Integration of statistical and administrative agricultural data from Namibia
Autor: | Colin Lewis-Beck, Johgho Im, Jie Li, Zhengyuan Zhu, Emily Berg |
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Rok vydání: | 2021 |
Předmět: |
Economics and Econometrics
business.industry 05 social sciences 01 natural sciences Agricultural economics Management Information Systems 010104 statistics & probability Geography Agriculture 0502 economics and business 0101 mathematics Statistics Probability and Uncertainty business 050205 econometrics |
Zdroj: | Statistical Journal of the IAOS. 37:557-578 |
ISSN: | 1875-9254 1874-7655 |
Popis: | Statistical and administrative agencies often collect information on related parameters. Discrepancies between estimates from distinct data sources can arise due to differences in definitions, reference periods, and data collection protocols. Integrating statistical data with administrative data is appealing for saving data collection costs, reducing respondent burden, and improving the coherence of estimates produced by statistical and administrative agencies. Model based techniques, such as small area estimation and measurement error models, for combining multiple data sources have benefits of transparency, reproducibility, and the ability to provide an estimated uncertainty. Issues associated with integrating statistical data with administrative data are discussed in the context of data from Namibia. The national statistical agency in Namibia produces estimates of crop area using data from probability samples. Simultaneously, the Namibia Ministry of Agriculture, Water, and Forestry obtains crop area estimates through extension programs. We illustrate the use of a structural measurement error model for the purpose of synthesizing the administrative and survey data to form a unified estimate of crop area. Limitations on the available data preclude us from conducting a genuine, thorough application. Nonetheless, our illustration of methodology holds potential use for a general practitioner. |
Databáze: | OpenAIRE |
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