Adaptive Interactive Profit Expectations and Small World Networks

Bell, William Paul (2008): Adaptive Interactive Profit Expectations and Small World Networks.

Abstract

The aim of this paper is to simulate profit expectations as an emergent property using an agent based model. The paper builds upon adaptive expectations, interactive expectations and small world networks, combining them into a single adaptive interactive profit expectations model (AIE). Understanding the diffusion of interactive expectations is aided by using a network to simulate the flow of information between firms. The AIE model is tested against a profit expectations survey.

The paper introduces “optimal calibration model averaging” and the “pressure to change profit expectations index” (px). Optimal calibration model averaging is an adaptation of “model averaging” to enhance the prediction performance of multiple equilibria models. The px is a subjective measure representing decision making in the face of uncertainty.

The paper benchmarks the AIE model against the adaptive expectations model and the rational expectations hypothesis, finding the firms may have adequate memory although the interactive component of AIE model needs improvement. Additionally the paper investigates the efficacy of a tuneable network and equilibrium averaging. Finding the tuneable network produces widely spaced multiple equilibria and the optimal calibration model averaging enhances calibration but not prediction. Further research includes disaggregating the AIE model, using an input–output table to reflect the intensity of interaction between firms of different divisions, and supplementing optimal calibration model averaging with runtime weighted model averaging.

• Item Type: MPRA Paper
• Language: English
• Keywords: Expectations; Interactive; Adaptive; Business cycle; Profit; Networks
• Subjects: Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology; Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology > Z13 - Economic Sociology ; Economic Anthropology ; Social and Economic Stratification; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D85 - Network Formation and Analysis: Theory; L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C60 - General; L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L14 - Transactional Relationships ; Contracts and Reputation ; Networks; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D84 - Expectations ; Speculations; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty

References

ABS 2002, Cat. No. 5250.0 Australian Business Expectations Mar and Dec 2003, Canberra.

---- 2006, Cat. No. 1292.0 Australian and New Zealand Standard Industrial Classification (ANZSIC).

Amarala, LAN & Ottino, JM 2004, 'Complex networks: Augmenting the framework for the study of complex systems', The European Physical Journal B, vol. 38, pp. 147-62.

Baggio, R 2008, 'Network analysis of a tourism destination', The School of Tourism, The University of Queensland, Brisbane.

Bak, P, Paczuski, M & Shubik, M 1997, 'Price variations in a stock market with many agents', Physica A: Statistical and Theoretical Physics, vol. 246, no. 3-4, pp. 430-53.

Bates, JM & Granger, CWJ 1969, 'The Combination of Forecasts', Operational Research Quarterly, vol. 20, no. 4, pp. 451-68.

Beinhocker, ED 2006, Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics, Harvard Business School Press, Cambridge, Mass.

Bell, WP 2008, 'Adaptive interactive profit expectations using small world networks and runtime weighted model averaging', in DV Nicolau & G Metcalfe (eds), Complexity and Nonlinear Dynamics II, Biomedical Applications of Micro- and Nanoengineering IV and Complex Systems RMIT University, Melbourne, Australia, vol. 7270, p. 727011.

—— 2009a, 'Adaptive Interactive Expectations: Dynamically Modelling Profit Expectations', Doctor of Philosophy thesis, University of Queensland.

—— 2009b, 'Network Averaging: a technique for determining a proxy for the dynamics of networks', in Complex ’09, the 9th Asia-Pacific Complex Systems Conference, Chuo University, Tokyo, Japan.

Bowden, MP & McDonald, S 2006, 'The Effect of Social Interaction and Herd Behaviour on the Formation of Agent Expectations', Computing in Economics and Finance 2006, no. 178.

Clemen, RT 1989, 'Combining forecasts: A review and annotated bibliography', International Journal of Forecasting, vol. 5, pp. 559-83.

D&B 2006, Standard Industrial Classification Australia, <http://www.dnb.com.au/pdfs/general/SIC_Booklet.pdf>.

