Abstract
In recent years, researchers from MIT and Harvard University have developed a complexity approach to economic development. This perspective implicitly follows some characteristic elements of the complexity scientific paradigm emerged in the second half of the twentieth century but focuses on a practical application to economic development. As in the more general theory of complexity economics, this Harvard-MIT approach has many points in common with Austrian economics. This paper highlights these similarities, concerning capital theory, entrepreneurship, a knowledge-based view of the economy, organizational capabilities, and economic growth. As a result of these similarities, we also present the policy implications derived from the shared elements of the two currents, which materializes in the idea that the Harvard-MIT approach can adopt the Market Policy Pogramme (MPP), conceived by David Harper as a practical application of the fundamental theoretical principles of Austrian economics.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
Not applicable.
Code availability
Not applicable.
Notes
Hereinafter we will refer to this approach as “the Harvard-MIT approach” and because it comprises many authors, we will use the term “Hausmann et al.” to mention all of them.
Rosser Jr. (2010) states that Hayek held on the idea of equilibrium until 1981, abandoning it in Hayek (2012). However, as Kolev (2010) points out, Hayek moved away from static equilibrium after 1936 (Hayek, 1937), and especially after 1946 (Hayek, 1948b). Therefore, we can place the abandonment of the concept before 1981, specifically, in 1936.
It is worth noting that authors such as Nell (2010) and Seagren (2011) have found ABMs compatible with Austrian economics. Indeed, relevant works such as those of Axelrod (1984, 1997) using computer simulations display a certain affinity to Austrian economics, more concretely Hayek’s works, regarding the focus on cooperative, evolutionary strategies in competition.
It is important not to confuse computational economics with computable economics. The former deals with the logical foundations of using computers in economics while the latter focuses on particular applications and methods (Rosser Jr., 2009b). In this case, since Markose (2005) and Koppl (2009) refer to the similarities between Velupillai (2000) and Hayek, we must use the term computable.
It assumes heterogeneity among agents, for example, concerning the differences among firms or countries in terms of capabilities (Hausmann & Hidalgo, 2011). There is no global controller in their model, but many dispersed interactions between firms through a great variety of entangled networks exemplified in the product space (Hidalgo et al., 2007). They conceive development as a diffusion process over a network of products (Hidalgo & Hausmann, 2008). That network is permanently subject to change which entails agents (firms) continually adapt their behavior (production) according to the changing endowment of capabilities, the introduction of new technology, or the demand for different but related products. Moreover, development implies path-dependencies on the previous structure of the heterogeneous product space (Hidalgo & Hausmann, 2009) or the previous state of productive knowledge (Hausmann et al., 2013), and increasing returns as a country accumulates more capabilities (Hausmann & Hidalgo, 2011). Precisely, Arthur (1989, 1994), as one of the leading figures of the Santa Fe complexity, highly emphasizes both notions of path-dependency and increasing returns. Additionally, the Harvard-MIT approach escapes from traditional views on economic development and creates an out-of-equilibrium model involving nonlinearities: the network changes as a reflection of the market processes underlying the product space.
The concept of productive knowledge is not clear in Hausmann et al. (2013). It is unclear whether the authors mean productive knowledge by the term knowhow or refer to any other concept. They do not define knowhow as such but use productive knowledge and knowhow interchangeably throughout their work. Moreover, whereas Hausmann et al. (2013) state that economic development depends on the accumulation of productive knowledge, Hausmann (2016) states that it depends on the accumulation of knowhow. Even they talk about productive knowhow, which denotes that productive knowledge and knowhow are not the same. Although Hausmann et al. (2013) do not specify the difference between knowhow and productive knowledge, Hidalgo (2015) distinguishes between knowledge and knowhow, and Hausmann (2016) between tools or embodied knowledge, recipes or codified knowledge, and knowhow or tacit knowledge. Hidalgo (2015) finds the source of prosperity in the accumulation of both knowledge and knowhow. He regards knowhow as different from knowledge because the former involves the capacity to act, whereas the latter concerns relationships between entities in which the individual plays the role of a mere observer. More concretely, according to Hidalgo (2015, p. 17), knowhow “is the tacit computational capacity that allows us to perform actions”. Likewise, Hausmann (2016) emphasizes the tacit nature of knowhow, in contrast to the explicit character of knowledge or productive knowledge.
Lachmann wrote that capital goods are heterogeneous because of their use and not due to their physical properties or appearance. Even from a knowledge-based view on capital, Baetjer and Lewin (2011) point out that capital goods are heterogeneous because knowledge embedded in them is it so too.
