According to 2013 statistics from the Economic Commission for Latin America and the Caribbean (EC-LAC 2013), a mere 3.03% of the total agricultural area in the region uses some type of irrigation technology. Thus, there is a high degree of sub-utilization of existing hydric infrastructure given that the supply of irrigation capacity in many countries is greater than the calculated use (see Herrera et al. 2005; IICA 2011; CONAGUA 2014, among others). Nonetheless, there are a limited number of studies that characterize the factors affecting the adoption of irrigation by small and mid-sized farmers in the influence area of irrigation projects. This manuscript presents a novel empirical decision model applicable to irrigation adoption based on exogenous and endogenous factors in the context of LAC countries, which is solved through a binary equation system with latent variables. The main goals are to capture the effect that certain idiosyncratic variables, such as lack of credit access, can have over the decision of irrigation adoption; as well as the costs associated to private goods, financed through credit, which are necessary to access to the benefits of the provision of irrigation as a public good.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
For more details see Cremer & Laffont (2003)
This vector is comprised of soil texture, fertility, slope and some climate variables that may influence crop productivity or viability.
While observing private investment costs may prove challenging, suitable proxies would be the relative distances described above, which can be constructed by GIS procedures based on land plot maps. The assumption that investment costs across farmers should vary proportionally to the distance to the nearest water source should be suitable for surface irrigation adoption.
This could be constructed by a careful combination of data obtained by both geo-referenced survey collection and manipulation of digital maps of land plot characteristics by means of GIS procedures. Section 3 will present an example of such approach.
In Ecuador, the smallest administrative-political unit is the parish. In this case study, these are Ricaurte, Catarama and Ventanas.
Angrist JD, Pischke JS (2008) Mostly harmless econometrics: an empiricist’s companion. Princeton University Press, Princeton
Bartus T (2005) Estimation of marginal effects using margeff. Stata J 5(3):309–329
CAPSERVS (2011) Estudio de Línea Base para el Proyecto de Riego y Drenaje del Río Catarama. Consultora CAPSERVS Medios
Chiburis RC, Das J, Lokshin M (2012) A practical comparison of the bivariate probit and linear IV estimators. Econ Lett 117(3):762–766
Christofides LN, Stengos T, Swidinsky R (1997) On the calculation of marginal effects in the bivariate probit model. Econ Lett 54(3):203–208
CONAGUA (2014) Estadísticas del Agua en México, Edición 2013. Comisión Nacional del Agua, Secretaría de Medio Ambiente y Recursos Naturales (CONAGUA)
Cremer H, Laffont JJ (2003) Public goods with costly access. J Publ Econ, Elsevier, 87(9):1985–2012
EC-LAC (2013) Anuario Estadístico de América Latina y el Caribe. Website accessed on September 2014 from http://interwp.cepal.org/anuario_estadistico/anuario_2013/default.asp
Escalante R, Catalán H, Basurto S (2013) Determinantes del crédito en el sector agropecuario mexicano: un análisis mediante un modelo Probit. Cuadernos de Desarrollo Rural 10(71):101–124
FAO (2000) Irrigation in Latin America and the Caribbean in Figures (Water Report, 20). Food and Agriculture Organization of the United Nations (FAO). ISBN 92-5-004459-3
FAO (2016) AQUASTAT website. Food and Agriculture Organization of the United Nations (FAO). Website accessed on 2016/05/28 from http://www.fao.org/nr/aquastat/
Fernandez-Cornejo J, McBride WD (2002) Adoption of bioengineered crops. ERS Agricultural Economic Report No. AER810
Green G, Sunding D, Zilberman D, Parker D (1996) Explaining irrigation technology choices: a microparameter approach. Am J Agric Econ 78(4):1064–1072
Hausman JA (1978) Specification tests in econometrics. Econometrica 46:1251–1271
Heckman JJ (1978) Dummy endogenous variables in a simultaneous equation system. Econometrica 46:931–959
Herrera PA, van Huylenbroeck G, Espinel RL (2005) Institutional economic assessment of irrigated agriculture: the case of the peninsula of Santa Elena. ISBN 978-9059-89-072-5
Herrera PA, van Huylenbroeck G, Espinel RL (2006) Asymmetric information on the provision of irrigation through a public infrastructure. Water Resour Manag 20(3):431–447
Huber PJ (1967) The behavior of maximum likelihood estimates under nonstandard conditions. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. Berkeley, University of California Press, vol 1, pp 221–233
IICA (2011) Boletín informativo mensual AgroAcontecer número 15. Instituto Interamericano de Cooperación para la Agricultura (IICA)
Leiton Soubannier JS (1985) Riego y Drenaje, Año de Edición: 1985. ISBN 978-9977-64-190-4
MAGAP (2011) Plan nacional de riego y drenaje. Ministerio de Agricultura, Ganadería, Acuacultura y Pesca - Subsecretaría de Riego y Drenaje (MAGAP)
Murphy A (2007) Score tests of normality in bivariate probit models. Econ Lett 95(3):374–379
Negri DH, Brooks DH (1990) Determinants of irrigation technology choice. West J Agric Econ:213–223
Norton RD (2004) Política de desarrollo agrícola. Conceptos y principios. Food and agriculture Organization of the United Nations (FAO). Website accessed on July 2016 from http://agris.fao.org/agris-search/search.do?recordID=XF2015041479
Oluwasola O, Alimi T (2008) Determinants of agricultural credit demand and supply among small-scale farmers in Nigeria. Outlook on Agriculture 37(3):185–193
White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48:817–830
Wooldridge JM (2010) Econometric analysis of cross section and panel data. MIT press, Cambridge, pp 453–461
Wu D-M (1974) Alternative tests of independence between stochastic regressors and disturbances: finite sample results. Econometrica 42:529–546
Zeller M, Diagne A, Mataya C (1998) Market access by smallholder farmers in Malawi: implications for technology adoption, agricultural productivity and crop income. Agric Econ 19(1):219–229
The authors acknowledge the Prefectura de Los Ríos, Ecuador, and the Japan International Cooperation Agency (JICA) for supporting the data collection phase and for allowing its use. Also, collaboration from Juan Carlos Pindo and Maria Fernanda Loor was paramount for the success of this work.
About this article
Cite this article
Villa-Cox, G., Herrera, P., Villa-Cox, R. et al. Small and Mid-Sized Farmer Irrigation Adoption in the Context of Public Provision of Hydric Infrastructure in Latin America and Caribbean. Water Resour Manage 31, 4617–4631 (2017). https://doi.org/10.1007/s11269-017-1769-4
- Irrigation adoption
- Rural credit and development
- Recursive bivariate Probit
- Endogenous linear probability model