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åke E. Andersson, David Emanuel Andersson, Björn Hårsman and Zara Daghbashyan

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Edited by David Emanuel Andersson, Åke E. Andersson and Charlotta Mellander

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Edited by David Emanuel Andersson, Åke E. Andersson and Charlotta Mellander

With the publication of The Rise of the Creative Class by Richard Florida in 2002, the ‘creative city’ became the new hot topic among urban policymakers, planners and economists. Florida has developed one of three path-breaking theories about the relationship between creative individuals and urban environments. The economist Åke E. Andersson and the psychologist Dean Simonton are the other members of this ‘creative troika’. In the Handbook of Creative Cities, Florida, Andersson and Simonton appear in the same volume for the first time. The expert contributors in this timely Handbook extend their insights with a varied set of theoretical and empirical tools. The diversity of the contributions reflect the multidisciplinary nature of creative city theorizing, which encompasses urban economics, economic geography, social psychology, urban sociology, and urban planning. The stated policy implications are equally diverse, ranging from libertarian to social democratic visions of our shared creative and urban future.
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Åke E. Andersson and David Emanuel Andersson

The games of markets including entrepreneur-driven economic development have always taken place on an arena of the combined material and non-material infrastructure. The infrastructure thus constitutes the arena; it is public capital that facilitates and constrains the rapid “games” of buying and selling that economic agents play. Agents perceive the arena as stable because its evolution is so much slower than that of markets for goods and services. Synergetic theory is well equipped to handle such multiple timescales. Its application to economic phenomena enables us to show that competitive equilibrium theory requires prior specification of the infrastructural arena, which consists of public knowledge, space-bridging networks and institutions. Synergetic theory can also help us avoid the pitfalls of conventional macroeconomic theory. In this chapter, we demonstrate how macroeconomic equilibrium depends on the infrastructure. We claim that all goods are durable and are thus instances of capital. This means that historical trajectories, current outcomes, uncertain expectations and changes in spatial accessibility all influence the growth and fluctuations in the value of capital goods. Dynamic non-linear interactions between scientists, inventors and entrepreneurs affect investments. New technological or design ideas spread most easily among spatially proximate firms within communication and transport networks. Such network effects shape processes of spatial clustering, agglomeration and urbanization. Based on causal and various econometric considerations, it has been common for economists to resort to difference equation in their modeling strategies. But if we include dynamic interactions within a system of difference equations—so as to accommodate realistic causal assumptions—it will often result in complex models with chaotic outcomes. However, there are ways out of chaos in economic modeling. The first is to focus on continuous dynamic synergetic models, which implies a careful separation of variables and dynamic processes according to their relevant timescales as well as the collectiveness of their impacts.

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Åke E. Andersson and David Emanuel Andersson

Classical economists such as Adam Smith, David Ricardo, John Stuart Mill and Karl Marx introduced the concepts of time and capital to economics. They developed the labor theory of value, thereby assuming that the historical process of accumulated labor would determine the value of capital goods. By the end of the nineteenth century, a number of economists had started to question this approach to capital theory. Carl Menger proposed a completely different theory, focusing instead on the role of expectations. He used this new theory as an argument against the labor theory of value; the subjective preferences of consumers rather than labor inputs were for Menger the ultimate source of economic value, including the value of capital. According to Menger, historical circumstances have made goods available in the present, and these circumstances mostly reflect producers’ expectations of future profits. Subsequently, Eugen von Böhm-Bawerk and Knut Wicksell formulated dynamic models that showed that the expected future flow of returns would determine the value of capital. They linked this to an optimality condition that required the expected growth rate of the capital value to equal the interest rate on loanable funds. In this chapter, we show that markets for works of art offer an especially lucid illustration of the importance of expectations and the irrelevance of labor inputs. Frank Knight was the first economist to analyze the structural uncertainty of long-term expectations, while Irving Fisher showed that the credit market is essential for investors in real capital. Fisher suggested the possibility of using a two-stage decision process. In the first stage, the investor would aim to maximize the expected value of a project. The second stage would make the investor aim at an optimal solution by becoming a borrower in the credit market. Wicksell and later John Maynard Keynes modeled the dual problem of an equilibrium interest rate and another interest rate that arises within the banking system as a cause of inflation or unemployment. Only much later was this to become the main concern of central banks.

