Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage

Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage

Advances in agricultural data production provide ever-increasing opportunities for pushing the research frontier in agricultural economics and designing better agricultural policy. As new technologies present opportunities to create new and integra...

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Bibliographic Details
Main Authors: Carletto, Calogero, Dillon, Andrew, Zezza, Alberto
Format: Working Paper
Language:English
Published: World Bank, Washington, DC 2021
Subjects:
AGRICULTURE
SURVEY DESIGN
DATA COLLECTION
Online Access:http://documents.worldbank.org/curated/en/751081627578468610/Agricultural-Data-Collection-to-Minimize-Measurement-Error-and-Maximize-Coverage
http://hdl.handle.net/10986/36056
id okr-10986-36056
recordtype oai_dc
spelling okr-10986-360562021-08-06T05:10:30Z Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage Carletto, Calogero Dillon, Andrew Zezza, Alberto AGRICULTURE SURVEY DESIGN DATA COLLECTION Advances in agricultural data production provide ever-increasing opportunities for pushing the research frontier in agricultural economics and designing better agricultural policy. As new technologies present opportunities to create new and integrated data sources, researchers face trade-offs in survey design that may reduce measurement error or increase coverage. This paper first reviews the econometric and survey methodology literatures that focus on the sources of measurement error and coverage bias in agricultural data collection. Second, it provides examples of how agricultural data structure affects testable empirical models. Finally, it reviews the challenges and opportunities offered by technological innovation to meet old and new data demands and address key empirical questions, focusing on the scalable data innovations of greatest potential impact for empirical methods and research. 2021-08-05T13:00:04Z 2021-08-05T13:00:04Z 2021-07 Working Paper http://documents.worldbank.org/curated/en/751081627578468610/Agricultural-Data-Collection-to-Minimize-Measurement-Error-and-Maximize-Coverage http://hdl.handle.net/10986/36056 English Policy Research Working Paper;No. 9745 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper
repository_type Digital Repository
institution_category Foreign Institution
institution Digital Repositories
building World Bank Open Knowledge Repository
collection World Bank
language English
topic AGRICULTURE
SURVEY DESIGN
DATA COLLECTION
spellingShingle AGRICULTURE
SURVEY DESIGN
DATA COLLECTION
Carletto, Calogero
Dillon, Andrew
Zezza, Alberto
Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
relation Policy Research Working Paper;No. 9745
description Advances in agricultural data production provide ever-increasing opportunities for pushing the research frontier in agricultural economics and designing better agricultural policy. As new technologies present opportunities to create new and integrated data sources, researchers face trade-offs in survey design that may reduce measurement error or increase coverage. This paper first reviews the econometric and survey methodology literatures that focus on the sources of measurement error and coverage bias in agricultural data collection. Second, it provides examples of how agricultural data structure affects testable empirical models. Finally, it reviews the challenges and opportunities offered by technological innovation to meet old and new data demands and address key empirical questions, focusing on the scalable data innovations of greatest potential impact for empirical methods and research.
format Working Paper
author Carletto, Calogero
Dillon, Andrew
Zezza, Alberto
author_facet Carletto, Calogero
Dillon, Andrew
Zezza, Alberto
author_sort Carletto, Calogero
title Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
title_short Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
title_full Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
title_fullStr Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
title_full_unstemmed Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
title_sort agricultural data collection to minimize measurement error and maximize coverage
publisher World Bank, Washington, DC
publishDate 2021
url http://documents.worldbank.org/curated/en/751081627578468610/Agricultural-Data-Collection-to-Minimize-Measurement-Error-and-Maximize-Coverage
http://hdl.handle.net/10986/36056
_version_ 1764484336655007744

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