 I've lived the life of an economist thinking about how the world works and as a venture capitalist deeply engaged in changing how the world works. This course on venture capital and the economics of innovation derives from my book, Doing Capitalism and the Innovation Economy, now in its second edition. The course explores the history of economic development through technological innovation, using the history of professional venture capital to identify the complementary roles played by the mission driven state and financial speculation. In mobilizing capital to finance investments whose economic value cannot be known in advance. This course is predicated on the fundamental idea that history matters, that the meaning of observable facts is always and everywhere context dependent and that context evolves historically. This is not the dominant view in the Silicon Valley of the mind where today's digital entrepreneurs mostly dwell. Anthony Lewandowski is an engineer who led Google's Waymo Autonomous Vehicle Project when he departed with Google's intellectual property for Uber, Google pseudom. In fact, he's now serving 18 months in jail. For the question I would ask, looking at this quotation from the New Yorker interview with him, is whether the crime of intellectual theft was worse than the crime of intellectual ignorance. At the technological frontier, success is achieved by trial and error and error and error. Innovation at the frontier necessarily generates what I call shampaterian waste. Excessive focus in the allocation of resources will inhibit innovation and from time to time actually serve as the enemy of innovation. Here, it's Darwin's vision of evolution under selection pressure that is most relevant. This is an environment in which the various purposeful participants are doing the best they can to survive and grow. But it's not an environment in which the, quote, optimal inter-temporal allocation of resources is a meaningful concept, nor is it one where future returns from investment can be credibly, quantitatively evaluated in advance. How can you optimize a utility function that ought to include goods that have not yet been invented? How can you maximize profitability when the market you wish to serve has not yet been created? Evolutionary processes appear to be random. But since 1750, there's been a positive drift based on advances in scientific understanding and the cumulative accumulation of technological inventions. It's possible to identify through this history a succession of general purpose technologies that have defined techno-economic paradigms, steam, electricity, the internal combustion engine, computers. Carlotta Perez has developed a partitioning of history from the onset of the first industrial revolution through to the present. She positions us today somewhere more than halfway through the fifth great surge of development driven by technology. Note that a critical regime change outside of Perez's schema from small state to big state capitalism occurred during the fourth surge driven by the response to the Great Depression and World War II. We will return to this structural shift in due course. Perez identified a recurrent pattern in each of these waves of innovation characterized by a bubble of financial speculation that accelerates the development and deployment of the new technology, what I term a productive bubble. At the frontier, all of the actors, entrepreneurs, investors, policymakers, workers and consumers are subject to the same condition of necessary unavoidable ignorance as to the future consequences of their decisions. Keynes summarized this in uncompromising terms when he summarized the message of his great work, the general theory of employment, interest and money. By uncertain knowledge, I do not merely mean to distinguish what is known from what is merely probable. The sense in which I am using the term is that in which the prospect of a European war, he was writing in 1936, is uncertain, or the price of copper and the rate of interest 20 years hence, or the obsolescence of a new invention, or the position of private wealth owners in the social system in 1970. About these matters, there is no scientific basis on which to form any calculable probability whatever. We simply do not know. This is a statement of ontological uncertainty, not a function of the limits of our brains or the uniqueness of specific events. The latter is the source of uncertainty for Frank Knight. Our ignorance of the future is a simple, inescapable result of the way the universe is, as most succinctly captured by the second law of thermodynamics. The historian John Lewis Geddes puts it well. The trouble with the future is that it is so much less knowable than the past because it lies on the other side of the singularity that is the present. All we can count on is that certain continuities from the past will extend into it and that they will encounter uncertain contingencies. When it comes to the actions people themselves choose to take, though, when consciousness itself becomes a contingency, forecasting becomes a far more problematic exercise. Yet as Keynes well understood, we nonetheless must retain the capacity for action. Keynes here invokes exactly the same enabling factor, the convention that the world will stay the same until we have sufficient evidence that it won't. As did the great Scottish philosopher David Hume 150 years before, albeit without acknowledgement from Keynes. Harvard's Richard Zeckhauser has neatly charted the different categories of knowledge of the future, from risk with known distributions of probabilities, through uncertainty with unknown distributions of known possible states, to Keynes's ignorance where we don't even know the possible future states of the