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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?

What Do Banks Do? Adair Turner

This essay on Adair Turner’s essay ‘What Do Banks Do? Why Do Credit Booms and Busts Occur? What Can Public Policy Do About It?’ taken from the book ‘The Future of Finance – The LSE Report’

  • 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

Turner’s argument is as follows

  1. First Principles: Turner lays out the theoretical roles of banks in the economy.
  2. Hypothesis tests: Then he establishes tests for measuring banking’s effectiveness at these roles.
  3. Statistics – Δ in x: Turner describes the massive developments in banking.
  4. Statistics – no Δ in y: But shows there is little evidence these changes are resulting in better economic outcomes.
  5. Null hypothesis false?: Turner questions whether the assumption that more banking is always better is true in several key areas.
  6. Solutions: Turner offers some possible solutions.

1. First Principles: Turner lays out the theoretical roles of banks in the economy

Four categories of financial system activities.

  1. Provision of payment services, both retail and wholesale.
  2. Pure insurance services.
  3. Creation of markets in spot/short-term futures instruments e.g. foreign exchange & commodities.
  4. Financial intermediation between providers of funds and users of funds, savers and borrowers, investors and businesses crucial for capital allocation.

Problems of crisis were with category 4, where intermediation of non-matching assets and liabilities entails four functions.

  1. Pooling of risks.
  2. Maturity transformation via balance-sheet intermediation – banks lend longer than they borrow. Risks are offset by the equity cushion.
  3. Maturity transformation via provision of market liquidity.
  4. Risk-return transformation – different mix of debt and equity investment options for savers than naturally arises from the liabilities of the borrowers.

2. Hypothesis tests: Then he establishes tests for measuring banking’s effectiveness at these roles.

This four transformation functions add value to the economy in three ways.

  1. Investment of pooled assets directly affects capital allocation. Although much capital allocation goes on within firms and their use of retained earnings.
  2. Maturity transformation means higher consumer welfare, particularly consumption smoothing because both savers and borrowers can get personalised maturity mix of assets and liabilities.
  3. All four factors mean individual household sector savers can hold a mix of assets different from the mix of liabilities owed by business users of the funds.

3. Statistics – Δ in x: Turner describes the massive developments in banking.

Financial intensification of the four transformation functions occurred through:

  1. Securitization pooled new assets groups e.g. mortgages.
  2. Transformed risk-return characteristics of assets through tranching.
  3. New forms of contractual balance-sheet maturity transformation through structured investment vehicles (SIVs), conduits and mutual funds which enabled short-term providers of funds to fund longer term credit extensions.
  4. Extensive trading in credit securities providing market liquidity.

Four trends in particular have occurred:

  1. Growth & changing mix of credit intermediation through UK bank balance sheets.
    • Significant financial deepening both loans and deposits as a percentage of GDP. UK balance sheet by 2007 was 500% of GDP compared to 34% in 1964.
    • Significant increases in income leverage of both household and corporate sectors.
    • Leverage growth dominated by increasing debt levels secured against assets in both household (mortgage lending 14% to 79% of GDP) and corporate sectors.
  2. Growth of complex securitization.
    • Over the last two decades the  rise of off bank balance sheet pooling and tranching.
  3. Difficulty in quantifying aggregate maturity transformation from first two changes.
    • Nonetheless undeniably increase in scale and complexity of intra-financial system claims.
  4. Growth in financial trading activity.
    • Value of foreign exchange traded from 11x global trade value in 1980 to 73x today.
    • Interest rate derivates grown from 0 in 1980 to $390 trillion in mid 2009.

4. Statistics – no Δ in y: Shows there is little evidence these changes are resulting in better economic outcomes.

Fundamental problem is volatility in the supply of credit to the real economy and biases in the sectoral mix of that credit. It is assumed that there is a trade-off between capital requirements and credit extension, risk of financial recessions and productive investment.

Bank Credit Extension

  • However, fixed capital formation in building and structures is around 6% of GDP, the same as 1964 when total lending to real estate developers was much lower and without the risk of credit and asset price cycles.
  • Gross plant, machinery, vehicles, ships and aircraft has fallen from more than 9% in the 1960s to less than 6% today.

