http://www.charlesleadbeater.net/NotaBlog/blog-2008.aspx

Even so, there is an exception to your basic rule in economic systems: comparative advantage. Here, each side can concentrate in the pre-existing differentiation where it has the best efficiency. The theory does not require the next step of an additional innovation to increase per capita income. After that, of course, growth is a steady alternation between innovation and trade.

Indeed I meant “opening of new markets” in the older usage of the term, i.e. of exploration or contact with other countries and trade liberalization — opening a foreign country to trade, having more people to sell to, the prelude to comparative advantage.

On #4: with regard to a theory where agents choose the easy innovations first, can it be other than trivial? It is a tautology that, if innovation rates decrease, the “most valuable easiest” innovations were pursued first. But to write that the rates decrease “when” this is done, made me think this was more than mere definition.

I also did not realize that by “innovation value” (#3) you meant immediate monetary economic value, and not (as any old systems theorist would naturally be thinking!) something like what economists would call “positive externalities” or “network effects.” But then how do you define “big” vs. “small” innovations? I think you are incorrect about the specific importance of private property in the web of institutions under its rubric — but let’s take another example. It seems to me that a big innovation was the telephone, and I would define it as big because of the extraordinary positive externalities, leading to an incalculable chain of growth and profits over a centruy. Yet you write that “most innovation value comes from many small innovations” (#3). So how do you draw the line between “big” and “little,” in technological innovations?

But if innovators gain the full value their innovation creates, then what’s the point of encouraging innovation? An innovator creates something that makes $100 million for the world economy as a whole, they get paid $100 million, so the rest of us are no better off than we were before. Furthermore, if any gains I get from an innovation simply go to the innovator, why bother adopting the innovation in the first place? Why buy a more efficient washing machine if the capital cost of the washing machine plus payment to the innovator is equal to the discounted value of the energy saved? Why buy a new medicine if I’m just going to be taxed enough that I’ll be as miserable as I was without the medicine? So, under your scenario where the innovator is paid the full value of their innovation, there is in fact too little innovation as no one else has an incentive to make use of the innovation in the first place.

The only reason it makes sense to provide incentives for innovation is that the innovator does *not* capture the full value of their innovation.

“Systems are parts in a structure” In this and what follows, your definitions appear to be contradictory: “systems are parts in a structure” (in #1); “innovations are better part or structure designs” (#1); there are “part innovations” and “system innovations” (#5); there are “system structures” (#6).

Exactly how are you using the word “system” in all of these?

Wouldn’t it be better to say instead that systems are certain structures that have separable but interlocking parts, there may be separable subsystems, and that innovations are changes among the parts?

#1 “innovations are better part or structure designs” Why are innovations “better?” The answer is, usually because they REDUCE the space, time, or personal physical effort that is required to effect a transfer, transformation, transaction, or transportation between two parts of the structure. There is a reduction or condensation or concentration quality to it.

At the next hierarchical level up, this condensation may be seen as a specialization or differentiation, to be integrated with others, again via a larger type of transfer, transformation, transaction, transportation, in that higher level.

#2 The growth in systems is due to both (a) “collecting” innovations, and (b) the simple enlargement or increase of the system, including by accretion. A example of (b) is population growth, such as in societies or ecosystems, or the “opening” of new markets. It is hard to maintain that “most” growth is due to innovations, unless you restrict the discussion to certain systems along certain time scales: e.g. modern economic growth, or the eons of evolutionary time.

#3 In the case of institutions, which are homologous to innovations but instantiated at a different (usually higher) hierarchical level, the value often proceeds almost entirely from the single BIG change. Private property, for example, enables the easier transformation of resources and easier transfer of possession among individuals — which Locke was on to. There was of course a host of “lesser” innovations to attend to private property, such as contracts and so on. But your point was about where most “innovation value” comes from, and institutions are a type system-wide innovation with an enormous importance and value; they are a sort of technology at the social level. (You may dissent from likening private property, or any institution, to an innovation, but then you cannot define innovation as “structure design” in #1 — at least, not for all structures.)

