arXiv 27 Oct 2025 · Econometrics
arXiv:2510.22884 · PDF · Extracted main text
This paper studies a class of models for two-sided interactions, where outcomes depend on latent characteristics of two distinct agent types. Models in this class have two core elements: the matching network, which records which agent pairs interact, and the interaction function, which maps latent characteristics of these agents to outcomes and determines the role of complementarities. I introduce the Tukey model, which captures complementarities with a single interaction parameter, along with two extensions that allow richer complementarity patterns. First, I establish an identification trade-off between the flexibility of the interaction function and the density of the matching network: the Tukey model is identified under mild conditions, whereas the more flexible extensions require dense networks that are rarely observed in applications. Second, I propose a cycle-based estimator for the Tukey interaction parameter and show that it is consistent and asymptotically normal even when the network is sparse. Third, I use its asymptotic distribution to construct a formal test of no complementarities. Finally, an empirical illustration shows that the Tukey model recovers economically meaningful complementarities.
appendix boundary found by appendix_command · 66% of the source is main text. Read the extracted text to check this.
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 | Card, D., J. Heining, and P. Kline (2013) Workplace heterogeneity and the rise of West German wage inequality | 1.000 | 7 | 4 | 100% |
| 2 | Kline, P (2024) Firm wage effects | 1.000 | 7 | 3 | 100% |
| 3 | Bonhomme, S., T. Lamadon, and E. Manresa (2019) A distributional framework for matched employer employee data | 1.000 | 6 | 3 | 100% |
| 4 | Tukey, J. W (1949) One degree of freedom for non-additivity | 1.000 | 5 | 3 | 100% |
| 5 | Limodio, N (2021) Bureaucrat allocation in the public sector: Evidence from the world bank | 0.874 | 9 | 2 | 100% |
| 6 | Abowd, J. M., F. Kramarz, and D. N. Margolis (1999) High Wage Workers and High Wage Firms | 0.874 | 6 | 2 | 100% |
| 7 | Jochmans, K. and M. Weidner (2019) Fixed-effect regressions on network data | 0.843 | 3 | 3 | 100% |
| 8 | Fenizia, A (2022) Managers and productivity in the public sector | 0.811 | 4 | 2 | 100% |
| 9 | Kline, P., R. Saggio, and M. Slvsten (2020) Leave-out estimation of variance components | 0.737 | 3 | 3 | 67% |
| 10 | Bai, J (2009) Panel data models with interactive fixed effects | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 54 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 1 Linear Regression with Centrality Measures | 0.644 | 2 | 2 |