For the differences between the neoclassical theory and the Austrian theory regarding capital and macroeconomics see Huerta de Soto (1998).
Arthur (1989) holds that a laissez-faire policy can be inefficient to achieve that a superior technology reveals itself and survives in the long run in cases of increasing returns, and therefore proposes the intervention of a central authority. However, it is important to note that while Arthur makes this point within his agent-based complexity framework, Hausmann and Rodrik (2003) reach their conclusion within a general-equilibrium framework, which is epistemologically inconsistent when viewed from a complexity perspective. See Vaughn (1999) for an Austrian, Hayekian, perspective on the market-failure issue as it was raised by some complexity theorists.
The idea of a public policy programme is an adaptation of Lakatos’s (1999) concept of scientific research programme. The hard-core propositions deal with the nature of the world, thus these propositions are regarded as irrefutable by scientists working within the programme. Moreover, these hard-core propositions include positive heuristics, which are sets of instructions to develop the research programme and decision rules for handling problems.
Similar to the MPP, Potts (2019) speaks about innovation commons, which are systems of rules to incentivize cooperation to pool distributed knowledge and other inputs, thus facilitating the entrepreneurial discovery of economic opportunities. From his point of view, innovation is the source of economic growth, and for innovation to take place, an innovation commons is necessary as a governance institution. These commons are more than simply the market; they are institutions spontaneously emerged from cooperation in particular groups, so they do not cover the entire market but certain groups of agents. In this sense, they take a smaller and more concrete form than the market, which can be seen as a more general and vague term. The environment to which Hausmann et al. refer can also crystalize in Potts’s innovation commons, which also constitute an Austrian and Hayekian theory of growth.
References
Arthur, W. B. (1989). Competing technologies, increasing returns, and lock-in by historical events. The Economic Journal, 99, 116–131. https://doi.org/10.2307/2234208
Arthur, W. B. (1994). Increasing returns and path dependence in the economy. University of Michigan Press.
Arthur, W. B. (1999). Complexity and the economy. Science, 284, 107–109. https://doi.org/10.1126/science.284.5411.107
Arthur, W. B. (2015). Complexity economics: A different framework for economic thought. In W. B. Arthur (Ed.), Complexity and the economy (pp. 1–29). Oxford University Press.
Arthur, W. B., Durlauf, S. N., & Lane, D. A. (1997). Introduction. In W. B. Arthur, S. N. Durlauf, & D. A. Lane (Eds.), The economy as an evolving complex system II (pp. 1–14). Addison-Wesley.
Axelrod, R. M. (1984). The evolution of cooperation. Basic Books.
Axelrod, R. M. (1997). The complexity of cooperation : Agent-based models of competition and collaboration. Princeton University Press.
Baetjer, H. (1998). Software as capital: An economic perspective on software engineering. IFEE Computer Society.
Baetjer, H. (2000). Capital as embodied knowledge: Some implications for the theory of economic growth. The Review of Austrian Economics, 13, 147–174. https://doi.org/10.1023/a:1007808618703
Barabási, A. L. (2007). From network structure to human dynamics. IEEE Control Systems, 27, 33–42. https://doi.org/10.1109/MCS.2007.384127
Barbieri, F. (2013). Complexity and the Austrians. Filosofía de la Economía, 1, 47–69.
Chaitin, G. J. (1987). Algorithmic information theory. Cambridge University Press.
Chaumont-Chancelier, F. (1999). Hayek’s complexity. Journal des Économistes et des Études Humaines, 9, 543–564. https://doi.org/10.1515/jeeh-1999-0405
Day, R. H. (1994). Complex economic dynamics, volume 1: An introduction to dynamical systems and market mechanisms. MIT Press.
Dekker, E., & Kuchar, P. (2021). A Mengerian theory of knowledge and economic development. Cosmos and Taxis.
Espinosa, V. I., Wang, W. H., & Zhu, H. (2020). Israel Kirzner on dynamic efficiency and economic development. Procesos de Mercado: Revista Europea de Economía Política, 17, 283–310.
Fiori, S. (2009). Hayek’s theory on complexity and knowledge: Dichotomies, levels of analysis, and bounded rationality. Journal of Economic Methodology, 16, 265–285. https://doi.org/10.1080/13501780903128548
Gaus, G. F. (2007). Social complexity and evolved moral principles. In L. Hunt & P. McNamara (Eds.), Liberalism, conservatism, and Hayek’s idea of spontaneous order (pp. 149–176). Palgrave Macmillan US.
Gleick, J. (1987). Chaos: Making a new science. Viking Penguin.