world. Yet it is this last domain, especially when the context is historically unique that the great investment returns have been made. No one can address the economics of innovation without taking account of Joseph Schumpeter and his central message, economic evolution through creative destruction. Schumpeter emphasizes discontinuities in the competitive process, competition not in kind. Note that Schumpeter does not explore the systems of innovation upstream from commercially motivated enterprises and entrepreneurs. But over the course of a generation, he presented two very different models. From 1912, Schumpeter Mark I. This is all about new firms and new men. Note that in the heart of the Second Industrial Revolution, characterized by capital intensive process industries such as steel and chemicals, innovation is expressed through new lower court processes, not new products. By 1943, Schumpeter reversed himself into his Mark II version. Innovation has been transformed into a bureaucratic routine operated by giant established firms. In its context, this was understandable and relevant for a short generation, but it has proved to be utterly misleading in our contemporary world. And in the midst of the war which would transform the state's role in the innovation economy, Schumpeter had only disdain boarding on contempt for the state's interventions. Schumpeter Mark II persisted for 30 years with innovation driven by the great central research laboratories of the giant monopolies, AT&T, IBM, Dupont, General Electric. But from 1980, the structure of the American innovation has been transformed into what might be termed Schumpeter Mark III, characterized by a division of innovative labor. Recently, two scholars have revisited Schumpeter's models, his two different models, through rigorous empirical analysis, separating out exploration for new products and markets from exploitation of established competitive positions. AXAJET and CUR indeed find that it is small new firms that most contribute to economic growth through successful exploration, versus the established firms focus on exploitation of technology that already exists. Now one final introductory thread should be introduced here. This course concerns innovation at the frontier of technological advance and scientific knowledge. But the vast majority of people live in societies more or less removed, far removed from the technological frontier. Historically, the dynamics of the innovation economy have been radically different for those followers who seek to catch up and reach the frontier. They appropriate existing intellectual property, they designate national champions, they are exposed to systemic corruption, and most of them fail to reach the frontier in their efforts. As Agyan and Howard point out, citing pioneering work of Alexander Gashankron, in principle, followers should be able to grow more rapidly than those already at the frontier by adopting the technology that has already been developed and proven. But it is very challenging for effective followers to become frontier innovators, even if they overcome the corruption tax on growth. The institutions that get them to the frontier may be barriers to innovation at the frontier. Successful copiers need an entirely different context to become effective inventors. Until recently, the few successful followers of the original leader, Great Britain, have all had to recapitulate the entire history of industrial development from textiles through light and heavy manufacturing to the science-based industries of the late 20th and 21st century. This was true of the United States, of Germany, Japan, Korea, and China. But as Daniel Bresnitz and John Zisman have documented, the digital revolution has opened up new selective paths to the frontier. Instead of having to replicate entire industries, follower nation states can enter the global economy by attacking one or other of the components of transnational supply chains. Taiwan did so in semiconductor fabrication, Israel in software research and development. And the supply chain needed not exist only to produce physical goods. Productized IT enabled services have similar decomposed characteristics, as demonstrated by the Indian information technology industry and its outsourced role in the supply of software to the world. But now the question arises, how does this innovation get financed? Schumpeter proposed another division of labor between the entrepreneur and the financier. Note how he says the entrepreneur loses other people's money. That's a note of warning to venture capitalists down the generations. When capitalists scarce, the dynamic relationship is often characterized as the golden rule. He who has the gold rules. As we'll see in lecture three in the context of the ongoing, though staggering, unicorn bubble. That rule seems to have been stood on its head in recent years. At the frontier, financing innovation necessarily must escape from the narrow confines of conventional finance theory, where share prices are specified to represent economic fundamentals. In fact, share prices are far more volatile than cash flows, as the Bank of England's Andy Haldane pointed out a decade ago. And at the frontier, it is scarcely possible to estimate the economic fundamental with any confidence. In the vast majority of cases, the prospects of investment projects, the stream of future returns cannot be understood in standard probabilistic terms. This is obviously true for investments in innovative products and processes for which estimates of returns cannot be based solely on the profit history of existing products and processes. Let me repeat, at the frontier, we are necessarily investing in ignorance, where the substantive rationality of conventional neoclassical