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Article

Estimation of Determinants of Farmland Abandonment and Its Data Problems

Division of Natural Resource Economics, Graduate School of Agriculture, Kyoto University, Oiwake-cho, Kitashirakawa, Sakyo-ku, Kyoto 606-8502, Japan
Academic Editors: Ilan Stavi and Manuel Pulido Fernádez
Land 2021, 10(6), 596; https://doi.org/10.3390/land10060596
Received: 8 May 2021 / Revised: 27 May 2021 / Accepted: 30 May 2021 / Published: 4 June 2021
Abandoned farmland is particularly problematic in developed countries where agriculture has a comparative disadvantage in terms of effective use of land resources invested over time. While many studies have estimated the causes of these problems, few have discussed in detail the impact of data characteristics and accuracy on the estimation results. In this study, issues related to the underlying data and the estimation of the determinants of farmland abandonment were examined. Most previous studies on farmland abandonment in Japan have used census data as the basis of their analyses. However, census data are recorded subjectively by farmers. To address this, surveys of abandoned farmland are being conducted by a third party, and the results are compiled into a geographic information system (GIS) database. Two types of datasets (subjective census data and objective GIS data) were examined for their estimation performance. Although the two sets of data are correlated, there are considerable differences between them. Subjective variables are compatible with subjective data, and objective variables are compatible with objective data (meaning that parameters are easily identified). Original data for analysis, such as policy variables, are compatible with objective data. In policy evaluation research, attention should be paid to objective data collection. View Full-Text
Keywords: farmland abandonment; agricultural production; land use; subjective and objective data; geographic information system; food security farmland abandonment; agricultural production; land use; subjective and objective data; geographic information system; food security
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MDPI and ACS Style

Kitano, S. Estimation of Determinants of Farmland Abandonment and Its Data Problems. Land 2021, 10, 596. https://doi.org/10.3390/land10060596

AMA Style

Kitano S. Estimation of Determinants of Farmland Abandonment and Its Data Problems. Land. 2021; 10(6):596. https://doi.org/10.3390/land10060596

Chicago/Turabian Style

Kitano, Shinichi. 2021. "Estimation of Determinants of Farmland Abandonment and Its Data Problems" Land 10, no. 6: 596. https://doi.org/10.3390/land10060596

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