Complex Securitized Credit

  • No data?

Market making

  • High profitability of market making/liquidity provision suggests 1) end customers value liquidity 2) market makers with market share + skill can use their knowledge valuably.
  • However, what optimal level of liquidity is is unclear.

5. Null hypothesis false?: Turner questions whether the assumption that more banking is always better is true in several key areas.

Bank Credit extension

  • Perhaps there is no trade-off between credit extension and capital requirements. You can have the latter without losing the former.

Complex Securitized Credit

  1. Market completion.
    • Although beneficial theoretically if complex structuring is for tax/capital arbitrage then it is socially useful.
    • Market completion is subject to diminishing marginal returns of increased tailoring.
  2. Increased credit extension.
    • Undoubtedly true, particularly the extension of credit to sub-prime borrowers.
    • However, lifecycle consumption smoothing benefits outweighed by credit + asset price bubbles.
  3. Better risk management.
    • Most compelling argument.
    • However two inherent problems.
      1. Maturity transformation makes financial system more vulnerable to shocks because much of the demand (perhaps half) long-term securities are funded by short-term demand (which disappeared in the crisis).
      2. Self-referential pricing leads to greater inherent instability. Particularly as credit spreads were so clearly incorrect.

Market making

  • Benefits
    1. Increased liquidity means trading at low bid-offer spreads.
    2. Lower costs per transaction mean more trading.
    3. Liquidity is valuable because it means market completion.
    4. High liquidity means efficient price discovery.
    5. Liquidity means reduced volatility because speculators are incentivized to profit from divergences in optimal price.
  • However benefits have limits
    1. Market liquidity, like market completion suffers from declining marginal utility.
    2. Speculation can lead to destablizing and harmful momentum effects.
    3. Active trading creates the same volatility which customers seek liquidity to protect themselves from.

6. Solutions: Turner offers some possible solutions.

Bank Credit Extension – 4 possible approaches.

  1. Interest rate policy takes account of credit/asset price cycles as well as CPI.Downside is cannot differentiate and knock-on effects.
  2. Countercyclical capital requirements. Downside is not varied by sector.
  3. Countercyclical capital requirements varied by sector. Downside is credit supply from foreign banks.
  4. Borrower-focused policies.

Complex Securitized credit.

  • Borrower focused constraints as well as lender policies in case bank balance sheet capital controls are evaded by going off balance sheet with securitized credit.
  • Need to develop macroprudential tools.

Market making

  1. Set trading-book capital requirements in favour of conservatism (over liquidity).
  2. Speculation (including non-bank) should be curtailed perhaps by leverage limits.
  3. Financial transaction taxes

Radical Reform – not sufficient.

  1. ‘Too big to fail’
    • Cost of bailing out banks is at most 2-3% of GDP. Real cost is the increase in public debt burdens by perhaps 50% of GDP because credit dries up.
    • Therefore futures banks should not be put into insolvency as this will lead to a sudden contraction of lending but instead impose losses on subordinated debt holders and senior creditors sufficient to ensure that the bank can maintain operations without tax payer support.
    • Also lots of small banks failing like in 1930-33 could be just as harmful as one large bank failing.
  2. Separating commercial from investment banking.
    • Separation is desirable because trading losses can lead to general credit supply constraints however legislated separation is neither straightforward or sufficient.
      1. Clear distinction between proprietary trading and market-making, customer facilitation and hedging is difficult.
      2. Just as large integrated banks (e.g. Citi, RBS and UBS) played a role so did pure commercial banks (HBOS, Northern Rock and IndyMac).
      3. Destablising interactions could still exist through the market e.g. commercial banks originating credit and non-banks buying it.
  3. Separating deposit banks from commercial banks.
    • John Kay’s proposal is that deposit banks would be 100% backed by the government.
    • Lending banks would by wholesale funds or uninsured retail/commercial deposits.
    • This would perhaps solve the moral hazard problem but not the procyclical, self-referential problem of volatile credit supply.
  4. Abolishing banks: 100% equity support for loans.
    • Kotlikoff’s proposal is that ;ending banks become mutual loan funds i.e. 100% equity funded.
    • Banks therefore would pool risks but not tranche them but this would again not solve the stable credit supply problem.

