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Presentation ID 16804

The mechanism through which exit options and outside opportunities affect cooperation outcomes has not been well studied in the resource management literature, since a deep analysis of the concepts of “exit options” and “outside opportunities” is missing. This article analyzes these concepts across the common pool resource management literature, investigates the factors that underlie “opting out” decisions, and reviews potential ways to operationalize these concepts for empirical analysis. It also explores how the relationship of cooperation and exit options may be influenced by broad economic processes, such as economic integration.

DRAFT. Do Not Cite. Formally published as: Anglade, Boaz, Pilar Useche, and Carmen Diana Deere. “Decomposing the Gender Wealth Gap in Ecuador.” World Development 96 (August 2017): 19–31. https://doi.org/10.1016/j.worlddev.2017.02.003.

This study examines the intra-household bargaining its impact on the productivity of coffee and other crops functions and on the gender productivity gap, using household-level data from 615 farmers in Colombia and Ecuador. The OLS estimates and the Oaxaca-Blinder (O-B) decomposition method corroborate the hypothesis that given a gain bargaining power through the distribution factor “female participation in the intra-household decision-making” would exacerbate household productivity and the gender gap as long this bargaining is not balanced and wives do not obtain fair benefits from agricultural activities. The results also confirm that differences in observed factors between female and male-headed households are the main reason for the gender gap.

Rice farmers in Peru are one of the world’s social groups that are more highly and heterogeneously exposed to climate change. While aggregate climate predictions provide important guidance for impact mitigation policy, actual climate perceptions and coping behavior observations provide a unique view into the heterogeneity of households’ exposure to climate risks and related livelihood stresses. In this study we show how farmer perceptions provide a nuanced picture of climate change in Northern Peru and analyze the different coping actions of agricultural households as they respond to diverse climatic stress factors. We examine the complexity of adaptation strategies by evaluating the complementarity/substitutability between different coping actions. For example, we find that households adopting new rice varieties as a coping strategy use this option as a substitute to getting credit, reducing the rice area or diversifying the crop. We also find that non-agricultural strategies such as migrating, mortgaging the land and pawning assets are high complements of asking for credit, reducing area or diversifying the crop, and relying on the help of family and friends.

Our research examines how the changing cultural norms and legal status in Ecuador have impacted women’s empowerment in the agricultural sector and in rural communities. Cacao provides a particularly relevant case because of its economic and ecological importance to Ecuador and the region. The traditional cacao agroforests also provide many ecological services such as habitat for many endangered plants and animals. However, they are not as profitability as the monoculture systems. Because of these economic and ecological concerns, promotion of cacao agroforests has been the focus of development efforts by the Ecuadorian government, nongovernmental organizations, and international donor agencies, many of whom also have goals of empowering Ecuadorian women (Suarez 2013). Thus, women’s involvement in cacao production would be an important indicator of women’s status in rural Ecuador. To determine the value that men on women place on these nonmarket benefits and ability of women to influence household production decisions, we conducted 350 household interviews throughout coastal Ecuador from February through July, 2013. We implemented a choice experiment separately with the principle male and female member of the household. The choice experiment consisted of the household member choosing between pictures of two parcels to determine how much more profit the participant would need to receive in order to prefer the monoculture system over the agroforestry system. By employing a Random Effects Logit regression, we were able calculate men and women’s average willingness to pay for the attributes of the cacao agroforests (Birol et al. 2006). We found that both genders place a higher value on the agroforests than monoculture corps; however, women place a higher value on these benefits than men do.

Many factors besides profit maximization such as nonmarket ecological and social benefits influence smallholder households to adopt one agricultural production system or another. Thus, different techniques are needed that take into consideration more than monetary income to fully capture these additional benefits in order to better understand the production decision of smallholder farmers. We build upon previous work on the household model and shadow wage estimation to develop a shadow wage for Ecuadorian cacao producers that includes these nonmarket benefits. We found that the shadow wage correctly indicated that these households would prefer to use an agroforestry production system instead of the more profitable modern system because these additional nonmarket benefits in additional to the economic benefits from participating in specialty markets make the traditional cropping system more attractive to these households.

