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Economic history is mobilized by neo-institutionalists to explain the different paths to development observed in post-colonial countries. Acemoglu and Robinson have considered Haiti as an archetype of colonial institutional legacy to describe why Nations fail. Is this deterministic lecture sufficient to understand the troubled development journey of the first free Black Country? In this research, we show, with empirical and historical evidence, that institutional path-dependence theory is not the best analytical framework for the case of Haiti. Critical juncture theory appears to be more appropriate to capture what is really going on in neocolonial Haiti. We also contribute to the critical juncture theory with long-term historical evidence. [ABSTRACT FROM AUTHOR]

Agricultural mechanization is recognized as an important technology to increase agricultural productivity, face labor shortages, and reduce post-harvest loss. However, variations among farms' characteristics and agricultural production systems suggest adopting a targeted strategy in mechanization programs for farmers. This research aimed to answer the following questions in the particular case of Haiti: are there different types of smallholder farmers in terms of mechanization use and socio-economic characteristics? What types of mechanization are used by farmers, and what drives their use among different types of farmers? What are the different types of farms in terms of mechanization use? We used typology construction methodology (principal component analysis (PCA) and hierarchical cluster analysis (HCA)) for a sample of 637 farmers and have identified four different clusters of farmers according to the characteristics of the farms they managed: "Little rain-fed farms" (cluster 1), "Little lowlands farms" (cluster 2), "Medium-sized farms in irrigated plains" (cluster 3), and "Large fragmented mountain farms". Farms in cluster 3 were those who used more agricultural mechanization, and the results of multinomial logistic regression (MNLR) model revealed that the significant drivers of this use were location, access to credit and low food security status. Mechanization use of farms in clusters 1 and 4 was distinctively driven by saving behavior and off-farm income, respectively. In the pooled sample, the drivers of mechanization were: regions or location, age of the farmers, irrigation, livestock, access to credit, off-farm income and food security status. This study contributes to the literature by testing new drivers of agricultural mechanization such as food security status, and off-farm income. The findings can be used to design appropriate mechanization strategies to increase productivity and face labor price/scarcity challenges. They suggest that mechanization policies should focus on agricultural equipment that are adapted to the specificities of the production systems of each farm type, and strengthen access to credit. Otherwise, mechanization will be predominantly used only in irrigated lowlands. [ABSTRACT FROM AUTHOR]

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