Determination of Farmers’ Willingness to Pay for Sustainable Agricultural Land Use in the GAP-Harran Plain of Turkey

There is a risk of salinity and degradation in soil structure due to excessive irrigation in the GAP-Harran Plain. The purpose of the research is to determine farmers’ willingness to pay (WTP) for applications of sustainable agricultural land usage practices to avoid salinization in soil based on irrigation problems related to the demands of the farmers’, their needs, and which factors affect their willingness to accept payment. The basic material of the research was obtained through face-to-face questionnaires from farmers who were selected by a method of simple random sampling in 2018. Heckman’s two-stage model was used in the analysis of the data in Stata. According to the results obtained from the research, 27.85% of the participants indicated WTP and the average amount was USD 16.2/hectare. The average WTP is calculated as USD 4.43/hectare for all participants and 735.38 thousand USD/year for the whole plain. The agricultural income, household size, farming experience, land amount, non-agricultural income, education level, working in the non-agricultural sector, and membership of farmers’ union were determined as statistically effective factors. It is necessary to raise the awareness of farmers through extension services. As awareness increases, both WTP and the adoption of applications will increase. The results supply useful data for people working on this subject for the planning and implementation of sustainable usage of resources in Turkey and to regions with similar socio–economic characteristics. This study is the first of its kind in GAP-Harran, Turkey.

Farmers’ Willingness to Pay for Services to Ensure Sustainable Agricultural Income in the GAP-Harran Plain, Şanlıurfa, Turkey

Sustainable agriculture is necessary for farmers to have a sustainable income. This research aims to determine the willingness to pay (WTP) of farmers in the GAP-Harran Plain for services that would ensure sustainable agricultural income, the factors affecting their willingness, and the minimum amount they would be willing to pay. The main material of the research has been obtained by means of face-to-face surveys involving farmers selected by a simple random sampling method in the GAP-Harran Plain. The sampling volume was determined with a 95% confidence limit and a 5% error margin. Heckman’s two-stage model was used for the analysis. According to the results of the research, 22.61% of the participants showed WTP, and the average amount they were willing to pay was 180.82 TL/hectare (ha) ($31.86/ha). This amount was 3.08% of the average annual agricultural income calculated. About 41.22% of the participants showed no WTP. They believed that the public sector is accountable of the services and consequently, they should be provided free of charge. About 23.14% of the participants showed WTP only for the services that they needed. The average WTP for all participants was calculated as 40.9 TL/ha ($7.21/ha) and 1.2 million $/year for the GAP-Harran Plain. This amount is the minimum and may increase by several folds with a demand-based variety of service delivery. The factors that statistically effect WTP have been determined as age, education, experience, number of households working in agriculture, amount of land, agricultural income, non-agricultural income, membership status of agricultural cooperatives, and product pattern. The results provide useful information to guide researchers, decision-makers, and policy-makers.

DEA Performance Measurements in Cotton Production of Harran Plain, Turkey: A Single and Double Bootstrap Truncated Regression Approaches

A single and a double bootstrap of data envelopment analysis examines Harran Plain cotton farming in Turkey. The single bootstrap technique was employed to derive the bias-corrected efficiency values under both constant returns to scale (CRS) and versus variable returns to scale (VRS) technologies while discriminating between the two technologies using a smoothed bootstrap test statistic. Results indicated that the farms operated under VRS technology. Given that VRS technology prevailed across Harran Plain cotton farmers sampled, we then determined factors affecting the bias-corrected technical efficiencies using the double bootstrap technique. Another important finding in the single bootstrap analysis is that cotton farmers in the region have a U-shaped technical efficiency based on the input and output scale. Thus, small-scale farmers tend to use their resources more efficiently in cotton farming than that of both medium- and large-scale farmers. Interestingly, the medium-scale farmers with resource inefficiency are at the forefront of the other two types of farmers (i.e., small-scale and large-scale) on the Harran Plain in Turkey. The results also showed that most of the farm and farmer specific as well as economic factors play a significant role in explaining the technical efficiency values.