Abstract
The purpose of this paper is to evaluate the efficiency of agricultural production in Asia and analyze the production function of Asian countries. Methodologically, we employ the stochastic frontier model with the concern about dependency between two-sided error term and one-sided inefficiency. Likewise, we try to improve the performance of the standard stochastic frontier model by applying quantile regression to the frontier production function. Therefore, this paper introduces the model called Copula-based stochastic frontier quantile model as an alternative tool for this issue. The accuracy of this model is proved through a simulation study before applying to the agricultural production data of Asia.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bezat-Jarzbowska, A., Rembisz, W.: Efficiency-focused economic modeling of competitiveness in the agri-food sector. Procedia Soc. Behav. Sci. 81, 359–365 (2013)
Kaditi, E.A., Nitsi, E.: Applying regression quantiles to farm efficiency estimation. In: 2010 Annual Meeting, pp. 25–27, July 2010
Farrell, M.J.: The measurement of productive efficiency. J. R. Stat. Soc. Ser. A (Gen.) 120(3), 253–290 (1957)
Aigner, D.J., Lovell, C.A.K., Schmidt, P.: Formulation and estimation of stochastic frontier production function models. J. Econ. 6, 21–37 (1977)
Duy, V.Q.: Access to credit and rice production efficiency of rural households in the Mekong Delta (2015)
Gregg, D., Rolfe, J.: The value of environment across efficiency quantiles: a conditional regression quantiles analysis of rangelands beef production in north Eastern Australia. Ecol. Econ. 128, 44–54 (2016)
Bernini, C., Freo, M., Gardini, A.: Quantile estimation of frontier production function. Empirical Econ. 29(2), 373–381 (2004)
Das, A.: Copula-based stochastic frontier model with autocorrelated inefficiency. Cent. Eur. J. Econ. Model. Econometrics 7(2), 111–126 (2015)
Smith, M.D.: Stochastic frontier models with dependent error components. Econometrics J. 11(1), 172–192 (2008)
Wiboonpongse, A., Liu, J., Sriboonchitta, S., Denoeux, T.: Modeling dependence between error components of the stochastic frontier model using copula: application to intercrop coffee production in Northern Thailand. Int. J. Approximate Reasoning 65, 34–44 (2015)
Horrace, W.C., Parmeter, C.F.: A Laplace stochastic frontier model. Econometric Rev. 1–27 (2015)
Burns, R.C.J.: The simulated maximum likelihood estimation of stochastic frontier models with correlated error components, Unpublished Dissertation, Department of Econometrics and Business Statistics, The University of Sydney, Australia (2004)
Battese, G.E., Coelli, T.J.: A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Econ. 20(2), 325–332 (1995)
Snchez, B.L., Lachos, H.V., Labra, V.F.: Likelihood based inference for quantile regression using the asymmetric Laplace distribution. J. Stat. Comput. Simul. 81, 1565–1578 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Pipitpojanakarn, V., Maneejuk, P., Yamaka, W., Sriboonchitta, S. (2016). Analysis of Agricultural Production in Asia and Measurement of Technical Efficiency Using Copula-Based Stochastic Frontier Quantile Model. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_59
Download citation
DOI: https://doi.org/10.1007/978-3-319-49046-5_59
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-49045-8
Online ISBN: 978-3-319-49046-5
eBook Packages: Computer ScienceComputer Science (R0)