Commentary

The four economies

From building investment themes, trading strategies to incubating and scaling start-ups and building nations and conducting macroeconomic policies. To understand economic growth and the intricate relationship between factor supply and demand on a maneuvrable canvas is key. A look beyond the national economy and an acknowledgement of the relevance of supply chains, city networks/urban economics and the impact of information technology in formation of what constitutes growth. 
Inspired by reading on the works of Jane Jacobs and her attempt to look at the economy from the urban economics / networks of cities view and and seeing Manuel Castells network society become more and more dominant in my reasoning of how markets work, and challenging myself to understand the open-source economy as a dominant feature of the information age, I was intrigued to render my thinking about macroeconomics and the chase on alpha in value-oriented investments in terms of a four economy model. So while I didn’t have the opportunity to look at the statistics of the model yet, the concept appears robust when thinking about mutual exclusivity of dynamics. So this is a brief take on the conceptual world.

Intro

Let’s start with what the four economies are.

National Economy:

Of course, there is the traditional national economy that is being studied by economists all around the world. Its existence gave rise to a fairly solid way of recording economic activity standardized in the System of National Accounts (SNA 2008). A system actively promoted by the UN and leading to the level of standardization that eliminates at least the worst fallacies around building macroeconomic models on incompatible data sets.
Why is this still a hot and relevant “aggregate” to look at?
a) Human Capital Freedom of Movement: Yep, even in 2018, still limited movement. You country gives you citizenship. Your country’s foreign policy limits the freedom to visit and move. And negotiates treaties and contracts to make it easier to move around (Shengen). While still making it more or less impossible to migrate (source nation-based immigration quotas)
b) The object is a fairly converged legal environment: The system of recording and aggregation is within national boundaries pretty much aligned and standardized. And while for most cases the national economy makes no sense as an aggregate from a business perspective, never did and surely does not now, the unified legislation, taxation and all that Jazz makes it the biggest unified object of study. With all the rights of legislation and executive branch to obtain data desired and needed.
But also looking at the academic approaches towards providing micro-foundations to our macro-economic world and policy making – c) yes, policy making on national level requires this national economy view and all supra-national or inter-national policy making is ultimately a negotiation of state actors.
But then, again, it’s also easy to see that the tools at hand are good enough to connect stylized micro behaviour to generate time series that resemble the dynamic interrelationships of macroeconomic dynamics. But is certainly not enough to deeply understand what is practically going on.

The supply chain network economy:

