Understanding self -employment success among participants of microenterprise training programs
Creators: name: Soto, Enrique
Publisher: name: ProQuest
Year: 2023
Subjects: classificationCode: 44
subject: Human society
classificationCode: 4407
subject: Policy and administration

description: Microenterprise initiatives have gained popularity in the United States due to their widespread use and effectiveness in Third World countries as strategies to alleviate poverty and foster development, and more recently by changes in welfare policies limiting benefits and imposing work requirements on welfare recipients. Microenterprise training supporters consider that this type of effort have positive results in the economic well being of trainees and makes them more likely to run microbusinesses that will contribute to improve their living standard. Drawing on theories of entrepreneurship and empirical studies about self-employment initiatives, and using data from the Self-Employment Learning Project (SELP) of the Economic Opportunities Program of the Aspen Institute, this dissertation seeks to identify predictors of business success among individuals who received self-employment training services (loans, technical support, classroom training) from seven microenterprise training programs operating in the United States. SELP's participant survey followed a random sample of 405 microentrepreneurs for five years through five waves of interviews, collecting data on their employment status, earnings, income, training program participation, business operation and household and demographic characteristics. Individuals in the training programs were self-selected but the sample of SELP's survey was randomized. However, because of the lack of a control group this study's results are generalizable only to the population of participants in the seven microenterprise programs in the Aspen study. Six models of self-employment success using logistic regression analyses were tested: (1) business earnings push family income above 150% of poverty threshold at Wave 5; (2) greater business earnings at Wave 5; (3) greater personal earnings at Wave 5; (4) greater personal assets at Wave 5; (5) lower means-tested benefits at Wave 5; and (6) with an open business at Wave 5. Predictors included: demographic characteristics (age, gender, race/ethnicity, marital status, household composition), owner resources and characteristics (human capital and financial resources such as previous business experience, hours worked, educational level, household net worth, presence of other adults in the household), and program training characteristics (provision of credit, hours of program assistance). Complete data available for testing the models ranged between 148 and 191 cases out of 269 respondents in the last wave (Wave 5). Significant predictors were found for five models, and included gender, age, being self-employed, marital status, educational level, hours of program assistance, and household net worth. Implications for microenterprise programs were outlined in five areas: training for women, follow-up services, training program characteristics, educational level and program assistance, and provision of credit.