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Abstract

A method was developed with time series models to test hypotheses about the relationship between market structure and spatial price dynamics. Long-run dynamic multipliers measuring the magnitude of lagged adjustments for spatial milled rice prices were calculated from the time series model and used as the dependent variable in a regression model that included a number of factors expected to influence price determination. Results show that price adjustments were slower as regional submarket concentration increased and were faster in the regions with a higher market share. Arkansas, the state with the largest market share, was consistently a price leader

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