Distinguishing between endogenous and exogenous price volatility in food security assessment: An empirical nonlinear dynamics approach

We propose an empirical scheme—based on nonlinear dynamics—for diagnosing real-world market dynamics from observed price series data. The scheme distinguishes between endogenous and exogenous volatility in observed price series, tests whether endogenous volatility is generated by low-dimensional deterministic market dynamics, simulates these dynamics with a phenomenological market model, and models extreme volatility probabilistically. These diagnostics allow policymakers to make an empirically-informed determination of whether laissez-faire or interventionist policies are most promising in reducing price volatility in particular cases. We apply the diagnostic scheme to provide compelling empirical evidence that observed volatility in organic apple, pear, orange, and lemon prices at the Milano (Italy) Ipercoop is due to endogenous market dynamics governed by low-dimensional nonlinear behavior. The implication for food policy is that this inherently unstable market cannot be relied upon to systematically stabilize observed price volatility from random exogenous shocks. There may be scope for public interventions targeted to increasing the flexibility of organic fruit producers in responding to changing market conditions.