It is not just a structural problem with our institutions but a problem with liquid markets themselves.

  1. Higher capital and liquidity requirements.
  2. Countercylical macroprudential tools.

PART 2 – QUESTIONS ABOUT THE MODEL

  • Key question is allocation of capital. How do you measure efficiency particularly when it comes to new industries?
  • Liquidity is fundamentally exogenous shock risk.
  • banks work on hte assumption of indendpence but everything is connected so nothing is independent.

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

PART 4 – APPLICATIONS/IMPLICATIONS OF THE MODEL

The Problem With Comparative Advantage And Justin Yifu Lin's CAF Strategy of Economic Development

My friend recently posted on my Facebook an article which quoted Bill Gates saying that people don’t realise how many jobs are going to be automated in the near future. The implication being that my previous essay ‘Technology growth will lead to mass unemployment’ was correct. However, I’ve been spending a lot of time thinking about the idea of ‘what would convince me that I’m wrong?’ as a way to stay open-minded and avoiding being emotionally attached to my ideas, something that Michael Burry, of Michael Lewis’ ‘The Big Short’ impressed on me. Apparently he hated writing quarterly letters to investors for exactly this reason because in defending his ideas he would become attached to them and may not be able to leave them even if they were wrong. One unexpected fallout of this way of thinking is that an expert, someone you respect or even the person paying your cheques saying your wrong (or right!) does not qualify as a legitimate reason for changing your mind. Of course, if they present good arguments then that’s fine but just trusting in another persons intelligence or superior understanding is unfortunately not allowed. So although, I have to admit the absurdity of me critiquing an economist of Justin Yifu Lin’s reputation I nonetheless I have to persist until someone can convince me that my arguments are wrong. Having said that, to test my own understanding of his theory of Comparative Advantage Following (CAF) Economic Development the first part of this essay will simply be an attempt to relate an unadultered narrative of his theories and ideas. This may also serve as a way to get you up to speed on his ideas in case you are not familiar with them. The second part of the essay will be when I share some of my own ideas and critiques.

PART ONE – JUSTIN YIFU LIN’S CAF DEVELOPMENT STRATEGY

So here is the problem. You’re a poor, largely agricultural developing economy and you want to grow. Fast. What should you do? Well the obvious thing would be to look and see what your most successful neighbours have that you don’t. What you would find is they tend to have well-developed capital-intensive manufacturing industries. Therefore much of economic theory is built upon the idea that poor countries need to build up their industrial base. However, this won’t just happen on its own and so requires government policy to incentivise capital accumulation. Justin Yifu Lin argues that this can have the opposite of the desired effect crippling the poor country for decades just like we saw with China in the 1950s and 60s. In Yifu Lin’s view prematurely developing capital intensive manufacturing industries is like trying to walk before you can crawl. Instead countries should focus on industries in which they have a comparative advantage and can develop a surplus in. These industries he describes as viable because they can compete and survive without government support. Over time the developing country can invest its economic surplus in capital and gradually become more capital intensive. As the economy changes so will the industries in which the country has a comparative advantage in and thus you will have economic development smoothly transitioning to increasingly capital intensive industries. In ‘Part One – Justin Yifu Lin’s CAF Development Strategy’ I shall first outline more specifically the pitfalls of artificially developing a manufacturing base or what Justin Yifu Lin calls ‘Comparative Advantage Defying’ theory of economic development with specific reference to China’s economic story. Then, I will describe Yifu Lin’s ‘Comparative Advantage Following’ economic theory .

YIFU LIN ON WHY ‘CAD’ STRATEGIES DON’T WORK

As previously described poor countries that want to quickly develop an industrial base need to intervene in the market because otherwise heavy industry capital investment will not naturally occur. This is for three reasons in particular.

  1. Capital intensive heavy industries require long construction periods and this in turns means large interest rate costs. To counteract this the government needs to artificially lower the interest rate.
  2. Key technology and capital needs to be imported but as we’re talking about poor countries with limited exports they do not have enough FX to buy the capital required. Therefore governments need to intervene in the exchange rates to make imports cheaper.
  3. Huge barriers to entry because of large initial capital outlays make investing in capital intensive heavy industry very expensive. For agragrian economies with limited surplus this is a particularly serious problem. Therefore to help incentivize capital accumulation by increasing expected profits need to grant monopoly status to firms as well as lower productive input costs namely lowering wages.

