Saying Sayonara to the Farm: Hierarchical Bayesian Modeling of Farm Exits in Japan

Abstract

Off-farm employment opportunities are thought to have an effect on farm exit rates, though evidence on the sign of this effect has been mixed. Examining this issue in the context of Japanese agriculture, we find that farm exits are related to off-farm income as a share of household income, and more specifically to the nature of off-farm work. Two econometric models are developed: a hierarchical Bayesian linear model and a hierarchical Bayesian Poisson model. Both models perform well in predicting exit rates across the towns and prefectures of Japan.

Competitive Analyses of the Pig Industry in Swaziland

“…Similar trends have been reported in Africa, where 2.11% growth (2003-2008), and 1.73% growth (2008-2015) labour productivity was reported [82]. In contrast to the findings of the present study, [83] reported consistently falling Japanese agricultural production due labour shortages and significant migration of rural agriculture to off-farm income in urban areas.…”

Confident or captured? Commercial producers in South Africa

“…This also applies to part-time farming (see RIRDC, 2007; Martini and Kimura, 2009; NFU, 2011; Antman et al. , 2015; Ramsey et al. , 2019), which has a below-average role in South Africa's commercial farms.…”

“…, 2015; Lowder et al. , 2016; European Commission, 2017; Shimizu, 2017; Padmanabhan, 2018; Ramsey et al. , 2019), it became clear that three categories of factors appeared to have the largest effect on the change in producer numbers, whether increasing or decreasing it.…”

“…Globally in primary agriculture, policy-and market-driven factors appear to have the largest effect on the change in producer numbers, whether increasing (Lowder et al, 2016;Padmanabhan, 2018;World Bank, 2019a, b, c) or decreasing (Gale, 2003;Katchova and Ahearn, 2014;European Commission, 2017;Shimizu, 2017) them. This also applies to parttime farming (see RIRDC, 2007;Martini and Kimura, 2009;NFU, 2011;Antman et al, 2015;Ramsey et al, 2019), which has a below-average role in South Africa's commercial farms.…”

“…After numerous international literature sources were consulted (Gale, 2003;Rural Industries Research and Development Corporation [RIRDC], 2007;Martini and Kimura, 2009;National Farmers Union [NFU], 2011; Katchova and Ahearn, 2014;Antman et al, 2015;Lowder et al, 2016;European Commission, 2017;Shimizu, 2017;Padmanabhan, 2018;Ramsey et al, 2019), it became clear that three categories of factors appeared to have the largest effect on the change in producer numbers, whether increasing or decreasing it. Within the context of investment in agriculture, or the withdrawal of investment from agriculture, the factors can be divided into three groups-personal, financial and policy-although with some interrelated occurrences.…”