Households’ Willingness to pay for Water Hyacinth Control to Lake Tana, Ethiopia: An application of Contingent Valuation Method

dc.contributor.advisorTewodros, Negash (PhD)
dc.contributor.authorTesfa, Getnet
dc.date.accessioned2019-10-18T12:05:50Z
dc.date.accessioned2023-11-04T10:28:10Z
dc.date.available2019-10-18T12:05:50Z
dc.date.available2023-11-04T10:28:10Z
dc.date.issued2019-06
dc.description.abstractCurrently, Water Hyacinth (WH) has become a growing problem in Lake Tana. Infestations of this weed have been, causing environmental, economic, and social problems to the riparian communities. This study uses a cross-sectional survey of 398 randomly selected households in Bahir Dar city, Ethiopia, to assess their willingness to pay (WTP) for Water Hyacinth Control to Lake Tana applining contingent valuation approach, and Considering hypothetical scenarios encircling different socio-economic variables. The Tobit regression model was used to analyze the socio-economic factors influencing urban households’ WTP decisions for water hyacinth Control in Lake Tana. The results showed that household’s were on average willing to pay the amount of 1011.436 ETB with a total contribution of 77,624,226.2 ETB for a one-time payment to clean water hyacinth from Lake Tana. Results reveal that residents’ WTP for control of water hyacinth is significantly related to income, member of household’s having job and awareness of water hyacinth, among other factors. The mean WTP that found can be a guide for municipal officials in setting a more appropriate fee that can finance cleaning up water hyacinth, where both regional and federal governments have co-operated.en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/19500
dc.language.isoen_USen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectHousehold'sen_US
dc.subjectTobit regressionen_US
dc.subjectWater hyacinthen_US
dc.titleHouseholds’ Willingness to pay for Water Hyacinth Control to Lake Tana, Ethiopia: An application of Contingent Valuation Methoden_US
dc.typeThesisen_US

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