Valuation of Access to Irrigation Water in Rural Ethiopia: Application of Choice Experiment and Contingent Valuation Methods

Mekonnen, Alemu; Gebreegziabher, Zenebe; Beyene, Abebe D.; Hagos, Fitsum

doi:10.1142/s2382624x19500073

Cited by 9 publications

(8 citation statements)

References 41 publications

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“…The other part

ε_{ij}

is a stochastic element representing unobservable factors that affect the respondent's decisions in choosing different management scenarios (Rolfe et al, 2004). Therefore, the probability that the individual i chooses alternative j over all other alternatives given in the choice set S can be stated as (Mekonnen et al, 2019; Goibov et al, 2012)

Pij goodbreak= pr ((), Uij > Uik) for all normalJ \in normalS normalJ \neq normalk

Substituting the Equation in , we get

italicPi goodbreak= \Pr true(V ((),, Xij, Si) goodbreak+ italicεij > \Pr ((), V ((),, Xik, Si) goodbreak+ italicϵik) italicfor italicall J \in S, J \neq k

The above dissemination of the error term suggests that the probability of any specific alternative j being chosen as the most preferred one is expressed in logistic distribution (McFadden, 1973) expressed in the following equation number (). This specified equation is known as the conditional model expressed as (Hanley et al, 2001)

P ((),, italicUij > italicUik, italicfor italicall) j \neq k goodbreak= \frac{\exp ((), μVij)}{\sum \exp ((), μVij)}

where

μ

is the scale parameter, inversely proportional to the standard deviation of error term

V ((), eij) \frac{π^{2}}{6 σ^{2}}

where

σ

is the standard deviation of the error distribution (Ben‐Akiva & Lerman, 1985) and is standardized to one.…”

Section: Methodsmentioning

confidence: 99%

“…Once we estimate the parameters in Equation , the valuation of Dal Lake attributes can be obtained through the following equation (Mekonnen et al, 2019):

italicWTP goodbreak= \frac{\ln \sum_{m} \exp ((), italicVm 1) - italicln \sum_{m} \exp ((), italicVm 0)}{α_{monetary a ttribute}}

Where WTP is the welfare measure,

α

represents the income or output from improvement in Lake attributes. This is also denoted through the coefficient of a monetary attribute in the CE.…”

Section: Methodsmentioning

confidence: 99%

“…The other part ε ij is a stochastic element representing unobservable factors that affect the respondent's decisions in choosing different management scenarios (Rolfe et al, 2004). Therefore, the probability that the individual F I G U R E 4 Stages of choice experiment design i chooses alternative j over all other alternatives given in the choice set S can be stated as (Mekonnen et al, 2019;Goibov et al, 2012)…”

Section: Econometric Methodologymentioning

confidence: 99%

“…Once we estimate the parameters in Equation 8, the valuation of Dal Lake attributes can be obtained through the following equation (Mekonnen et al, 2019):…”

Section: Marginal Wtp and Estimation Of Welfare Measuresmentioning

confidence: 99%

See 3 more Smart Citations

Valuation and effective management of the Dal Lake's diverse ecosystem using choice experiment method

Bhat

Ahmad²,

Sofi

et al. 2022

Ecohydrology

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This study estimates economic values of changes in variegated ecological, social and economic attributes of dominant environmental resource (viz., Dal Lake), proffers to its key stakeholders through choice experiment design selecting relevant attributes for better management. In addition to the conditional logit model, the random logit model and the random logit model with interactions are calculated to account for the heterogeneity of the public prospects for the different purposes of the wetland.Willingness to pay for the selected attributes like preservation of wetland biodiversity turned out to be ₹18.47

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“…The other part

ε_{ij}

Pij goodbreak= pr ((), Uij > Uik) for all normalJ \in normalS normalJ \neq normalk

Substituting the Equation in , we get

italicPi goodbreak= \Pr true(V ((),, Xij, Si) goodbreak+ italicεij > \Pr ((), V ((),, Xik, Si) goodbreak+ italicϵik) italicfor italicall J \in S, J \neq k

P ((),, italicUij > italicUik, italicfor italicall) j \neq k goodbreak= \frac{\exp ((), μVij)}{\sum \exp ((), μVij)}

where

μ

is the scale parameter, inversely proportional to the standard deviation of error term

V ((), eij) \frac{π^{2}}{6 σ^{2}}

where

σ

is the standard deviation of the error distribution (Ben‐Akiva & Lerman, 1985) and is standardized to one.…”

Section: Methodsmentioning

confidence: 99%

“…Once we estimate the parameters in Equation , the valuation of Dal Lake attributes can be obtained through the following equation (Mekonnen et al, 2019):

italicWTP goodbreak= \frac{\ln \sum_{m} \exp ((), italicVm 1) - italicln \sum_{m} \exp ((), italicVm 0)}{α_{monetary a ttribute}}