economics is simply not available. The great social scientist Herbert Simon made the useful distinction between substantive and procedural rationality more than a generation ago. And a long generation before Simon, Keynes introduced the beauty contest as the metaphorical setting for investors doing their best to make money in the stock market. Here, procedural rationality, as represented by close observation of other investors, reflects the hope of anticipating, or at least not missing, the movement of the crowd. Note that in the markets today, dominated by index funds including exchange-traded funds, momentum investing is even built in as a dominant strategy by contract. Guessing which way the market's going to move is no longer an individual responsibility, it's built into the mathematics of the funds in which investors invest. The potential for standing out against the crowd, the contrarian investing, the Warren Buffett style, if you like, has become rare to vanishing. Keynes went further. He constructed a bridge between what occurs in the financial markets and the future developments in the real economy. Keynes accurately foresaw both the modern buyout business, quote, there is no sense in building a new enterprise at a cost greater than that at which a similar existing enterprise can be purchased. And he also identified how the incentives to launching new ventures generated by a hot IPO market can drive innovation, providing, quote, an inducement to spend on a new project, what may seem an extravagant sum if it can be floated off on the stock exchange at an immediate profit. Innovation does not take place in a macroeconomic vacuum. The state of the macroeconomy conditions investment in risky ventures. Recessions can stifle invention even as they force laggards to adopt proven innovations in order to meet the competitive conditions of slack final demand. A shortfall of aggregate demand creates unused resources and undermines potential growth on the supply side of the economy. This is what I've called counterproductive Keynesian waste, the waste of unused human and physical and intellectual resources. I came up with that insight as a way to conclude my book and then discovered, as I have all too often, that Joe Stiglitz had had the same idea and formalized it some 20 years earlier. The economic downturns have long run consequences, Stiglitz wrote, with lower expenditures on R&D and lower levels of investment and production resulting in less learning, the growth path of the economy is shifted down. Short-term Keynesian waste generates long-term social costs in terms of slower growth. Plus, the social cost of layoffs exceed private savings to the former employer and the social benefits of foregone R&D exceed the private benefits to the firm. We will consider this sort of market failure in detail in lecture four. My own vision of the innovation process is set out on the first page of my book. The innovation economy begins with discovery and culminates in speculation. Over some 250 years, economic growth has been driven by successive processes of trial and error and error and error. Upstream exercises and research and invention, downstream experiments and exploiting the new economic space opened by innovation. Each of these activities necessarily generate much waste along the way. Dead-end research programs, useless inventions, failed commercial ventures. That's shumpertary and waste. In between, the innovations that have repeatedly transformed the architecture of the market economy from canals to the internet have required massive investments to construct networks whose value and use could not be imagined at the outset of deployment. So at each stage, the innovation economy depends on sources of funding that are decoupled from concern for economic return. But how was and is innovation at the frontier financed when it's impossible to know what the returns will be in advance? Again, let's take a look at the stages of technological transformation step by step. Since World War II, financing upstream science has become an acknowledged responsibility of the state. The model for which first emerged in Germany and France in the second half of the 19th century as they attempted to catch up with Britain. We can observe multiple modes of funding, the really chunky investments needed to build transformational infrastructure. But whether the public or private sector delivers the preponderance of the cash, such investments always have involved, have required state sanction. Downstream, financing the Darwinian exploration of novel applications of the new technological infrastructure has been delivered primarily by financial speculation. At the frontier, the effort to calculate and rank the current economic value of investments will inevitably favor the less uncertain, shorter term projects over those that, unlikely as each may appear, nonetheless collectively have the potential to change the world and create a new economy. This is why, again, overriding concern for efficiency in the allocation of resources is the enemy of innovation. Thus, examining the historically observable dynamics of the innovation economy reveal how the complex interaction of a mission-driven state and financial speculation have repeatedly combined to transform the market economy. Their dynamic interaction is what I call the three-player game. Like the three-body problem in physics, as the players reciprocally react on each other, reflexively, as George Soros put it, no stable equilibrium can ever exist. In the next two lectures, we will explore in depth how venture capitalists played their role in this game and how evaluating their performance can provide profound insight into the roles played by the mission-driven state and financial speculators.