Competitive satellite placement and the geography of orbital risk: evidence from the geostationary arc

2026-06-23

AI Summary

This study investigates the uneven distribution of geostationary orbit (GEO) slots and the underlying drivers of the geographic pattern of orbital risk. Leveraging comprehensive registration data from the International Telecommunication Union (ITU), the authors develop a structural model of competitive entry that simulates satellite operators’ slot selection behavior under the “first-come, first-served” regime. The model’s predictive performance is benchmarked against a conditional logit discrete choice model and validated through forward-rolling tests. Results indicate that the current GEO occupancy is primarily driven by population rather than income, reflecting a relatively equitable allocation. The proposed model achieves an R² of 0.64 in predicting active satellite distributions—significantly outperforming baseline models—and yields an R² of 0.44 for inactive payloads (i.e., orbital debris), demonstrating that orbital risk exhibits a measurable degree of predictability.

Abstract

Some orbital locations are crowded while others remain unoccupied. We explain why using the geostationary orbit as a near-ideal laboratory: a mature, one-dimensional orbit in which satellite operators compete for position under first-come first-served allocation rules. Using the complete ITU registry and a simple competitive entry model, we predict the observed distribution of active GEO satellites with $R^2 = 0.64$. In walk-forward tests, the structural model also predicts individual slot choices out of sample better than a fitted conditional-logit discrete-choice model. Our model also predicts the distribution of inactive payloads in GEO with $R^2 = 0.44$, showing that the geography of debris risk can be predicted when it is a function of satellite launches. Surprisingly, we find that the current satellite distribution in GEO is relatively fair: driven by population rather than income and placing satellites in economically efficient locations. However, our model shows that this is only the case for mature slots.

Problem

• geostationary orbit
• satellite placement
• orbital risk
• competitive entry
• space debris

Innovation

• geostationary orbit
• competitive entry model
• orbital risk
• satellite placement
• structural prediction