Carlos Omar Trejo-Pech

This study investigates side‐selling in Mexican coffee cooperatives, seeking to answer what drives side‐selling, what drives the expected share side‐sold and what non‐cooperative farmers perceive about side‐selling. Our conceptual framework, a contribution to this literature, proposes that farmers’ economic pressure, coffee quality and commitment to cooperatives explain side‐selling through utility maximization, transaction cost economics and attitude–behaviour theory. Our logit and fractional logit models find that delayed payments and cash shortages are the main economic drivers of side‐selling, suggesting that growers who need immediate cash at harvest and those who perceive their cooperatives as slow to pay are more likely to side‐sell. Regarding coffee quality, farmers growing speciality shade‐grown coffee and those growing coffee at higher elevations are less likely to side‐sell, and when they do, they side‐sell a smaller share. Regarding the farmer‐cooperative relationship, side‐selling is less likely to occur―and if it occurs, the share side‐sold is likely to be lower―among farmers with longer cooperative membership tenure and in larger cooperatives. Finally, as a second contribution, the study provides a descriptive analysis of non‐cooperative farmers’ perceptions of side‐selling. Insights from non‐cooperative farmers helped to validate some of the variables included in our models.

This study evaluates equity analysts’ earnings forecasts, comparing United States (U.S.) sugar‐using firms (SUF), and a selected group of agribusinesses (AGB). Aspects of U.S. sugar policy, reinitiated in 1982, help to ensure a reliable and predictable domestic supply of SUF's primary ingredient, sugar. U.S. sugar policy requires the U.S. Department of Agriculture (USDA) to generate publicly available sugar supply and demand forecasts through its World Agriculture Supply and Demand Estimates ( WASDE ) report, introduced in 1992 and expanded in 2008 to include Mexican sugar forecasts. Therefore, we examined whether the reinitiation of U.S. sugar policy, the initiation of WASDE sugar forecasts, and the implementation of the North American Free Trade Agreement (NAFTA) for sugar trade benefited SUF by improving equity analysts’ earnings per share (EPS) forecasting accuracy for these firms. This analysis, mainly based on difference‐in‐differences and event‐study regression, focused on EPS forecast accuracy from 1976 to 2025. Consistent with our hypothesis, we found that improvements in SUF EPS forecast accuracy were statistically associated with the reinitiation of U.S. sugar policy in 1982 and, to a lesser extent, with the implementation of the NAFTA sugar provision in 2008. More broadly, our analysis suggests that, given its role as a price‐ and supply‐stabilizer, U.S. sugar policy might have caused a structural shift in the U.S. sugar industry, providing a more predictable business environment, and that its legacy may remain present in the contemporary forecasting environment.

Purpose: This study conducted an economic evaluation of a hybrid poultry production system implemented in Rwanda through a public-private partnership from 2017 to 2020. The program, funded by the United States Agency for International Development and other agencies, subsidized farmers with a zero-interest loan to acquire and equip a coop to grow 100 chickens per flock. The main objective of this study was to evaluate the financial performance of 489 farmers who participated in the program. A secondary objective was to determine whether small-scale farmers in this program could be competitive relative to Rwanda’s commercial broiler production standards or those in other developing countries. Design/methodology/approach: The study estimated and analyzed deterministic and stochastic financial statements and metrics. Relevant financial statement items were simulated stochastically according to observed variability within the data by selecting the best-fitted distributions according to the Akaike Information Criterion. The database contained over 2,200 farmer/flock observations from 489 farmers participating in the Rwanda hybrid broiler program from 2017 to 2020. Analyzed outputs per flock or production cycle included net income, cash flow before labor, the return on sales, the return on assets and selected production parameters. Findings: The evaluated hybrid system had production standards comparable to commercial production. However, identified opportunities for improvement included increasing the number of flocks harvested per year and reducing the feed conversion ratio (FCR). The financial analysis revealed a 70.5% probability (64.3% probability without a subsidy) that farmers would break even or generate a positive net income. Regarding cash flow before labor, farmers were 78.3% likely (72.8% without a subsidy) to take cash home. The analysis also found that farmers’ profitability and the FCR improved over time as they gained experience producing chickens. Originality/value: This analysis showed that a hybrid broiler production system has the potential to succeed in Rwanda and help the most economically vulnerable farmers in this country. Such a model would contribute to Rwanda’s 2017 long-term national livestock master plan, which aims to reduce poverty and increase national security.

The goal of this case study is to explore the complexities and relevance of accurately estimating the cost of capital, which serves as a reference for key decisions in corporate finance and equity valuation. Despite the simplicity of a company’s cost-of-capital formula, in practice, estimating the cost of capital is not simple because it requires substantial judgment, and alternative approaches exist. This prevents a straightforward method for calculating the cost of capital, leading to inaccuracies. This case study features an equity analyst reviewing survey-based studies on best practices for cost-of-capital estimation and gathering data to estimate and analyze the cost of capital for leading US grocery firms. A technical note on the cost of capital is appended to support the development and solution of the case. Broadly, this study highlights the lack of consensus among practitioners on several aspects of cost-of-capital estimation and underscores the importance of making informed judgments based on finance and economics principles.