#4 I wonder if you would please give an example, real or theoretical, from social systems or biology, where innovation rates “decrease when the most valuable easiest innovations tend to be pursued first.” I am unfamiliar with this. Are you limiting this to a single technological lineage, as opposed to a whole system of them? Is there an example from biological evolution?

#5 Again, what characterizes “system innovation” in this list of basics? I.e., how and when do you say that the whole thing has changed?

“1. Systems are parts in a structure; innovations are better part or structure designs. An innovation embodies insights whose value depends on a context, and so changes with that context.”

The first second is already obvious to everybody. The second is not so much. For example, there isn’t a good appreciation (much less quantitative theory) for how much cross-disciplinary collaborations contribute to the rate of new invention. Within legal academia, the best theory I’ve seen has been done by Paul Heald and Scott Kieff, both of whom have a good grasp of how the alternative of trade secrets to patents is costly both from an institutional perspective AND from a perspective of decreased spillover effects. Among academic economists, I’m still trying to figure out myself what state of the art is. But I know that people are saying that Paul Romer will win a Nobel for his work modeling “spillover effects.” So maybe you will consider this adequately covered. I don’t because I don’t think modeling back from a macroeconomic level is as useful in developing insights into institutional design as developing an understanding of what generates the macroeffects at a micro level.

“2. Most growth in the number or size of large systems has been due to collecting innovations.”

Does this mean human capital development has been the biggest driver of economic growth in economies? As with 1, this point is generally appreciated, but witness the fact that a “Journal of Human Capital” didn’t exist until last year and you’ll see what I mean about how more work could be done.

“3. Wars, quakes, and diseases may be distributed so most impact comes from the few largest instances. In contrast, in large systems most innovation value comes from many small innovations. Even big innovations require many matching small innovations to be viable.”

I’m not even sure I agree with this. I would say that the invention of the printing press and the internet are as catastrophic (in a positive way) as large wars, quakes, famines, or diseases in their consequences for human capital development.

“4. Innovation rates increase when early innovations make it easier to pursue later innovations, and decrease when the most valuable easiest innovations tend to be pursued first. Steady (exponential) growth suggests that these factors roughly cancel. Since growth rates commonly increase then decrease, usually the second factor eventually wins.”

You’re describing what I think Schumpeter would have called waves of creative destruction. Since he published “Business Cycles” in 1939 and Harold T. Davis published in 1941, I don’t know that many economists (and certainly no patent lawyers) have given much thought to how the phenomena you describe could be modeled with time-frequency distributions. In fact, I think we will have to convince academic economists to introduce a new fundamental hypothesis (of periodicity) into economic theory before we make any progress in arguing for time-frequency distribution models as an alternative to the static models of aggregate supply and demand or time-series analysis that have been in vogue for the last fifty years. As far as I can tell, the good academic economists have developed a number of ways of cobbling dynamics onto their mental models for supply and demand (e.g., by imagining how elasticity shifts in time). But nobody has gone back to first principles and connected time-varying patterns of consumption and production up to the supply and demand curves that are taught to be fundamental in intro to Econ. What a blind spot!

“5. Innovation in large systems comes mostly from part innovation, so system innovation is steadier than part innovation, and the largest systems grow steadiest.”

This is already obvious. You’re describing how economies of scale diminish as scale increases. We’ve already got that one down. Still, I would say that there is a kind of prisoners’ dilemma that startups and large corporations face in negotiating technology transfer that hasn’t been solved yet. For example, what if either the startup or company with economy of scale refuses to deal on reasonable terms for technology transfer? Now the startup will wastefully repeat the process of establishing manufacturing capacity, and channels of distribution and marketing that have already been established by the large company. I realize that this is not the point 5. But if more startup CEOs (and their investors) had point 5 vividly in mind, then there might be less wasteful competition. But they are also quite reasonably worried that the large company will not pay enough if they don’t threaten to compete head-to-head. Stronger patent rights would obviously help solve the problem. Paradoxically, many startups and VCs are AGAINST stronger patent rights now.

