A Spatial Analysis of Irrigation Technology

Abstract

The nature of spatial spillovers in the adoption of irrigation technology is examined in this paper. Adopting a new technology is a decision that is based on economic and individual-specific factors. One of these individual factors might be communication with other users. It makes sense to expect that contact between users and non-users would follow a spatial pattern, and if knowledge spillovers are important to the adoption decision then resource managers need to be aware of their existence. Using counties in the Texas High Plains as the study area, the adoption of center pivot technology is examined using both Ordinary Least Squares and spatial regression models to determine if knowledge spillovers exist. Ultimately, no evidence was found that adoption practices in a county affects its neighbors; however, geographic location does matter to who adopts and when.

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A. Wright, D. Hudson and M. Mutuc, "A Spatial Analysis of Irrigation Technology," Natural Resources, Vol. 4 No. 4, 2013, pp. 307-318. doi: 10.4236/nr.2013.44037.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] M. Caswell and D. Zilberman, “The Effects of Well Depth and Land Quality on the Choice of Irrigation Technology,” American Journal of Agricultural Economics, Vol. 68, No. 4, 1986, pp. 798-811. doi:10.2307/1242126
[2] R. Shrestha and C. Gopalakrishnan, “Adoption and Diffusion of Drip Irrigation Technology: An Econometric Analysis,” Economic Development and Cultural Change, Vol. 41, No. 2, 1993, pp. 407-18. doi:10.1086/452018
[3] A. Abdulai and W. Huffman, “The Diffusion of New Agricultural Technologies: The Case of Crossbred-Cow Technology in Tanzania,” American Journal of Agricultural Economics, Vol. 87, No. 3, 2005, pp. 645-59. doi:10.1111/j.1467-8276.2005.00753.x
[4] P. Koundouri, C. Nauges and V. Tzouvelekas, “Technology Adoption Under Production Uncertainty: Theory and Application to Irrigation Technology,” American Journal of Agricultural Economics, Vol. 88, No. 3, 2006, pp. 657-670. doi:10.1111/j.1467-8276.2006.00886.x
[5] G. Green, D. Sunding, D. Zilberman and D. Parker, “Explaining Irrigation Technology Choices: A Microparameter Approach,” American Journal of Agricultural Economics, Vol. 78, No. 4, 1996, pp. 1064-1072. doi:10.2307/1243862
[6] E. Mansfield, “Technical Change and the Rate of Imitation,” Econometrica, Vol. 29, No. 4, 1961, pp. 741-766. doi:10.2307/1911817
[7] F. Bass, “A New Product Growth for Model Consumer Durables,” Management Science, Vol. 15, No. 5, 1969, pp. 215-227. doi:10.1287/mnsc.15.5.215
[8] P. Geroski, “Models of Technology Diffusion,” Research Policy, Vol. 29, No. 4-5, 2000, pp. 603-625. doi:10.1016/S0048-7333(99)00092-X
[9] B. Wejnert, “Integrating Models of Diffusion of Innovations: A Conceptual Framework,” Annual Review of Sociology, Vol. 28, No. 1, 2002, pp. 297-326. doi:10.1146/annurev.soc.28.110601.141051
[10] E. Rogers, “Diffusion of Innovations,” 5th Edition, Free Press, New York, 2003.
[11] N. McRoberts and A. Frank, “A Diffusion Model for the Adoption of Agricultural Innovations in Structured Adopting Populations,” Working Paper No. 29, Land Economy Research Group, 2008. http://ageconsearch.umn.edu/handle/61117
[12] G. Feder, R. Just and D. Zilberman, “Adoption of Agricultural Innovations in Developing Countries: A Survey,” Economic Development and Cultural Change, Vol. 33, No. 2, 1985, pp. 255-298. doi:10.1086/451461
[13] A. Foster and M. Rosenzweig, “Microeconomics of Technology Adoption,” Center Discussion Paper No. 984, Economic Growth Center, Yale University, 2010. http://www.econ.yale.edu/growth_pdf/cdp984.pdf
[14] K. Fuglie and C. Kascak, “Adoption and Diffusion of Natural Resource Conserving Technology,” Review of Agricultural Economics, Vol. 23, No. 2, 2001, pp. 386-403. doi:10.1111/1467-9353.00068