The core goal in understanding the micro level of national economics is to identify partially isolated economic sub-systems as good ol’ Niklas Luhmann would understand them, that can be studied below the macro economic level and that provide sufficient data to be studied.
Industry Networks: Classic areas of study, again, from a national economy point or view, large scale corporate run oligopoly markets that formed the areas of “industry economics” is a core economic discipline. Space and time and become independent. But direct competition becomes more relevant. How much does marketing and sales activity focus on the same people and on mutually exclusive product purchases. And how do competitors regulate cost to the company by coordinating those activities?
De-clustering those competing companies by products and customer segments, and by modelling this not only on a global “landscape”, but in a inter-termporal flow-of-goods perspective yields market segments, supply chain networks, etc. The classic global supply chain network analysis.
Or by companies that are feeding into the value creation of other companies in a platform economic play. More modern, but same take. Looking at those inter-relations by understanding how costs and revenues between companies match. The platform economy is essentially the supply chain economy for digital goods. Isn’t it? [Disclaimer: Who knows]
Boiling those dynamics “supply chain” views down to a “landscape” view lands you in the world of industry classifications. And we understand that the market cap or total revenues somehow represents the power position in the supply chain – although that again is not part of the industry classification.
Human Flow Networks: Beyond that field of legal entity networks or company networks, we see increasing studies on top executives and rich people flows around the globe. While this already goes into the direction of the next “economy” – the city network economy -, it bears mentioning that the evolution of supply chain networks and industry dynamics is not understood to its entirety by merely looking at the flows of goods, but needs to understand the flow up demand and supply for skilled labour. To put it simple: if a company at the top of the supply chain – the large volume, large margin behemoth sitting in between the forking landscape of upstream and downstream supply chain – is losing out on talent and skill to one of its neighbors in the chain, it is going to go down. Simple. But that’s just what it is. With our new consumerized companies and “industrialized” millenials [joking], the traditional “play” of increasing spending on talent acquisition to win over the best is no longer working. Brand authenticity and proper design of management and incentive systems to drive the right culture is becoming more and more important. At least IMHO.
Summary:
Basics While indusry classifications are good for “portfolio” structuring – nice beta and alpha clustering within the “cluster” -, it doesn’t work for studying the network. Industry economics and supply chain analysis makes more sense. And thinking of a supply chain as a bundle of fibres that contain material flows and looking at velocity and volume of material flows and margins and competitive dynamics (long-/value-investment strategies) is a cool thing for looking at trading strategies or looking at industry consolidation opportunities (PE view) is, too.
Human Capital Flows: Updating that 90s and 00s view with recent advancements in measuring human capital flows, and understanding in detail the human capital supply of university ecosystems, understanding the percolation of key resources through the system – from periphery upstream to core players and within core players – using scrapers on linkedIn and other career networks, and understanding factor loadings from these data sources on predictabiltiy of revenues and margins, competitive position and so forth is becomes viable for hedge fund-ish strategies.
Industry Dynamics and the global economy: And the area remains an active area of study. After all, good business relationships between businesses like to last. And the stability in supply and demand networks within larger supply chains makes the “supply chain network” aspects of the economic analysis relevant. After all, it is THE de facto context where most of the stuff taught in economics is being applied. Comparative advantage between national economies enter here. New companies form somewhere at the end of the world, material flow cost using container ships connect goods. IoT technology from Israel is increasing measurability, and the big data solutions from the US make it measurable. The edge computing technology of European TelCos make it accessible to the European enterprise.
Lobbying: But more importantly is to understand cash generation and interest syndication within industry dynamics to understand lobbying behaviour and impact on local legislation. Itis not rich people, personal networks or cities that “join” forces to influence regulation and policy making. It is the industry.
Innovation: Last, but not least, the percolation of skills as transported by human resources among e.g. the lumber, the fashion, banking and technology industry is somewhat predictable, too.

City networks: 

