Quantifying Roman economic performance by means of proxies : pitfalls and potential
Many histories of economic growth over the longue durée usually start around AD 1000, tracing a gradual growth in the early middle ages with the weakening of feudalism and the development of urbanism, markets and economic institutions. Long-run models and graphs of world economic performance tend to...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Book section |
| Published: |
Edipuglia
2014
|
| _version_ | 1797053749088223232 |
|---|---|
| author | Wilson, A |
| author2 | de Callataÿ, F |
| author_facet | de Callataÿ, F Wilson, A |
| author_sort | Wilson, A |
| collection | OXFORD |
| description | Many histories of economic growth over the longue durée usually start around AD 1000, tracing a gradual growth in the early middle ages with the weakening of feudalism and the development of urbanism, markets and economic institutions. Long-run models and graphs of world economic performance tend to retroject the period before this as a more or less steady state, contributing to a view in which economic progress in preindustrial societies is minimal or gradual, but without engaging with the possibility of either sustained growth or serious economic collapse. Building on recent work in archaeology and ancient history, however, we can extend the perspective back beyond the AD 1000 watershed, and open up some very different views. Increasingly, historians and archaeologists are attempting to grapple with these questions by using proxy data that may be thought to bear some relation to certain sectors of the economy, or to overall performance. Most of the proxies used have turned out to be problematic in one or another aspect, but this does not invalidate the exercise; probing the reasons for data bias leads to a better understanding of what the evidence actually does show. In this paper I examine criteria for proxy construction and presentation, to reduce the misleading effects of graphing often imprecise data. I examine a number of commonly used proxies (shipwrecks, stature, lead and copper pollution, animal bone consumption), looking at their strengths and weaknessess. I also present some early attempts at constructing new proxies, some of which might hold greater promise but which currently either suffer from small sample sizes (fish-salting capacity, water-mills) or regionally uneven collection policies (building inscriptions), neither of which is an insuperable problem. The different pictures presented by archaeological, literary and documentary data for the same phenomena are compared, and the importance of regional disaggregation stressed. Finally, the paper tackles attempts to compare the trends suggested by several proxies. |
| first_indexed | 2024-03-06T18:48:03Z |
| format | Book section |
| id | oxford-uuid:0f38ea6b-c273-42b1-b2fb-a21f2d95f94b |
| institution | University of Oxford |
| last_indexed | 2024-03-06T18:48:03Z |
| publishDate | 2014 |
| publisher | Edipuglia |
| record_format | dspace |
| spelling | oxford-uuid:0f38ea6b-c273-42b1-b2fb-a21f2d95f94b2022-03-26T09:50:04ZQuantifying Roman economic performance by means of proxies : pitfalls and potentialBook sectionhttp://purl.org/coar/resource_type/c_3248uuid:0f38ea6b-c273-42b1-b2fb-a21f2d95f94bSymplectic Elements at OxfordEdipuglia2014Wilson, Ade Callataÿ, FMany histories of economic growth over the longue durée usually start around AD 1000, tracing a gradual growth in the early middle ages with the weakening of feudalism and the development of urbanism, markets and economic institutions. Long-run models and graphs of world economic performance tend to retroject the period before this as a more or less steady state, contributing to a view in which economic progress in preindustrial societies is minimal or gradual, but without engaging with the possibility of either sustained growth or serious economic collapse. Building on recent work in archaeology and ancient history, however, we can extend the perspective back beyond the AD 1000 watershed, and open up some very different views. Increasingly, historians and archaeologists are attempting to grapple with these questions by using proxy data that may be thought to bear some relation to certain sectors of the economy, or to overall performance. Most of the proxies used have turned out to be problematic in one or another aspect, but this does not invalidate the exercise; probing the reasons for data bias leads to a better understanding of what the evidence actually does show. In this paper I examine criteria for proxy construction and presentation, to reduce the misleading effects of graphing often imprecise data. I examine a number of commonly used proxies (shipwrecks, stature, lead and copper pollution, animal bone consumption), looking at their strengths and weaknessess. I also present some early attempts at constructing new proxies, some of which might hold greater promise but which currently either suffer from small sample sizes (fish-salting capacity, water-mills) or regionally uneven collection policies (building inscriptions), neither of which is an insuperable problem. The different pictures presented by archaeological, literary and documentary data for the same phenomena are compared, and the importance of regional disaggregation stressed. Finally, the paper tackles attempts to compare the trends suggested by several proxies. |
| spellingShingle | Wilson, A Quantifying Roman economic performance by means of proxies : pitfalls and potential |
| title | Quantifying Roman economic performance by means of proxies : pitfalls and potential |
| title_full | Quantifying Roman economic performance by means of proxies : pitfalls and potential |
| title_fullStr | Quantifying Roman economic performance by means of proxies : pitfalls and potential |
| title_full_unstemmed | Quantifying Roman economic performance by means of proxies : pitfalls and potential |
| title_short | Quantifying Roman economic performance by means of proxies : pitfalls and potential |
| title_sort | quantifying roman economic performance by means of proxies pitfalls and potential |
| work_keys_str_mv | AT wilsona quantifyingromaneconomicperformancebymeansofproxiespitfallsandpotential |