Purpose: The design of effective policies that increase access to agricultural credit should consider understanding credit constraint farmers’ groups and their response to changes in the credit conditions. To contribute to this understanding, this study surveyed farmers from Chile and classified them into five credit constraint categories discussed in credit literature. In addition, these farmers indicated how they would react to a series of hypothetical conditions related to changing interest rates, loan maturity and grace periods. Their responses were employed to measure credit demand scores (i.e. relative elasticities). Regression tests evaluated how different types of farmers reacted to changing credit conditions.Design/methodology/approach: Farmers from Chile were surveyed using a mix of random and convenience sampling. Surveyed farmers were classified into five credit constraint categories proposed by previous research. Farmers rated their demand for credit on a five-point Likert-type scale for hypothetical changes in interest rates, loan maturities and grace periods. Their responses were employed to measure credit demand scores or relative credit elasticities. The study evaluated credit elasticity as a function of farmers’ credit constraint and some control variables using several regressions, including OLS, ordered probit and hierarchical regression.Findings: The study identified 44% unconstrained nonborrowing farmers, 23% unconstrained borrowers, 14% quantity-constrained, 16% risk-constrained and 3% transaction cost-constrained farmers. Unconstrained borrowers and quantity-constrained farmers responded most to changing interest rates and loan maturity conditions. In addition, unconstrained nonborrowers and risk-constrained farmers were statistically less sensitive to changes in credit conditions than unconstrained borrowers. This finding is significant because, as discussed, unconstrained nonborrowers represent 44% of our sample. Furthermore, risk-constrained farmers were the least sensitive to changes in interest rates and loan maturity across all other credit categories.Practical implications: This study gives insights that can guide agribusiness policies to enhance access to credit in developing countries such as Chile. Agricultural credit capital institutions can better target their clientele by identifying farmers’ possible reactions before implementing policy changes to increase access to credit. This study’s credit constraint categorization and the results discussed can guide that identification. For instance, policies directed toward unconstrained borrowing farmers may find positive responses. However, implementing policies targeting the other three groups (unconstrained nonborrowing, risk-constrained and transaction cost-constrained farmers) is more challenging because these farmers are less responsive to changing credit conditions.Originality/value: This article correlates farmers’ propensity to borrow and credit constraints across five categories of farmers. Prior research using this categorization framework has not identified farmers into the five groups. Furthermore, in addition to interest rate and loan maturity credit demand relative elasticity, this study adds the grace period elasticity, which has not been included in previous studies on agricultural credit.

Forest residues have been suggested as potential feedstock for sustainable aviation fuel (SAF) production through different pathways. However, the bulky density and scatter distribution require efficient size-reduction processes to enhance the feedstock supply. Thus, this study analyzes the impact of alternative preprocessing and conversion technologies on the SAF supply chains from logging residues (the predominant share of forest residues) using a two-stage mixed-integer linear programming model. The model determines the optimal location of biomass preprocessing depots, conversion facilities, and airports receiving SAF by minimizing the net present value of the total supply chain cost over 10 years. Using high-resolution spatial data in the Southeast U.S.A. as a case study, the results show that the technology and scale of the facilities heavily influenced the SAF’s breakeven cost and maximum supply quantity. The most economically efficient system that adopts a rotary shear milling system and pyrolysis conversion process could generate up to 650 million gallons of SAF from logging residues in the region, with nearly 62% of the SAF being produced from hardwood residues. Also, the most efficient system has an estimated breakeven cost of US$5.51 per gallon of SAF.

Woody biomass feedstock processing, including sorting, drying, and size reduction of biomass to provide standardized reactor-ready biomass to the biorefinery, is crucial to biofuel conversion. This study compares two comminution technology systems applied to woody biomass processing at a depot before being utilized for biofuel production at a biorefinery. The conventional comminution technology, known as the hammermill system, is compared with a rotary shear system developed by Forest Concepts™. Potential economic savings of using the new technology are evaluated by applying a deterministic and a stochastic partial capital budgeting model based on results from an experiment that processed chipped hybrid poplar chips and forest residues with both systems. The stochastic partial capital model estimates that savings will vary between approximately USD 28 and USD 42 per ton of reactor-ready processed biomass, with mean and median values around USD 34 per ton. It is 90% likely that savings will be between USD 30 and USD 39 per ton of reactor-ready processed biomass. The estimated savings are mainly due to differences in input (feedstock) to output (reactor-ready biomass) yields between technologies, affecting feedstock and drying costs.