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Tarımsal Ar-Ge Harcamalarının Tarımsal Toplam Faktör Verimliliği Üzerindeki Etkileri: Seçilmiş Latin Amerika Ülkeleri Örneği

Yıl 2018, Cilt: 19 Sayı: 2, 17 - 26, 01.07.2018

Sefa Işık

Öz

Bu çalışmanın amacı, 1981-2013 döneminde seçilmiş 5 Latin Amerika ülkesini kapsayan tarımsal AR-GE harcamalarının tarımsal toplam faktör verimliliği üzerindeki etkilerini araştırmaktır. Çalışmada yatay kesit bağımlılığı altında panel eşbütünleşme analizi ve tamamen değiştirilmiş en küçük kareler FMOLS yöntemi kullanılmıştır. Çalışmanın sonucunda tarımsal AR-GE harcamaları ile tarımsal toplam faktör verimliliği arasında eşbütünleşme ilişkisi tespit edilmiş olup tarımsal AR-GE harcamalarının esneklik katsayısı 0,58 olarak bulunmuştur

Anahtar Kelimeler

AR-GE Toplam Faktör Verimliliği Tarım Sektörü

Kaynakça

  • Agricultural Science and Technology Indicators (ASTI, 2018). Retrieved from www.asti.cgiar.org.
  • Alene, A.D. (2010). “Productivity growth and the effects of R&D in African agriculture”, Agricultural Economics, 41, 223–238.
  • Alston, J.M., Chan-Kang, C., Marra, M.C., Pardey, P.G. and Wyatt, T.J. (2000). A Meta-Analysis of Rates of Return to Agricultural R&D: Ex Pede Herculem? Washington D.C.: IFPRI Research Report No 113.
  • Breusch, T., and A. Pagan (1980). “The lagrange multiplier test and its application to model specification in econometrics”, Review of Economic Studies, 47, 239– 253.
  • Chen, P. C., Yu, M. M., Chang, C. C., and Hsu, S. H. (2008). “Total factor productivity growth in China's agricultural sector”, China Economic Review, 19(4), 580-593. doi:https://doi.org/10.1016/j.chieco.2008.07.001
  • Cox, T., Mullen, J. and Hu, W.S. (1997). “Nonparametric measures of the impact of public research expenditures on Australian broadacre agriculture”, Australian Journal of Agricultural and Resource Economics, 41, 333–360.
  • Evenson, R. E., Pray, C. E., and Rosegrant, M. W. (1999). Agricultural research and productivity growth in India, Research Report, 109. Washington: IFPRI.
  • FAO. (2017). The future of food and agriculture – Trends and challenges. Rome.
  • Fuglie, K.O., MacDonald, J.M., and Ball, E. (2007). Productivity growth in U.S. agriculture, United States Department of Agriculture – Economic Research Service (USDA – ERS), Economic Brief Number 9.
  • Khundrakpam, J.K. and Ranjan, R. (2010). “Saving-investment nexus and international capital mobility in India: Revisiting Feldstein-Harioka hypothesis”, Indian Economic Review, New Series, Vol. 45, No. 1, 49-66.
  • Ludena, C. (2010). “Agricultural productivity growth, efficiency change and technical progress in Latin America and the Caribbean”. Inter-American Development Bank, Working Paper Series No. 186, Washington DC..
  • Lusigi, A. and Thirtle, C. (1997). “Total factor productivity and the effects of R&D in African Agriculture”, Journal of International Development, Vol. 9, No. 4, 529-538.
  • McAtee, W. (1936). “The Malthusian Principle in Nature”. The Scientific Monthly, 42(5), 444-456. Retrieved from http://www.jstor.org/stable/15956.
  • Mullen, J.D. and Cox, T.L. (1995). “The returns from research in Australian broadacre agriculture”, Australian Journal of Agricultural Economics, 39, 105–128.
  • Nin-Pratt, A., Falconi, C., Ludena, C.E., and Martel, P. (2015). “Productivity and the performance of agriculture in Latin America and the Caribbean: from the lost decade to the commodity boom”. Inter-American Development Bank, Working Paper No. 608 (IDB-WP-608), Washington DC..
  • OECD (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264239012-en
  • Pedroni, P. (2000). “Fully-modified OLS for heterogeneous cointegrated panels”, Advances in Econometrics, 15, 93-130.
  • Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. J. Appl. Econ., 22: 265–312. doi: 10.1002/jae.951
  • Phillips, P., and Hansen, B. (1990). “Statistical inference in instrumental variables regression with I (1) processes”, Review of Economic Studies, Vol. 57, Issue: 1, 99–125.
  • Salim, R. A., and Islam, N. (2010). “Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia”, The Australian Journal of Agricultural and Resource Economics, 54, 561–582.
  • Singh, R.B., Kumar, P., and Woodhead, T. (2002). Smallholder farmers in India: food security and agricultural policy, FAO Regional Office for Asia and the Pacific, RAP publication: 2002/03.
  • Suphannachart, W. and Warr, P. (2011). “Research and productivity in Thai agriculture”, Australian Journal of Agricultural and Resource Economics, 55: 35–52. doi: 10.1111/j.1467-8489.2010.00519.x.
  • The World Bank (2018), Population indicators. Retrieved from https://data.worldbank.org/indicator/SP.POP.TOTL
  • United States Department of Agriculture – Economic Research Service (USDA – ERS, 2018), International Agricultural Productivity (Data set). Retrieved from www.ers.usda.gov.
  • USDA (2012). Total factor productivity has become the primary source of growth in world agriculture. Retrieved from https://www.ers.usda.gov/data- products/chart-gallery/gallery/chart-detail/?chartId=76219
  • Westerlund, J. (2008). Panel cointegration tests of the Fisher effect, Journal of Applied Econometrics, 23: 193 233.
  • Zereyesus, Y.A., Dalton, T.J. (2017) “Rates of return to sorghum and millet research investments: A meta-analysis”. PLoS ONE 12(7): e0180414. https://doi.org/10.1371/journal.pone.0180414

