Not Your Average Job
Understanding the constraints to agricultural growth in Africa relies on the accurate measurement of smallholder labor. Yet, serious weaknesses in these statistics persist. The extent of bias in smallholder labor data is examined by conducting a randomized survey experiment among farming households in rural Tanzania. Agricultural labor estimates obtained through weekly surveys are compared with the results of reporting in a single end-of-season recall survey. The findings show strong evidence of recall bias: people in traditional recall-style modules reported working up to four times as many hours per person-plot as those reporting labor on a weekly basis. Recall bias manifests both in the intensive and extensive margins of labor reporting: while hours are over-reported in recall, the number of people and plots active in agricultural work are under-reported. The evidence suggests that this recall bias is driven not only by failures in memory, but also by the mental burdens of reporting on highly variable agricultural work patterns to provide a typical estimate. All things equal, studies suffering from this bias would understate agricultural labor productivity.
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Format: | Journal Article biblioteca |
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Elsevier
2018-01
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Subjects: | FARM LABOR, AGRICULTURAL PRODUCTIVITY, RECALL ERROR, MEASUREMENT ERROR, SURVEYS, REPORTING BIAS, |
Online Access: | http://hdl.handle.net/10986/29301 |
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dig-okr-10986293012023-04-03T10:30:53Z Not Your Average Job Measuring Farm Labor in Tanzania Arthi, Vellore Beegle, Kathleen De Weerdt, Joachim Palacios-López, Amparo FARM LABOR AGRICULTURAL PRODUCTIVITY RECALL ERROR MEASUREMENT ERROR SURVEYS REPORTING BIAS Understanding the constraints to agricultural growth in Africa relies on the accurate measurement of smallholder labor. Yet, serious weaknesses in these statistics persist. The extent of bias in smallholder labor data is examined by conducting a randomized survey experiment among farming households in rural Tanzania. Agricultural labor estimates obtained through weekly surveys are compared with the results of reporting in a single end-of-season recall survey. The findings show strong evidence of recall bias: people in traditional recall-style modules reported working up to four times as many hours per person-plot as those reporting labor on a weekly basis. Recall bias manifests both in the intensive and extensive margins of labor reporting: while hours are over-reported in recall, the number of people and plots active in agricultural work are under-reported. The evidence suggests that this recall bias is driven not only by failures in memory, but also by the mental burdens of reporting on highly variable agricultural work patterns to provide a typical estimate. All things equal, studies suffering from this bias would understate agricultural labor productivity. 2018-02-01T20:53:13Z 2018-02-01T20:53:13Z 2018-01 Journal Article Article de journal Artículo de revista Journal of Development Economics 0304-3878 http://hdl.handle.net/10986/29301 CC BY-NC0ND 3.0 IGO World Bank http://creativecommons.org/licenses/by-nc-nd/3.0/igo application/pdf Elsevier |
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FARM LABOR AGRICULTURAL PRODUCTIVITY RECALL ERROR MEASUREMENT ERROR SURVEYS REPORTING BIAS FARM LABOR AGRICULTURAL PRODUCTIVITY RECALL ERROR MEASUREMENT ERROR SURVEYS REPORTING BIAS |
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FARM LABOR AGRICULTURAL PRODUCTIVITY RECALL ERROR MEASUREMENT ERROR SURVEYS REPORTING BIAS FARM LABOR AGRICULTURAL PRODUCTIVITY RECALL ERROR MEASUREMENT ERROR SURVEYS REPORTING BIAS Arthi, Vellore Beegle, Kathleen De Weerdt, Joachim Palacios-López, Amparo Not Your Average Job |
description |
Understanding the constraints to agricultural growth in Africa relies on the accurate measurement of smallholder labor. Yet, serious weaknesses in these statistics persist. The extent of bias in smallholder labor data is examined by conducting a randomized survey experiment among farming households in rural Tanzania. Agricultural labor estimates obtained through weekly surveys are compared with the results of reporting in a single end-of-season recall survey. The findings show strong evidence of recall bias: people in traditional recall-style modules reported working up to four times as many hours per person-plot as those reporting labor on a weekly basis. Recall bias manifests both in the intensive and extensive margins of labor reporting: while hours are over-reported in recall, the number of people and plots active in agricultural work are under-reported. The evidence suggests that this recall bias is driven not only by failures in memory, but also by the mental burdens of reporting on highly variable agricultural work patterns to provide a typical estimate. All things equal, studies suffering from this bias would understate agricultural labor productivity. |
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Journal Article |
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FARM LABOR AGRICULTURAL PRODUCTIVITY RECALL ERROR MEASUREMENT ERROR SURVEYS REPORTING BIAS |
author |
Arthi, Vellore Beegle, Kathleen De Weerdt, Joachim Palacios-López, Amparo |
author_facet |
Arthi, Vellore Beegle, Kathleen De Weerdt, Joachim Palacios-López, Amparo |
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Arthi, Vellore |
title |
Not Your Average Job |
title_short |
Not Your Average Job |
title_full |
Not Your Average Job |
title_fullStr |
Not Your Average Job |
title_full_unstemmed |
Not Your Average Job |
title_sort |
not your average job |
publisher |
Elsevier |
publishDate |
2018-01 |
url |
http://hdl.handle.net/10986/29301 |
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