Modelling non-linear Spatial Market Integration and Equilibrium Processes in Hidden Markov Framework

Abstract

Along the basic rationale of the Enke-Samuelson-Takajama-Judge spatial equilibrium theory and the dynamic conceptualizations made from arbitrage processes, the study explores regime-switching techniques in hidden Markov framework. This is motivated by complex non-linear structure inherent in market integration processes, which is derived from multiple equilibria conditions, and transaction costs constrained threshold autoregressive (TAR) effects. These place theoretical limitations on current time series empirical models that are applied in market integration studies. In equilibrium representation, the non-linearities imposed by both alternating rent levels and switching adjustment parameters are directly accommodated. Two synthesized time series market data sets of varying levels of non-linear structures are used to highlight the strengths and limitations of the Markov variants vis-à-vis the band-TAR models that have currently dominated market integration analysis. The former model could capture alternating adjustment processes implied by the relatively complex non-linear market data set while the later produced mixed results.