Adopting sustainable irrigation technologies in Italy: a study on the determinants of inter- and intra-farm diffusion

References

• Alcon, F., M. D. de Miguel, and M. Burton. 2011. “Duration Analysis of Adoption of Drip Irrigation Technology in Southeastern Spain.” Technological Forecasting and Social Change 78: 991–1001. doi:10.1016/j.techfore.2011.02.001.
   Web of Science ®Google Scholar
• Antonelli, C. 1990. “Induced Adoption and Externalities in the Regional Diffusion of Information Technology.” Regional Studies 24: 31–40. doi:10.1080/00343409012331345764.
   Web of Science ®Google Scholar
• Antonelli, C. 2006. “Diffusion as a Process of Creative Adoption.” The Journal of Technology Transfer 31: 211–226. doi:10.1007/s10961-005-6107-y.
   Google Scholar
• Arslan, A., N. McCarthy, L. Lipper, S. Asfaw, and A. Cattaneo. 2014. “Adoption and Intensity of Adoption of Conservation Farming Practices in Zambia.” Agriculture, Ecosystems & Environment 187: 72–86. doi:10.1016/j.agee.2013.08.017.
   Web of Science ®Google Scholar
• Asfaw, S., N. McCarthy, L. Lipper, A. Arslan, and A. Cattaneo. 2016. “What Determines Farmers’ Adaptive Capacity? Empirical Evidence from Malawi.” Food Security 8: 643–664. doi:10.1007/s12571-016-0571-0.
   Web of Science ®Google Scholar
• Battisti, G., and P. Stoneman. 2003. “Inter- and Intra-Firm Effects in the Diffusion of New Process Technology.” Research Policy 32: 1641–1655. doi:10.1016/S0048-7333(03)00055-6.
   Web of Science ®Google Scholar
• Bazzani, G. M., S. Di Pasquale, V. Gallerani, S. Morganti, M. Raggi, and D. Viaggi. 2005. “The Sustainability of Irrigated Agricultural Systems Under the Water Framework Directive: First Results.” Environmental Modelling & Software 20: 165–175. doi:10.1016/j.envsoft.2003.12.018.
   Web of Science ®Google Scholar
• Berbel, J., C. Gutiérrez-Martín, and A. Expósito. 2018. “Impacts of Irrigation Efficiency Improvement on Water Use, Water Consumption and Response to Water Price at Field Level.” Agricultural Water Management 203: 423–429. doi:10.1016/j.agwat.2018.02.026.
   Web of Science ®Google Scholar
• Burton, R. J. F. 2004. “Seeing Through the ‘Good Farmer’s’ Eyes: Towards Developing an Understanding of the Social Symbolic Value of ‘Productivist’ Behaviour.” Sociologia Ruralis 44: 195–215. doi:10.1111/j.1467-9523.2004.00270.x.
   Web of Science ®Google Scholar
• Caswell, M., and D. Zilberman. 1985. “The Choices of Irrigation Technologies in California.” American Journal of Agricultural Economics 67: 224–234. doi:10.2307/1240673.
   Web of Science ®Google Scholar
• CGIAR. 2019. Global Geospatial Potential EvapoTranspiration & Aridity Index Methodology and Dataset Description. https://cgiarcsi.community/data/global-aridity-and-pet-database/ (accessed on May 2019).
   Google Scholar
• Colombelli, A., J. Krafft, and F. Quatraro. 2021. “Firms’ Growth, Green Gazelles and eco-Innovation: Evidence from a Sample of European Firms.” Small Business Economics 56: 1721–1738. doi:10.1007/s11187-019-00236-8.
   Web of Science ®Google Scholar
• Costantini, V., F. Crespi, and A. Palma. 2017. “Characterizing the Policy Mix and Its Impact on Eco-Innovation: A Patent Analysis of Energy-Efficient Technologies.” Research Policy 46: 799–819. doi:10.1016/j.respol.2017.02.004.
   Web of Science ®Google Scholar
• Dearing, J. W. 2009. “Applying Diffusion of Innovation Theory to Intervention Development.” Research on Social Work Practice 19: 503–518. doi:10.1177/1049731509335569.
   PubMed Web of Science ®Google Scholar
• Doss, C. R., and M. L. Morris. 2000. “How Does Gender Affect the Adoption of Agricultural Innovations? The Case of Improved Maize Technology in Ghana.” Agricultural Economics 25: 27–39. doi:10.1111/j.1574-0862.2001.tb00233.x.
   Web of Science ®Google Scholar
• EEA. 2019. Climate Change Adaptation in the Agriculture Sector in Europe (No. EEA Report No. 4/2019). Copenhagen: European Environmental Agency.
   Google Scholar
• EU Commission. 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 Establishing a Framework for Community Action in the Field of Water Policy, OJ L. 327.
   Google Scholar
• EU Commission. 2019a. Farm-to-Fork Strategy.
   Google Scholar
• EU Commission. 2019b. European Green Deal.
   Google Scholar
• Allen, R. G., and FAO, eds. 1998. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements, FAO Irrigation and Drainage Paper. Rome: Food and Agriculture Organization of the United Nations.
