MATLAB code for A Birth-Death Markov Chain Monte Carlo Method to Estimate the Number of States in a State-Contingent Production Frontier Model

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To run BDMCMC with the Tarlac rice dataset

  1. Place all contents of this package on the same folder and make it the active folder in Matlab.
  2. BDMCMC_Dummy_Trend_Mono runs the monotonicity-constrained dummy time trend model.
  3. BDMCMC_Linear_Trend_Mono runs the monotonicity-constrained linear time trend model.
  4. RiceIM contains the dataset scaled to input means (used on the estimation process).
  5. Rice contains the dataset in its original units of measurement. This is a subset of the dataset used in Villano, O’Donnell and Battesse (2004) and the same dataset used by ODG.

References

Villano, R.A., C.J. O’Donnell, and G.E. Battese. 2004. “An Investigation of Production Risk, Risk Preferences and Technical Efficiency: Evidence from Rainfed Lowland Rice Farms in the Philippines.” Article presented at Asia-Pacific Productivity Conference, Brisbane, 14–16 July.

 

 

 

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