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Block rate pricing is often applied to income taxation, telecommunication services, and brand marketing, in addition to its best-known application in public utility services. Under block rate pricing, consumers face piecewise-linear budget constraints. A discrete/continuous choice approach is usually used to account for piecewise-linear budget constraints in demand and price endogeneity. A recent study proposed a method to incorporate a separability condition ignored by previous studies, by implementing a Markov chain Monte Carlo simulation based on a hierarchical Bayesian approach. To extend this approach to panel data, our study proposes Bayesian hierarchical models incorporating random and fixed individual effects.