Agricultural Economics最新文献

Measuring power is central to empirical work on intrahousehold and gender relations. This paper reviews how progress in the measurement of power within households has facilitated our understanding of household decision-making and creates new opportunities for programs and policy. Early efforts to test household models focused on measuring spousal bargaining power, usually in models featuring two decision-makers within the household. Proxy measures for bargaining power included age, education, assets, and “outside options” that could affect spouses’ threat points within marriage. Evidence rejecting the collective model of the household has influenced the design of policies and programs, notably conditional cash transfer programs. Efforts have since shifted to measuring empowerment, drawing on theories of agency and power. Since 2010, several measures of women's empowerment have been developed, including the Women's Empowerment in Agriculture Index (WEAI) and its variants. A distinct feature of the WEAI, like other counting-based measures, is its decomposability into its component indicators, which makes identifying sources of disempowerment possible. The WEAI indicators also embody jointness of decision-making or ownership, which better reflects actual decision-making within households compared to 2-person bargaining models. The paper concludes with suggestions for future research.

Despite the extensive use of industry expectations in measuring forecast accuracy and price reactions to USDA reports, very little is known about their properties beyond the basic statistical characteristics of bias, rationality, efficiency, and relative accuracy. Using unique proprietary data of firm-level expectations for upcoming USDA corn and soybean production estimates, we demonstrate that these forecasts exhibit cognitive biases such as attribution and anchoring. Prior success leads to overconfidence and bolder forecasts, and firms base their forecasts on a known reference value. We also show that the bolder the forecasts, the lesser the accuracy, indicating that substantially deviating from the herd does not pay off when it comes to crop production forecasts.

This study evaluates the effectiveness of the common practice of providing free trial packs alongside demonstration plots managed by local extension agents to promote learning-by-doing and increase technology adoption among bean farmers in Tanzania. The experiment randomly assigned some villages to forgo trial packs containing seeds and a seed treatment for 1 year. Adoption data were collected 1 and 4 years after the intervention. Our findings show that trial packs raised program costs by 37.5 times, but did not lead to a significant or cost-justified increase in adoption. The adoption of improved bean varieties increased from 11% pre-intervention to 28% 4 years post-intervention, with no significant difference between villages with and without trial packs. Although trial packs showed potential for specific groups—such as female, more educated farmers, households in farmer groups, and those living closer to demonstration plots or in smaller villages—their overall impact was limited. These results suggest that demonstration plots, a lower-cost intervention, are more cost-effective. Trial packs may still hold value when targeted, but their widespread use does not justify the additional costs. This study offers key insights for policymakers and development practitioners seeking to implement scalable, efficient agricultural interventions.

Temporary migration is a widely observed phenomenon among poor rural households, yet often overlooked by policy-makers and not captured well in standard household surveys. Although temporary migration is often related to agricultural seasonality, household preferences for temporary over longer-term migration, and the differential effects of these two types of migration on livelihoods, are not yet well understood. Here, we use survey data collected in northern Bangladesh to analyze determinants of households’ choice between temporary and longer-term migration, and effects on various livelihood indicators. Issues of selection bias and endogeneity are addressed with instrumental variables. We show that temporary migration is more common than longer-term migration in poor agrarian societies, partly determined by socioeconomic and family demographic constraints. Although longer-term migration has larger positive effects on household income, temporary migration has larger positive effects on food consumption and dietary quality during lean periods. Our results suggest that temporary migration is an important strategy for poor rural households to cope with risks and therefore deserves more explicit attention in research and policy.

The core of Colombia's coffee growing region was designated as a World Heritage (WH) site in 2011, making a distinction between “the core” of the region and “the periphery.” However, the coffee cultural heritage does not abruptly stop at the WH boundary but it exists inside and outside the boundary. This allows us to use a regression discontinuity design (RDD) to identify the income effect for farmers located just inside the WH site. We find that the WH designation of the region increases coffee farmers’ income by up to $757 per month. The mechanism includes more tourism activities inside the coffee farms by 39%, higher adoption of sustainable farming practices, increasing organic coffee production by 8.38%, and increasing payments for environmental services (PES) by 2.35%.

Nature-based land management (NLM) practices are increasingly promoted for their potential to bridge yield gaps and increase overall crop production. Yet, the extent of NLM adoption, the factors driving it, and its impact on yields remain unknown, particularly among smallholder farmers. This study addresses this knowledge gap using a unique three-round panel dataset from independent smallholder oil palm growers in Indonesia, focusing on three main NLM practices: composting, manual weeding, and organic soil amendments (SA) using lime and gypsum. We employ panel data estimators and a multivariate probit model to examine the yield effects of these practices and assess any potential interdependencies among them. Our findings indicate that the adoption of NLM practices among smallholder growers have been low and inconsistent. We identify several socioeconomic, agricultural, and biophysical factors that contribute to these low and inconsistent adoption rates. Our analysis further reveals little interdependence among the NLM practices, with none displaying a statistically significant positive association with oil palm yields. However, the application of fertilizers and herbicides is associated with higher yields. When we do not control for these yield-increasing inputs, only SA using lime and gypsum shows a positive association with yield gains. Our findings illustrate the complex relationship between NLM practices and oil palm yields among smallholders, shedding light on their potential limitations and challenges.