Heterodox Shocks Prepared for Eastern Economic Association conference, New York, May 9, 2013

1. Heterodox ShocksPrepared for Eastern Economic Association conference,New York, May 9, 2013 Greg Hannsgen Levy Economics Institute of Bard College Annandale-on-Hudson, New York, United States www.levyinstitute.org

4. Views from reference works: • 2nd edition Companion to Post Keynesian Economics (2012)—Mentions shocks only as part of exogenous approach in entry on “business cycles” • New Palgrave Dictionary (1987 edition)—mentions “innovations”—time-series forecast errors—in entry for “time series.” But no separate listing for “shocks” of any kind

5. Idea of paper • Readers and heterodox economists (W.C. Mitchell [1927], J.M. Keynes [1936], H. Minsky [1954], M. Kalecki [1956], L. Pasinetti [1962], G. Shackle [1973], L. Taylor [2010], W. Godley [2012], many others)alike have benefited from the use of this tool/trope. • Looking at this topic a bit like studying our pencils or computers. They are there, but not often thought of as a subject in themselves or seriously studied. • The two types of shocks correspond broadly to (Type 1) Keynes’s “changes in independent variables” (1936) and (Type 2) random simulation shocks as in Kalecki’sTheory of Economic Dynamics (1956).

6. Type 1 shocks (one-time impulses) have roots in Keynes’s General Theory • Chapter 18 divides exogenous factors into “independent variables” and “given factors” • In practice, “…there is not one [factor] which is not liable to change without much warning, and sometimes substantially” (p. 249). • Example: Relatively stable but “precarious” social conventions normally undergird stock-market prices. • Sudden “crises” are a distinct dynamic phenomenon developed in Chapter 22 on the business cycle • OTHER RELEVANT SOURCES: J.M. Keynes (1937) and in G.L.S. Shackle’s Keynesian Kaleidics(1973) • Often used as one-time simulation shocks, as in this example from Lavoie and Godley ([2006] 2012)

7. Type 2 heterodox shocks: randomly drawn shocks used in simulations • Stochastic error terms or parameters used throughout simulations, not just to set initial conditions • Example 1: C. Chiarella, P. Flaschel, and R. Franke (2005), chapter on Keynes-Metzler-Goodwin-Taylor rule model: normally distributed shocks to aggregate demand equation. • Example 2: W. Godley used random demand shocks in simulations of a sequence of events in posthumously published “Macroeconomics without Equilibrium or Disequilibrium” (2012).

8. Practical suggestions (tentative) • Some forms of hybrid shocks, if you will, may be useful. Occasional shocks for simulations, a bit like regime changes • Condition expected size or rate of occurrence of shocks on prior events. Example: Mean rate of occurrence = f(fragility, time since last occurrence)Size, given that crisis occurs = g(fragility, time since last occurrence, size of economy) • Consider use of stable(i.e., “Lévy-stable” or “alpha-stable”) shocks (potentially fat-tailed and/or skewed) when empirical work suggests that they fit.

9. Possible characteristics of shocks considered in sections of the paper • Keynesian? • Exogenous? • Noneconomic? • Inexplicable? • Random? • Stably distributed? • Unexpected? • Symmetric? • Comparable to other heterodox techniques? • Anomalous? • Merely expositional? • Historical? • Pragmatic? • Jumpy (discontinuous)?

10. Pragmatic considerations • Sometimes things jump exogenously with a major effect on macro variables—how else do you model a 10-percent market correction in one day? • Shocks sometimes allow role for history—sometimes it does matter, even in economics • Avoid implication of complete predictability, given model and initial conditions • Not everything can be ascribed to deterministic causes. Yes, there are nonlinear endogenous dynamics; don’t forget them either • Often just as good as deterministic model if goal is model that can mimic properties of data series. • Use them to show robustness to a skeptical public

11. J. Steindl: They are there “My personal point of view is that the shocks are there in any case…I think it is most important keep a theory of the cycle flexible so that it will be capable of accommodating all the exogenous influences: the history, the accidents, and that a simple endogenous model cannot possibly take into account.” In “Reflections on Kalecki’s Dynamics” (1989)

12. Shackle: transformation in an hour or a moment By the kaleidic theory I mean the view that the expectations, which together with the drive of needs or ambitions make up the ‘spring of actions’, are at all times so insubstantially founded upon data and so mutably suggested by the stream of ‘news’, that is, of counter-expected or totally unthought-of events, that they can undergo complete transformation in an hour or even a moment, as the patterns in the kaleidoscope dissolve at a touch… In Keynesian Kaleidics(1973)

13. Source: Approaches to Stock-flow Modeling, Lavoie and Zezza, eds., New York, Palgrave Macmillan, 2012. Back to outline

14. Sources: C. Chiarella, P. Flaschel, and Frankë, Foundations for a Disequilibrium Theory of the Business Cycle, Cambridge University Press, 2005 Back to outline

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17. Back to outline Source: Book authors’ webpage containing Eviews macros for Monetary Economics: An Integrated Approach to Credit, Money, Income, Production and Wealth, Palgrave Macmillan, 2006, 2012http://gennaro.zezza.it/software/eviews/glch10.php#insout5