Such policies however lead to many unintended consequences which ultimately make the efforts counter-productive. Taking China as an example although there was remarkable capital accumulation: 24.2% of GDP in the 1st Five Year Plan and 30.8% in the 2nd economic growth in the period of 1952 to 1981 was a pitiful 0.5% a year at best. This is because although China had developed capital intensive manufacturing industries they were terribly inefficient and uncompetitive, only kept alive by government support. Support that was funded by the already poor Chinese farmers.

The reason why this happens gets a little messy but the key thing to keep in mind is that the government is trying to push the economy into industries its not naturally suited for, the market however pushes back which leads to lots of problems. Specifically

  1. The aforementioned strategy of lowering interest rates also lowers savings and as the level of savings help determine the investment level it results in a short-run shortage of capital.
  2. In manipulating the exchange rate although imports become cheaper exports simultaneously become more expensive which lowers foreign exchange reserves, which means less capital.
  3. For a country that is already poor paying for the huge capital costs becomes prohibitively expensive. Essentially you end up taxing poor farmers to subsidize inefficient manufacturing. In particular, the policy of lowering wages in turn reqruires lowering the prices of daily necessities which leads to shortages. In the China story the government therefore had to intervene in the agricultural products markets with disastrous effect. In fact the China’s effort to control the agricultural markets through the Peoples’ Commune suffered a 15% reduction in grain production both in 1959 and 1960 and the deaths of more than 30 million people.

As 1. changing the exchange and 2. the interest rates mean that not only are heavy industry capital costs cheaper but so are light industry and agricultural costs there is a danger that the already limited capital is diverted away from heavy industries to the less expensive light and agricultural industries. Therefore the government in pursuit of its policy of prioritizing heavy industries is forced to nationalize. But in doing so suffers from all the negative incentive effects of government control with the potential for corruption and poor management and ultimately inefficient uncompetitive manufacturing.

YIFU LIN ON WHY ‘CAF’ STRATEGIES DO WORK

Instead of trying to artificially upgrade the industrial and technological structure Yifu Lin argues that countries should seek to upgrade the underlying endowment structure. With this successfully done the desried industrial and technological structure will naturally arise. As land and natural resources cannot be changed and labour growth differences between countries are minimal the key thing is to focus on capital acccumulation. This you will recognise is the same goal as the ‘CAD’ strategies. What Yifu Lin disagrees with though is the not the aim but the method. In particular he argues the best way to accumulate capital is to increase the economic surplus or profit that is made in each period as well as increase the percentage of that surplus that is invested in capital.

At the heart of ‘CAF’ strategies is by definition the concept of comparative advantage. Ever since its conception in 1817 by David Ricardo comparative advantage has been the bedrock of international trade. What comparative advantage says is that even if one country, let’s say America, is more efficient at producing goods than another country, let’s say Russia there can still be gains from trade. If you imagine a two good world of grain and ipods. In this world America produces both grain and ipods cheaper than Russia. However America is excellent at producing ipods but only very good at producing grain, in other words its relatively better at producing ipods. Russia in turn although it’s worse than America at producing everything it is good at producing grain but bad at producing ipods thus it is relatively better at producing grain. Therefore if America focuses all its effort on producing ipods and Russia all its effort on producing grain world output increases because each countries’ factors of production have been utilized doing what they are relatively best at doing.

A developing country following ‘CAF’ strategy essentially is picking its battles. Rather than trying to go up against the developed countries in industries they have huge advantages in, by following comparative advantage developing countries can pick industries in which they don’t have to compete against developed countries. CAF strategy in contrast involves competing against developed countries companies in industries they are more efficient in. Of course developing countries can try and support their companies through subsidies etc but an inefficient company backed by a poor country is still going to lose against a developed countries efficient and more technologically advanced companies. Even though for a developing country, focusing on its comparative advantage industries, the spoils of victory might not be as great companies competing in these industries will be what Yifu Lin calls ‘viable.’ Which he defines as companies that are normally managed with no government support that can achieve a normal profit in an open, free and competitive markets. Then over time countries will shift from the labour intensive industries to the more capital intensive ones as companies invest their profits competing in their comparative advantage industries into accumulating capital.