The Impacts of Agricultural Research and Development Expenditures on Agricultural Total Factor Productivity: Evidence from Selected Latin American Countries

Yıl 2018, Cilt: 19 Sayı: 2, 17 - 26, 01.07.2018

Sefa Işık

Öz

The aim of the study is to investigate the impacts of agricultural research and development expenditures on agricultural total factor productivity by using annual panel data set covering 5 selected Latin American countries from 1981 to 2013. In doing so, we use the panel cointegration analysis under cross-section dependence and panel fully modified ordinary least squares FMOLS method. At the end of the analysis; there is a cointegration relationship between research and development and total factor productivity in agriculture sector for these selected countries. Also, the elasticity coefficient of agricultural research and development expenditures is 0.58.

Anahtar Kelimeler

Research and Development Total Factor Productivity Agriculture Sector

Kaynakça

  • Agricultural Science and Technology Indicators (ASTI, 2018). Retrieved from www.asti.cgiar.org.
  • Alene, A.D. (2010). “Productivity growth and the effects of R&D in African agriculture”, Agricultural Economics, 41, 223–238.
  • Alston, J.M., Chan-Kang, C., Marra, M.C., Pardey, P.G. and Wyatt, T.J. (2000). A Meta-Analysis of Rates of Return to Agricultural R&D: Ex Pede Herculem? Washington D.C.: IFPRI Research Report No 113.
  • Breusch, T., and A. Pagan (1980). “The lagrange multiplier test and its application to model specification in econometrics”, Review of Economic Studies, 47, 239– 253.
  • Chen, P. C., Yu, M. M., Chang, C. C., and Hsu, S. H. (2008). “Total factor productivity growth in China's agricultural sector”, China Economic Review, 19(4), 580-593. doi:https://doi.org/10.1016/j.chieco.2008.07.001
  • Cox, T., Mullen, J. and Hu, W.S. (1997). “Nonparametric measures of the impact of public research expenditures on Australian broadacre agriculture”, Australian Journal of Agricultural and Resource Economics, 41, 333–360.
  • Evenson, R. E., Pray, C. E., and Rosegrant, M. W. (1999). Agricultural research and productivity growth in India, Research Report, 109. Washington: IFPRI.
  • FAO. (2017). The future of food and agriculture – Trends and challenges. Rome.
  • Fuglie, K.O., MacDonald, J.M., and Ball, E. (2007). Productivity growth in U.S. agriculture, United States Department of Agriculture – Economic Research Service (USDA – ERS), Economic Brief Number 9.
  • Khundrakpam, J.K. and Ranjan, R. (2010). “Saving-investment nexus and international capital mobility in India: Revisiting Feldstein-Harioka hypothesis”, Indian Economic Review, New Series, Vol. 45, No. 1, 49-66.
  • Ludena, C. (2010). “Agricultural productivity growth, efficiency change and technical progress in Latin America and the Caribbean”. Inter-American Development Bank, Working Paper Series No. 186, Washington DC..
