Three Centuries of Luxury Textile Consumption in the Low Countries and England, 1330 - 1570: New Methodologies for Estimating Changes in Real Values
Bibliographic record
Abstract
This study is a much revised and extended version of two previously issued working papers on the production, sale, and consumption of woollen textiles in England and the Low Countries, from the fourteenth to the sixteenth centuries. It focuses on the hey-day of the production and international trade in heavy-weight, very high quality, luxury woollen broadcloths (Flemish and English), during these three centuries. From the 1290s to the 1460s, as I have argued in earlier publications, the consequences of widespread international warfare, and the consequent dislocations to major trading routes, the sharp rise in transportation and transaction costs, and taxation, combined with disruptive coinage debasements and various trade barriers, and drastic declines in population (from plagues and warfare) produced major transformations in the international trade and production of textiles: a relative shift from cheaper line textiles (whose producers were price-takers) to very high priced luxury textiles – silks and woollens (whose producers were price-makers). Table 1 provides the wool compositions, dimensions, and weights of the various textiles. The major concern of this study is to estimate changes in the ‘real’ value of luxury woollen over these three centuries, especially for the longest price series: for the Ghent dickedinnen broadcloths, from the 1330s to the 1570s. The available price data are, of course, in current money-of-account: the pond groot of Flanders. Because of the chronic coinage debasement that afflicted this era, we cannot use current prices. Thus, for example, in the two centuries from 1350 to 1550, the quantity of fine silver in the Flemish penny or groot was reduced, in both fineness and weight, from 2.067 grams to 0.474 g – an overall reduction of 77.1 percent; and by 1580, that quantity had fallen to just 0.300 g. Most historians have sought a false remedy for this problem of coinage debasement: to estimate ‘real’ prices in terms of ‘silver equivalents’, i.e., the quantity of fine silver represented in the current circulating silver penny and thus in the penny (1d) of the money-of-account. Why this method is fallacious (in several respects) is a major aspect of this paper. Instead, three alternative methods of estimating real values over time have been utilized. The first is a method similar to the common calculation of real wages (NWI/CPI = RWI): that is, using a common base period of 1451-75 for all prices, I have calculated price indexes for all the textiles (Flemish and English) in this study; and I have then divided that index by the Consumer Price Indexes for Flanders, Brabant, and England (Table 18). If the textile price index rose more than did the CPI, its real value had also risen. The second and related method does not involve index numbers, but a comparison of the market values of the three ‘baskets of consumables’ with those of the textiles: the number of such ‘baskets of consumables’ whose market value equalled the value of each of the luxury woollen broadcloths under consideration, over these three centuries. The third method involves the purchasing power of labour: using my own tabulations of daily money wages for master masons and carpenters in the leading towns of Flanders, Brabant, and England, over these centuries, I have calculated the number of days’ wages that a master mason would have required to buy a unit of these textiles, over these three centuries. For any short period, such as that given in Table 2 (1535-44), comparing values of woollens and worsteds, all three methods provide the same results. But over the longue durée of this study, from the 1330s to the 1570s, these methods often produce differing results: for sometimes the real values of these textiles in terms of masons’ wages rose, while their values in terms of commodity baskets fell. The explanation for such a divergence is that the MRP of labour and the purchasing power of masons’s wages did not change in accordances with changes in the real values of the commodities in the ‘baskets of consumables’. The study ends by demonstrating the enormous differences in the purchasing power of modern-day building craftsmen with that of sixteenth-century craftsmen – and the sharp fall in the percentage shares of textiles and foodstuffs in the consumer price indexes, then and now (i.e., in Canada, in 2008).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".