 | 1 |
| 3 | Tractable Identification of Strategic Network Formation Models with Unobserved Heterogeneity | 0.405 | 1 | 1 |