GM corn seed companies have innovated continuously with the introduction of new traits and, more recently, with the creation of stacked varieties, which combine more than one trait. This work develops a Bayesian model of adoption dynamics that demonstrates how uncertainty with a package technology with known risk can lead to a sequential adoption pattern in which farmers adopt a single component first. We then develop a semiparametric panel data model of adoption dynamics to measure the effects of experience with single trait (non-stacked) varieties on the adoption of stacked varieties. The results underscore the importance of early experience with the non-stacked technology in the subsequent adoption of stacked varieties, i.e., a sequential adoption process. There is also evidence that farmers with more human capital tend to learn faster from own experience and that as the GM corn-technology diffusion process deepens, the importance of early experience decreases.

We used a state contingent approach to give a detailed analysis of the uncertainty surrounding seed trait adoption. Our framework emphasizes the role of timing and information in farmers’ adoption decisions. The inherent embeddedness of seed traits results in timing restrictions and the inability of post-planting adjustments, this in turn results in farmers necessarily engaging in a game with nature. Two main types of traits we identify are supplementing traits and stabilizing traits – classification into each category is directly related on the mobility of the production factor the trait intends to substitute. Supplementing traits allow for acting after nature (i.e., ex post) while stabilizing traits are better modeled as acting before nature (i.e., ex ante). The type of trait results in different determinants of the farmers’ WTP function.

This article extends the characteristics-based choice framework of technology adoption to account for decisions taken by boundedly-rational individuals in environments where traits are not fully observed. It is applied to an agricultural setting and introduces the concept of ambiguity in the agricultural technology adoption literature by relaxing strict informational and cognition related assumptions that are implied by traditional Bayesian analysis. The main results confirm that ambiguity increases as local conditions become less homogeneous and as computational ability, own experience and nearby adoption rates decrease. Measurement biases associated with full rationality assumptions are found to increase when decision makers have low computational ability, low experience and when their farming conditions differ widely from average adopter ones. A complementary empirical paper (Useche 2006) finds that models assuming low confidence in observed data, ambiguity and pessimistic expectations about traits predict sample shares better than models which assume that farmers do not face ambiguity or are optimistic about the traits of new varieties.

Advances in the genetic modification of agricultural seeds have allowed a range of new opportunities for manipulating seed traits according to production, market and environmental concerns. As seed varieties continue to become increasingly differentiated, preferences for specific seed traits may be expected to impart significant effects on farmer demand for new seeds. This paper proposes a model of technology adoption that integrates demand for traits of new technologies with the potential for heterogeneity based on farm and farmer characteristics. The model is applied to recent GM corn adoption data from Minnesota and Wisconsin farmers, and uses conditional logit and mixed multinomial logit econometric models to estimate the effects of traits and farm and farmer characteristics on adoption outcomes.

This work offers a new approach to the adoption of GM crop varieties by adopting the econometric methodology of the characteristics-based demand literature. A random utility framework was implemented through different specifications of a conditional (CL) and a mixed multinomial logit (MMNL) model of crop-variety choice. Willingness-to-pay and price elasticity estimates for traits were calculated. The MMNL approach demonstrates that individuals' tastes for some traits significantly vary across the population. Results further suggest that labor saving technologies have a much wider potential to be adopted. Overall, the use of a trait-based model to examine the adoption patterns of GM crop varieties among corn farmers in Minnesota and Wisconsin reveals a new set of results and lessons that classic adoption models cannot provide.

We examine access to, use of, and participation in decisions on improved water supply in the Volta basin of Ghana, one of the first countries to introduce a community-based approach to rural water supply on a large scale. While 71 percent of the households interviewed have access to improved water, 43 percent of these continue to use unsafe sources as their main domestic water source. Our results indicate that quality perceptions and opportunity costs play an important role in households’ choice of water source. The effect of prices and income levels on this choice differs according to the pricing system used. Given that supply characteristics such as the location and pricing system affect household decisions to use the improved source, households may try to influence these characteristics in their favor during the community decision-making process for the improved source. However, less than 40 percent of the households interviewed participated in decisions on location or technology. We argue that the decision whether to participate depends on three main factors: (i) the household’s bargaining power, (ii) the potential benefits from influencing outcomes, and (iii) the cost of participation, (mainly opportunity cost of time). Our results indicate that bargaining power matters more than potential benefits. Moreover, we find an extremes effect: the poorest, uneducated and the richest, highly educated segments of the community are more likely to participate in decision-making for improved domestic water supply than the middle class. We conclude with policy implications and needs for further research.