The Economic Origins of Government: Allen, Bertazzini & Heldring (2023)

What this is. The paper’s core results, the natural experiment it exploits (river shifts in ancient southern Iraq), the identification strategy, and the main estimating equations: enough to know what it found and how, without reading all 39 pages. To replicate or extend it, read the full source at https://doi.org/10.1257/aer.20201919.

TL;DR

The paper uses river shifts in southern Mesopotamia around 2850BCE as a natural experiment to test two competing theories of government formation. When a river shifts away from a farming area, direct irrigation becomes impossible and public canals requiring multi-community coordination are needed. This creates demand for a coordinating government (cooperative theory), whereas an extraction-based theory (where government forms to collect surplus) predicts states would be more likely where the river stays. Constructing a new archeological panel dataset of 5x5 km grid cells across southern Iraq for the period 3900BCE-2700BCE, the paper runs a panel difference-in-differences design comparing grid cells that lost river access to control cells that did not. A river shifting away increased the probability of state formation by 14 percentage points, the probability of canal construction by 12 percentage points, the probability of tribute payment by 21 percentage points, and the number of administrative buildings by 0.44. The result is entirely driven by new state formation, not expansion of existing states. Text analysis of 5,885 surviving cuneiform tablets shows increased mentions of lineage-leader titles and tribute after the shift, consistent with the cooperative interpretation. Extractive theories of Olson (1993) and Carneiro (1970) predict the opposite sign, and the results reject them.

Core results

Magnitudes and standard errors are as reported; clustered SE in parentheses, Conley (1999) SE in brackets. Locators point into the source PDF (pp.2507-2545).

#	Result	Locator	Magnitude
R1	River shift away increases probability of state formation by 14pp	Table 3, col 1, p.2530	+0.14 (SE=0.04) [0.03]; sample mean 0.06; treatment-period mean 0.24; pretrend p=0.23
R2	Effect driven entirely by new state formation, not expansion of existing states	Table 3, col 3-4, p.2530	New state: +0.11 (SE=0.04) [0.03]; existing state: +0.02 (SE=0.02) [0.01]
R3	River shift increases probability of canal construction by 12pp	Table 4, col 1, p.2534	+0.12 (SE=0.03) [0.02]; mean 0.28; pretrend p=0.81
R4	River shift increases probability of defensive wall in nearest city by 11pp	Table 4, col 2, p.2534	+0.11 (SE=0.04) [0.03]; mean 0.14; pretrend p=0.57
R5	River shift doubles the probability of tribute payment being recorded	Table 4, col 3, p.2534	+0.21 (SE=0.06) [0.10]; mean 0.19; pretrend p=0.20
R6	River shift increases administrative buildings in nearest city by 0.44	Table 4, col 4, p.2534-2535	+0.44 (SE=0.15) [0.17]; mean 0.70; pretrend p=0.69
R7	Effect concentrated in high population density areas before the shift	Table 5, Panel A, p.2536	High: +0.18 (SE=0.05) [0.03]; low: +0.03 (SE=0.02) [0.03]; Chow p=0.06
R8	Result holds across the full 7,000-year panel (5000BCE-1950CE, all 6 river shifts)	Table 6, col 1, p.2539	Canal: +0.11 (SE=0.02) [0.02]; mean 0.40

Overall (paper’s conclusion, p.2540-2541). Where rivers shifted away, communities formed new states, built canals and defensive walls, and paid tribute to their governments. These results are consistent with cooperative (demand-side) theories: states form to solve coordination failures in public good provision, not to extract. The first states resembled scaled-up versions of the lineage social structure that preceded them, with government coordinating between extended kinship groups (lineages) rather than ruling over individuals.

Theory / model

The paper has no formal mathematical model. Instead it derives two competing sets of testable hypotheses from the theoretical literature on state formation and maps them onto the sign of the main difference-in-differences coefficient.

Cooperative (demand-side) theory. Government is an organization with a comparative advantage in providing public goods (Baumol 1952; Samuelson 1954). Problems of externalities and coordination failure (Olson 1965) prevent private provision. When a river shifts away, arid-land farming can continue only via public irrigation canals spanning multiple communities. No individual community can credibly commit to build and maintain such canals alone. This coordination failure creates demand for a government. Members pay tribute in exchange for canal access and defense. The framework builds on Acemoglu and Robinson (2000), who model the bargaining between social groups that determines whether and what form of government emerges. Under this view, states form where the river shifted away (positive $\beta_0^{\text{treatment}}$ in equation 1).

