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Technical Efficiency and Spatial Econometric Model: Application to Rice Production of Thailand

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Behavioral Predictive Modeling in Economics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 897))

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Abstract

Bayesian statistics and the MCMC simulation applied to the spatial panel data is presented in this paper focusing on rice farming in Thailand. Rice is chosen because it can be grown in all geographic regions of the country as the main staple and for domestic market and export. The rice sector has been crucial in all facets of the Thai society and rice farmers have been regarded as the backbone of the country. However, there are some obstacles curbing the improvement of rice production and rice farming systems. This paper is conducted employing the panel time-series data to investigate the spatial effects on the productivity of rice farming in Thailand. Yearly panel time-series data obtained from 76 provinces of Thailand is used for this study which includes three sections: (1) The overview of rice production in Thailand, (2) Technical efficiency reports for regional rice farming areas, and (3) Spatial panel econometric investigation to arrive at some significant findings for making effective policy recommendations. The empirical results from this study can be useful for those with interest in political benefit and contribute to the body of knowledge necessary for further research in agricultural economics.

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Notes

  1. 1.

    A rai is a unit of area which equals to 1,600 square meters (16 ares, 0.16 hectares, 0.3954 acres)

  2. 2.

    The standard instrument for the measurement of rainfall is the 203 mm (8 in.) rain gauge. This is essentially a circular funnel with a diameter of 203 mm which collects the rain into a graduated and calibrated cylinder. The measuring cylinder can record up to 25 mm of precipitation

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Author information

Authors and Affiliations

  1. Administration and Liberal of Art, Rajamangala University of Technology Lanna, Chiang Mai, Thailand

    Thunyawadee Sucharidtham

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Satawat Wannapan

Authors
  1. Thunyawadee Sucharidtham
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  2. Satawat Wannapan
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Corresponding author

Correspondence to Thunyawadee Sucharidtham .

Editor information

Editors and Affiliations

  1. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

  2. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  3. Faculty of Economics, Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand

    Woraphon Yamaka

Appendix A

Appendix A

Fig. 3
figure 3

The panel bar of rice productions (tons) in 76 provinces of Thailand

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Fig. 4
figure 4

The panel bar of rice planting areas (Rai) in 76 provinces of Thailand

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Fig. 5
figure 5

The panel bar of fertilizer usages (tons) in 76 provinces of Thailand

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Fig. 6
figure 6

The panel bar of rice farmer families (units) in 76 provinces of Thailand

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Fig. 7
figure 7

The panel bar of yearly rainfall measurement (mm.) in 76 provinces of Thailand

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Fig. 8
figure 8

The scatter plots of bootstrapping efficiencies of rice productions assuming bias corrections in 76 provinces of Thailand

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Fig. 9
figure 9

The scatter plots of bootstrapping efficiencies of rice productions assuming no bias corrections in 76 provinces of Thailand

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Fig. 10
figure 10

The scatter plots of bootstrapping efficiencies of rice productions with modified bias corrections in 76 provinces of Thailand

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Sucharidtham, T., Wannapan, S. (2021). Technical Efficiency and Spatial Econometric Model: Application to Rice Production of Thailand. In: Sriboonchitta, S., Kreinovich, V., Yamaka, W. (eds) Behavioral Predictive Modeling in Economics. Studies in Computational Intelligence, vol 897. Springer, Cham. https://doi.org/10.1007/978-3-030-49728-6_22

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