Carlos Trejo-Pech

Carlos Trejo-Pech

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Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 May 2023 in Agricultural and Food Economics
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Journal Article
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CTCarlos Trejo-Pech
Carlos Trejo-Pech
Roselia Servín-JuárezRoselia Servín-Juárez
Roselia Servín-Juárez
ÁRÁlvaro Reyes-Duarte
Álvaro Reyes-Duarte
This study investigates what factors relate to the coffee farmer’s cooperative affiliation decision and whether this decision impacts the farmer’s cash holdings. First, we propose a cooperative affiliation model based on transaction cost economics theory. There is a lack of consensus in the literature on what factors explain the farmer’s cooperative affiliation decision in the coffee sector. Overall, we find that the more specialized coffee farmers are, the more likely they will become cooperative affiliates. This is consistent with transaction cost economics predicting that cooperatives are business structures that can reduce transaction costs and safeguard specialized assets from opportunistic behavior. Specifically, logit regression models suggest that shade-grown coffee plantations, off-farm income, coffee farming experience, low-level market competition, farmland size, altitude, and private farmland are statistically related to the farmer’s decision to affiliate with cooperatives. Results on farmland size and shade-grown coffee plantations can be particularly relevant for scholars, policymakers, cooperative leaders, and extension professionals in the region. Second, based on the affiliation model, we employ propensity score matching to evaluate the impact of the farmer’s cooperative affiliation decision on cash holdings, particularly on cash shortness. It is often claimed that farmers do not affiliate with cooperatives because these organizations cannot pay them in full at harvest and coffee collection time. It is believed that cooperatives’ inability to pay farmers early increases the likelihood of farmers’ cash shortness and their need for additional financing to operate or cover household needs. However, this study finds no evidence that the affiliation decision is related to the likelihood of the farmer experiencing cash shortness around harvesting and selling time.

1 July 2015 in Contaduría y Administración
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Journal Article
Open access
CTCarlos Trejo-Pech
Carlos Trejo-Pech
MNMagdy Noguera
Magdy Noguera
SWSusan White
Susan White
A sample of recommendation reports by equity analysts covering Mexican publicly traded firms in Mexico is studied. We propose a set of “most preferred” financial ratios from this sample. It is found that the most preferred ratios by equity analysts, a group of sophisticated users, are not those ratios typically covered in financial textbooks. Moreover, by using panel regression analysis, we test the relationship between financial ratios and leading stock returns during the 1995–2011 period. Overall, consistent with the efficient market hypothesis, the results show that estimates of financial ratios most preferred by equity analysts have predictive power on 1-year future stock returns. We find no evidence of predictive power on 2-year stock returns

8 August 2019 in Energies
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CTCarlos Trejo-Pech
Carlos Trejo-Pech
JLJames Larson
James Larson
Burton EnglishBurton English
Burton English
T. Edward YuT. Edward Yu
T. Edward Yu
This study evaluates biorefinery bio-oil feedstock costs at the plant gate for a prospective field pennycress (Thlaspi arvense L.) to sustainable aviation fuel (SAF) supply chain. The biorefinery would supply SAF to the Nashville, Tennessee international airport. Supply chain activities include pennycress production, transporting oilseed to a crushing facility, processing of oilseed into bio-oil, and transporting bio-oil to the biorefinery. The analysis shows profit potential for economic agents in the prospective supply chain. Estimated breakeven cost (profit = 0) of growing, harvesting, and transporting oilseed to a crushing facility is 17.7 ¢ kg−1. A crushing facility can pay up to 23.8 ¢ kg−1 for pennycress oilseed during the first year of production and provide investors 12.5% annual rate of return. Therefore, a profit margin of up to 6.1 ¢ kg−1 is available for the crushing facility to induce prospective pennycress producers to supply oilseed for SAF production. However, the estimated profit margin was sensitive mainly to uncertain oilseed yields, changes in field production costs, and pennycress meal and bio-oil prices. A spatial biorefineries sitting model, the Biofuels Facility Location Analysis Modeling Endeavor, estimated that the least-cost supply chain configuration is to establish three crushing facilities located in Union City, Huntington, and Clarksville, TN, to supply bio-oil to the biorefinery, with the biorefinery sited in an industrial park about 24.14 km from the Nashville international airport aviation fuel storage. Estimated total costs of bio-oil at the biorefinery plant gate are between 83 and 109 ¢ kg−1 if crushing facility oilseed procurement costs are between 17.7 and 23.8 ¢ kg−1 for oilseed.

1 January 2015 in SSRN Electronic Journal
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CTCarlos Trejo-Pech
Carlos Trejo-Pech
This conference proceedings collection includes full papers, abstracts or extended abstracts of research work presented at IBEC 2015. Authors retain copyright o

13 January 2015 in Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie
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CTCarlos Trejo-Pech
Carlos Trejo-Pech
RWRichard N. Weldon
Richard N. Weldon
MGMichael A. Gunderson
Michael A. Gunderson

18 May 2018 in Journal of International Food & Agribusiness Marketing
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Journal Article
Closed access
JAJ. Jaime Arana-Coronado
J. Jaime Arana-Coronado
CTCarlos Trejo-Pech
Carlos Trejo-Pech
MVMargarita Velandia
Margarita Velandia
JPJesús Peralta-Jimenez
Jesús Peralta-Jimenez
We study the factors influencing the percentage of organic and fair trade certified coffee sold through a cooperative by growers of five cooperatives in Mexico. The percentage of coffee sold through the cooperative was used as a proxy of growers’ engagement with a cooperative. Using factor analysis and a fractional probit regression, we evaluated the proposition that the level of engagement can be explained by transaction cost economics, social norms and connections, and farmer and farm business characteristics. We found that farm size, uncertainty regarding cooperative time of payment to the members and cooperative commitment on price to be paid negatively influence the level of engagement. In contrast, asset specificity, relational commitment, and price have a positive impact on engagement. Our results may help cooperatives and policy makers to build strategies aiming to increase this level of engagement. This is relevant because lower grower engagement has been found to be positively correlated with weak performing cooperatives.