Extractive (supply-side) theory. Government is an organization founded by an elite with coercive power to manage extraction (Carneiro 1970; Olson 1993). Under Olson (1993), “roving bandits” settle where the expected tax base is largest and find it worthwhile to provide minimal stability in exchange for an extractive monopoly. Where a river shifts away, the agricultural tax base collapses: land is no longer productive without irrigation. A predatory ruler would prefer to locate where the river remains. Under this view, states form where rivers stay, not where they shift (negative or zero $\beta_0^{\text{treatment}}$). Mayshar, Moav, and Pascali (2022) provide recent empirical support for a related extractive channel in which taxable surplus (storable crops) predicts state location. The circumscription theory of Carneiro (1970) also fits this supply-side cluster: states arise where it is hard to escape extraction.

Empirical mapping. The sign of the main coefficient distinguishes the two clusters. A positive and significant $\beta_0^{\text{treatment}}$ (R1 = +0.14) is consistent only with cooperative theories, since extractive theories predict the opposite or no effect. The placebo test (estimating the effect of a river shifting closer rather than away) yields a consistently negative coefficient throughout the paper, confirming the cooperative interpretation. Sánchez De La Sierra (2020) finds extractive state formation in the Congo using a comparable natural-experiment design; the two settings differ in the nature of the shock and the role of public goods versus looting.

Method

The paper applies a standard panel difference-in-differences estimator via OLS, using the first large river shift in history (around 2850BCE) as a quasi-random shock. It builds on difference-in-differences and panel-regression.

Treatment definition. A 5x5 km grid cell $c$ is defined as on a river in period $t$ if its centroid is within 5 km of the nearest river. Cell $c$ is treated in period $t = 0$ (Early Dynastic I, 2900BCE-2700BCE) if it was on the river in period $t - 1$ (the Jemdet Nasr period, 3100BCE-2900BCE) and is no longer on a river in period $t$. Treatment is time-invariant and applies to roughly 13 percent of the 1,374 grid cells in the study area (Table 1, p.2517). Rivers shift by 30-40 km on average, so treated cells lose water access entirely, not marginally.

Main estimating equation. The panel DiD model for the main study period is (equation 1, p.2525):

$$Y_{ct} = \sum_{k=-4}^{0} \beta_k^{\text{treatment}} \times \mathbf{1}\{\text{period}_k\} \times \text{treated}_c + \rho_c + \gamma_t + v_{ct} + \varepsilon_{ct} \tag{1}$$

where $Y_{ct}$ is the outcome for grid cell $c$ in period $t$; $\text{treated}_c$ equals 1 if cell $c$ loses river access at $k = 0$; $\mathbf{1}\{\text{period}_k\}$ are indicators for each period $k$ relative to treatment; $\beta_k^{\text{treatment}}$ are the period-relative-to-treatment interaction coefficients (normalized to zero at $k = -1$, the last pre-period); $\rho_c$ are unit (grid cell) fixed effects; $\gamma_t$ are period fixed effects; $v_{ct}$ is a vector of period fixed effects interacted with time-invariant covariates (survey area indicators, average rainfall, average temperature, pre-shift urban status); and $\varepsilon_{ct}$ is clustered at the grid cell level. Conley (1999) standard errors with a 484 km spatial cutoff are reported in parallel.

The coefficient of interest is $\beta_0^{\text{treatment}}$: the treatment effect in the Early Dynastic I period (the period of first state formation). Pre-period coefficients $\beta_{-2}^{\text{treatment}}, \ldots, \beta_{-4}^{\text{treatment}}$ serve as pretrend tests; all are indistinguishable from zero (pretrend p-values reported in Tables 3-4, pp.2530, 2534).

Extended panel estimator. For all six river shifts across the full 7,000-year panel (5000BCE-1950CE), a pooled DiD (equation 2, p.2538) is estimated:

$$Y_{ct} = \beta \cdot \text{treated}_{ct} + \rho_c + \gamma_t + v_{ct} + \varepsilon_{ct} \tag{2}$$

where $\text{treated}_{ct}$ is now time-varying (equals 1 when cell $c$ is treated in period $t$ for any of the six shifts), and $\beta$ captures the average effect across all shifts.

Empirical specifications

All regressions are OLS. Unit of observation: 5x5 km grid cell. Time series: archeological period (average 240 years in the main sample). Standard errors clustered at the grid cell level; Conley (1999) SE with a 484 km cutoff in brackets.

