{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108488"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108488","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Ambiguity and credence quality: Implications for technology adoption","abstract":"Use of fertilizer and hybrid seed remains low in much of Sub-Saharan Africa. A possible contributor to low adoption is that farmers are uncertain about the quality of agricultural inputs available to them. While previous studies have shown that risk and uncertainty preferences are relevant to the decision to adopt a technology, existing research assumes that farmers have homogeneous beliefs about the quality of available inputs. I test this assumption using an incentivized Becker-DeGroot-Marschack auction in Tanzania and examine how farmer beliefs about mineral fertilizer quality in local markets influence their willingness-to-pay. I find that farmers are willing to pay 46% more for fertilizer that was laboratory tested and found to be pure than for untested fertilizer. Farmers who believe that more of the fertilizer for sale in their local market is low in quality are willing to pay a higher premium for laboratory-tested pure quality fertilizer, compared to untested fertilizer. Yet these results present something of a puzzle, given that three rounds of testing of fertilizer for sale in regional markets over five years have demonstrated that the nutrient content of fertilizer for sale in these contexts is consistently at or near advertised levels. Farmers appear to believe that low-quality fertilizer is far more prevalent in proximate markets than it actually is. How have farmers’ incorrect beliefs persisted in equilibrium? I posit two interconnected mechanisms. First, misattribution: Yields are stochastic due to weather and other factors, and when a yield in a particular year is unusually low, farmers misattribute noise as indicative of low-quality fertilizer. Second, farmers experience both risk (uncertainty about whether a bag of fertilizer is bad) and ambiguity (uncertainty about the likelihood a bag of fertilizer is bad), and thus hold multiple priors. I develop a Bayesian learning model that incorporates both misattribution and multiple priors and show that in equilibrium beliefs do not converge to the truth. Supporting the model's findings, I use farmer survey data from Uganda to establish that historic precipitation variability relates to farmers’ fertilizer quality belief distributions. I use the learning model to simulate several policy interventions, and show that subsidies, information campaigns, and plot-specific fertilizer recommendations improve beliefs, but do not cause beliefs to fully converge to the truth. Instead, policy makers should consider programs that address the misattribution problem.","abstract_html":"Use of fertilizer and hybrid seed remains low in much of Sub-Saharan Africa. A possible contributor to low adoption is that farmers are uncertain about the quality of agricultural inputs available to them. While previous studies have shown that risk and uncertainty preferences are relevant to the decision to adopt a technology, existing research assumes that farmers have homogeneous beliefs about the quality of available inputs. I test this assumption using an incentivized Becker-DeGroot-Marschack auction in Tanzania and examine how farmer beliefs about mineral fertilizer quality in local markets influence their willingness-to-pay. I find that farmers are willing to pay 46% more for fertilizer that was laboratory tested and found to be pure than for untested fertilizer. Farmers who believe that more of the fertilizer for sale in their local market is low in quality are willing to pay a higher premium for laboratory-tested pure quality fertilizer, compared to untested fertilizer. Yet these results present something of a puzzle, given that three rounds of testing of fertilizer for sale in regional markets over five years have demonstrated that the nutrient content of fertilizer for sale in these contexts is consistently at or near advertised levels. Farmers appear to believe that low-quality fertilizer is far more prevalent in proximate markets than it actually is. How have farmers’ incorrect beliefs persisted in equilibrium? I posit two interconnected mechanisms. First, misattribution: Yields are stochastic due to weather and other factors, and when a yield in a particular year is unusually low, farmers misattribute noise as indicative of low-quality fertilizer. Second, farmers experience both risk (uncertainty about whether a bag of fertilizer is bad) and ambiguity (uncertainty about the likelihood a bag of fertilizer is bad), and thus hold multiple priors. I develop a Bayesian learning model that incorporates both misattribution and multiple priors and show that in equilibrium beliefs do not converge to the truth. Supporting the model's findings, I use farmer survey data from Uganda to establish that historic precipitation variability relates to farmers’ fertilizer quality belief distributions. I use the learning model to simulate several policy interventions, and show that subsidies, information campaigns, and plot-specific fertilizer recommendations improve beliefs, but do not cause beliefs to fully converge to the truth. Instead, policy makers should consider programs that address the misattribution problem.","abstract_has_math":false,"creators":["Norton, Benjamin Prescott"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Agricultural & Applied Econ","degree_department":null,"school":null,"contributors":["Michelson, Hope","Manyong, Victor","Winter-Nelson, Alex","Crost, Benjamin"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-10-07T20:59:51Z","date_published":"2020-10-07T20:59:51Z","updated_at":"2026-07-22T22:24:48Z","subjects":["Development","agriculture","inputs","beliefs","Tanzania","Sub-Saharan Africa","quality","experimental economics"],"languages":["en"],"rights":["Copyright 2020 by Benjamin Prescott Norton. All rights reserved."