This article investigates the differences in yield production, production efficiency, and yield risk for farmers both with and without off-farm work. Using a nationwide survey of rice farmers in Taiwan, we estimate two stochastic production frontier models that accommodate technical inefficiency and production risk simultaneously for farmers both with and without off-farm work. The stochastic dominance criterion is then applied to compare the differences in the distributions of the estimated technical efficiency and yield risk between groups. The empirical results indicate that these two groups of farmers use resources in different ways, and off-farm work is not necessarily associated with lower technical efficiency. For farmers in the lower percentiles of the efficiency distribution, those with off-farm work are more efficient than their counterparts without off-farm work. In addition, farmers with off-farm work face higher production risk and this result is robust for the entire distribution.JEL classifications: J21, Q12

This review briefly summarizes the situation regarding food security in East and Southeast Asia. In accordance with the World Food Summit definition and 2009 Declaration of the World Summit on Food Security, the four pillars of food security—food availability, access to food, the stability of food supplies, and food utilization—are closely scrutinized along with the characteristics of food security at the sub-regional level. Historical trends for the agricultural economy and the food trade, such as food imports and exports, production and consumption, and the food price index in the sub-region, are presented and statistically analysed. Additionally, because agricultural industry in this region is vulnerable to climate change, issues about how climate change affects food security in food production systems, agricultural livelihoods, nutrition, and food policy making, which can be linked to the four pillars in different ways, are also discussed.

Sustaining competitiveness over the long run can suggest that decision makers must acquire knowledge to support the selection of technology systems and an understanding of an implemented technology. Social learning is an important source of knowledge acquisition as the decision maker exchanges and discusses information with other decision makers via social communication. The empirical questions are (i) how does the decision maker choose learning partners, and (ii) how does the social learning behavior influence the firm’s production decision and technology over time? This study constructs an econometric model to reflect the connection between the decision maker’s social learning and the production behavior. The latent class stochastic frontier model (LCSFM) is used to estimate a model of heterogeneous learning using the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) India data. Since caste rank plays an important role in people’s social life in rural areas in India, the empirical results reveals the connection between social learning and production behavior by showing the importance of caste rank in production decisions.

A better understanding of farmers’ investment strategies associated with climate and weather is crucial to protecting farming and other climate-exposed sectors from extreme hydrometeorological events. Accordingly, this study employed a field experiment to investigate the investment decisions under risk and uncertainty by 213 farmers from four regions of Taiwan. Each was asked 30 questions that paired “no investment,” “investment with crop insurance,” “investment with subsidized crop insurance,” and “investment” as possible responses. By providing imperfect information and various probabilities of certain states occurring, the experimental scenarios mimicked various types of weather-forecasting services. As well as their socioeconomic characteristics, the background information we collected about the participants included their experiences of natural disasters and what actions they take to protect their crops from weather damage. The sampled farmers became more conservative in their decision-making as the weather forecasts they received became more precise, except when increases in risk were associated with high returns. The provision of insurance subsidies also had a conservatizing effect. However, considerable variation in investment preferences was observed according to the farmers’ crop types. For those seeking to create comprehensive policies aimed at helping the agricultural sector deal with the costs of damage from extreme events, this study has important implications. This approach could be extended to research on the perceptions of decision-makers in other climate-exposed sectors such as the construction industry.

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