When looking at how industries start to form and actually evolve, we leave the world of the national economy and industry dynamics. While industry opportunity sparks activity of entrepreneurs, the “incubation” is driven by different factors.
To understand this, let’s look at influential human types: there are two types of human actors that matter for this. The “investor” type and the “maker” type. Investors in essence live in a forest and deploy capital to the best networks globally. Without knowing anyone. And without caring about knowing anyone. To understand this type is to understand that they do not take a stand on anything. Whoever raises money for anything is not raising from the investor type. But from intermediaries. For the real investor, investment flows are ideally so bifurcated and obscured that nobody knows they exist. And then there are the “maker” types. People in control of larger volume of juice/capital in a (geographically) “limited area”. And here we get back to Jane Jacobs.
The big difference between the investor type – who obscures his existence and maximizes his return and enjoys life outside of scrutiny – and the maker type – who wants to prove himself and be in the limelight – is what allows us to study the existence and ongoing emergence of clusters. Yes, let’s go theory and talk about what clusters are.
In principle, a “simple pure play” cluster is a network between people that are equal or similar in their command/control of resources that are useful to the group and are similar in intent and in behaviour enough to play jointly on pursuing something.
This could be a group of musicians forming a band. A group of investors pooling their money to invest. A group of academics citing each other to win the Publish or Perish war. Etc.
A “extended pure play” cluster is a combination of simple pure play clusters that complement each other into a joint whole. Money meeting skills meeting business meeting academia meeting labour supply = Silicon Valley. If the clusters not only co-exist in an environment that is dense in transactions, but are joint in efforts, you get an “effective cluster”.
A city now is a governmental entity – it derives its power from the national political sphere – that via regulation and existing “citizens” (= past success) collects “extended pure play” networks and creates environments that inspire and promote dense and fruitful transactions between them. If a city does this well, this means more power, more taxes collected, more attraction for human capital, more power and taxes, etc.
Ideally, superclusters form. If a city it quite bad at it, it’s a local matador expert cluster. Invisible and irrelevant to the world. If it fails it is not a host of extended pure play clusters, but of simple pure play clusters. And it becomes poor and over-indebted and puts money into museums and art. Because being a failing city means hosting a set of connected people that are essentially not able to survive in the city ecosystem and must reach outward. If those people are smart, they make the connection and survive. MOre likely if they and the city are not smart, both fail and are mediocre.
Samples of successful cities include New York (financial, real estate, stock markets, etc.); Seoul (home of chaebols with worldwide reach); Tel Aviv (locally autark innovation capital).
A trans-city then is a collection of cities who together create a more successful city, just without being geographically local. A tier 1 trans-city being a collective of cities who host a set of tier 1 extended pure play clusters and who align their policies, etc. in a way to maximize the efficiency of the extended pure play clusters. Think German automotive supply chain networks in the South of Germany. Or the Silicon Valley (a geographically localized trans-city).
While all those concepts are not from Jane Jacobs, the concept of the city and its crucial impact on society is. Combing back to Manuel Castells, he wrote about New York, London and Tokyo being the prime financial “hubs” which push money and access to capital to their regional branches. Things certainly changed a bit since Castells wrote about it. But the Core Network to peripheral network architecture still works more or less. These network architectures among cities around key “topics” that would form “simple pure play” networks still make sense. And the fact that such simple networks focused on isolated topics still form such hub-and-spoke networks is indicative for human personal networks driving the design such networks. Which again is something that makes it both random and also supports the idea that taking control over these network formations is somethign that cities should focus on and being something that cities do focus on. So it is an object worth studying.
But the central elements went down in this argument. The one element being the “tier” or level of quality of city networks. The other being
The level of quality here can be understood by comparing the Wealth in New York’s top families to that of let’s say Frankfurt Germany’s top families. While this is an object of study for sociologist and papparazis, the impact of this is more substantial. And more felt in the Silicon Valley. The amount of local wealth and give back make the region attractive. The amount of discrimination against outsiders – how much Valley money does flow into Turkish entrepreneurs?  – does, too. And looking at the level of competitiveness for outsides in New York banking, law, real estate versus the level of competition in Sao Paolo is again substantial.
Summing up this part.
Proximity networks: The 3rd economy or the city economy is the economy that is created via proximity of interest, capability and geography that creates exchange, transaction and opportunity. In other words: economic activities do not really start and live in “economies”, or in “industries”, but happen mostly in “cities”. Even if city looks like an outdated concept. In 18th century London and New York versus other cities it certainly was a very relevant and clear concept. And the geographic proximity appears to still create more focused and value-igniting environments than long-distance relationships. Which are for the investors and less for the maker.
But even if abandoning “proximity” and the idea of “cities”, the nodern terms of clusters and ecosystems are just as good. Ecosystems can be geographically dispersed, but they are community-ational enough to form unity that operate similar to the “city” concept in Jacob’s work.
Geographic Networks: the picture shifts from a-geographic and network driven evolution towards a clear geographic strategy. Natural resources are where they are. Logistic capacity, tax and trade systems play a role in optimizing network flow problems and overall everything culminates in geographic areas somewhere along the value chain. Whether dense urban areas provide excessive access towards consumption power – distributing fashion chains among key urban hotspots – or provide a signalling effect as value chain core hotspots – tech in Silicon Valley, banking in New York, fashion in Milan, tech manufacturing in Shenzen – or are merely hotspots in the upstream and associated services – Singapore in some sense in the global fullfillment sector, Hong Kong/Shenzen in China-based exports. Cities dominate in their own aspect and form their own hub-and-spoke architectures either consuming or distributing flows. Cities combine their local elites and key influencers who leave their social network status on a global scale to contribute to the local ecosystem of the geographically centered network architecture. Service and technology innovations mostly happen in such areas and not in isolated hubs, unless a clear systematic issue can be observed. The forces behind the dynamics is clear: integrate the tax base of the region/national state and use welfare distribution to create attraction for specific human resource pools to then create incentives for building a local culture and specialization and drive what Jane Jacobs called import replacement, or what we understand as comparative advantage in the human resource pool.
The concept is somewhat clear and recently has been promoted by the “Silicon Valley export” model. The concept of providing a regional density of core effectuators of an industry – the core driver of the value chain – in a single region and building a cohesive group dynamic among key factors that add to the success of the effectuators. Leland talked about specializations in fashion, finance, automobile, manufacturing, trade and distribution and leadership is signalling.
The core issue is to understand that human resource manufacturing in the form of higher education and signal-strong target universities and its inter-relation with financing and business incubation capability and the ability to market to the total TAM all fall into the city networks economy, but that they only become fruitful if the city development is capable of providing a social network economy dominance. Something that happened in Israel, Beijing and the Valley, and did not happen in the EMEA region, the wider ASEAN, LatAm or African region. Reasons probably are manifold from lack of governance and institutions to lack of integration of regional interest via economically unfavorable isolation of national interest in local party systems.

