Univariate filters used in output gap estimation are subject to criticism as being purely statistical and having no economic content. The information content of the output gap measures estimated by standard multivariate filtering techniques, on the other hand, can be distorted because of the possibly unrealistic restriction that system parameters stay constant over time. In this study, we seek to address these shortcomings by proposing an output gap estimation method that takes into account changing economic relations. We employ a nonlinear time series framework along with the extended Kalman filter, in which economic content is used by inflation and output gap dynamics and the parameters are allowed to be time varying. We use the Turkish economy as a laboratory to show that our method provides useful results, both in terms of the properties of output gap estimates and for the assessment of change in macroeconomic dynamics.
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