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Time, Space and Capital

Åke E. Andersson and David Emanuel Andersson

In this challenging book, the authors demonstrate that economists tend to misunderstand capital. Frank Knight was an exception, as he argued that because all resources are more or less durable and have uncertain future uses they can consequently be classed as capital. Thus, capital rather than labor is the real source of creativity, innovation, and accumulation. But capital is also a phenomenon in time and in space. Offering a new and path-breaking theory, they show how durable capital with large spatial domains — infrastructural capital such as institutions, public knowledge, and networks — can help explain the long-term development of cities and nations.
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Chapter 7: Expectations, capital and entrepreneurship

Åke E. Andersson and David Emanuel Andersson

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Expectations of the future as influenced by a recent time series of returns tend to have the greatest influence on the value of capital. Most models of capital valuation employ the assumption that investors in capital make decisions that include a trade-off between risk (also known as “probabilistic uncertainty”) and expected returns. The so-called “CAPM” and “APT” models that we discuss in this chapter posit that investors optimize their portfolios of capital by minimizing risk subject to some required expected return. These procedures are applicable in situations of probabilistic uncertainty where the securities and other assets have a well-documented and uneventful history and other transparent characteristics. However, measures of statistical risk are no more than guesswork in the structurally uncertain situations that are associated with new start-ups and firms that specialize in disruptive product innovations. Uncertainty in this Knightian sense implies a set of possible future outcomes that is open-ended; there is no way to know how many possible outcomes should be listed as feasible. There is thus no structure that allows investors to make use of subjective probabilities in any meaningful sense. Optimism bias is common in situations of structural uncertainty, according to numerous empirical studies. This bias is particularly common when the stakes are high, such as when investment decisions involve start-ups or mergers and acquisitions. In this chapter we also discuss different theories of entrepreneurship before arriving at our conclusion, which is that Frank Knight’s entrepreneurship theory—with ownership, uncertainty and judgment as catchwords—is especially useful as a theoretical foundation for understanding dynamic markets. It is possible to extend Knightian theory in various directions, for example by integrating processes of adaptation and learning along the lines of Brian Arthur’s work. The aggregation of capital into a macro entity is another problem that we address in this chapter. We conclude that the only logical way of measuring macroeconomic capital is using the expectation-derived valuations of firms that stock markets and real estate markets continuously provide to market participants.

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