29th January 2016 meeting

Meeting Toflit18 – 29/01/2016

Attending :
Loïc Charles, Guillaume Daudin, Béatrice Dedinger, Federico D’Onofrio, Paul Girard, Jérôme Hericourt, Emmanuelle Lavallée, Ivan Ledezma, Guillaume Plique, Samuel Sanchez, Grégory Tible, Elisa Tirindelli

1 – Discussion around RICardo

2 – Back to Manylines

3 – New data exploration tools for Toflit (with,380 000 trade flows and 44,000 different goods and a number of different partners)
There are for the time being 4 ways to get into the data in the tool.
* Classification
This is where one can treat the multiplicity of names in the data. For each case (goods and parters for the time being), there are at least three steps : orthographic normalisation // simplification (with no loss of information) // categorization (with some information loss)
How to update a classification ?
– Choose one (e.g. simplification)
– Export it in csv
– Open with LibreOffice (UTF-8)
– Modify the three-column file (last 2 columns)
– Import the csv
– This generates an «import report» about the links with the further classifications (e.g. changing «simplification» will have an effect on «categorization»

Issues
– Shall we do a versioning ?
– How to treat the «import report» ?

* Metadata
This is where one can see the available flows in the data
One can select the type of breakdown (in addition to year) : (direction, source, goods/partner classificatons, goods/partner simplication, grouping (product ou country)).
This yields 2 graphs :
Number of different groups per year
Number of flows per year

* Indicators
This is where one can see graphs with time series
On can make a selection according to :
– Source Type
– Product
– Country
– Direction
– Kind (import, export, total)

Two curves are created :
– Number of flows by year
– Sum of value by year

There can be up to 6 choices.
For the time being, it is a bit slow, but results are put in a cache to be reused easily

* Globals
This is were on can visualize graphs. The only one available is between directions and partners. The algorithms clusterizes geographical areas.
Latter in the meeting, we realize that it would be useful to be able to link goods and directions and not only partners and directions.
It would be nice also if a term network could be included.

4 – Paper presentations
4.1 Elisa on the analysis of bilateral trade flows between France and Hamburg between 1750-1789

Elisa Presentation_29 01 2016
French dataset (in 2014) : 3407 flows aggregate flows (Hamburg is often included in the North)
German dataset 1609 export flows between 1733-1798
Issues with both datasets : various units of measurement (even for the values) // linking products (changing named) // difficulty with prices and conversion rates
Solutions : work on common years / only on exports
The work that has been done : corrélation of the data in both sources. The correlation is rather strong (0.93 for the evolution of total flows, 0.98 for the breakdown by big sectors, 0.81 for the breakdown by products.

New exploration tools : linear regression and testing the Benford’s law
New questions on exogenous shocks : Seven year war, American revolution war, Interruption of commerce between France and Hamburg (1761-1769), trade liberalisation 1780.
To sum up : how reliable is the data ? What is the effect of wars ? What is the effect of treaties ?

There is a discussion on the share of Hamburg in the North and the importance of discrepancies in Hamburg.

4.2 Federico on Grain trade 1725-1821

Federico Presentation_29 01 2016
Only 6000 trade flows, broken down in 5 categories : Froment / other grains / third class grains / panifiable / transformed goods.
Directions : 6 directions with between 200 and 300 flows in each (only maritime)
Origins : Italie and the Baltic
Exports : colonies, Espagne, Italie, Nord…

Time series :  : the food crisis are very apparent (70-71/89/1817)

Extending the national series: repeated sale method
Distribution of grain trade :  Marseilles is the main export port by a large margin.

Links between the grain trade and population growth ? Role of riots ? The strongest correlation is between riots and t-1 exports. Is that because exports are in the summer and riots in the next spring ? Or because past exports stoke the fear for new permits ?

Projects : look at the geography of trade through GIS ? look at networks ? look at DEMETO models : demography and climate ? Thinking of co-occurences leads us to suggest that in the global view one should be able to link goods and directions and not only partners and directions.

4.3 Ivan and Emmanuelle on international production network in the 18th century Evidence from the French data (abstract)

The breakdown of the value added chain is not a 20th century innovation. They look at the sugar network. French per capita consumption is only 1/10th of English one.
The study of this international value-added chain is interesting. Especially the movement of the location of sugar transformation (which is a high VA activity).
One way to look at it is too look at the words associated with sugar.

The next meeting is at 9.30 of February 19th at the médialab.


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