The information economy:

The final economy is the internet or free information ecomomy. It defies the dynamics and discriminating effects of both the network and city economic world and basically provides a first global economic good which also defines the required financing and support from any national interest. Anyone can add and extract value.
While this is still young, the core goal here will be to create short-term transactional relationships and the economic rent they provide.
Example: Assuming the creation of a product P requires 100 people to do tasks A to Z over time. The completely decoupled system would be that 1 person is working on on letter from A to Z at any point in time. And because n people choose to do so over time, the product is being created. Every individual is acting in complete isolation of everyone else and the motivation to do any letter X is independent of the value or “vision” of the product P, but merely defined by the price of value of his contribution at the time t when he/she/heshe/shehe/it is performing the task.
In essence, that is what the current system is telling us. Any action is an atomic action to a set of things that can be derived from a series of atomic actions, etc. etc. that have a price which refers to eternal rent of a product being created by nebulous activity, etc.
Just think about the world as the text of the Talmuth. And every human being can randomly shift any letter at any time. That is the atomic, zero-contract evolution of information society. And if let’s say K people change the right letters at the right time and the K+1th person reads the current information at the right time, too, a new insight is created and life rewards for the insight by chancing the course of history. Etc.
How can society maximize the creation of such insights to stear the world to a course of history that is most beneficial. Etc.
Ignoring the esoterics here, the information society is one where nations, industry dynamics and people networks do not matter any more for the creation of value and rent from that value. Something that is on the rise. But probably – due to political aspects and due to violence and human nature – will not become a dominant mode of operation as of right now.

Where is the alpha case?

