CrisisDB Explorer
Exploring power transitions and elite dynamics using the Crisis Database
What is this?
This is an interactive exploration of the CrisisDB Power Transitions dataset, testing predictions from Peter Turchin's Structural Demographic Theory (SDT).
SDT predicts that institutional complexity (measured by administrative levels) leads to elite overproduction—more elite positions mean more competition, which manifests as intra-elite conflict during power transitions.
Data: 3,447 power transitions from 264 polities, merged with Seshat complexity metrics. This is a subset of the full CrisisDB.
Explore the Patterns
What do polities at different complexity levels typically experience? Configure parameters and explore historical patterns from 3,447 observed transitions.
Configure Polity Profile
Using observed Markov transition rates
Compare to Real Polity
Historical Patterns at Complexity 5
Based on 25 polities, 352 transitions
Simulation
Click "Simulate" to see one possible trajectory based on historical rates
Detailed Findings
1. Elite Overproduction
Does administrative complexity predict intra-elite conflict? Testing Turchin's core hypothesis.
Elite Overproduction: Complexity → Conflict
Administrative levels vs intra-elite conflict rate
2. Violence Contagion
Is violence "sticky"? Does a violent transition increase the probability of subsequent violence?
Violence Contagion
Markov transition dynamics: violence is "sticky"
Transition Matrix
| → Peaceful | → Violent | |
|---|---|---|
| Peaceful | 78% | 22% |
| Violent | 40% | 60% |
Convergence to Equilibrium
The system spends ~36% of time in violent states at equilibrium.
3. Ruler Tenure
Do violent usurpers reign shorter? Testing instability cascades at the individual level.
Ruler Tenure: Survival by Accession Type
Does violent accession predict shorter reigns?
Which Violence Types Shorten Reigns Most?
Military revolts have the strongest effect: usurpers who seize power via coup reign 4 years shorter on average.
Violence Begets Violence
Rulers who seized power violently are 2.5x more likely to be removed violently. Chi-square p < 0.0001.
4. Transitions Over Time
When and where do power transitions cluster? Explore the temporal distribution.
Power Transitions Over Time
1,862 transitions from -500 to 1500
5. Notable Patterns
Outliers and trajectories that complicate—or illuminate—the complexity-conflict relationship.
Complexity Without Conflict
Venice (admin=6, conflict=0-5%), Egypt Old Kingdom (admin=6, conflict=0%), and Northern Song (admin=7, conflict=11%) maintained complex bureaucracies with remarkably low intra-elite violence during transitions.
Suggests strong succession institutions can buffer elite competition.
The Aztec Paradox
Aztec Empire (admin=6, conflict=0%, n=7) shows zero intra-elite conflict despite their reputation for ritualized violence and warfare.
Key distinction: "intra-elite conflict" here measures violence during power transitions, not general societal violence. Aztec succession was highly ritualized—external violence (sacrifice, warfare) didn't translate to contested successions.
Byzantine Degradation
Conflict rates escalate across Byzantine phases: I (56%) → II (50%) → III (100%). The late Byzantine Empire saw every single power transition turn violent.
Consistent with SDT: declining resources + persistent elite expectations = intensified competition.
Mamluk Escalation
Similar pattern in Mamluk Egypt: I (68%) → II (73%) → III (80%). Military slave systems may have structural instability in succession.
Highest sustained conflict rates in the dataset.
Methodology & Limitations
Data Sources
- CrisisDB: Power transitions with mechanism coding (P/IP/A/IA)
- Seshat Equinox 2022: Administrative levels and complexity metrics
- Merged on polity name (n = 87 with ≥5 transitions)
Limitations
- Partial CrisisDB subset (power_transitions.csv only)
- Correlation does not imply causation
- Selection bias toward well-documented polities
- Merging introduces data loss
Source Quality
Some polities (Aztec Empire, Egyptian Old Kingdom) have sparse documentary records. Apparent low conflict may reflect data gaps rather than actual peaceful transitions. Use the filter above to exclude these polities and verify that findings hold.
Feedback from CSH Vienna confirms that filtering does not change core findings.
Acknowledgments
This work builds on data and theory from Peter Turchin and the Complexity Science Hub Vienna. CrisisDB and Seshat are maintained by the Seshat: Global History Databank team.
Special thanks to the Seshat team for making historical data accessible for quantitative analysis.