Non-Robust Dynamic Inferences from Macroeconometric Models: Bifurcation Stratification of Confidence Regions

Barnett, William A. and Duzhak, Evgeniya A. (2007): Non-Robust Dynamic Inferences from Macroeconometric Models: Bifurcation Stratification of Confidence Regions. Forthcoming in: Physica A

Abstract

Grandmont (1985) found that the parameter space of the most classical dynamic models are stratified into an infinite number of subsets supporting an infinite number of different kinds of dynamics, from monotonic stability at one extreme to chaos at the other extreme, and with many forms of multiperiodic dynamics between. The econometric implications of Grandmont’s findings are particularly important, if bifurcation boundaries cross the confidence regions surrounding parameter estimates in policy-relevant models. Stratification of a confidence region into bifurcated subsets seriously damages robustness of dynamical inferences.

Recently, interest in policy in some circles has moved to New Keynesian models. As a result, in this paper we explore bifurcation within the class of New Keynesian models. We develop the econometric theory needed to locate bifurcation boundaries in log-linearized New-Keynesian models with Taylor policy rules or inflation-targeting policy rules. Central results needed in this research are our theorems on the existence and location of Hopf bifurcation boundaries in each of the cases that we consider.

• Item Type: MPRA Paper
• Language: English
• Keywords: Bifurcation, Hopf bifurcation, Euler equations, New Keynesian macroeconometrics, Bergstrom-Wymer model
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles

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