Heinrich, Torsten (2015): Growth Cycles, Network Effects, and Intersectoral Dependence: An Agent-Based Model and Simulation Analysis.
Preview |
PDF
MPRA_paper_79575.pdf Download (651kB) | Preview |
Abstract
An agent-based model of economic growth and technological change with network effects is proposed. The dynamics generated by network externalities are self-reinforcing and may bring about rapid growth, but will also for some time prevent further innovation. This circular pattern may appear in different economic sectors (or regions), may synchronize and resonate between sectors. This gives rise to growth waves on the macro-level and may be a novel approach to explain growth cycles. The paper uses an agent-based model for the study of single sector industry dynamics. This design is extended into a multi-sector version with an intersectoral effect on the network externality terms. The model is then simulated both with interconnected (with different network structures) and - as a control treatment - with isolated sectors. The emerging wave pattern on the macro-level is analyzed using both the autocorrelation spectrum and the frequency spectrum obtained with a fast Fourier transformation (FFT) of the simulation's output data.
Item Type: | MPRA Paper |
---|---|
Original Title: | Growth Cycles, Network Effects, and Intersectoral Dependence: An Agent-Based Model and Simulation Analysis |
Language: | English |
Keywords: | Growth Cycles; Network Externalities; Technological Change; Multisector Growth Models; Agent-Based Modeling |
Subjects: | E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes O - Economic Development, Innovation, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O41 - One, Two, and Multisector Growth Models |
Item ID: | 79575 |
Depositing User: | Torsten Heinrich |
Date Deposited: | 08 Jun 2017 05:40 |
Last Modified: | 27 Sep 2019 11:17 |
References: | Aghion P, Howitt P (1992) A model of growth through creative destruction. Econometrica 60(2):323–351 Arthur WB (1988) Self-reinforcing mechanisms in economics. In: Anderson KJA Philip, Pines D (eds) The Economy as an Evolving Complex System, Santa Fe Institute Studies in the Sciences of Complexity, Redwood City California, Addison Wesley, pp 9–31 Arthur WB, Ermoliev YM, Kaniovski YM (1987) Path dependent processes and the emergence of macro-structure. European Journal of Operational Research 30:294–303 Brynjolfsson E (1993) The productivity paradox of information technology. Communications of the ACM 36(12):66–77 Carvalho VM (2008) Aggregate fluctuations and the network structure of intersectoral trade. Dissertation submitted to the University of Chicago, 2008, available online: http://crei.cat/people/carvalho/carvalho aggregate.pdf Cass D (1965) Optimum growth in an aggregative model of capital accumulation. The Review of Economic Studies 32(3):233–240 Chen P (2002) Microfoundations of macroeconomic fluctuations and the laws of probability theory: the principle of large numbers versus rational expectations arbitrage. Journal of Economic Behavior & Organization 49(3):327– 344, DOI 10.1016/S0167-2681(02)00003-3 Choi JP (2004) Tying and innovation: A dynamic analysis of tying arrangements. The Economic Journal 114(492):83–101 Christiano LJ, Eichenbaum M (1992) Current real-business-cycle theories and aggregate labor-market fluctuations. The American Economic Review 82(3):pp. 430–450 Conlisk J (1989) An aggregate model of technical change. The Quarterly Journal of Economics 104(4):787–821 David PA (1985) Clio and the economics of QWERTY. American Economic Review 75(2):332–337 Dosi G, Fagiolo G, Roventini A (2010) Schumpeter meeting keynes: A policy-friendly model of endogenous growth and business cycles. Journal of Economic Dynamics and Control 34(9):1748 – 1767, DOI http://dx.doi.org/10.1016/j.jedc.2010.06.018 Elsner W, Heinrich T, Schwardt H (2015) Microeconomics of Complex Economies: Evolutionary, Institutional, Neoclassical, and Complexity Perspectives. Academic Press, Amsterdam, NL, San Diego, CA, et al. Farmer JD, Lafond F (2016) How predictableis technological progress? Research Policy 45(3):647 – 665, DOI http://dx.doi.org/10.1016/j.respol.2015.11.001 Foley DK (1998) Introduction to ’barriers and bounds to rationality’. In: Foley DK (ed) Barriers and Bounds to Rationality: Essays on Economic Complexity and Dynamics in Interactive Systems, by Albin, P.S., with an Introduction by Foley, D.K., Princeton University Press, Princeton, N.J., pp 3–72 Freeman C, Perez C (1988) Structural crisis of adjustment, business cycles and investment behaviour. In: Dosi G, Freeman C, Nelson R, Silverberg G, Soete L (eds) Technological Change and Economic Theory, Pinter Publishers, London, N.Y., pp 38–66 Gaffeo E, Delli Gatti D, Desiderio S, Gallegati M (2008) Adaptive microfoundations for emergent macroeconomics. Eastern Economic Journal 34(4):441–463, DOI 10.1057/eej.2008.27 Goodwin RM (1967) A growth cycle. In: Feinstein C (ed) Socialism, Capitalism and Economic Growth, Cambridge University Press, Cambridge, UK, pp 54–58 Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD protocol: A review and first update. Ecological Modelling 221(23):2760 – 2768 de Groot B (2006) Essays on economic cycles. PhD thesis, Published