Where WTP is the welfare measure,

α

represents the income or output from improvement in Lake attributes. This is also denoted through the coefficient of a monetary attribute in the CE.…”

Section: Methodsmentioning

confidence: 99%

Section: Econometric Methodologymentioning

confidence: 99%

“…Once we estimate the parameters in Equation 8, the valuation of Dal Lake attributes can be obtained through the following equation (Mekonnen et al, 2019):…”

Section: Marginal Wtp and Estimation Of Welfare Measuresmentioning

confidence: 99%

See 2 more Smart Citations

Valuation and effective management of the Dal Lake's diverse ecosystem using choice experiment method

Bhat

Ahmad²,

Sofi

et al. 2022

Ecohydrology

View full text Add to dashboard Cite

show abstract

“…The existing studies show that farmers' adoption of sustainable practices and new technologies are contingent on a number of factors that are categorized into five broader categories, namely, farm and farmer specific characteristics, social and cultural norms, availability of support and resources, and perceived benefit. (e.g., Barham et al, 2015;Dumbrell et al, 2016;Mekonnen et al, 2020;Pannell et al, 2006;Weber, 2012). Farmers' adoption is also dependent on the types of practices and technologies, but the practice or technology itself has been under-emphasized (Pannell and Zilberman, 2020).…”

Section: Introductionmentioning

confidence: 99%

Factors affecting Farmers' Adoption of and Willingness to Pay for Biodegradable Mulch Films in China

Yang

Jian-ling

et al. 2022

Preprint

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Biodegradable mulch films (BDMs) technology is an environmentally-friendly substitute to traditional plastic mulch films in agricultural production. Given the high price and it is new to the market, it is not easy for farmers to accept and adopt it. This paper aims to explore the key factors affecting farmers’ adoption of and willingness to pay for BDMs to understand the complex process of farmers’ decision-making. This paper employs a double hurdle model to explore the multi-stage decision-making process in the adoption of BDMs using the sample of 1247 observations from Yunnan province China, where two mechanisms of decision-making (i.e., direct rejection of technology and lack of resources) were used to capture zero willingness to pay (WTP) for BDMs. The results indicate the two-stage decision-making process, where the role of technology-specific characteristics is more important than adopter-specific characteristics in the adoption of BDMs in China – training for understanding and using the technology has a positive effect on both the adoption and willingness to pay. The paper is the first attempt that empirically analyses the determinants of farmers’ WTP for BDMs. It contributes to the literature on adoption analysis by 1) considering farmers’ adoption choices as a two-step process by using a hurdle model and 2) addressing the importance of technology-specific characteristics on farmers’ WTP for BDMs. Understanding the role of factors on different stages of farmers’ decision-making could assist policymakers in designing programs, specifically tackling difficulties confronting farmers at different stages of decision-making.

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Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi

Tufa,

Alene,

Ngoma

et al. 2023

Agribusiness

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One of the main barriers to adopting smallholder agricultural mechanization in developing countries is the mismatch between the economies of scale of machines and farm size. Private sector‐led mechanization services hold a promise to address this challenge, but there is a lack of evidence on demand for smallholder mechanization services. This study estimates the farmers' willingness to pay for mechanization services using the double‐bounded contingent valuation method and data from 1512 households. Results show that, on average, farmers are willing to pay 11%, 33%, and 5% more than prevailing market rates for land preparation, maize shelling, and transportation services, respectively. The amounts farmers are willing to pay for the mechanization services vary by sex, age group, size of cultivated land, the value of farmer assets, market access, and agroecology. Men are willing to pay 26%, 25%, and 11% more than women for land preparation, maize shelling, and transportation services. Moreover, 40% of female and 90% of male farmers are willing to pay more than or equal to the prevailing market rate for land preparation services. The high demand for mechanization services among smallholder farmers points to the need for making the machinery available to rural communities through mechanization service providers or machinery hiring centers run by the private sector. The paper concludes by discussing the contextual factors and policy options for promoting smallholder mechanization in Malawi. [EconLit Citations: O33, Q11, Q13, Q16].

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Valuation of Access to Irrigation Water in Rural Ethiopia: Application of Choice Experiment and Contingent Valuation Methods

Cited by 9 publications

References 41 publications

Valuation and effective management of the Dal Lake's diverse ecosystem using choice experiment method

Valuation and effective management of the Dal Lake's diverse ecosystem using choice experiment method

Factors affecting Farmers' Adoption of and Willingness to Pay for Biodegradable Mulch Films in China

Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi

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