Harper, D. A. (2003). Foundations of entrepreneurship and economic development. Routledge.
Hausmann, R. (2016). Economic development and the accumulation of know-how. Welsh Economic Review, 24, 13–16. https://doi.org/10.18573/j.2016.10049
Hausmann, R., & Hidalgo, C. A. (2011). The network structure of economic output. Journal of Economic Growth, 16, 309–342. https://doi.org/10.1007/s10887-011-9071-4
Hausmann, R., & Rodrik, D. (2003). Economic development as self-discovery. Journal of Development Economics, 72, 603–633. https://doi.org/10.1016/S0304-3878(03)00124-X
Hausmann, R., Hwang, J., & Rodrik, D. (2007). What you export matters. Journal of Economic Growth, 12, 1–25. https://doi.org/10.1007/s10887-006-9009-4
Hausmann, R., Hidalgo, C. A., Bustos, S., et al. (2013). The atlas of economic complexity. MIT Press.
Hayek, F. A. (1937). Economics and knowledge. Economica, 4, 33–54. https://doi.org/10.2307/2548786
Hayek, F. A. (1945). The use of knowledge in society. The American Economic Review, 35, 519–530.
Hayek, F. A. (1948a). Individualism and economic order. The University of Chicago Press.
Hayek, F. A. (1948b). The meaning of competition. In Individualism and economic order (pp. 92–106). The University of Chicago Press.
Hayek, F. A. (1952). The sensory order: An inquiry into the foundations of theoretical psychology. The University of Chicago Press.
Hayek, F. A. (1963). Collectivist economic planning. Routledge & Kegan Paul.
Hayek, F. A. (1967). The theory of complex phenomena. In Studies in philosophy, Politics and Economics (pp. 22–42). Routledge & Kegan Paul.
Hayek, F. A. (1973). Law, legislation and liberty. Vol. I: Rules and Order. Routledge.
Hayek, F. A. (2002). Competition as a discovery procedure. The Quarterly Journal of Austrian Economics, 5, 9–23.
Hayek, F. A. (2009). The pure theory of capital. Ludwig von Mises Institute.
Hayek, F. A. (2012). The flow of goods and services. In H. Klausinger (Ed.), Business cycles, Part II. The Collected Works of F.A. Hayek (pp. 331–346). University of Chicago Press.
Hidalgo, C. A. (2015). Why information grows: The evolution of order, from atoms to economies. Basic Books.
Hidalgo, C. A., & Hausmann, R. (2008). A network view of economic development. Developing Alternatives, 12, 5–10.
Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences of the United States of America, 106, 10570–10575. https://doi.org/10.2307/40483593
Hidalgo, C. A., Winger, B., Barabási, A. L., & Hausmann, R. (2007). The product space conditions the development of nations. Science, 317, 482–487. https://doi.org/10.1126/science.1144581
Hoefman, K. (2020). Live agent-based models
Holt, R. P. F., Rosser Jr., J. B., & Colander, D. (2011). The complexity era in economics. Review of Political Economy, 23, 357–369. https://doi.org/10.1080/09538259.2011.583820
Horgan, J. (1997). The end of science: Facing the limits of knowledge in the twilight of the scientific age. Broadway Books.
Huerta de Soto, J. (1998). The ongoing Methodenstreit of the Austrian school. Journal des Economistes et des Etudes Humaines, 8, 75–113.
Huerta de Soto, J. (2010). Socialism, economic calculation and entrepreneurship. Edward Elgar Publishing.
Kaufmann, S. A. (1993). The origins of order: Self-organization and selection in evolution. Oxford University Press.
Kiesling, L. (2015). The knowledge problem. In C. J. Coyne & P. J. Boettke (Eds.), The Oxford handbook of Austrian economics (pp. 45–64). Oxford University Press.
Kilpatrick Jr., H. E. (2001). Complexity, spontaneous order, and Friedrich Hayek: Are spontaneous order and complexity essentially the same thing? Complexity, 6, 16–20. https://doi.org/10.1002/cplx.1035
Kirzner, I. M. (1966). An Essay on Capital. Augustus M. Kelley.
Kirzner, I. M. (1988). The economic calculation debate: Lessons for Austrians. The Review of Austrian Economics, 2, 1–18.
Kirzner, I. M. (1992). The meaning of the market process: Essays in the development of modern Austrian economics. Routledge.
Kirzner, I. M. (2013). Competition and entrepreneurship. Liberty Fund.
Kolev, S. (2010). F. A. Hayek as an ordo-liberal. HWWI Research Papers.
