Rooftop Photovoltaics Adoption and Farm Revenue

ABSTRACT Solar energy production has grown substantially in agriculture. This paper examines farmers' adoption of rooftop photovoltaic (PV) systems, and how rooftop PV installation is associated with farm revenue, farm business diversification, and labor allocation. We develop a theoretical model to illustrate how farmers decide to adopt rooftop PV systems. The empirical analysis is based on a population‐based sample of livestock and poultry farms drawn from the 2020 agriculture census survey in Taiwan. We address potential endogeneity bias using several treatment effect models based on the selection‐on‐observable approach to identify the relationship between rooftop PV installation and farm revenue. We find that more educated farm operators and farms located in areas with higher density of electrical substations are more likely to adopt PV. Furthermore, PV adopters report higher farm product sales and greater labor use in farm activities. These findings imply that rooftop PV adoption could provide a mutually beneficial opportunity to enhance photovoltaic generation and improve farm revenue.

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Publication Details

Journal
Agribusiness
Published
2025-09-19
DOI
https://doi.org/10.1002/agr.70035
Citations
1
Primary Topic
Energy and Environment Impacts
Type
article
Field-Weighted Citation Impact
0.50
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article

Rooftop Photovoltaics Adoption and Farm Revenue

Hung‐Hao Chang, Yu‐You Liou, Jeffrey C. Begun
1 citations
Agribusiness
Energy and Environment Impacts
0.50
article

Rooftop Photovoltaics Adoption and Farm Revenue

Hung‐Hao Chang, Yu‐You Liou, Jeffrey C. Begun
article en
1 citations

Abstract

ABSTRACT Solar energy production has grown substantially in agriculture. This paper examines farmers' adoption of rooftop photovoltaic (PV) systems, and how rooftop PV installation is associated with farm revenue, farm business diversification, and labor allocation. We develop a theoretical model to illustrate how farmers decide to adopt rooftop PV systems. The empirical analysis is based on a population‐based sample of livestock and poultry farms drawn from the 2020 agriculture census survey in Taiwan. We address potential endogeneity bias using several treatment effect models based on the selection‐on‐observable approach to identify the relationship between rooftop PV installation and farm revenue. We find that more educated farm operators and farms located in areas with higher density of electrical substations are more likely to adopt PV. Furthermore, PV adopters report higher farm product sales and greater labor use in farm activities. These findings imply that rooftop PV adoption could provide a mutually beneficial opportunity to enhance photovoltaic generation and improve farm revenue.

Agribusiness
National Taiwan University (TW)
Openalex Percentile: Top 35%
Energy and Environment Impacts
0.50
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