  • Lusigi, A. and Thirtle, C. (1997). “Total factor productivity and the effects of R&D in African Agriculture”, Journal of International Development, Vol. 9, No. 4, 529-538.
  • McAtee, W. (1936). “The Malthusian Principle in Nature”. The Scientific Monthly, 42(5), 444-456. Retrieved from http://www.jstor.org/stable/15956.
  • Mullen, J.D. and Cox, T.L. (1995). “The returns from research in Australian broadacre agriculture”, Australian Journal of Agricultural Economics, 39, 105–128.
  • Nin-Pratt, A., Falconi, C., Ludena, C.E., and Martel, P. (2015). “Productivity and the performance of agriculture in Latin America and the Caribbean: from the lost decade to the commodity boom”. Inter-American Development Bank, Working Paper No. 608 (IDB-WP-608), Washington DC..
  • OECD (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264239012-en
  • Pedroni, P. (2000). “Fully-modified OLS for heterogeneous cointegrated panels”, Advances in Econometrics, 15, 93-130.
  • Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. J. Appl. Econ., 22: 265–312. doi: 10.1002/jae.951
  • Phillips, P., and Hansen, B. (1990). “Statistical inference in instrumental variables regression with I (1) processes”, Review of Economic Studies, Vol. 57, Issue: 1, 99–125.
  • Salim, R. A., and Islam, N. (2010). “Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia”, The Australian Journal of Agricultural and Resource Economics, 54, 561–582.
  • Singh, R.B., Kumar, P., and Woodhead, T. (2002). Smallholder farmers in India: food security and agricultural policy, FAO Regional Office for Asia and the Pacific, RAP publication: 2002/03.
  • Suphannachart, W. and Warr, P. (2011). “Research and productivity in Thai agriculture”, Australian Journal of Agricultural and Resource Economics, 55: 35–52. doi: 10.1111/j.1467-8489.2010.00519.x.
  • The World Bank (2018), Population indicators. Retrieved from https://data.worldbank.org/indicator/SP.POP.TOTL
  • United States Department of Agriculture – Economic Research Service (USDA – ERS, 2018), International Agricultural Productivity (Data set). Retrieved from www.ers.usda.gov.
  • USDA (2012). Total factor productivity has become the primary source of growth in world agriculture. Retrieved from https://www.ers.usda.gov/data- products/chart-gallery/gallery/chart-detail/?chartId=76219
  • Westerlund, J. (2008). Panel cointegration tests of the Fisher effect, Journal of Applied Econometrics, 23: 193 233.
  • Zereyesus, Y.A., Dalton, T.J. (2017) “Rates of return to sorghum and millet research investments: A meta-analysis”. PLoS ONE 12(7): e0180414. https://doi.org/10.1371/journal.pone.0180414
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Araştırma Makalesi
Yazarlar

Sefa Işık Bu kişi benim

Yayımlanma Tarihi 1 Temmuz 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 19 Sayı: 2

Kaynak Göster

APA Işık, S. (2018). The Impacts of Agricultural Research and Development Expenditures on Agricultural Total Factor Productivity: Evidence from Selected Latin American Countries. Doğuş Üniversitesi Dergisi, 19(2), 17-26.