Early next year I will be giving a talk on the challenges and opportunities arising from the current transformation of economy and society by technology and technology enabled globalization. I am rapidly realizing though that I don’t have nearly enough time to chase down all the primary research to validate (or invalidate) some of my thinking. Here are some of the questions I am most interested in:
1. What is the foundational math of a Basic Income Guarantee? That is comparing some of the current government revenue base to expenditures to the total cost of a potential Basic Income Guarantee.
2. What can be learned from experiments with programs similar to Basic Income Guarantees that have taken place elsewhere?
3. What do we know about human behavior from tribes living in abundant areas? Including historic accounts, such as the first voyage of the Endeavour.
4. What behaviors are we observing in online systems that are marked by abundance?
5. What is the latest evidence on key macro trends, including population growth, levels of employment, under-employment and unemployment in economies around the world?
I am currently thinking that a graduate student in economics, politics or history here in the city (NYU, Columbia, Cuny, New School) would be ideal, but am entirely open to other backgrounds. This will be a paid position and I expect it to be on the order of 10 hours per week for at least a couple of months but could go on longer. Any and all suggestions on how to best find the right person are welcome!
Halloween is coming up. But if you really want to scare yourself, I suggest you read this interview with an associate director at the CDC about the “end of antibiotics.” Essentially we are not only seeing more bacteria that are resistant to absolutely every medication we have but these bacteria are now spreading outside of hospitals and are more rapidly sharing their genetic antibacterial immunity with other much more common bacteria.
In the meantime there are no (as in zero) new antibiotics in the drug pipeline. I for one am not inclined to say let’s wait for some startup to figure out that this might be an opportunity. Instead this is a perfect example of a massive market failure and exactly the kind of situation in which we need government to intervene. So far unfortunately we have not seen any action by politicians despite experts using words such as “nightmare” to describe the present situation.
So one other suggestion: if you are a newly minted billionaire or know one, this might be a good place to spend some serious money. Full drug development costs a fortune, but we need to put a lot of new ideas into the pipeline if we want to find something that works.
As previously announced, I have self-published my MIT PhD thesis. Today’s post is about the first paper, which is titled “Information Technology and Firm Size" which — as the rather plain title suggests — examines statistical evidence of the impact of the increased use of IT on firm size. Before starting any analysis of data it helps to have a hypothesis and so the question is should we expect to see larger or smaller firms? Unfortunately, there are many different ways that computers might impact firm size and some of those work in opposing directions! For instance, reduced coordination cost might lead to smaller firms but better use of information assets might result in larger ones.
The paper sets out all the forces I could think of and discusses some of their theoretical background. It then proceeds to compare the manufacturing and retail/services sectors for which the relative importance of the different forces shakes out differently. This is really the key idea of the paper. Because Census data on number or establishments and establishment size (establishment is roughly equal to a location) is available by industry it should be possible to test whether the impact fits with the hypothesis.
What I remember the most from working on this paper is how painful it was to assemble the data (which makes it all the more annoying that many moves later I seem to have lost it entirely). In particular, the Census bureau has a habit of changing definitions of industries and even measurements over time. Some of that is of course unavoidable as the economy changes, some of it seemed distinctly arbitrary. Also, my thesis predates much of this information being available for download and I rekeyed a lot of it from printed Census reports.
In the end though I was very happy with the results. Here is the summary of my findings for manufacturing:
For the manufacturing sector, the dominant effects appear to be the increased flexibility of physical assets, the heightened importance of skilled human assets, and the reduced coordination cost. As discussed (…), all of these effects favor smaller firms. Both in the correlation and the regression analyses, the coefficients point generally in the hypothesized direction. Information assets appear to have the hypothesized effect of leading to larger firms, but for manufacturing they are outweighed by the effects of physical assets and human assets.
And here by contrast is the summary for retail and services:
For the retail and service sectors, the dominant effect instead appears to be the increased importance of information assets which results in larger firms. The influence of physical assets seems to be insignificant for both the retail and service sectors. The results for human assets were somewhat inconclusive, with higher skill levels associated with larger firms in retail and smaller firms in services.
What’s particularly comforting is that these trends seem to have continued since. It is somewhat shocking to see that my data ends in 1992 (!) because the Census bureau used to be (and maybe still is) several years behind in publishing the data and I started working on this in 1996. Since then we have seen some massive growth in retailers (just think of the huge drug store chains) and also financial services firms. By contrast if anything it would seem that at least for US manufacturing we are likely to have even more small firms.
It would be terrific if someone were to update this analysis. For instance, it would be interesting to check if we are seeing an increasingly bi-modal size distribution. For instance, in banking we now have a few mega banks but it now also possible to get a “bank in box” from service providers and be up and running as a new bank with very little effort.