[15] S. Davies, “The Diffusion Process of Innovations,” Cambridge University Press, Cambridge, 1979.
[16] R. Just, D. Zilberman and G. Rausser, “A Putty Clay Approach to the Distributional Effects of New Technology under Risk,” In: D. Yaron and C. Tapiero, Eds., Operations Research in Agriculture and Water Resources, North-Holland Publishing Co., Amsterdam, 1980, pp. 97-121.
[17] G. Feder and G. O’Mara, “Farm Size and the Adoption of Green Revolution Technology,” Economic Development and Cultural Change, Vol. 30, No. 1, 1981, pp. 59-76. doi:10.1086/452539
[18] F. Shah, D. Zilberman and U. Chakravorty, “Technology Adoption in the Presence of an Exhaustible Resource: The Case of Groundwater Extraction,” American Journal of Agricultural Economics, Vol. 77, No. 2, 1995, pp. 291-299. doi:10.1086/452539
[19] W. Keller, “Are International R&D Spillovers Trade Related? Analyzing Spillovers among Randomly Matched Trade Partners,” European Economic Review, Vol. 42, No. 8, 1998, pp. 1469-1481. doi:10.1016/S0014-2921(97)00092-5
[20] W. Keller, “The Geography and Channels of Diffusion at the World’s Technology Frontier,” NBER Working Papers No. 8150, National Bureau of Economic Research, 2001. http://www.nber.org/papers/w8150.pdf
[21] M. Abreu, H. Groot and R. Florax, “Spatial Patterns of Technology Diffusion,” Tinbergen Institute Discussion Paper, TI-2004-079/3, 2004. http://www.tinbergen.nl/discussionpapers/04079.pdf
[22] High Plains Water District No. 1, “The Cross Section,” Various Issues, 1981-2005.
[23] High Plains Water District No. 1, “Personal Communication, Personal Communication Regarding the Number of Center Pivots Systems in the Water District in Various Years,” 2012.
[24] Texas Tech University Center for Geospatial Technology, “Texas County Water Information,” 2010. http://www.gis.ttu.edu/OgallalaAquiferMaps/
[25] US Department of Agriculture, National Agricultural Statistics Service, “Quick Stats: US and All States County Data-Crops,” 2010. http://www.nass.usda.gov/QuickStats/Create_County_All.jsp
[26] S. Stadler, “Aridity Indices,” In: J. E. Oliver, Ed., Encyclopedia of World Climatology, Spinger, Berlin, 2005. http://link.springer.com/referenceworkentry/10.1007/1-4020-3266-8_17/fulltext.html
[27] Western Regional Climate Center, “Western US Climate Historical Summaries,” 2012. http://www.wrcc.dri.edu/Climsum.html
[28] Federal Reserve Board of Governors, “Selected Interest Rates,” 2011. http://www.federalreserve.gov/releases/h15/data.htm
[29] L. Anselin, “Under the Hood: Issues in the Specification and Interpretation of Spatial Regression Models,” Agricultural Economics, Vol. 27, No. 3, 2002, pp. 247-267. doi:10.1111/j.1574-0862.2002.tb00120.x
[30] Texas State Historical Society, Various County WebPages, 2012. http://www.tshaonline.org/
[31] P. Moran, “The Interpretation of Statistical Maps,” Journal of the Royal Statistical Society, Series B (Methodological), Vol. 10, No. 2, 1948, pp. 243-251.
[32] P. Jeanty, “Spmlreg: Stata Module to Estimate the Spatial Lag, the Spatial Error, the Spatial Durbin, and the General Spatial Models,” 2010. http://ideas.repec.org/c/boc/bocode/s457135.html
[33] P. Jeanty, “Splagvar: Stata Module to Generate Spatially Lagged Variables, construct the Moran Scatter Plot, and Calculate global Moran’s I Statistics,” 2010. http://ideas.repec.org/c/boc/bocode/s457112.html
[34] P. Jeanty, “Spwmatrix: Stata Module to Create, Import, and Export Spatial Weights,” 2010. http://ideas.repec.org/c/boc/bocode/s457111.html
[35] M. Pisati, “Tools for Spatial Data Analysis,” Stata Technical Bulletin, No. 60, 2001, pp. 21-37. http://www.stata.com/products/stb/journals/stb60.pdf
[36] L. Anselin, “Exploring Spatial Data with GeoDa: A Workbook,” 2005. https://geodacenter.asu.edu/system/files/geodaworkbook.pdf

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