Evaluation of the factors influencing the adoption of agricultural and natural resource management technologies among small farmers in developing countries have been mostly limited to qualitative discussions or simple descriptive statistics resulting in superficial and inconclusive findings. This study introduces the use of Poisson Count Regressions as a statistically appropriate procedure to analyze certain common types of adoption data. It uses them to assess the impact of key socio-economic, bio-physical, and institutional factors on the adoption of integrated pest management, agroforestry, and soil conservation technologies among small farmers in three Central American countries: Costa Rica, Panama, and El Salvador
25 pages, Using linked data from multiple years of the U.S. Census of Agriculture, this study identifies farm and operator characteristics associated with beginning farm survival, growth, and success. Success is defined as continuing in business for 5 years without a decline in farm real estate asset value. The results indicate which types of beginning farms and farmers are likely to survive and grow—information which could be useful in targeting program resources. By identifying policy-amenable variables that correlate with both farm survival and business expansion, the results also suggest possible mechanisms for increasing the success of beginning farms.
