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The Mathematization of Macroeconomics: A Recursive Revolution

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  • K. Vela Velupillai

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    Abstract

    Frank Ramsey's classic framing of the dynamics of optimal savings, [51] as one to be solved as a problem in the calculus of variations and Ragnar Frisch's imaginative invoking of a felicitous Wicksellian metaphor to provide the impulse-propagation dichotomy, in a stochastic dynamic framework, for the tackling the problem of business cycles [17], have come to be considered the twin fountainheads of the mathematization of macroeconomics in its dynamic modes - at least in one dominant tradition. The intertemporal optimization framework of a rational agent, viewed as a signal processor, facing the impulses that are propagated through the mechanisms of a real economy, provide the underpinnings of the stochastic dynamic general equilibrium (SDGE) model that has become the benchmark and frontier of current macroeconomics. In this paper, on the 80th anniversary of Ramsey's classic and the 75th anniversary of Frisch's Cassel Festschrift contribution, an attempt is made to characterize the mathematization of macroeconomics in terms of the frontier dominance of recursive methods. There are, of course, other - probably more enlightened - ways to tell this fascinating story. However, although my preferred method would have been to tell it as an evolutionary development, since I am not sure that where we are represents progress, from where we were, say 60 years ago, I have chosen refuge in some Whig fantasies.

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    Paper provided by Department of Economics, University of Trento, Italia in its series Department of Economics Working Papers with number 0807.

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    Date of creation: 2008
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    Handle: RePEc:trn:utwpde:0807

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    Keywords: Macrodynamics; Mathematical Economics; Dynamic Economics; Computational Economics.;

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    1. Debreu, Gerard, 1991. "The Mathematization of Economic Theory," American Economic Review, American Economic Association, vol. 81(1), pages 1-7, March.
    2. Ricardo Lagos & Guillaume Rocheteau, 2004. "Inflation, output and welfare," Staff Report 342, Federal Reserve Bank of Minneapolis.
    3. Kydland, Finn E., 2004. "Quantitative Aggregate Theory," Nobel Prize in Economics documents 2004-4, Nobel Prize Committee.
    4. Debreu, Gerard, 1983. "Economic Theory in the Mathematical Mode," Nobel Prize in Economics documents 1983-1, Nobel Prize Committee.
    5. J.P. Fitoussi & K. Velupillai, 1990. "Macroeconomic Perspectives," UCLA Economics Working Papers 609, UCLA Department of Economics.
    6. Spear, Stephen E, 1989. "Learning Rational Expectations under Computability Constraints," Econometrica, Econometric Society, vol. 57(4), pages 889-910, July.
    7. K. Vela Velupillai, 2005. "The foundations of computable general equilibrium theory," Department of Economics Working Papers 0513, Department of Economics, University of Trento, Italia.
    8. Smale, Stephen, 1976. "Dynamics in General Equilibrium Theory," American Economic Review, American Economic Association, vol. 66(2), pages 288-94, May.
    9. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979.
    10. Debreu, Gerard, 1986. "Theoretical Models: Mathematical Forms and Economic Content," Econometrica, Econometric Society, vol. 54(6), pages 1259-70, November.
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    Cited by:
    1. K.Vela Velupillai, 2012. "Towards a Political Economy of the Theory of Economic Policy," ASSRU Discussion Papers 1217, ASSRU - Algorithmic Social Science Research Unit.
    2. Stefano Zambelli, 2012. "Dynamical Coupling, Nonlinear Accelerator and the Persistence of Business Cycles," ASSRU Discussion Papers 1214, ASSRU - Algorithmic Social Science Research Unit.
    3. Elisabetta De Antoni, 2009. "Money and finance: the heterodox views of R. Clower, A. Leijonhufvud and H. Minsky," Department of Economics Working Papers 0908, Department of Economics, University of Trento, Italia.

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