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A Behavioral Macroeconomic Model of Exchange Rate Fluctuations with Complex Market Expectations Formation

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Abstract

The paper investigates the emergence of complex market expectations (opinion dynamics) around nominal exchange rate adjustments using a macro-financial model of a small open economy featuring heterogeneous expectation formation (chartists and fundamentalists) and gradual adjustment processes in real and also to a certain degree in financial markets. The model shows among other things the mechanisms through which the first type of agents tends to destabilize the economy. Global stability can be ensured if opinions turn to fundamentalist behavior far off the steady state. This interaction of expectations and population dynamics is bounding the—due to chartist behavior—potentially explosive real-financial market interactions, but can enforce irregular behavior within these bounds. The size of output and exchange rate fluctuations can be dampened by adding suitable policy measures to the dynamics of the private sector.

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Notes

  1. Further contributions to this line of research in behavioral macroeconomic modeling are e.g. Charpe et al. (2011, 2012a, b) as well as Hartmann and Flaschel (2014).

  2. The term persistence must be understood throughout the paper not as the stability of a trend, but as the occurrence of a steady dynamical pattern for at least a while.

  3. The instability induced in the KMG approach by the wage-price spiral as discussed e.g. by Flaschel and Krolzig (2006) is also ignored.

  4. For any dynamic variable \(x\), \(\overset{.}{x}\) denotes its time derivative, \( \widehat{x}\) denotes its rate of growth, and \(x_{o}\) denotes its steady state value.

  5. E.g. Assenza et al. (2012) investigate systematically dynamic implications of various sets of expectation formation schemes for a macroeconomic equilibrium model. A similar procedure to analyze rigorously consequences of different expectational mechanisms could be applied to our model.

  6. Population shares are endogenized in the next section.

  7. The details of the approach are in Lux (1995) and Franke (2012).

  8. The software can be downloaded from http://www1.fee.uva.nl/cendef/whoiswho/makeHP/page.asp?iID=19

  9. We show ten years of iteration after transient period of 300 years.

  10. Note that the Largest Liapunov Exponent is positive for values of \(\beta _{\pi }\) slightly larger than zero, too. Since the LLE is no exact measure for complexity, the indicator only gives a hint for complexity. But we cannot confirm complex dynamics by the bifurcation diagram here. This might be due to the particularly brief remaining of the LLE in the positive area.

    Fig. 7
    figure 7

    Stabilizing opinion dynamics

    Fig. 8
    figure 8

    Are there ‘chaotic’ trajectories?

  11. Tobin (1978, 1996) proposed a currency transaction tax, which might work as a stabilizing device for international financial markets and generate revenues to be used by an international authority to finance economic development.

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Correspondence to Florian Hartmann.

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Flaschel, P., Hartmann, F., Malikane, C. et al. A Behavioral Macroeconomic Model of Exchange Rate Fluctuations with Complex Market Expectations Formation. Comput Econ 45, 669–691 (2015). https://doi.org/10.1007/s10614-014-9437-8

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