2018
DOI: 10.2139/ssrn.3188522
|View full text |Cite
|
Sign up to set email alerts
|

Land Measurement Bias: Comparisons from Global Positioning System, Self-Reports, and Satellite Data

Abstract: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
5
0

Year Published

2018
2018
2021
2021

Publication Types

Select...
4
3
1

Relationship

2
6

Authors

Journals

citations
Cited by 9 publications
(8 citation statements)
references
References 35 publications
(36 reference statements)
0
5
0
Order By: Relevance
“…Even though the inverse relationship holds for very small farms (0–3 ha), farms between 20 and 70 ha are substantially more productive due to mechanization and reduced labor input per hectare. Moreover, the studies by Carletto, Gourlay, and Winters () and Dillon and Rao () show that self‐reported farm sizes, as in our case, can lead to land measurement bias. Small farmers tend to overestimate, whereas large farmers tend to underestimate their land sizes (Carletto et al., ).…”
Section: Resultsmentioning
confidence: 65%
See 1 more Smart Citation
“…Even though the inverse relationship holds for very small farms (0–3 ha), farms between 20 and 70 ha are substantially more productive due to mechanization and reduced labor input per hectare. Moreover, the studies by Carletto, Gourlay, and Winters () and Dillon and Rao () show that self‐reported farm sizes, as in our case, can lead to land measurement bias. Small farmers tend to overestimate, whereas large farmers tend to underestimate their land sizes (Carletto et al., ).…”
Section: Resultsmentioning
confidence: 65%
“…input per hectare. Moreover, the studies by Carletto, Gourlay, and Winters (2015) and Dillon and Rao (2018) show that self-reported farm sizes, as in our case, can lead to land measurement bias. Small farmers tend to overestimate, whereas large farmers tend to underestimate their land sizes (Carletto et al, 2013).…”
Section: Labor Productivity (Kg/labor Day) Logmentioning
confidence: 64%
“…This is the total quantity of maize harvested per hectare of cultivated land. To be consistent with the studies by Dillon and Rao (2018) and Kilic et al (2018) on land size measurement error, we used Global Positioning System (GPS) to track and measure the land size of each respondent. This helped to avoid any misreporting problems that could lead to biased estimates.…”
Section: Theoretical Framework Study Design Sampling and Data Collectionmentioning
confidence: 99%
“…In some cases, the additional risk insight has increased the availability of coverage (see Box 5.2) Earth observation imagery can play a critical role in monitoring cultivation and yields for the extension of agricultural insurance (Mcintosh and Mansini 2018), (Rotairo et al 2019), (ADB 2018b), either on a stand-alone basis or in combination with field survey data to address gaps in coverage (Guan et al 2018). One recent study found that the use of publicly available Google Earth imagery for measuring the size of cultivated land in the Lao People's Democratic Republic, the Philippines, Thailand, and Viet Nam provided sufficient accuracy to serve as a cost-effective alternative for validating self-reported information from farmers (Dillon and Rao 2018).…”
Section: Lowering the Cost Of Underwritingmentioning
confidence: 99%