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          <titl xml:lang="sv">Impacts of reducing water collection times in rural Kenya: School-aged Children</titl>
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          <producer xml:lang="en" abbr="SND">Swedish National Data Service</producer><producer xml:lang="sv" abbr="SND">Svensk nationell datatjänst</producer>
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        <titl xml:lang="sv">Impacts of reducing water collection times in rural Kenya: School-aged Children</titl>
        <parTitl xml:lang="en">Impacts of reducing water collection times in rural Kenya: School-aged Children</parTitl>
        <IDNo xml:lang="en" agency="SND">snd1294-2-1</IDNo><IDNo xml:lang="en" agency="gu.se">MS-105</IDNo><IDNo xml:lang="en" agency="DOI">https://doi.org/10.5878/3est-4n47</IDNo>
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        <AuthEnty affiliation="Partnership for Economic Policy" xml:lang="en">Kabubo-Mariara, Jane
        </AuthEnty><AuthEnty affiliation="Partnership for Economic Policy" xml:lang="sv">Kabubo-Mariara, Jane
        </AuthEnty><AuthEnty affiliation="Commission on Revenue Allocation, Government of Kenya" xml:lang="en">Kimuyu, Peter
        </AuthEnty><AuthEnty affiliation="Commission on Revenue Allocation, Government of Kenya" xml:lang="sv">Kimuyu, Peter
        </AuthEnty><AuthEnty affiliation="School of Economics, Washington State University" xml:lang="en">Cook, Joseph
        </AuthEnty><AuthEnty affiliation="School of Economics, Washington State University" xml:lang="sv">Cook, Joseph
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        <keyword xml:lang="en" vocab="ELSST" vocabURI="https://elsst.cessda.eu/id/4/865cf541-dcbc-4320-aab3-2fae74663e7c">rural areas</keyword><keyword xml:lang="sv" vocab="ELSST" vocabURI="https://elsst.cessda.eu/id/4/865cf541-dcbc-4320-aab3-2fae74663e7c">landsbygd</keyword><keyword xml:lang="en" vocab="GEMET" vocabURI="http://www.eionet.europa.eu/gemet/concept/9157">water collection</keyword><keyword xml:lang="sv" vocab="GEMET" vocabURI="http://www.eionet.europa.eu/gemet/concept/9157">vattentäkt</keyword>
        <topcClas xml:lang="en" vocab="Standard för svensk indelning av forskningsämnen 2011">Social Sciences</topcClas><topcClas xml:lang="sv" vocab="Standard för svensk indelning av forskningsämnen 2011">Samhällsvetenskap</topcClas><topcClas xml:lang="en" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=Economics">ECONOMICS</topcClas><topcClas xml:lang="sv" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=Economics">EKONOMI</topcClas><topcClas xml:lang="en" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=Economics.EconomicSystemsAndDevelopment">Economic systems and development</topcClas><topcClas xml:lang="sv" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=Economics.EconomicSystemsAndDevelopment">Ekonomiska system och ekonomisk utveckling</topcClas><topcClas xml:lang="en" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=SocietyAndCulture.SocialConditionsAndIndicators">Social conditions and indicators</topcClas><topcClas xml:lang="sv" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=SocietyAndCulture.SocialConditionsAndIndicators">Sociala förhållanden och indikatorer</topcClas><topcClas xml:lang="en" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=SocietyAndCulture.TimeUse">Time use</topcClas><topcClas xml:lang="sv" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=SocietyAndCulture.TimeUse">Tidsanvändning</topcClas><topcClas xml:lang="en" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=Psychology">PSYCHOLOGY</topcClas><topcClas xml:lang="sv" vocab="CESSDA Topic Classification" vocabURI="https://vocabularies.cessda.eu/vocabulary/TopicClassification?code=Psychology">PSYKOLOGI</topcClas>
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      <abstract xml:lang="en">We measured momentary well-being using the Experience Sampling Method (ESM) among 220 water collectors in rural Meru County, Kenya over eight weeks. Subjects reported on affect and time use at four randomly-chosen times through the day (Monday through Saturday) on a custom-designed ODK survey app, deployed on a low-cost smartphone.  Subjects completed a second ODK survey each weekday evening, reporting on school attendance, study time and chores performed for each school-aged child in the household.  After several weeks of baseline data, half of households were randomly chosen to receive free delivery of water to their door for four weeks, reducing water collection times to (near) zero. In-person baseline, midline and endline surveys were conducted by enumerators.  The data from the daily survey of school-children is in the file “Meru schoolkids.dta”.  These can be linked back to the household level data in “Meru ESM RCT” using phoneid, and to the child-specific variables using the variable “pid”. The matching was done based on manually matching names in the baseline survey and this schoolchildren survey.  To protect confidentiality, these names cannot be included.  Where the pid field is missing either the name of the child was missing or could not be reasonably matched to the name of a child in the household.</abstract><abstract xml:lang="sv">We measured momentary well-being using the Experience Sampling Method (ESM) among 220 water collectors in rural Meru County, Kenya over eight weeks. Subjects reported on affect and time use at four randomly-chosen times through the day (Monday through Saturday) on a custom-designed ODK survey app, deployed on a low-cost smartphone.  Subjects completed a second ODK survey each weekday evening, reporting on school attendance, study time and chores performed for each school-aged child in the household.  After several weeks of baseline data, half of households were randomly chosen to receive free delivery of water to their door for four weeks, reducing water collection times to (near) zero. In-person baseline, midline and endline surveys were conducted by enumerators.  The data from the daily survey of school-children is in the file “Meru schoolkids.dta”.  These can be linked back to the household level data in “Meru ESM RCT” using phoneid, and to the child-specific variables using the variable “pid”. The matching was done based on manually matching names in the baseline survey and this schoolchildren survey.  To protect confidentiality, these names cannot be included.  Where the pid field is missing either the name of the child was missing or could not be reasonably matched to the name of a child in the household.</abstract>
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        <nation xml:lang="en" abbr="KE">Kenya</nation><nation xml:lang="sv" abbr="KE">Kenya</nation>
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