State formation (R1-R2, Table 3, p.2530). Equation (1) with two outcome definitions: column 1 uses an indicator for whether a grid cell is part of a city state, defined using administrative buildings (palaces, temples, ziggurats) and reconstructed territorial borders; column 2 uses only building presence without borders. Columns 3 and 4 decompose into new state formation (an indicator equal to 1 if the nearest city gains state status for the first time) and expansion of an existing state. All columns include grid cell and period fixed effects plus the four time-invariant covariate interactions. Pretrend p-values (0.23 and 0.24) confirm no differential pre-trends.

Public good provision and tribute (R3-R6, Table 4, p.2534). Four separate regressions using equation (1):

• Column 1: indicator for canal presence within 5 km of cell centroid, reconstructed from Chicago Oriental Institute excavation reports (Adams 1965, 1981; Adams and Nissen 1972).
• Column 2: indicator for defensive wall in the nearest city, from Bryce (2009) and Meyers (1997).
• Column 3: indicator for surviving cuneiform tablet in the nearest city (validated as a proxy for tribute payment and redistribution via keyword analysis of transliterated texts; Table RA29 in Results Appendix).
• Column 4: total count of palaces + temples + ziggurats in the nearest city (measure of state capacity and administrative infrastructure).

Heterogeneous effects (R7, Table 5, p.2536). Equation (1) estimated separately in two subsamples split by the median of the spatial lag of pre-treatment settlement density (a proxy for returns to coordination). The Chow test for coefficient equality has p-value 0.06. A second split by geographic costs (FAO potential productivity differential between irrigated and rainfed barley, and river water flow volume) yields similar heterogeneity.

Extended panel (R8, Table 6, p.2539). Equation (2) estimated on 27,106 grid cell-period observations across all 31 archeological periods (5000BCE-1950CE). Columns 2-3 split the sample into the first two river shifts (pre-state and state formation) and the four subsequent shifts (within established states). The effect is positive and similar in both sub-panels.

Datasets used

Dataset	Role in paper	Wiki page
Chicago Oriental Institute archeological surveys (Adams 1965, 1981; Adams and Nissen 1972)	Settlement history, canal network reconstruction, and city locations; basis for the 5x5 km grid panel covering 5000BCE-1950CE	No page yet
Cuneiform Digital Library Initiative (CDLI)	5,885 transliterated cuneiform tablets from the main study period; text analysis of tribute, canal, and lineage-leader term mentions (Section VII, Figure 6)	No page yet
Administrative building and state border data (Heinrich 1982, 1984; Meyers 1997; Bryce 2009)	Identification of palaces, temples, and ziggurats; reconstruction of state territorial borders	No page yet
River shift and course reconstructions (Cole and Gasche 1998)	Geographic reconstruction of river courses before and after each of six shifts; defines the treatment variable	No page yet
FAO soil and agricultural potential data	Potential productivity of irrigated vs. rainfed barley cultivation; used for geographic heterogeneity subsamples (Table 5, Panel B, p.2536)	No page yet

Sample: southern Iraq, 1,374 grid cells of 5x5 km covering the area between Baghdad and Basra. Main study: 3900BCE-2700BCE, five archeological periods (~240 yrs each). Extended study: 5000BCE-1950CE, 31 periods. The replication dataset (including all constructed variables) is publicly available at https://doi.org/10.3886/184167EV1.

When to read the full paper

Use the original paper if you are: testing theories of state formation in other historical or contemporary settings, where the identification approach (demand-side shock to coordination costs) can be adapted (Section IV); studying public good provision and tribute across the full 7,000-year Iraqi panel, including under the Babylonian and Assyrian empires (Section VI and Table 6); examining the internal organization of the first states via cuneiform tablet text analysis (Section VII and Figure 6, p.2541); or extending the dataset to other archeological outcome variables using the replication data. The online Data Appendix (68 pages) describes dataset construction, coding procedures, and robustness exercises in full detail.

Attribution and rights

Source: peer-reviewed, American Economic Review 113(10), October 2023. Freely available on the AEA website; no CC licence detected in Crossref metadata; redistribution is extract-only. This distillation was extracted by an LLM on 2026-06-24 and is not human-verified or independently reproduced.

Allen, Robert C., Mattia C. Bertazzini, and Leander Heldring. “The Economic Origins of Government.” American Economic Review 113, no. 10 (October 2023): 2507-2545. DOI: 10.1257/aer.20201919.