Carlota Perez - Technology Revolutions & Financial Capital

This essay on Carlota Perez’s Technological Revolutions & Financial Capital is in three parts.

  • PART 1 – SUMMARY OF MODEL & ARGUMENTS
  • PART 2 – QUESTIONS ABOUT THE MODEL
  • PART 3 – WHAT MIGHT CAUSE THE MODEL TO NO LONGER BE TRUE?
  • PART 4 – APPLICATIONS/IMPLICATIONS OF THE MODEL

 

 

PART 1 – SUMMARY OF MODEL & ARGUMENTS

Overview

Perez argues that technological revolutions should not thought of as a simple linear progression or as sprawling fractal stain of independent technological breakthroughs but instead as clusters of innovations that lead to ‘great surges of development’ that modernize the whole productive structure. Over the course of the (roughly fifty year) cycles there are two key relationships.

  1. New technology & society.
  2. Productive capital & financial capital.

The key dynamic is the acceptance/adaption of society to the new technology and its norms, institutions, laws, regulations etc. This does not happen smoothly but rather requires a ‘crash’ before the new technology and society can be aligned and integrated and society can enjoy a ‘golden age’ of broad-based prosperity. The driving force for the crash is a disconnect between financial capital and productive capital where basically financial capital starts to see big returns in one small part of the economy (the new technology) but no where else. This leads to a) a bubble in the new technology and b) the creation of questionable financial innovations and together they result in the turning point/crash that sparks the separates the ‘installation period’ from the ‘deployment period.’

5 stages of the model

In the table above you can see the two distinct phases of Perez’s ‘great surges of development.’ First you have the installation period in which a new technology is introduced and developed in an economy. Secondly, you have the deployment period in which the technology becomes widespread and the true economic benefits are reaped. To use Peter Thiel’s terminology the Installation period is zero-to-one and the deployment period one-to-n. These periods can in turn be sub-divided into distinct phases: Irruption, Frenzy, Crash, Synergy and Maturity. I have divided into three columns their distinct properties as related to Prodution capital (PK), Financial capital (FK) and social-economic paradigm/institutions etc. (Society). The phases that are ‘positive’ are in yellow, the phases that are ‘negative’ are in red. The key thing to notice is that the only period of alignment of Production and Financial Capital and widespread benefits to society is the Deployment Period of Synergy which makes the Crash that precedes it not only not a bad thing but actually necessary to enjoy the prosperity afterwards. Ironically, it is Financial Capital and Society’s alignment with the new technology that initially helped first develop and then propogate the last surge that actually works against the next surge until the last surge has completely run its course. Perhaps Perez’s most profound idea then, is that societal institutions and the best practices that govern both ‘Financial Capital’ and ‘Production Capital’ in each surge are not some ‘eternal truths’ of capitalism but instead just adapted for their time and their surge. Model vs history 

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PART 2 – QUESTIONS ABOUT THE MODEL

  1. How do you objectively measure the degree to which technological change occurs by clusters?
    • Maybe try and estimate the cost of developing a new technology and how that changes over time based upon breakthroughs in other areas?
  2. How do we tell where we are in the surge?
    • For example the Nasdaq 2000 crash and the Dot com boom are taken as the ‘turning point’ but so is the 2007 housing bubble and following Great Recession.
  3. Why is the wave cycle 50-60 years?
    • Is it function of technological cycles or the rate of change of our institutions? Perez offers a causal change of events but doesn’t not an explanation for the timing.
    • If it’s the latter could we accelerate technological progress by making our institutions adapt quicker? Imagine, requiring everyone to go to university half-way through a career i.e. from age 18-22 and then again at age 40-44. Wouldn’t that lead to more rapid socio-economic institutional adaptation to each new surge?
  4. Are crashes/turning points a necessary evil?
    • Can we not figure out a smoother way for our socio-economic institutions to adapt to each new surge?
  5. Is there a way of gauging what the next surge will be ahead of time?
    • Or even what the current surge is now?
    • If you define things broadely as software the surge may have a long-time to run but define it more tightly as hand held electronic devices maybe it has less time to run.
    • Maybe the key is locating the pervasive low-cost input.

PART 3 – WHAT MIGHT CAUSE THE MODEL TO NO LONGER BE TRUE?

  1. What if next wave requires large fixed cost investments?
    • The continuation of each wave requires that capital from the last wave in seeking out returns seeds the next wave.
    • What if the next wave requires large fixed cost investments (e.g. rocket technology)
  2. What if investors no longer maintain high expectations about returns and thus do not take risks investing in the new technologies from which the next surge will come?
    • Isn’t investing in housing a fundamental ‘useless’ investment because it leads to no technological advances or potentially new surges?
  3. Could there potentially be multiple surges occurring simultaneously in different countries?
    • A key assumption of the model is the high opportunity cost of capital such that it can only be directed towards one surge at a time.
    • In that case why is the total amount invested in Silicon Valley venture capital (the engine of the current surge) so pitifully small when compared to the global financial markets. With all that capital out there seeking returns there should be hundreds of surges being funded simultaneously.
    • Perhaps now you could have a surge in the United States in software technology and a surge in China in hardware technology occuring simultaneously.
    • Maybe, this would mean that turning points/crashes could be endured more easily as they would likely be out of sync and thus the recessions could cancel each other out.

PART 4 – APPLICATIONS/IMPLICATIONS OF THE MODEL

In each wave socio-economic institutions and norms are held as undeniable truths but Perez argues they are merely working best practices for each surge. This is very freeing. What will next wave look like?

  1. What type of socio-economic institutions are best suited for the next wave? American democracy or Chinese autocracy?
    • What if the next wave involves mass unemployment from the automation of low-skilled jobs?
    • What kind of socio-economic institutions would be required to make that society work?
  2. What types of financial firms?
    • Currently both equity investing and VC investing require very little domain expertise. For the former it’s about have a strong balance sheet and the latter an exponential growth curve.
    • Maybe future venture capital firms will require STEM domain expertise.

3. Is there a way to keep financial capital and productive capital more aligned with each other?

  • Is it primarily an information problem? Maybe there would be value in a massive database of start-ups and their profit streams?
  • Is it an expertise problem where investors don’t understand the technologies they are investing in?
  • Or is perhaps a future technology’s market size/economic demand the key unknowable?