Shock, risk attitude and rice farming: Evidence from panel data for Thailand

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Trung Thanh Nguyen
  • Manh Hung Do
  • Dil Rahut

Externe Organisationen

  • Asian Development Bank Institute (ADBI)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer100430
FachzeitschriftEnvironmental Challenges
Jahrgang6
Frühes Online-Datum21 Dez. 2021
PublikationsstatusVeröffentlicht - Jan. 2022

Abstract

Rice is one of the most important crops for food security and rural livelihoods in many developing countries in Asia. However, the current rice farming practices heavily rely on synthetic fertilizers and pesticides that pose a significant threat to the environment. Further, the overuse of inputs might lead to the wastage of resources. Therefore, this research examines the impact of shocks experienced by farmers on their risk attitude, input use, and technical efficiency in rice farming. We use a balanced panel dataset of 1220 rice households from Thailand collected in 2013 and 2017 and employ a fixed-effects estimation with instrumental variables to account for endogeneity concerns. Our results show that fertilizers and pesticides are risk-decreasing inputs, which means rice farmers, who are more unwilling to take risks, tend to apply more fertilizers and pesticides. Adverse shocks affect rural households’ risk attitudes, leading to over applications of fertilizers and pesticides and, therefore, reducing farming efficiency. We suggest that policies providing crop insurance and enhancing farmers’ awareness on proper input application are critical to mitigate the adverse impacts of shocks and reduce the inefficient use of these chemical inputs.

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Shock, risk attitude and rice farming: Evidence from panel data for Thailand. / Nguyen, Trung Thanh; Do, Manh Hung; Rahut, Dil.
in: Environmental Challenges, Jahrgang 6, 100430, 01.2022.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Nguyen, TT, Do, MH & Rahut, D 2022, 'Shock, risk attitude and rice farming: Evidence from panel data for Thailand', Environmental Challenges, Jg. 6, 100430. https://doi.org/10.1016/j.envc.2021.100430
Nguyen, T. T., Do, M. H., & Rahut, D. (2022). Shock, risk attitude and rice farming: Evidence from panel data for Thailand. Environmental Challenges, 6, Artikel 100430. https://doi.org/10.1016/j.envc.2021.100430
Nguyen TT, Do MH, Rahut D. Shock, risk attitude and rice farming: Evidence from panel data for Thailand. Environmental Challenges. 2022 Jan;6:100430. Epub 2021 Dez 21. doi: 10.1016/j.envc.2021.100430
Nguyen, Trung Thanh ; Do, Manh Hung ; Rahut, Dil. / Shock, risk attitude and rice farming : Evidence from panel data for Thailand. in: Environmental Challenges. 2022 ; Jahrgang 6.
Download
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title = "Shock, risk attitude and rice farming: Evidence from panel data for Thailand",
abstract = "Rice is one of the most important crops for food security and rural livelihoods in many developing countries in Asia. However, the current rice farming practices heavily rely on synthetic fertilizers and pesticides that pose a significant threat to the environment. Further, the overuse of inputs might lead to the wastage of resources. Therefore, this research examines the impact of shocks experienced by farmers on their risk attitude, input use, and technical efficiency in rice farming. We use a balanced panel dataset of 1220 rice households from Thailand collected in 2013 and 2017 and employ a fixed-effects estimation with instrumental variables to account for endogeneity concerns. Our results show that fertilizers and pesticides are risk-decreasing inputs, which means rice farmers, who are more unwilling to take risks, tend to apply more fertilizers and pesticides. Adverse shocks affect rural households{\textquoteright} risk attitudes, leading to over applications of fertilizers and pesticides and, therefore, reducing farming efficiency. We suggest that policies providing crop insurance and enhancing farmers{\textquoteright} awareness on proper input application are critical to mitigate the adverse impacts of shocks and reduce the inefficient use of these chemical inputs.",
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note = "Funding Information: The authors would like to thank the respondents from the surveyed provinces for their kind support and cooperation. We acknowledge the financial support of the German Research Foundation ( DFG - FOR 756/2 ) for the TVSEP project and appreciate the efforts of our colleagues at the Leibniz University Hannover for data collection and cleaning. MH Do would like to thank the German Academic Exchange Service (DAAD) for financial assistance. This paper was presented in a virtual conference titled “Environmental Challenges and Agricultural Sustainability in Asia: Interlinkages and Future Implications,” organized by the Asian Development Bank Institute on 8–10 December 2021. The views, information, or opinions expressed in the paper are those of the authors, and the usual disclaimer applies. Funding Information: Data for this research are from the ?Poverty dynamics and sustainable development: A long-term panel project in Thailand and Vietnam (www.tvsep.de)?, funded by the German Research Foundation (Deutsche Forschungsgemeinschaft - DFG-FOR 756/2). This project aims to generate a better and in-depth understanding of income and vulnerability to poverty dynamics in rural regions of the emerging economies of Thailand and Vietnam. Following the guidelines of the Department of Economic and Social Affairs of the United Nations (United Nations, 2005), the sampling process included a three-stage stratified random sampling procedure based on the administrative system of each country. In Thailand, the survey was conducted in three provinces, namely Buriram, Nakhon Phanom, and Ubon Ratchathani (see Fig. 1 for the study sites), where majority of the households live in rural area and are dependant on agriculture for their livelihood. In the first stage, sub-districts were selected in each province. Then, two villages were chosen with a probability proportional to the size of the population. At the third stage, a random selection of ten households was made based on the list of all households in the sampled villages with equal probability (see Nguyen et al. (2017), Klasen and Waibel (2015) for detailed information of the survey's designation and implementation). For this research, we use a balanced panel of 1220 rice farmers collected in 2013 and 2017. ",
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N1 - Funding Information: The authors would like to thank the respondents from the surveyed provinces for their kind support and cooperation. We acknowledge the financial support of the German Research Foundation ( DFG - FOR 756/2 ) for the TVSEP project and appreciate the efforts of our colleagues at the Leibniz University Hannover for data collection and cleaning. MH Do would like to thank the German Academic Exchange Service (DAAD) for financial assistance. This paper was presented in a virtual conference titled “Environmental Challenges and Agricultural Sustainability in Asia: Interlinkages and Future Implications,” organized by the Asian Development Bank Institute on 8–10 December 2021. The views, information, or opinions expressed in the paper are those of the authors, and the usual disclaimer applies. Funding Information: Data for this research are from the ?Poverty dynamics and sustainable development: A long-term panel project in Thailand and Vietnam (www.tvsep.de)?, funded by the German Research Foundation (Deutsche Forschungsgemeinschaft - DFG-FOR 756/2). This project aims to generate a better and in-depth understanding of income and vulnerability to poverty dynamics in rural regions of the emerging economies of Thailand and Vietnam. Following the guidelines of the Department of Economic and Social Affairs of the United Nations (United Nations, 2005), the sampling process included a three-stage stratified random sampling procedure based on the administrative system of each country. In Thailand, the survey was conducted in three provinces, namely Buriram, Nakhon Phanom, and Ubon Ratchathani (see Fig. 1 for the study sites), where majority of the households live in rural area and are dependant on agriculture for their livelihood. In the first stage, sub-districts were selected in each province. Then, two villages were chosen with a probability proportional to the size of the population. At the third stage, a random selection of ten households was made based on the list of all households in the sampled villages with equal probability (see Nguyen et al. (2017), Klasen and Waibel (2015) for detailed information of the survey's designation and implementation). For this research, we use a balanced panel of 1220 rice farmers collected in 2013 and 2017.

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