“6. System structures vary in how well they encourage and test innovations locally and then distribute the best ones widely. Better structures for this are meta-innovations.

* Good modularity reduces the need to match innovations in differing parts.
* Good abstraction puts similar innovation problems within the same part.”

The way I understand what you’re saying here is that inventions in institutional design are more important than other product or process inventions. That might seem obvious. And the first subpoint about modularity is obvious — that’s like saying that standards-making bodies are going to promote commercialization of inventions.

The second subpoint (about “abstraction”) is not obvious. This seems to go back again to the point about how cross-disciplinary work is beneficial to promoting innovation.

I would say that this point is even more important in the field of education theory than it is in patent law or economics. Most universities are balkanized into various departments. It’s not a trivial point to observe that every department would benefit from spending more time translating their work into terms that all other departments could understand. At least not for educators. Incidentally, I think this is why legal academics tend to pick up on new ideas in their literature quicker than other academics. It’s because they’re trained to “translate” whatever they read in the sense that they’re trained never to assume anything about the definitions of the words the authors of the texts that they read are using. No two judges ever have the same thing in mind when they talk about “fairness.”

“7. If a barrier isolates two systems, the faster growing one eventually dominates. A system that better promotes innovation can lose to a system with a larger source of innovation.”

This point in particular is underappreciated by politicians and economists considering the question of immigration. You could right a very important paper about how our immigration policy could end up putting us behind the rest of the world.

“8. In large innovation pools, similar innovations commonly arise from several semi-independent sources at nearly the same time. No single source was essential.”

This point, if anything, is overstated at the moment. A version of this appears in the recent Malcolm Gladwell piece about Intellectual Ventures. It’s somewhat true, as the history of Interference proceedings in the U.S. demonstrates quite vividly. But if you dig into the details of the history, you’ll find that inventions are as distinct and original as inventors.

“9. Current human society can give incentives to innovate too much, when innovation is used to signal, and to innovate too little, when innovators are not paid the full value gained by others.”

Although I don’t understand the subtleties of your theory of signals, I think I understand them well enough to say that that part of 9 is not obvious. Even the second part (substituting “full” for “part” as an earlier commenter pointed out is necessary) is not obvious — although it was to the Venetians in the 15th century, the Founding Fathers in the 18th, and Abraham Lincoln in the 19th century. The current modes of thought on incentives for innovation seem to be (a) let the government fund it; or (b) we don’t need incentives. (a) is wrong for reasons that people at GMU understand. (b) is wrong for reasons that most economists understand. And politicians now too since so many Ph.D.s are leaving the U.S. after earning their degrees.

One of the things I thought was so odd about being in grad school was how so many large corporations funded grad students. I thought, this is a rather mercenary move on their part, oversupplying the market for Ph.D.s so they can then underpay them the rest of their careers.

Well it turns out that some of those Ph.D.s don’t have to live in the U.S. and be underpaid.

But I would say that most of this stuff isn’t accepted as obvious by practicing lawyers, economists, or business people. More specifically, I would say that almost all of the points you make are worthy of a separate blog post, if not a separate academic paper.

The larger problem that I see is that the dominant theories of innovation (and patent law) are supplied by economists, and economists since the 1940s haven’t had a good set of tools for analyzing dynamics. Rather, they’ve been cobbling together models of very rich phenomena by using a bunch of coefficients that don’t have apparent physical meaning. Paul Romer’s work on spillover effects is an example of a success with this type of technique.

…but as every good physicist knows, sooner or later you have to go back and grapple with the underlying dynamics.

I would go so far as to say that even general observations about how and how much innovations decrease the period of time that it takes goods or services to be supplied would be new for a lot of people in the field.

You don’t have to have a whole complex theory of modularity to make improvements in the existing theory of innovation.