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  • Assessing the Impact of Education and Training Programs on the Development of Youth Entrepreneurs in Small and Medium Enterprises in Delhi-NCR

Assessing the Impact of Education and Training Programs on the Development of Youth Entrepreneurs in Small and Medium Enterprises in Delhi-NCR

Student: Afroz Khan

Supervisor: Alexandra Alexandrovna Moskovskaya

Faculty: Faculty of Social Sciences

Educational Programme: Politics. Economics. Philosophy (Master)

Year of Graduation: 2024

The main aim of this study is to Assess the Impact of Education and Training Programs on the development of youth entrepreneurs in Small and Medium Enterprises in Delhi. The following are the specific objectives of the study; Firstly; to Evaluate the effectiveness of education and training programs targeted at youth entrepreneurs in small and medium enterprises (SMEs) in Delhi. Secondly, to Identify the key factors influencing the participation and engagement of youth entrepreneurs in these education and training programs. Thirdly, to Assess the impact of education and training programs on the development and growth of youth-led SMEs in Delhi. Fourthly, Explore the challenges and barriers faced by youth entrepreneurs in accessing and benefiting from education and training initiatives. Finally, to Provide recommendations for enhancing the design and implementation of education and training programs to better support the development of youth entrepreneurs in Delhi's SME sector. This study makes use of the Causal research design in order to capture the essence of the study, while the study makes use of primary data collected through online survey and further transform to a modernize quantitative data for the purpose of analysis. The study further uses both the binary choice models and that of the multinomial choice models for analyzing the primary data collected via the maximum Likelihood approach. However, the use of these models was based on the structure of the data collected. Result from the binary logistic regression model was conducted on a dataset with 191 observations. The likelihood ratio chi-square statistic of 15.78 with 2 degrees of freedom resulted in a p-value of 0.0004, indicating that the model as a whole is statistically significant. The log-likelihood of the model is -81.565388, and the McFadden's R-squared is 0.0882, suggesting that the model explains about 8.82% of the variance in the dependent variable.

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