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 integrated data sources, researchers face trade-offs in sur...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Washington, D.C
The World Bank
2021
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| Schlagworte: | |
| Online-Zugang: | kostenfrei |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (93 Seiten) |
| DOI: | 10.1596/1813-9450-9745 |
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| 520 | 3 | |a 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 | |
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| spellingShingle | Carletto, Calogero Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage Agricultural Knowledge and Information Systems Agricultural Research Agricultural Sector Economics Agriculture Data Collection Survey Design |
| title | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage |
| title_auth | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage |
| title_exact_search | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage |
| title_exact_search_txtP | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage |
| title_full | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage Calogero Carletto |
| title_fullStr | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage Calogero Carletto |
| title_full_unstemmed | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage Calogero Carletto |
| title_short | Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage |
| title_sort | agricultural data collection to minimize measurement error and maximize coverage |
| topic | Agricultural Knowledge and Information Systems Agricultural Research Agricultural Sector Economics Agriculture Data Collection Survey Design |
| topic_facet | Agricultural Knowledge and Information Systems Agricultural Research Agricultural Sector Economics Agriculture Data Collection Survey Design |
| url | https://doi.org/10.1596/1813-9450-9745 |
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