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Consumption patterns in prehistoric Europe are consistent with modern economic behaviour

Nature Human Behaviour (2024)Cite this article

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Abstract

Have humans always sold and purchased things? This seemingly trivial question exposes one of the most conspicuous blind spots in our understanding of cultural evolution: the emergence of what we perceive today as ‘modern’ economic behaviour. Here we test the hypothesis that consumption patterns in prehistoric Europe (around 2300–800 bce) can be explained by standard economic theory, predicting that everyday expenses are log-normally distributed and correlated to supply, demand and income. On the basis of a large database of metal objects spanning northern and southern Europe (n = 23,711), we identify metal fragments as money, address them as proxies of consumption and observe that, starting around 1500 bce, their mass values become log-normally distributed. We simulate two alternative scenarios and show that: (1) random behaviour cannot produce the distributions observed in the archaeological data and (2) modern economic behaviour provides the best-fitting model for prehistoric consumption.

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Fig. 1: Chronological framework.
Fig. 2: The scrap hoard of Weißig (Germany).
Fig. 3: Spatial analysis.
Fig. 4: Quantal analysis.
Fig. 5: Probability distribution of the mass values of metal objects.
Fig. 6: Simulation scenario 1 with random fragmentation.
Fig. 7: Graphical model of simulation scenario 2 with monetary fragmentation.

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Data availability

All data supporting the findings of this study are available within the paper and its Supplementary Information.

Code availability

Custom code that supports the findings of this study is available within the paper and its Supplementary Information and publicly available via Zenodo at https://zenodo.org/doi/10.5281/zenodo.10959515 (ref. 65), under license CC BY-NC 4.0.

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Acknowledgements

We wish to thank Eleonore Pape, Elise Pape, N. Pape and D. Berger for their comments and advice on earlier versions of this work. The authors received no specific funding for this work.

Author information

Authors and Affiliations

  1. Seminar für Ur- und Frühgeschichte, Georg-August-Universität Göttingen, Göttingen, Germany

    Nicola Ialongo

  2. Department of Archeology and Heritage Studies, Aarhus University, Aarhus, Denmark

    Nicola Ialongo

  3. Dipartimento di Beni Culturali, Università del Salento, Lecce, Italy

    Giancarlo Lago

  4. Department of Economics, University of Bologna, Bologna, Italy

    Giancarlo Lago

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  1. Nicola Ialongo
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N.I. designed the research, performed data analysis and wrote the article. G.L. performed data analysis, wrote the article and created the code.

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Correspondence to Nicola Ialongo.

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Extended data

Extended Data Fig. 1 Orders of magnitude.

The boxplots show the distribution of the mass values balance weights pertaining to the shekel- and the mina-range, compared to the distribution of metal fragments and complete objects. Dotted lines indicate the approximate value of the weight units. Solid lines indicate the boundaries of the CQA sampling (7-200 g). Shekel: n = 244, min.=0.16 g, max.=469.41 g, centre=9,.77 g, box bottom=4.08 g, box top=32.01 g, whisker bottom=0.16 g, whisker top=100.00 g. Fragments: n = 6,881, min.=0.01 g, max.=9,220 g, centre=26.00 g, box bottom=7.90 g, box top=82.00 g, whisker bottom=2.70 g, whisker top=233.00 g. Complete: n = 6,746, min.=0.27 g, max.=8,750 g, centre=181.00 g, box bottom=375.27 g, box top=210.00 g, whisker bottom=31.30 g, whisker top=340.00 g. Mina: n = 367, min.=11.8 g, max.=5,050 g, centre=592.00 g, box bottom=375.27 g, box top=908.30 g, whisker bottom=235.20 g, whisker top=998.36 g. Outliers method: 1.5*Interquartile range. Graph made with Wavemetrics Igor Pro 6.05.0.

Extended Data Fig. 2 CQA, diachronic results.

Dotted lines represent the raw output of the quantal analysis. Solid lines represent the same output after smoothing. We indicate the number of measurements sub-sampled in each quantogram, and in parentheses the total sample size.

Extended Data Fig. 3 Monte Carlo Simulation.

CQA of the sample of bronze fragments of Phases 2-3 compared to the CQA results for balance weights. Left Y axis: balance weights. Right Y axis: bronze fragments. The horizontal dashed line represents the 5% significance level for the Monte Carlo simulation (ϕ(q)=7.35), lower than the peak value of bronze fragments (ϕ(q)=7.77).

Extended Data Fig. 4 Binned Frequency Distribution Analysis of metal fragments.

Bin size=1.11 g. The dots overlaid on the histograms represent multiples of 10 g (that is, the approximate value of the Pan-European shekel); the boundaries represent a CV = 5% at 1 SD. The dots’ Y values are arbitrarily placed for visual clarity. Above: Phase 1 (n = 397). Below: Phase 2 (n = 3,339) and 3 (n = 3,145).

Extended Data Fig. 5 Binned Frequency Distribution Analysis of complete metal objects.

Bin size=11.1 g. The dots overlaid on the histograms represent multiples of the theoretical value of Pan-European shekel of 10 g; the whiskers represent CV = 5% of each of these multiples at 1 SD. The dots’ Y values are arbitrarily offset, in order to avoid visual confusion generated by the overlapping error margins. Above: Phase 1 (n = 4,558). Below: Phase 2 (n = 1,075) and 3 (n = 1,113).

Extended Data Fig. 6 One-sample Kolmogorov Smirnov test for normality (two-sided).

The graphs compare the Cumulative Distribution Functions (CDF) of archaeological datasets and normal distributions. The p-values and test statistic D of each test are shown on the graphs.

Extended Data Fig. 7 Simulation scenario 2: Monetary fragmentation.

Green area: CI = 95% of the simulated results (DDF and Q-Q plots). Green line: mean values of the simulated results (DDF and Q-Q plots). Orange lines: KDE of the distribution of metal fragments. Orange dots: Q-Q plots of the distribution of metal fragments.

Extended Data Table 1 Results of the bootstrapped two-sample Kolmogorov-Smirnov test (two-sided)
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Supplementary information

Reporting Summary

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Supplementary Data 1

Database of the metal objects from Bronze Age hoards considered in this study.

Supplementary Data 2

Database of Bronze Age balance weights.

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Ialongo, N., Lago, G. Consumption patterns in prehistoric Europe are consistent with modern economic behaviour. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-01926-4

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