---- 2008, 'National Business Expectations Survey of business executives across Australia', viewed 20 February 2008, <http://www.dnb.com.au/general/business_expectations/business_expectations.asp?id=pr_2007_1105&Link_Page=AUS>.

Farmer, JD, Patelli, P & Zovko, II 2005, 'The predictive power of zero intelligence in financial markets', Proceeding of the National Academy of Science of the USA, vol. 102, no. 6, pp. 2254-9.

Flieth, B & Foster, J 2002, 'Interactive expectations', Journal of Evolutionary Economics, vol. 12, no. 4, pp. 375-95.

Goldstein, J 1999, 'Emergence as a Construct: History and Issues', Emergence, vol. 1, no. 1, pp. 49-73.

Gonzaleza, C, Danaa, J, Koshinob, H & Justc, M 2004, 'The framing effect and risky decisions: Examining cognitive functions with fMRI', Journal of Economic Psychology, vol. 26, no. 1.

Grimm, V, Revilla, E, Berger, U, Jeltsch, F, Mooij, WM, Railsback, SF, Thulke, H-H, Weiner, J, Wiegand, T & DeAngelis, DL 2005, 'Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology', Science, vol. 310, pp. 987-91.

Hanneman, RA & Riddle, M 2005, Introduction to social network methods, University of California, Riverside, California, <http://faculty.ucr.edu/~hanneman/nettext/>. Hicks, JR 1939, Value and capital, Oxford University Press, London.

Holt, CC, Modigliani, F, Muth, JF & Simon, HA 1960, Planning production, inventories, and work force, Prentice-Hall international series in management., Prentice-Hall, Englewood Cliffs, N.J.

Kahneman, D 2002, 'Maps of Bounded Rationality: A Perspective on Intuitive Judgement and Choice', paper presented to Les Prix Nobel 2002, Stockholm, <http://www.nobel.se/economics/laureates/2002/kahnemann-lecture.pdf>.

Lovell, MC 1986, 'Tests of the Rational Expectations Hypothesis', The American Economic Review, vol. 76, no. 1, pp. 110-24.

Miller, JH & Page, SE 2007, Complex adaptive systems : an introduction to computational models of social life, Princeton studies in complexity., Princeton University Press, Princeton, New Jersey.

Muth, JF 1960, 'Optimal Properties of Exponentially Weighted Forecasts', Journal of the American Statistical Association, vol. 55, no. 290, pp. 299-306.

---- 1961, 'Rational Expectations and the Theory of Price Movements', Econometrica, vol. 29, no. 3, pp. 315-35.

Nerlove, M 1964, 'On the Optimality of Adaptive Forecasting', Management Science, vol. 10, pp. 207-24.

Ormerod, P 2005, 'On system-wide failures in complex, evolving systems', paper presented to The International Workshop on Evolutionary Macroeconomics, University of Queensland, Brisbane, 14-17 July 2005, <http://www.uq.edu.au/economics/?page=34849>.

Shiller, RJ 2005, Irrational exuberance, 2nd edn, Princeton University Press, Princeton, N.J.

Sterman, JD 2000, Business dynamics : systems thinking and modeling for a complex world, Irwin/McGraw-Hill, Boston.

Tesfation, L 2008, Agent-Based Computational Economics, <http://www.econ.iastate.edu/tesfatsi/ace.htm>.

Tukey, J 1962, 'The Future of Data Analysis', The Annals of Mathematical Statistics, vol. 33, no. 1, pp. 1-67.

Watts, DJ & Strogatz, SH 1998, 'Collective dynamics of 'small-world' networks', Nature, vol. 393, pp. 440-2.

Wilensky, U 1999, NetLogo, Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL, 30 May 2007, <http://ccl.northwestern.edu/netlogo/>.

---- 2005, NetLogo Small Worlds model, Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL, <http://ccl.northwestern.edu/netlogo/models/SmallWorlds>.

Yu, A 2008, 'Seeing patterns in randomness: Irrational superstition or adaptive behaviour?' paper presented to The Queensland Brain Institute Neuroscience Seminar Series, The University of Queensland, Brisbane, 11 February 2008.