Kolmogorov, A. N. (1968). Three approaches to the quantitative definition of information. International Journal of Computer Mathematics, 2, 157–168. https://doi.org/10.1080/00207166808803030
Kolmogorov, A. N. (1983). Combinatorial foundations of information theory and the calculus of probabilities. Russian Mathematical Surveys, 38, 29–40. https://doi.org/10.1070/RM1983V038N04ABEH004203
Koppl, R. (2000). Teaching complexity: An Austrian approach. In D. Colander (Ed.), The complexity vision and the teaching of economics. Edward Elgar.
Koppl, R. (2006). Austrian economics at the cutting edge. The Review of Austrian Economics, 19, 231–241. https://doi.org/10.1007/s11138-006-9246-y
Koppl, R. (2009). Complexity and Austrian economics. In J. B. Rosser Jr. (Ed.), Handbook of research on complexity (pp. 393–408). Edward Elgar.
Koppl, R. (2018). Expert Failure. Cambridge University Press.
Koppl, R., Kauffman, S., Felin, T., & Longo, G. (2015). Economics for a creative world. Journal of Institutional Economics, 11, 1–31. https://doi.org/10.1017/S1744137414000150
Lachmann, L. M. (1976). From Mises to shackle: An essay on Austrian economics and the Kaleidic society. Journal of Economic Literature, 14, 54–62.
Lachmann, L. M. (1978). Capital and its structure. Sheed Andrews and McMeel.
Lachmann, L. M. (1986). The market as an economic process. Basil Blackwell.
Lakatos, I. (1999). The methodology of scientific research Programmes, volume I. Cambridge University Press.
Langlois, R. N. (1992). Orders and organizations: Toward an Austrian theory of social institutions. In B. J. Caldwell & S. Boehm (Eds.), Austrian economics: Tensions and new directions (pp. 165–192). Springer Netherlands.
Langlois, R. N. (1995). Do firms plan? Constitutional Political Economy, 6, 247–261. https://doi.org/10.1007/BF01303405
Langlois, R. N., & Robertson, P. L. (1995). Firms, markets and economic change. Routledge.
Langton, C. G. (1992). Life at the edge of chaos. In C. G. Langton, C. Taylor, J. D. Farmer, & S. Rasmussen (Eds.), Artificial Life II (pp. 41–91). Addison-Wesley.
Lavoie, D. (1985). Rivarly and central planning: The socialist calculation debate reconsidered. Cambridge University Press.
Lavoie, D. (1989). Economic Chaos or spontaneous order implications for political economy of the new view of science. Cato Journal, 8, 613–640.
Lewin, P. (2011). Capital in Disequilibrium: The role of capital in a changing world. Ludwig von Mises Institute.
Lewin, P., & Baetjer, H. (2011). The capital-based view of the firm. The Review of Austrian Economics, 24, 335–354. https://doi.org/10.1007/s11138-011-0149-1
Lewin, P., & Baetjer, H. (2015). The capital-using economy. In C. J. Coyne & P. Boettke (Eds.), The Oxford handbook of Austrian economics (pp. 144–163). Oxford University Press.
Lewis, P. (2012). Emergent properties in the work of Friedrich Hayek. Journal of Economic Behavior and Organization, 82, 368–378. https://doi.org/10.1016/j.jebo.2011.04.009
Loasby, B. J. (1996). The division of labour. History of Economic Ideas, 4, 299–323.
Loasby, B. J. (1999). Knowledge, institutions, and evolution in economics. Routledge.
Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22, 3–42. https://doi.org/10.1016/0304-3932(88)90168-7
Markose, S. M. (2005). Computability and evolutionary complexity: Markets as complex adaptive systems (CAS)*. The Economic Journal, 115, F159–F192. https://doi.org/10.1111/J.1468-0297.2005.01000.X
Menger, C. (2007). Principles of economics. Ludwig von Mises Institute.
Mirowski, P. (2007). Markets come to bits: Evolution, computation and markomata in economic science. Journal of Economic Behavior & Organization, 63, 209–242. https://doi.org/10.1016/J.JEBO.2005.03.015
Montgomery, M. R. (2000). Complexity theory: An Austrian perspective. In D. Colander (Ed.), Complexity and the history of economic thought (pp. 227–240). Routledge.
Nell, G. L. (2010). Competition as market progress: An Austrian rationale for agent-based modeling. The Review of Austrian Economics, 23, 127–145. https://doi.org/10.1007/s11138-009-0088-2
Oğuz, F. (2010). Hayek on tacit knowledge. Journal of Institutional Economics, 6, 145–165. https://doi.org/10.1017/s1744137409990312
Potts, J. (2019). Innovation commons: The origin of economic growth. Oxford University Press.