PART TWO – THE PROBLEM WITH ‘CAF’ AND COMPARATIVE ADVANTAGE

There I think three primary problems with comparative advantage and therefore Yifu Lin’s ‘CAF’ strategy.

COMPARATIVE ADVANTAGE DOESN’T MEAN NO COMPETITION

The first problem I think is that although through ‘CAF’ strategies countries can avoid competing with more developed countries in industries they are inherently inefficient at unfortunately there are still lots of poor countries whose comparative advantage is in labour intensive industries left to compete with. Countries in an effort to support their domestic industries may employ protectionist measures or risk having them out-competed. Even if a country’s countries are able to survive the competition between so many companies operating in the same industry inevitably erodes the profit margins. This is crucial because it is exactly this economic surplus from which future capital accumulation is supposed to arise. This competition not only occurs between poor developing countries but also developed countries because as the cost of copying technology is lower than the cost of innovating countries – at least to some extent – can converge. This is usually viewed as a good thing but it has the unwanted by product of resulting in economies with similar economic structures and therefore increased competition.

CONTINUOUS CAPITAL ACCUMULATION? OR DISCRETE?

Yifu Lin assumes that through focusing on the industries in which countries have a comparative advantage countries can gradually shift the isocost line and move away from labour intensive industries towards more capital intensive industries. This picture however is too simplistic because capital cannot be viewed as a continuous line. The reality is that accumulating capital in car manufacturing doesn’t mean that you can then smoothly jump to accumulating capital in ship manufacture. They don’t transfer that easily. This is also true of expertise and human capital. In reality each industry is relatively discrete. This means that countries can get trapped in a specific set of industries which they are viable at but cannot switch to different and perhaps more capital intensive industries without huge investment. Which of course leads us to exactly the same problem we were hoping ‘CAF’ would solve; that of a poor country trying to transition to a more capital intensive industrial structure but not having the capital to do it. Yifu Lin argues that because China enjoyed little economic growth in the 20 years until 1978 therefore China’s plan of transitioning to heavy industry was a failure, despite the incredible capital accumulation numbers. I would argue that perhaps China just showed an incredible resolve for a poor country to make itself poorer in the short-run so that in the long-run it can fundamentally shift its industrial structure and build the foundation for future runaway economic growth. For countries not willing to take this Faustian bargain the future may be bleak as the country gets trapped specializing in labour intensive industries and other countries become more and more efficient in the capital intensive industries.

COMPARATIVE ADVANTAGE ASSUMES FULL EMPLOYMENT

This last critique is perhaps the most controversial. To take the previous example of Russia and the United States even though America enjoys an absolute advantage over Russia in the production of both ipods and grain America specializes in its comparative advantage ipods and Russia in its comparative advantage grain. At the heart of comparative advantage though is the assumption that America doesn’t produce grain because its limited factors of production would be better spent producing ipods. However if America had sufficient factors of production to produce enough ipods and grain to satisfy world demand then the United States with its absolute advantage in both industries would out-compete Russia and Russian workers and capital would be left unemployed. It sounds of course implausible because surely the Russian factors of production would be employed doing something else but as we have seen in the Great Depression it is possible for economies to last long periods without fully utilizing all its factors of production. In fact it could be argued that most of economic theory is about jump-starting economies out of low employment equilibriums into high employment equilibriums. I think this critique is particularly significant because as I argued in another essay titled ‘Technology growth leads to mass unemployment’ I think there are compelling arguments to believe that unemployment of factors of production and in particular labour could soon be a widespread problem. Of course, this is against our economic intuition because our economic history is one of our economies and labour forces shifting from labour intensive agriculture to labour intensive manufacturing to labour intensive services. Thus although much of our economic growth has been fuelled by the automatization of the efforts of labour there have always been new industries to soak up the unemployed workers. I think now for the first time in human history that is potentially not going to be the case. In particular this oncoming robotization points to a fundamental decoupling of labour and capital such that in many manufacturing processes the concept of a diminishing return to capital because of limited labour to work that capital will become meaningless.