   Google Scholar
• FAO, IFAD, and WFP. 2015. “The State of Food Insecurity in the World 2015.” Meeting the 2015 International Hunger Targets: Taking Stock of Uneven Progress, Rome, Italy.
   Google Scholar
• Feder, G. 1982. “Adoption of Interrelated Agricultural Innovations: Complementarity and the Impacts of Risk, Scale, and Credit.” American Journal of Agricultural Economics 64: 94–101. doi:10.2307/1241177.
   Web of Science ®Google Scholar
• Feder, G., R. E. Just, and D. Zilberman. 1985. “Adoption of Agricultural Innovations in Developing Countries: A Survey.” Economic Development and Cultural Change 33: 255–298. doi:10.1086/451461.
   Web of Science ®Google Scholar
• Feder, G., and D. L. Umali. 1993. “The Adoption of Agricultural Innovations: A Review.” Technological Forecasting and Social Change 43: 215–239. doi:10.1016/0040-1625(93)90053-A.
   Web of Science ®Google Scholar
• Fischer, G., F. N. Tubiello, H. van Velthuizen, and D. A. Wiberg. 2007. “Climate Change Impacts on Irrigation Water Requirements: Effects of Mitigation, 1990–2080.” Technological Forecasting and Social Change 74: 1083–1107. doi:10.1016/j.techfore.2006.05.021.
   Web of Science ®Google Scholar
• Foster, A. D., and M. R. Rosenzweig. 2010. “Microeconomics of Technology Adoption.” Annual Review of Economics 2: 395–424. doi:10.1146/annurev.economics.102308.124433.
   Web of Science ®Google Scholar
• Geroski, P. A. 2000. “Models of Technology Diffusion.” Research Policy 29: 603–625. doi:10.1016/S0048-7333(99)00092-X.
   Web of Science ®Google Scholar
• Green, G., D. Sunding, D. Zilberman, and D. Parker. 1996. “Explaining Irrigation Technology Choices: A Microparameter Approach.” American Journal of Agricultural Economics 78: 1064–1072. doi:10.2307/1243862.
   Web of Science ®Google Scholar
• Huang, Q., Y. Xu, K. Kovacs, and G. West. 2017. “Analysis of Factors That Influence the Use of Irrigation Technologies and Water Management Practices in Arkansas.” Journal of Agricultural and Applied Economics 49: 159–185. doi:10.1017/aae.2017.3.
   Google Scholar
• Hubbard, A. E., J. Ahern, N. L. Fleischer, M. Van der Laan, S. A. Satariano, N. Jewell, T. Bruckner, and W. A. Satariano. 2010. “To GEE or Not to GEE: Comparing Population Average and Mixed Models for Estimating the Associations Between Neighborhood Risk Factors and Health.” Epidemiology 21: 467–474. doi:10.1097/EDE.0b013e3181caeb90.
   PubMed Web of Science ®Google Scholar
• Hunecke, C., A. Engler, R. Jara-Rojas, and P. M. Poortvliet. 2017. “Understanding the Role of Social Capital in Adoption Decisions: An Application to Irrigation Technology.” Agricultural Systems 153: 221–231. doi:10.1016/j.agsy.2017.02.002.
   Web of Science ®Google Scholar
• Knapp, T., and Q. Huang. 2017. “Do Climate Factors Matter for Producers’ Irrigation Practices Decisions?” Journal of Hydrology 552: 81–91. doi:10.1016/j.jhydrol.2017.06.037.
   Web of Science ®Google Scholar
• Koundouri, P., C. Nauges, and V. Tzouvelekas. 2006. “Technology Adoption Under Production Uncertainty: Theory and Application to Irrigation Technology.” American Journal of Agricultural Economics 88: 657–670. doi:10.1111/j.1467-8276.2006.00886.x.
   Web of Science ®Google Scholar
• Mairesse, J., and P. Mohnen. 2010. “Chapter 26: Using Innovation Surveys for Econometric Analysis.” In Handbook of the Economics of Innovation, edited by B. H. Hall and N. Rosenberg, 1129–1155. North-Holland. doi:10.1016/S0169-7218(10)02010-1.
   Google Scholar
• Mango, N., C. Makate, L. Tamene, P. Mponela, and G. Ndengu. 2018. “Adoption of Small-Scale Irrigation Farming as a Climate-Smart Agriculture Practice and Its Influence on Household Income in the Chinyanja Triangle, Southern Africa.” Land 7: 49. doi:10.3390/land7020049.
   Web of Science ®Google Scholar
• Moreno, G., and D. L. Sunding. 2005. “Joint Estimation of Technology Adoption and Land Allocation with Implications for the Design of Conservation Policy.” American Journal of Agricultural Economics 87: 1009–1019. doi:10.1111/j.1467-8276.2005.00784.x.
   Web of Science ®Google Scholar
• Mundlak, Y. 1978. “On the Pooling of Time Series and Cross Section Data.” Econometrica 46: 69–85. doi:10.2307/1913646.