Rizzello, S. (2004). Knowledge as a path-dependence process. Journal of Bioeconomics, 6, 255–274. https://doi.org/10.1007/S10818-004-2925-5
Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94, 1002–1037.
Rosser Jr., J. B. (2010). How complex are the Austrians? In R. Koppl, S. Horwitz, & P. Desrochers (Eds.), What is so Austrian about Austrian Economics? Advances in Austrian Economics (pp. 165–179). Emerald Group Publishing Limited.
Rosser Jr., J. B. (1999). On the complexities of complex economic dynamics. Journal of Economic Perspectives, 13, 169–192. https://doi.org/10.1257/jep.13.4.169
Rosser Jr., J. B. (2009a). Introduction. In J. B. Rosser Jr. (Ed.), Handbook of research on complexity (pp. 3–11). Edward Elgar.
Rosser Jr., J. B. (2009b). Computational and dynamic complexity in economics. In J. B. Rosser Jr. (Ed.), Handbook of research on complexity (pp. 22–35). Edward Elgar.
Rosser Jr., J. B. (2012). Emergence and complexity in Austrian economics. Journal of Economic Behavior and Organization, 81, 122–128. https://doi.org/10.1016/j.jebo.2011.09.001
Rosser Jr., J. B. (2015). Complexity and Austrian economics. In C. J. Coyne & P. J. Boettke (Eds.), The Oxford handbook of Austrian economics (pp. 594–611). Oxford University Press.
Seagren, C. W. (2011). Examining social processes with agent-based models. The Review of Austrian Economics, 24, 1–17. https://doi.org/10.1007/s11138-010-0128-y
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423. https://doi.org/10.1002/J.1538-7305.1948.TB01338.X
Simon HA (1957) Models of man. John Wiley & Sons Ltd
Simon, H. A. (1991). The architecture of complexity. In Facets of systems science (pp. 457–476). Springer.
Solomonoff, R. J. (1964a). A formal theory of inductive inference. Part I. Information and Control, 7, 1–22. https://doi.org/10.1016/S0019-9958(64)90223-2
Solomonoff, R. J. (1964b). A formal theory of inductive inference. Part II. Information and Control, 7, 224–254. https://doi.org/10.1016/S0019-9958(64)90131-7
Solow, R. M. (1956). A contribution to the theory of economic growth. The Quarterly Journal of Economics, 70, 65–94.
Tucker, W. (1996). Complex questions: The new science of spontaneous order. Reason.
Vaughn, K. I. (1999). Hayek’s theory of the market order as an instance of the theory of complex, Adaptative systems. Journal des Économistes et des Études Humaines, 9, 241–256. https://doi.org/10.1515/jeeh-1999-2-304
Velupillai, K. (2000). Computable economics. Oxford University Press.
von Böhm-Bawerk, E. (1890). Capital and interest: A critical history of economical theory. Macmillan and Co..
von Mises, L. (1935). Economic calculation in the socialist commonwealth. In F. A. Hayek (Ed.), Collectivist economic planning (pp. 87–130). Routledge & Kegan Paul.
von Mises, L. (1998). Human action: A treatise on economics. Ludwig von Mises Institute.
von Mises, L. (2012). Socialism: An economic and sociological analysis. Liberty Fund.
Vriend, N. J. (2002). Was Hayek an ace? Southern Economic Journal, 68, 811–840. https://doi.org/10.2307/1061494
Wagner, R. E. (2010). Mind, society, and human action: Time and knowledge in a theory of social economy. Routledge.
Weimer, W. B. (1982). Hayek’s approach to the problems of complex phenomena: An introduction to the theoretical psychology of the sensory order. In W. B. Weimer & D. S. Palermo (Eds.), Cognition and the symbolic processes (pp. 241–285). Lawrence Erlbaum Associates.
Wolfram, S. (1984). Universality and complexity in cellular automata. Physica D: Nonlinear Phenomena, 10, 1–35. https://doi.org/10.1016/0167-2789(84)90245-8
Acknowledgements
The author wishes to thank two anonymous referees and, especially, Dr. Erwin Dekker, for their thoughtful comments and suggestions. The usual caveat applies.
Funding
Not applicable.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
Not applicable.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Moreno-Casas, V. The Harvard-MIT complexity approach to development and Austrian economics: Similarities and policy implications. Rev Austrian Econ 36, 515–539 (2023). https://doi.org/10.1007/s11138-021-00565-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11138-021-00565-6