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Spatial Analysis of Research-Productivity Nexus: A Case of Thai Rice Sector

  • Waleerat Suphannachart
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

Location matters for agricultural production and for farmers’ decision on adopting new crop varieties. Similar outputs, inputs, and productivity tend to be observed in areas with close proximity suggesting the importance of neighbourhood influence. However, this spatial pattern has been ignored when estimating the agricultural research impact on productivity in which agricultural research has been recognised as a primary source of productivity change. This study aims to test the existence of any spatial pattern of research-productivity relation using subnational-level data for the case of Thai rice production. The estimation incorporates the spatial effects in the total factor productivity (TFP) determinant model using the provincial-level data which includes 76 provinces of Thailand during 2004–2012. The simple spatial econometric models, spatial lag and spatial error, are employed. The significance of the spatial dependence is confirmed using the spatial lag model suggesting the TFP in one province is significantly associated with the TFP in neighbouring provinces. The findings generally confirm the existence of neighbourhood influence, and so the spatial pattern should be taken into account when measuring the agricultural research impact on productivity using subnational-level data.

References

  1. Anselin, L. (1988). Spatial econometrics: Methods and models. Boston: Kluwer Academic.CrossRefGoogle Scholar
  2. Anselin, L. (1999). Spatial econometrics. Center School of Social Sciences. Bruton: University of Texas at Dallas.Google Scholar
  3. Anselin, L., Bongiovanni, R., & Lowenberg-DeBoer, J. (2004). A spatial econometric approach to the economics of site-specific nitrogen management in corn production. American Economic Journal of Agricultural Economics, 86, 675–687.CrossRefGoogle Scholar
  4. APO. (2001). Measuring total factor productivity: Survey report. Tokyo: Asian Productivity Organization.Google Scholar
  5. Baylis, R., Paulson, D., & Piras, G. (2011). Spatial approaches to panel data in agricultural economics: A climate change application. Journal of Agricultural and Applied Economics, 43(3), 325–338.CrossRefGoogle Scholar
  6. Capello, R., & Lenzi, C. (2015). The knowledge-innovation Nexus: Its spatially differentiated returns to innovation. Growth and Change, 46(3), 379–399.CrossRefGoogle Scholar
  7. Evenson, R. (2001). Economic impacts of agricultural research and extension. In B. Gardner & G. Rausser (Eds.), Handbook of agricultural economics (1st ed., pp. 573–628). Amsterdam: Elsevier.Google Scholar
  8. Evenson, R., & Gollin, D. (2003). Crop variety improvement and its effect on productivity. Cambridge: CABI Publishing.CrossRefGoogle Scholar
  9. Evenson, R., & Pray, C. (1991). Research and productivity in Asian agriculture. Ithaca: Cornell University Press.Google Scholar
  10. Fan, S., & Pardey, P. (1997). Research, productivity, and output growth in chinese agriculture. Journal of Development Economics, 53(1), 115–137.CrossRefGoogle Scholar
  11. GeoDa Center. (2016). Research. The Center for Spatial Data Science, The University of Chicago. Available via http://spatial.uchicago.edu/research2. Accessed 19 Nov 2016.
  12. Kelvin, B., Alastair, B., & Iain, F. (2005). Measuring the impact of R&D on productivity from a econometric time series perspective. Journal of Productivity Analysis, 24(1), 49–72.CrossRefGoogle Scholar
  13. Khunbanthao, K., & Suphannachart, W. (2016). Analysis of total factor productivity of rice in Thailand. 5th National Conference on Agricultural economics, resource economics, food economics and agribusiness, Bangkok, Thailand, 15 July 2016.Google Scholar
  14. Pochanukul, P. (1992). An economic study of public research contributions in Thai crop production: A time and spatial analysis. Dissertation, Kyoto University.Google Scholar
  15. Ruttan, V. (1987). Agricultural research policy and development. Rome: Food and Agriculture Organization of the United Nations.Google Scholar
  16. Setboonsarng, S., & Evenson, R. (1991). Technology, infrastructure, output supply, and factor demand in Thai agriculture. In R. Evenson & C. Pray (Eds.), Research and productivity in Asian Agriculture. Ithaca: Cornell University Press.Google Scholar
  17. Suphannachart, W. (2013). Total factor productivity of main and second rice production in Thailand. Applied Economics Journal, 20(1), 1–22.Google Scholar
  18. Suphannachart, W. (2016). Returns to major agricultural R&D sources in Thailand. American Journal of Economics, 6(1), 22–26.Google Scholar
  19. Suphannachart, W., & Warr, P. (2011). Research and productivity in Thai agriculture. The Australian Journal of Agricultural and Resource Economics, 55(1), 35–52.CrossRefGoogle Scholar
  20. Suphannachart, W., & Warr, P. (2012). Total factor productivity in Thai agriculture: Measurement and determinants. In K. O. Fuglie, S. L. Wang, & V. E. Ball (Eds.), Productivity growth in agriculture: An international perspective. Oxfordshire: CAB International.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Agricultural and Resource EconomicsFaculty of Economics, Kasetsart UniversityBangkokThailand

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