Congress Resources: Papers, posters and presentations

< Return to abstract list

Effects Of Regulated Surface Water Markets On Farmers´ Wue Located At Limarí Valley (lv) (chile)

Congress: 2015
Author(s): Guillermo Donoso (Santiago, Chile), Maria Molinos, Oscar Melo, Oscar Cristi, Ramon Sala-Garrido

University of Valencia1, Pontificia Universitad Católica de Chile2, Universidad San Sebastián 3

Keyword(s): Sub-theme 9: Water allocation among competing uses and users,

1. INTRODUCTION Water markets emerged more than 30 years ago as an important policy instrument to facilitate a reallocation of scarce and fully committed water resources between competing users (Bjornlund, 2003). Several papers have evaluated WUE in agriculture under different contexts and for different purposes. In order to contribute to the research on this matter, the primary aim of this paper is to assess the effects of regulated surface water markets on farmers´ WUE. In doing so, an empirical application is developed using a sample of 108 farmers located at Limarí Valley (LV) (Chile). The Limarí river basin is located between latitudes 30°15' and 31°25' and is bordered by the Elqui River watershed to the north, and by the Choapa River watershed on the south, in the Coquimbo Region of Chile. The second objective of the paper is to explore additional factors of water markets participation that might affect global efficiency (GE) and WUE. 2. METHODOLOGY To measure the efficiency of decision making units (DMUs) (farmers in our case study) the DEA method was chosen for this study. We apply the Russell model (RM) which is a non-radial and non-oriented model (Färe et al., 1994). Once the RM and WUE were calculated for all evaluated farmers, we tested if average scores differed among the following three groups --water sellers, water buyers and non-traders. Since efficiency scores computed using DEA are based on a non-parametric method, it is natural to apply non-parametric statistics to provide a basis for statistical inference. Moreover, this approach does not require assumptions that the underlying distribution of efficiency scores is normal (Grosskopf, 1996). The approach followed in this study was based on grouping the DMUs according to certain characteristics or factors that appear to be related to efficiency, and verifying whether there are statistically significant differences between the group efficiency scores using the Kruskal-Wallis and Mann-Whiney non-parametric tests (Molinos-Senante et al., 2014). The sample used in this study consists of 108 farms located in the Limarí Valley (LV) in Chile. Thirty percent of surveyed farmers buy or sell water in the spot market, while only 18% have participated in the permanent water market, trading water rights independently from land. 4. RESULTS The efficiency of individual inputs and RM were calculated in General Algebraic and Modeling System (GAMS) software. Table 1 shows the mean of efficiency scores for each input and the global efficiency (RM) for the 108 farms comprising our sample and grouped according the three groups of farmers defined. For the complete sample, it is shown that the efficiency levels for each input, and therefore the GE for the whole group are low. The average GE score is 0.412, indicating that there is substantial improvement potential for the 108 farmers evaluated as a whole. The input with the highest efficiency score was water use except for non-traders. This finding confirms the importance of good water management and the value of recent efforts intended to reduce water consumption. When comparing GE among the different groups in our study, the average RM is highest among water sellers (0.517), followed by the water-buyers (0.412). The non-traders group has the lowest GE (0.343). The higher GE of water-sellers is mainly due to their superior efficiency in water use since the efficiency in the use of such input is considerably larger than for the other inputs involved in the assessment. For water-buyers, the input with the largest efficiency is also water use although in this case, differences between inputs efficiency are not as remarkable as in the case of water-sellers. On the other hand, for non-trader farmers, the efficiency in the use of the five inputs analysed is quite similar. In fact, the score of WUE is the lowest one of all inputs. To verify from a statistical point of view whether global and input efficiency differences among the farmers´ groups are statistically significant the non-parametric test of Kruskal-Wallis was performed. The p-values shown in Table 2. The p-values indicate that the differences in the global efficiency among water-sellers, water buyers and non-traders are statistically significant. Regarding the efficiency of the individual inputs, for water use and pesticides the efficiency scores between farmers´ groups for these inputs are statistically different. On the other hand, for the other three inputs --fertilizer, energy and labour- the differences in the efficiency scores between farmers´ groups are not statistically significant. Based on previous studies (Lilienfeld and Asmild, 2007; Njiraini and Guthiga, 2013) and our observations and taking into account the available information, we assumed that GE and WUE may be affected by the following factors: (i) size of the farm, (ii) type of crop grown; (iii) farmers´ experience in agriculture and; (iv) irrigation system. The analysis evidenced that none of the evaluated variables --cultivated area, type of crop, farmers´ experience in agriculture and irrigation technology-- significantly affects GE and WUE. From a policy perspective, this finding evidences the importance of water markets as a driver to improve both GE and WUE. CONCLUSIONS The assessment of the WUE provides information to both farmers and policy makers. In regions where water markets are implemented the improvement of the WUE is essential not only for agriculture but also for other water demanding sectors enhancing the sustainability of water resources management. Previous studies on this topic have evaluated the efficiency in the use of water in agriculture but did not focus on the effect of a formal and regulated surface water market on WUE. To overcome this drawback, and for the first time, efficiency in the use of fertilizers, pesticides, energy, water and labour inputs were evaluated classifying farmers as water sellers, water buyers and non-traders. In doing so, the non-radial Russell DEA model was applied. The advantage of this model is that it provides an efficiency score for each input as well as a GE score. The empirical application developed using a sample of farms located in Limarí Valley (Chile) has shown that mean WUE is moderate-low. Hence, there is considerable possibilities to reduce agricultural water consumption. The assessment by groups illustrated that farmers participating in water markets are more efficient --from a global and water use point of view- than farmers who do not participate in water trading. In particular, water sellers are the most efficient in the use of water. On the other hand, non-traders are farmers that present the lowest WUE. From a policy perspective, some important implications can be drawn from this research. Given that farmers participating in water markets are more efficient than farmers who do not participate in them, water authorities and policy makers should promote water markets. 1. Bjornlund, H. (2003). Farmer participation in markets for temporary and permanent water in southeastern Australia. Agricultural Water Management, 63 (1), 57-76. 2. Färe, R., Grosskopf, S., Lovell, C.A.K. (1994). Production Frontiers. Cambridge University Cambridge. 3. Grosskopf, S. (1996). Statistical inference and nonparametric efficiency: A selective survey. Journal of Productivity Analysis, 7 (2-3), 161-176. 4. Molinos-Senante, M., Hernandez-Sancho, F., Sala-Garrido, R. (2014). Benchmarking in wastewater treatment plants: A tool to save operational costs. Clean Technologies and Environmental Policy, 16 (1), 149-161.

© 2011 IWRA - International Water Resources Association - - Admin