I always admired the work of Francois Quesnay (Tableau Economique). It is an early (18th C / 1758) precursor to input output analysis. It is also connected to the modern work of Walter Isard (inter-regional input output models) and to the classical economics / Marx inspired "production of commodities in terms of commodities." (Sraffa). Modern economic geographers (Michael Webber and David Rigby) have also explored the theoretical connections. [The Golden Age Illusion: Rethinking Postwar Capitalism by Michael J. Webber; David L. Rigby]. Surely another ill-fated example is the attempt at Soviet style central planning -- notorious for making too many of the wrong items, due to lack of market driven price signals. So we come back to the market and big data efforts of retailers like Walmart who have long explored patterns with terabytes of data.

Until your nice question / comment I had not really joined these ideas to connect to big data, but you are correct -- there is a nice lineage. At least I think so!

What is significant about the Physiocratic system is how the flows between sectors—manufacturing, agricultural, and artisan lead to equilibrium. We must be mindful also that the surplus arise from nature and not entrepreneurial risks. While big data sets are possible for the sectors, there appears to be some fuzziness about the cross flows. Also, advances do not necessarily initiate from the agricultural sector in a modern economy. I recall that input-output was tried on a small scale data set but structural relationships were imposed on an a priori bases. Hopefully we can extend such analysis to big data sets.

I always admired the work of Francois Quesnay (Tableau Economique). It is an early (18th C / 1758) precursor to input output analysis. It is also connected to the modern work of Walter Isard (inter-regional input output models) and to the classical economics / Marx inspired "production of commodities in terms of commodities." (Sraffa). Modern economic geographers (Michael Webber and David Rigby) have also explored the theoretical connections. [The Golden Age Illusion: Rethinking Postwar Capitalism by Michael J. Webber; David L. Rigby]. Surely another ill-fated example is the attempt at Soviet style central planning -- notorious for making too many of the wrong items, due to lack of market driven price signals. So we come back to the market and big data efforts of retailers like Walmart who have long explored patterns with terabytes of data.

Until your nice question / comment I had not really joined these ideas to connect to big data, but you are correct -- there is a nice lineage. At least I think so!

HI, if my memory is all right, I saw your previous question and answer on cities. I cannot see that discussion anymore. Do you know why? Thanks.

Hi Bin Jiang,

Can you give me some idea which particular one so I can sort it out for you?

Cheers,

Bernard

Dear Bernard, You asked something about relationship between cities and countries, and I answered by referring to my notion of natural cities. That is all that I remember now. Any hints? Thanks.

I am no expert on Physiocratic economics but if if you think of land as a resource owned by the "proprietary class" and that "productive class" are the workers that turned this land into food that could be sold for for a profit then it isn't much of a stretch to think of "data" as an asset owned by "proprietary class" but can only be turned into "knowledge" through the work of the productive class (e.g., health economists, data scientists, etc.) which can "monetize" Big Data thus creating a multiplier effect then it is not much of a stretch to make that analogy to the Physiocrats.  One of many hesitations I have with this analogy is the difficulty in managing property rights on different forms of Big Data in the internet age as well as the shortage in the supply of the productive class in the world of Big Data compared to 18th century France.  In some sense it is almost flipped to the point that there are more owners of Big Data then there are experts can create true knowledge from it which is its source of value.  On the other hand, the proprietary class are the ones with the means to apply the knowledge to create wealth in some respect; however, silicon value is a counter example where the productive class can neogiate with the proprietary class to obtain their fair share of the wealth created by the multiplier effect of the nexus of Big Data, the expertize to analyze it and create valuable knowledge which can be applied with enormous scale.  There is also the "network effect" at play as well.  The more people that utilize the applied form of the knowledge created from Big Data, the more data is produced so in many respects, Big Data is not a limiting factor in the same way as land was in the 18th century. 

Again, I am no expert in Physiocratic economics but I sure there are lessons to be learned here from it that could be applied to the Big Data economy, hopefully lessons that could help us to not repeat mistakes of the past and create more of "win-win" so the growth rate is not only sustainable in the long term but creates synergies that make the multiplier effect even larger.

Thanks for sharing the idea.

Best regards, Brian

Dear Bin Jiang,

This was my response to your views on cities as microcosms:

"Dear Bin Jiang,

Thanks for your enthusiastic answers, I guess taking a Big Data approach allows for structures to emerge ("data speak for itself") and contributes to theory- construction? As far as I know there are no "microcosm theories" per se but perhaps we can fall back on something analogous to fractal geometry?

Going one step in the other direction, suppose we need to define "a city within a city", like the case of some spatial complex (e.g. mall complexes, theme parks etc.), would the head/tail break approach be useful as a classifier?

Regards,

Bernard"

Dear Brian,

Thanks for your views on the parallels between data resources and land. Yes indeed not every database is created equal just like the parcels of land would be heterogenous. And the layers of ownership rights not to mention privacy clearances needed. It would seem that the beauty of Big Data is in its reliance on emergent properties that surfaces at high levels of aggregation. And the ability to make inferences using such technologies as user-generated social graphs. But perhaps such an approach is only reliable if we have less grainy data at the lower levels and it becomes a matter of data granularity?

Best Regards,

Bernard

If I agree with Morton that there may be some lineage between the Physiocrats and the Big Data movement, I will however add an important distinction between them. The Physiocratic movement was directly issued from the work of Bacon at the beginning of the XVIIth century, as the citation of his work in thee frontispiece of Moheau Recherches et considérations sur la population de la France (1778) clearly shows. Bacon in his Novum Organon distinguished between two scientific ways: There are and can be only two kinds of searching into and discovering truth. The one flies from the senses and particulars to the most general axioms, and from these principles, the truth of which it takes for settled and immovable, proceeds to judgement and to the discovery of middle axioms. And this way is now in fashion. The other derives axioms from the senses and particulars, rising by a gradual and unbroken ascent, so that it arrives at the most general axioms last of all. This is the true way, but as yet untried. This second way gave rise to modern scientific thought with its inductive method applied by Descartes, Pascal, Newton, etc. Graunt (1662), from whom the Physiocratic movement was born, was also trying to follow the second way of Bacon and the Political Arithmetic School was going in the same direction, as well in England than in France (see the joint paper). For the Big Data movement I don’t see any approach of this kind to be followed. It appears to me as following the first way of Bacon, taking these data as settled and immovable and trying only to find something from them, without any thinking of an inductive method, in the Baconian sense.

While I enjoyed the diversity of ideas and agree with most of what Lall B. Ramrattan, Morton E. O'Kelly, Brian Griner, and Daniel Courgeau have contributed, I tend to look at the history of economics analysis as interconnected.  It seems to me that even opposing ideas often share a conceptual lineage; for example, one may fuel the other.  

Like Morton O'Kelly I have always been impressed with the ability of scholars like François Quesnay to venture away from their training (i.e., Quesnay was a physician); perhaps it was his connection as a physician for prominent people (e.g., Madame de Pompadour and Louis XV - I think) that exposed him to economic conjectures.  

I suspect  the other ideas being debated such as mercantilism in Europe around that time, fostered spirited discussion.  I have wondered if the physiocrats would have ever developed, let alone flourish, as a school of thought without recognizing the shortcomings of mercantilism.

I am convinced that as scholars we are a product of what other scholars helped us to recognize along with a creative element.  In a twist of Pasteur's famous quote, it seems to me that creativity is the product of a prepared mind.  If I am correct, then the lineage may be even more extensive than suggested in the question posed by Shian-Loong Bernard Lew.

Wow.  I've missed some good posts.  Will catch up.

Very interesting topic.

Brian