So yeah, the four economies concept is about understanding how four different and distinct economies are operating. And acknowledging that their rules and regulation takes place in different contexts. And if “regulatory” or rule shocks enter an economic system, there is usually an alpha play if you predict it. Nothing more or less is revealed in the insider and prop trading concepts in the TV show billions. Whether you are paying homeless people to watch whose corporate CEOs are visting Wachtel, Rosen, Lipton & Kratz, or you are counting trucks parked at a Chinese lumber factory, or you are calling or wiretapping the entire front desk secertaries of corporate Korea, you are obtaining information that will impact the economies above. Changing supply chain deals, changing interests voiced in a regional hub, etc. Classic alpha.
But Jane Jacobsons Life and Death of the American City also allows us to look at intermediary time period plays on macro and segment performance. Who is wooing the economically useful millenials to undergrad education and where are they moving after their Bachelors? What about grad school entry requirements and where are those folks moving? On local, regional, national, supra-national and global level? Yes, US banks might hire Tsinghua grads. But is Walmart? What about Aldi? What about Generali? Is Albibaba hiring ETH folks? What about RWTH folks? What about Sorbonne?
How are the dispersion and percolation statistics of people from different ecosystems within organizations? What economic rents are captured and distributed to peers? Or is everyone running a solo game? Which HR department on this planent is hiring truly diversified and supresses all network formations based on heritage, university network, etc.? Yes, noone. And what does this mean in the distributions of rents and margins?
If you find predictors of combining skills and experiences based on life journey and experiences, and its impact on competitive performance, you look at another alpha case.
Clearly, you will have no agent buying and investing in an entire loosely coupled global supply chain from raw materials to B2C end products. So you won’t look at distributing Harvard Law Grads in the toy manufacturing supply and value chain around Mattel. But what’s the play here? And what combinatins lead to bad reviews on Glassdoor and how do glassdoor reviews result from clear and powerful social dynamics in firms? Based on heritage and educational history of key employees? Or is this all differentiated into elite / management and workforce hiring and is it only workforce leaving reviews?
Thinking about the mind plays above, and moving from investor alpha to governmental alpha… what does a local community, a city, a state or a nation have to do to attract alpha potential? And what does alpha potential in a social system or geographic or national ecosystem have on liquidity flowing to it and what does liquidity have to do with returns and capital growth?
Again coming back to Jane Jacobs and the concept of cities and city networks of drivers of innovation, growth and so forth. Is it not unnatural to assume:
1) nation states don’t control supply chains or human capital networks and movement
2) within industry supply chains, nodes are competing so hard, that they are not really looking to invest into such HR plays. They are busy on margins and bargains and safety of delivery.
3) Information economies too immature to go anywhere.
4) The city network is the network where people form value-added relationships and “transcend” status quo. High skilled labour defecting from institutions to build their own. Tapping into capital supply and financial intermediaries. Taking on risk to be held by portfolio bag-holders. All in the same city.
So cities work. For innovation.
Case in point – Amazon in New York City
Just think about Amazon moving to New York City at massive tax cuts. The FTEs getting premium salaries fuel local service businesses with cash and generate taxes that otherwise were nil. The educational resources locally will increase in placing talent, making the instution more attractive, attractive more future tax streams to the region, increasing real estate demand and prices, increasing taxes on rental incomes, etc. etc. etc. The choice is tax impactful.
With taxes comes more budget for subsidies and support systems, which attracts more lower income and mid income people. Increasing tax income again. Etc.
With increasing population quality and increasing talent pool. more companies are incubated and relocated to the vicinity, having more positive tax impacts. Giving more tax money to the local governance bodies. Etc.
It is a self-sustaining system on the local city level.
With a high power “throughput” society in the city, and by the very nature of cities being cities, supply networks to large cities (=other cities) get to bid for access to the supply networks. With potential to increase tax income. And participate in the same dynamics as above. Creating co-dependence or at least uni-directional dependence of the supply city to the mega city. Classic supply network game.
The entire case creates new “alpha” for all cities involved! Why? The total average of human capital in society remains static. Output remains static for every individual. No impact on the net expected production per capita. But with network effects in the region or geograhy that is non-replicable to imitators, we are looking at classic alpha. Those alpha rents go in large portions to investors of those local ecosystems. Only taxes are going back to the general public.
 
From cities back to industry and supply chains
Moving the supply chain closer together increases proximity-based alignment and overall coherence and alignment. Reducing friction.
But it creates entry barries – # of companies competing in value chain spots within distance – with positive and negative effect on talent supply – local talent capacity limitedand bleeding to rivalling industries increasing bargaining power and cost of talent, etc. vs. locally rigid talent supply within distance regions (e.g. 200 miles).
Complexity increases quickly when looking at physical goods supply chains. In information supply chains, less relevant. Dispersed and optimized for comparative advantage wins over unit economic costs, but locally dense wins in per capita output if and only if talent quality and density is high (enough).
 
And forward to national economies
Taking the above to the national economics, the game is simple: take thought and care into assembling networks in cities. AS a nation and state, move nation and state building to building cities and ecosystems. Don’t care about local prideand local interests, but design top-down from national interest.
The ability of a national economy to create GDP growth should be driven by its capabilitytgo design and support cities that nurture the right transactions. And using those city network architectures to assembly supply of human capital from technical and engineering talent to business prodigy and financial power. All that Jazz.

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