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108488","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Michelson, Hope","Manyong, Victor","Winter-Nelson, Alex","Crost, Benjamin"]},{"key":"dc:creator","label":"Author","values":["Norton, Benjamin Prescott"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-10-07T20:59:51Z","2020-07-21","2020-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural & Applied Econ"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Development","agriculture","inputs","beliefs","Tanzania","Sub-Saharan Africa","quality","experimental economics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 by Benjamin Prescott Norton. 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I find that farmers are willing to pay 46% more for fertilizer that was laboratory tested and found to be pure than for untested fertilizer. Farmers who believe that more of the fertilizer for sale in their local market is low in quality are willing to pay a higher premium for laboratory-tested pure quality fertilizer, compared to untested fertilizer. Yet these results present something of a puzzle, given that three rounds of testing of fertilizer for sale in regional markets over five years have demonstrated that the nutrient content of fertilizer for sale in these contexts is consistently at or near advertised levels. Farmers appear to believe that low-quality fertilizer is far more prevalent in proximate markets than it actually is. How have farmers’ incorrect beliefs persisted in equilibrium? I posit two interconnected mechanisms. First, misattribution: Yields are stochastic due to weather and other factors, and when a yield in a particular year is unusually low, farmers misattribute noise as indicative of low-quality fertilizer. Second, farmers experience both risk (uncertainty about whether a bag of fertilizer is bad) and ambiguity (uncertainty about the likelihood a bag of fertilizer is bad), and thus hold multiple priors. I develop a Bayesian learning model that incorporates both misattribution and multiple priors and show that in equilibrium beliefs do not converge to the truth. Supporting the model's findings, I use farmer survey data from Uganda to establish that historic precipitation variability relates to farmers’ fertilizer quality belief distributions. I use the learning model to simulate several policy interventions, and show that subsidies, information campaigns, and plot-specific fertilizer recommendations improve beliefs, but do not cause beliefs to fully converge to the truth. Instead, policy makers should consider programs that address the misattribution problem.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-10-02 without embargo terms","The student, Benjamin Norton, accepted the attached license on 2020-07-14 at 10:28.","The student, Benjamin Norton, submitted this Thesis for approval on 2020-07-14 at 10:37.","This Thesis was approved for publication on 2020-07-21 at 11:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15603 on 2020-10-02 at 15:13:22","Made available in DSpace on 2020-10-07T20:59:51Z (GMT). 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While previous studies have shown that risk and uncertainty preferences are relevant to the decision to adopt a technology, existing research assumes that farmers have homogeneous beliefs about the quality of available inputs. I test this assumption using an incentivized Becker-DeGroot-Marschack auction in Tanzania and examine how farmer beliefs about mineral fertilizer quality in local markets influence their willingness-to-pay. I find that farmers are willing to pay 46% more for fertilizer that was laboratory tested and found to be pure than for untested fertilizer. Farmers who believe that more of the fertilizer for sale in their local market is low in quality are willing to pay a higher premium for laboratory-tested pure quality fertilizer, compared to untested fertilizer. Yet these results present something of a puzzle, given that three rounds of testing of fertilizer for sale in regional markets over five years have demonstrated that the nutrient content of fertilizer for sale in these contexts is consistently at or near advertised levels. Farmers appear to believe that low-quality fertilizer is far more prevalent in proximate markets than it actually is. How have farmers’ incorrect beliefs persisted in equilibrium? I posit two interconnected mechanisms. First, misattribution: Yields are stochastic due to weather and other factors, and when a yield in a particular year is unusually low, farmers misattribute noise as indicative of low-quality fertilizer. Second, farmers experience both risk (uncertainty about whether a bag of fertilizer is bad) and ambiguity (uncertainty about the likelihood a bag of fertilizer is bad), and thus hold multiple priors. I develop a Bayesian learning model that incorporates both misattribution and multiple priors and show that in equilibrium beliefs do not converge to the truth. Supporting the model's findings, I use farmer survey data from Uganda to establish that historic precipitation variability relates to farmers’ fertilizer quality belief distributions. I use the learning model to simulate several policy interventions, and show that subsidies, information campaigns, and plot-specific fertilizer recommendations improve beliefs, but do not cause beliefs to fully converge to the truth. Instead, policy makers should consider programs that address the misattribution problem.","Submission original under an indefinite embargo labeled 'Open Access'. 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All rights reserved."],"dc:subject":["Development","agriculture","inputs","beliefs","Tanzania","Sub-Saharan Africa","quality","experimental economics"],"dc:title":["Ambiguity and credence quality: Implications for technology adoption"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Agricultural & Applied Econ"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:48Z"}