Agricultural Economics最新文献

Mkupete, M. J., and Davalos, J. 2025. “Implications of Climate-Smart Agriculture Technology Adoption on Women's Productivity and Food Security in Tanzania.” Agricultural Economics 56: 247–267. https://doi.org/10.1111/agec.12874.

We inadvertently omitted an important acknowledgement of the financial support that made this research possible. The article should include the following acknowledgement:

This work was carried out with financial and scientific support from the Partnership for Economic Policy (PEP) through funding provided by Global Affairs Canada (GAC).

We sincerely apologize for this oversight.

The adoption of higher-nutrient grass varieties, such as Brachiaria, offers long-term economic benefits for ranchers while enhancing soil health and pasture productivity in Latin America's lowland climates. Despite widespread adoption, the field-level impacts remain largely unexplored. This study, focusing on Colombia's largest beef-producing regions, analyzes how the transition to introduced pastures affects productivity, revenue, and land requirements for ranching. Our findings reveal that 66% of pasture acreage among sampled ranchers is now comprised of these introduced varieties. Factors like distance to technology centers, historical violence, and shocks to transportation and trade, hinder adoption. Transitioning from native savannas to introduced pastures significantly boosts productivity, particularly when paired with practices such as weed control and fertilization; however, yield gains fall short of the expectations set by agronomic trials. Overall, the increased revenue per hectare underscores the need to promote introduced-pasture-based systems, especially given the limitations of intensive silvopastoral methods.

We conduct a systematic empirical investigation into the consistency of competing industry-level total factor productivity (TFP) series in the United States, including the crop and animal production or farm sector. We apply an algorithm based on time-series methods to three widely-used databases frequently utilized by researchers to study productivity. Our analysis reveals a substantial proportion of inconsistent industry-level TFP series across these databases, including those for the farm sector. We further investigate the potential causes of such discrepancies by examining the consistency of the individual output and input variables used in the calculation of the TFP series. Individual input and output series pairs show different patterns of inconsistency across databases. Our findings highlight the need for publishing agencies and researchers to explore opportunities for methodological standardization.

Agricultural extension can have direct and important impacts on vulnerable populations, strengthening both rural livelihoods and urban food security through technology adoption and increased agricultural production. Digitally-supported extension utilizing mobile phones can be a cost-effective method for delivering information to farmers. However, different digitally-supported extension delivery mechanisms may have differential impacts on farmer knowledge and behavior, especially (i) in the face of new and emergent threats to farm production, and (ii) in crises or violent conflict when trust in outside information is low and conventional extension channels are disrupted. We conducted a randomized controlled trial to evaluate two digitally-supported extension designs—direct SMS and a novel hybrid lead-farmer-supported SMS method—in delivering fall armyworm management guidance to maize farmers in Myanmar after a military coup. Both approaches improved farmer knowledge. There is suggestive evidence that the lead-farmer-supported group spent more on pesticides and hired labor compared to the control group and used pesticides more effectively in damage control than the SMS group.

With the rise of market-led development, marketing cooperatives have emerged that offer smallholder producers a guaranteed minimum price for their cash crops. Their existence is threatened when members side-sell a part of their harvest to outside buyers. We conduct a framed field experiment with indigenous coffee producers in southern Mexico to examine the effect of four factors on the marketing decision: additional income, the presence of microcredit and/or technical assistance, average outside buyer price, and harvest quantity. Our results show that participants allocate on average 82% of their harvest to the certain-price buyer. Changes in harvest quantity and outside-buyer price have minimal effects. The offer of complementary services has a null effect. Moreover, 22% of the participants always allocate their entire harvest to the certain-price buyer. Extra income increases this probability by 10%. Subgroup analysis reveals that this effect is limited to existing cooperative members.

The agri-food sector is a key contributor to greenhouse gas emissions and is also the economic sector most at risk from climate change. The sector is heavily protected by government intervention, particularly through trade policy, which can have significant environmental implications by either promoting or hindering the trade of polluting versus clean goods. In this paper, we study to what extent the pattern of trade policy hinders or promotes GHG emissions embedded in imported agri-food goods, focusing on three main pollutants as follows: carbon dioxide, methane, and nitrous oxide. Our findings reveal a significant environmental bias in agri-food trade policy, with most countries effectively applying a negative carbon tax—that is, an implicit subsidy—for all the pollutants considered. Notably, the structure of the trade policy of the European Union countries implies a substantial implicit carbon subsidy, while more polluting countries, such as China and Brazil, apply smaller carbon subsidies or even a carbon tax. The results have important implications for current mitigation policy.

This paper investigates methodological issues related to attribute non-attendance (ANA) in choice experiments (CEs). First evaluates the variation in the prevalence of ANA across various non-hypothetical choice experiments (NHCEs) elicitation formats compared to hypothetical choice experiments (HCEs). Second, it investigates whether eliciting respondents’ self-reported ANA after each choice set (choice task (CT)) or at the end of the choice task (seria task (ST)yields comparable results. Finally, it examines how incorporating self-reported ANA information affects respondents’ willingness to pay (WTP) and the external predictive powers of the estimated choice models. To answer these research questions, four treatments were conducted: HCE, NHCE, non-hypothetical rank-order discrete choice experiment (NHROCE), and non-hypothetical best worst scaling (NHBWS). The results indicate that accounting for ANA information significantly improves the goodness-of-fit of the estimated choice models, especially when full ranking information (NHROCE and NHBWS) is used. In terms of marginal WTP estimates, the results show that modeling ANA, independently of the elicitation approach of ANA (ST or CT), significantly influences consumers’ WTP values. However, the results suggest that incorporating ANA information does not substantially enhance the predictive power of the estimated choice model.