Question to Economist and Computational science grads: A biologist POV to economy

[T.J]

Hi,

 

I have a question to an economics major or perhaps computational grad student. I work in biology and hence my perspective is different. 

 

Perspective: You must have herd about Human Genome project and Genome mapping etc. Basically there are about 40,000 genes that regulate our body functions and whose misregulation leads to diseases. 

 

Question:

 

1. Is there a current understanding of lets say 40,000 companies and independent entities (government, profit and non-profit) identified in an economy (Lets say in USA to be country specific) and how they are perhaps related to each other.

 

(Lets say, company A -is linked to Companies B-Z (agriculture for instance) however, company C (consulting firm in oil and gas) is only linked to company D, E and F and so on.  )

 

2. Is there is a huge interaction Mapping of a particular economy where u can predict WHAT IF you knock out COMPANY A -> how many companies are affected, and so on..? 

 

I do realize that such a prediction if existed, would perhaps predict the stock market and everybody would get rich. But, the complexity in biology is tremendously difficult, from measurement to standardization and further predictions based on existing model. However, it works! So, I cant imagine someone in economy/computational application in economy would have not conceived this.

 

Thanks for listening to my rant

[ajaxp91]

Strangely enough this has already been studied (e.g. GIS links, production networks, network topology, graphing, etc.).

 

I distinctly remember this issue obtaining "pop-culture" status when the New Scientist magazine wrote an article about a 2011 PLOS One study by Battiston, Glattfelder, and Vitali (http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0025995). It was released right around the time that OWS protests began, so naturally the media was overly excited about it. The research identified a significant number of transnational corporations which had ownership of global companies. There was some overlap in ownership, and additionally these core organizations controlled a large share of the global economy (approx. 40%, I think).

 

This is a very interesting economic subject, but I doubt it holds the potential for any stock market prowess. But there has been research modeling the interdependence of stock markets and assets to predict market shifts: (http://www.sciencedirect.com/science/article/pii/S0378437112004190). You also may want to look into electronic trading algorithms, which are becoming more dynamic and may incorporate this sort of modeling into their structure.

 

What ignited this question? Are you planning to do any work like this?

 

I do think the cross-over between subjects (e.g. genome mapping and market mapping) is really exciting. But I wonder what it will do, especially for economics... in the long run I suppose we'll all find out, eh?

 

Also, perhaps there is someone more senior (in educational rank, not in age) than I who can chime in. I've only a BS in economics and BA in philosophy to my name, so I'm not some expert.

[T.J]

Thank you for the reply@ cautiously_optimistic. I will definitely read those articles. I really appreciate it! I was bored waiting for my results for grad school applications. I have a background in Materials Engineering and I plan to do PhD in Biomedical Eng/Biomedical Sciences. So, I'm not planning on working on this area. I was engaging myself in quantum mechanics, genetics, economics specifically related to inflation and economic bubbles and so on to pass my time. 

 

So, my question was more out of curiousity and reading than anything more. 

 

In terms of genome mapping and market mapping subjects, I think it has tremendous potential. I had the opportunity to work in genome data and analyzing the datasets to make meaningful predictions of what is going on in a biological system. Within few days of getting my feet wet in the water, I could see the potential. Also, it is already used and implemented to predict and successfully discover what is happening in a system (like cancer, genetic diseases, etc). Having realized the complexity of the biological systems and achieving this accuracy in predictions, I thought this should give good advantage in economics as well.