by Rotterdam School of Management (RSM) Erasmus University, Erasmus Research Institute of Management (ERIM), URL http://repub.eur.nl/res/pub/8216/ Heinrich T (2013) Technological Change and Network Effects in Growth Regimes: Exploring the Microfoundations of Economic Growth. Routledge, Oxon and New York Heinrich T (2014) Standard wars, tied standards, and network externality induced path dependence in the ICT sector. Technological Forecasting and Social Change 81:309–320, DOI http://dx.doi.org/10.1016/j.techfore.2013.04.015 Jalava J, Pohjola M (2008) The roles of electricity and {ICT} in economic growth: Case finland. Explorations in Economic History 45(3):270 – 287, DOI http://dx.doi.org/10.1016/j.eeh.2007.11.001 Kaldor N (1940) A model of the trade cycle. The Economic Journal 50(197):78–92 Keen S (1995) Finance and economic breakdown: Modeling Minsky’s ”financial instability hypothesis”. Journal of Post Keynesian Economics 17(4):607–635 Lines M (1990) Slutzky and lucas: Random causes of the business cycle. Structural Change and Economic Dynamics 1(2):359 – 370, DOI http://dx.doi.org/10.1016/0954-349X(90)90009-W Lorenz HW (1987) Strange attractors in a multisector business cycle model. Journal of Economic Behavior & Organization 8(3):397 – 411, DOI 10.1016/0167-2681(87)90052-7 Lucas RE (1972) Expectations and the neutrality of money. Journal of Economic Theory 4(2):103–124 Lucas RE (1981) Studies in Business Cycle Theory. Basil Blackwell, Oxford Mandelbrot B (1997) The variation of certain speculative prices. In: Fractals and Scaling in Finance, Springer New York, pp 371–418, DOI 10.1007/978-1-4757-2763-0 14 Marx K (1963 [1885]) Das Kapital: Kritik der politischen Ökonomie. Buch II: Der Zirkulationsprozeß des Kapitals. Dietz Verlag, Berlin, GDR, reprint in Marx-Engels Collected Works (Marx-Engels Gesamtausgabe), Volume 24 Minsky HP (1980) Capitalist financial processes and the instability of capitalism. Journal of Economic Issues 14(2):pp. 505–523, URL http://www.jstor.org/stable/4224935 Nelson RR, Winter SG (1974) Neoclassical versus evolutionary theories of economic growth: Critique and prospectus. Economic Journal 84(336):886–905 Nelson RR, Winter SG (1982) An Evolutionary Theory of Economic Change. Harvard University Press, Cambridge Nooteboom B (1994) Innovation and diffusion in small firms: theory and evidence. Small Business Economics 6(5):327–347 Samuelson PA (1939) Interactions between the multiplier analysis and the principle of acceleration. The Review of Economics and Statistics 21(2):75–78 Saviotti PP, Pyka A (2013) From necessities to imaginary worlds: Structural change, product quality and economic development. Technological Forecasting and Social Change 80(8):1499 – 1512, DOI http://dx.doi.org/10.1016/j.techfore.2013.05.002 Saviotti PP, Pyka A (2015) Innovation, structural change and demand evolution: does demand saturate? Journal of Evolutionary Economics pp 1–22, DOI 10.1007/s00191-015-0428-2 Shy O (2001) The Economics of Network Industries. Cambridge University Press, New York, NY, USA Silverberg G, Lehnert D (1993) Long waves and ‘evolutionary chaos’ in a simple Schumpeterian model of embodied technical change. Structural Change and Economic Dynamics 4(1):9 – 37, DOI DOI: 10.1016/0954-349X(93)90003-3 Silverberg G, Dosi G, Orsenigo L (1988) Innovation, diversity and diffusion: A self-organisation model. The Economic Journal 98(393):1032–1054 Skulimowski AMJ (2012) Discovering complex system dynamics with intelligent data retrieval tools. In: Zhang Y, Zhou ZH, Zhang C, Li Y (eds) Intelligent Science and Intelligent Data Engineering: Second Sino-foreign-interchange Workshop, IScIDE 2011, Xi’an, China, October 23-25, 2011, Revised Selected Papers, Springer Berlin Heidelberg, Berlin, Heidelberg, pp 614–626 Slutzky E (1937 [1927]) The summation of random causes as the source of cyclic processes. Econometrica 5(2):105–146, translated from Russian (Problems of Economic Conditions, 3:1, 1927, ed. by The Conjuncture Institute, Moscow) Solow RM (1956) A contribution to the theory of economic growth. The Quarterly Journal of Economics 70(1):65–94 Taghawi-Nejad D (2010) Technology shocks and trade in a network. In: Li Calzi M, Milone L, Pellizzari P (eds) Progress in Artificial Economics: Computational and Agent-Based Models, Springer Berlin Heidelberg, Berlin, Heidelberg, pp 101–112, DOI 10.1007/978-3-642-13947-5 9 Uzawa H (1965) Optimum technical change in an aggregative model of economic growth. International Economic Review 6(1):18–31 Watanabe C, Matsumoto K, Hur JY (2004) Technological diversification and assimilation of spillover technology: Canon’s scenario for sustainable growth. Technological Forecasting and Social Change 71(9):941 – 959, DOI http://dx.doi.org/10.1016/S0040-1625(03)00069-6 Way R, Lafond F, Farmer JD, Lillo F, Panchenko V (2017) Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves. arXiv:1705.03423 Worldbank (2016) Worldbank DataBank: http://databank.worldbank.org/data/home.aspx. Accessed 06/01/2016 Yule GU (1925) A mathematical theory of evolution, based on the conclusions of Dr. J. C. Willis, F.R.S. Philosophical Transactions of the Royal Society B 213(402-410):21–87 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/79575 |