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Åke E. Andersson and David Emanuel Andersson

Trade across space is central to economic theory. Trade presumes the existence of a transport system. Already in the eighteenth and nineteenth centuries, economists such as Adam Smith and David Ricardo elaborated upon the gains from trade between two nations. It was the Law of Comparative Advantage in production that explained the gains from trade, according to Ricardo. Eli Heckscher and Bertil Ohlin reformulated Ricardian trade theory by treating spatially trapped resources in different locations as the root cause of the existence of comparative advantages. Their treatment of space-bridging frictions remained implicit, however. Stella Dafermos and Anna Nagurney addressed this neglect by transforming older theories of international trade into a very general class of network-based interregional models of trade and transportation. These were the so-called “variational inequality models.” The German economist Johann Heinrich von Thünen developed an early spatial alternative to mainstream trade theory. In 1826, he formulated a complete general equilibrium theory of transport, location, land use and trade in a continuous one-dimensional model. In the second half of the twentieth century, Martin Beckmann and Tönu Puu showed that von Thünen’s model is applicable to two-dimensional continuous space. Spatial economic theory, which in principle includes all theories of international and interregional trade, has evolved over time. Early implicit models evolved into models with discrete systems of regions and then into models with continuous one- or two-dimensional space. However, all of these theories and models assume the prior existence of a transport system. In this chapter we show that economic actors create networks of nodes (towns) and links (trading routes) because they expect various advantages to arise due to new opportunities for trade. Such network creation is a type of entrepreneurship that exhibits consequences that are unusually collective. Hence agglomerations of people and productive activities reflect accessibility differences and these differences are associated with unequal internal and external scale economies. We also show that there is a self-organizing process of network creation that makes cities more efficient over time.

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Åke E. Andersson and David Emanuel Andersson

Linear and linearized equations dominate economic and econometric modeling. The gains in terms of solubility and interpretation are considerable. However, important phenomena such as social interactions are then at best subject to informal treatments and at worst relegated to the class of supposedly irrelevant phenomena. This chapter explores the potential of non-linear dynamic theories and models of growth and development. We discuss examples of non-linear phenomena that are amenable to formal analysis such as the spread of infectious diseases, segregation processes and imitative behavior. Multiple equilibria occur frequently in non-linear models. One example is the Kaldor model of business cycles; another is Mees’s model of urban growth and decline. Analyzing the stability of models is central to the study of economic dynamics, where the dynamic stability of an equilibrium requires negative feedback. From the 1960s onward, structural stability became a recurrent catchphrase in dynamic analyses. In this chapter we claim that structural instability is a precondition for creativity in the development of new ideas in science and the arts. It is generally only possible to achieve a new stable equilibrium in conjunction with the completion of a creative process. Realistic dynamic economic models tend to contain a mixture of positive and negative feedback loops, leading to chaotic outcomes. One consequence is deterministic and stochastic processes become indistinguishable in practice. It is for this reason that Benoit Mandelbrot claimed that most “financial analyses” are spurious applications of stochastic theory to situations where fractal models would yield better pattern predictions.

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Åke E. Andersson and David Emanuel Andersson

The duration of human life has been increasing steadily in most parts of the world for at least the past 50 years, and in many cases over a much longer time period. The well-known Preston Curve shows that the material standard of living as reflected in per capita real income is associated with the mean life expectancy, but with a weaker association at high levels of income. In this chapter we discuss the impact of a consumer’s choice on his or her life expectancy. In affluent societies, lifestyle choices have much greater effects on individuals’ lifespans: people have more discretionary income and infectious diseases are less prevalent. Affluent people therefore have far greater control over their own personal life expectancies than people in less fortunate circumstances. Although most people know that the composition of their diet and their drinking, smoking and exercise habits influence their life expectancies, genetic factors and interdependencies among health-affecting choices make such effects highly uncertain. Empirical studies nonetheless show that high education elasticities are associated with choices that increase the expected duration of life, perhaps because old age is less unattractive to people who derive utility from cerebral activities. Oeppen and Vaupel have shown that the Preston Curve underestimates long-term increases in life expectancy. We believe that the Preston Curve is shifting upward over time as a consequence of slow but persistent infrastructural improvements to public knowledge, communications and institutions. Our trend analysis of time use implies a long-run reduction of remunerative working time toward levels as low as 1,300 hours per year. This implies that we expect that the time allocated to work will drop to 7 or 8 percent of the 900,000 hours (102.7 years) of life that we expect in the most post-industrial regions in the very long run.

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Åke E. Andersson and David Emanuel Andersson

In this chapter we claim that all goods are durable and in this respect they are all capital goods by definition. Our claim builds on Frank Knight’s analysis: any durable good is capital and must thus have a future return that is intrinsically uncertain. It is this uncertain return that is the subject matter of entrepreneurial judgment, as Knight also explained. But it is not only goods that are capital. Labor is also capital, which is why it makes more sense to speak of human capital. And this, too, reflects uncertain future returns, in this case of investments in education. Even land is capital, since inaccessible land without network links to the rest of the world yields no return: it lacks capital value. The durability of capital and the rate of depreciation are key attributes of capital. Deterministic models show that if households and firms were to optimize these attributes, then the equilibrium growth rate would equal the real interest rate in a multi-good economy. We also show that a good’s durability determines the number of firms and thus the potential market form, in the case that production, transport and transaction costs jointly determine equilibrium. The greater the durability of a good is, the smaller its trading cost will be, other things being equal. Trade will keep expanding until there are no price differences between different locations for the limiting case of extremely durable goods. For goods with extreme durability and low transportation and transaction costs, the law of one market price will thus prevail.

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Åke E. Andersson and David Emanuel Andersson

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.