   Web of Science ®Google Scholar
• Neuhaus, J. M. 1992. “Statistical Methods for Longitudinal and Clustered Designs with Binary Responses.” Statistical Methods in Medical Research 1: 249–273. doi:10.1177/096228029200100303.
   PubMedGoogle Scholar
• Neuhaus, J. M., J. D. Kalbfleisch, and W. W. Hauck. 1991. “A Comparison of Cluster-Specific and Population-Averaged Approaches for Analyzing Correlated Binary Data.” International Statistical Review / Revue Internationale de Statistique 59: 25–35. doi:10.2307/1403572.
   Web of Science ®Google Scholar
• Papke, L. E., and J. M. Wooldridge. 2008. “Panel Data Methods for Fractional Response Variables with an Application to Test Pass Rates.” Journal of Econometrics 145: 121–133. doi:10.1016/j.jeconom.2008.05.009.
   Web of Science ®Google Scholar
• Pérez-Blanco, C. D., A. Hrast-Essenfelder, and C. Perry. 2020. “Irrigation Technology and Water Conservation: A Review of the Theory and Evidence.” Review of Environmental Economics and Policy 14: 216–239. doi:10.1093/reep/reaa004.
   Web of Science ®Google Scholar
• Pérez-Blanco, C. D., A. Loch, F. Ward, C. Perry, and D. Adamson. 2021. “Agricultural Water Saving Through Technologies: A Zombie Idea.” Environmental Research Letters 16: 114032. doi:10.1088/1748-9326/ac2fe0.
   Web of Science ®Google Scholar
• Pokhrel, B., K. Paudel, and E. Segarra. 2018. “Factors Affecting the Choice, Intensity, and Allocation of Irrigation Technologies by U.S. Cotton Farmers.” Water 10: 706. doi:10.3390/w10060706.
   Web of Science ®Google Scholar
• Reidsma, P., F. Ewert, A. O. Lansink, and R. Leemans. 2010. “Adaptation to Climate Change and Climate Variability in European Agriculture: The Importance of Farm Level Responses.” European Journal of Agronomy 32: 91–102. doi:10.1016/j.eja.2009.06.003.
   Web of Science ®Google Scholar
• Rogers, E. M. 1971. Diffusion of Innovations. New York: The Free Press.
   Google Scholar
• Somda, J., A. J. Nianogo, S. Nassa, and S. Sanou. 2002. “Soil Fertility Management and Socio-Economic Factors in Crop-Livestock Systems in Burkina Faso: A Case Study of Composting Technology.” Ecological Economics 43: 175–183. doi:10.1016/S0921-8009(02)00208-2.
   Web of Science ®Google Scholar
• Stoneman, P. 2013. “The Impact of Prior Use on the Further Diffusion of New Process Technology.” Economics of Innovation and New Technology 22: 238–255. doi:10.1080/10438599.2012.708133.
   Google Scholar
• Stoneman, P., and G. Battisti. 2010. “Chapter 17: The Diffusion of New Technology.” In Handbook of the Economics of Innovation, edited by B. H. Hall and N. Rosenberg, 733–760. North-Holland. doi:10.1016/S0169-7218(10)02001-0.
   Google Scholar
• Stoneman, P., and P. Diederen. 1994. “Technology Diffusion and Public Policy.” The Economic Journal 104: 918–930. doi:10.2307/2234987.
   Web of Science ®Google Scholar
• Streletskaya, N. A., S. D. Bell, M. Kecinski, T. Li, S. Banerjee, L. H. Palm-Forster, and D. Pannell. 2020. “Agricultural Adoption and Behavioral Economics: Bridging the Gap.” Applied Economic Perspectives and Policy 42: 54–66. doi:10.1002/aepp.13006.
   Web of Science ®Google Scholar
• Taylor, R., and D. Zilberman. 2017. “Diffusion of Drip Irrigation: The Case of California.” Applied Economic Perspectives and Policy 39: 16–40. doi:10.1093/aepp/ppw026.
   Web of Science ®Google Scholar
• Tobin, J. 1958. “Estimation of Relationships for Limited Dependent Variables.” Econometrica 26: 24–36. doi:10.2307/1907382.
   Web of Science ®Google Scholar
• Woodill, A. J., and M. J. Roberts. 2018. “Adaptation to Climate Change: Disentangling Revenue and Crop Choice Responses.” Presented at the WCERE 2018.
   Google Scholar
• Wooldridge, J. M. 2010. Econometric Analysis of Cross Section and Panel Data. 2nd ed. Cambridge: MIT Press.
   Google Scholar
• Ziliak, S. T., and D. N. McCloskey. 2004a. “Significance Redux.” The Journal of Socio-Economics 33: 665–675. doi:10.1016/j.socec.2004.09.038.
   Google Scholar
• Ziliak, S. T., and D. N. McCloskey. 2004b. “Size Matters: The Standard Error of Regressions in the American Economic Review.” The Journal of Socio-Economics 33: 527–546. doi:10.1016/j.socec.2004.09.024.
   Google Scholar