Making dynamic modelling effective in economics
Mathematics has been extremely effective in physics, but not in economics beyond finance. To establish economics as science we should follow the Galilean method and try to deduce mathematical models of markets from empirical data, as has been done for financial markets. Financial markets are nonstationary. This means that 'value' is subjective. Nonstationarity also means that the form of the noise in a market cannot be postulated a priroi, but must be deduced from the empirical data. I discuss the essence of complexity in a market as unexpected events, and end with a biological speculation about market growth.
|Date of creation:||Mar 2004|
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- Per Bak & Simon F. Norrelykke & Martin Shubik, 1998.
"The Dynamics of Money,"
cond-mat/9811094, arXiv.org, revised May 1999.
- Per Bak & Simon F. Norrelykke & Martin Shubik, 1998. "The Dynamics of Money," Research in Economics 98-11-102e, Santa Fe Institute.
- A. Meltzer & Peter Ordeshook & Thomas Romer, 1983. "Introduction," Public Choice, Springer, vol. 41(1), pages 1-5, January.
- Mirowski,Philip, 2002. "Machine Dreams," Cambridge Books, Cambridge University Press, number 9780521772839, August.
- Mirowski,Philip, 2002. "Machine Dreams," Cambridge Books, Cambridge University Press, number 9780521775267, August.
- Gemunu H. Gunaratne & Joseph L. McCauley, 2002. "A theory for Fluctuations in Stock Prices and Valuation of their Options," Papers cond-mat/0209475, arXiv.org.
- A. P. Thirlwall, 1983. "Introduction," Journal of Post Keynesian Economics, M.E. Sharpe, Inc., vol. 5(3), pages 341-344, April. Full references (including those not matched with items on IDEAS)
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