Evaluating the Impact of Education on Earnings in Nepal
Journal Title: Delhi Business Review: An International Journal of SHTR - Year 2017, Vol 18, Issue 1
Abstract
Purpose: This study contributes to the literature of return on investment in education and help policymakers while allocating the budget to education sector since education level causes significant increment in earnings in the context of Nepal. Design/Methodology/Approach: This paper has applied a Semi-log multivariate regression model using data from Nepal Labor Force Survey to provide empirical evidence in the entire analysis on this issue. Not just academic qualifications, but also there are several other factors which cause increase in income. We explore this fact to identify the impact of experience, age, training, gender, and other variables in their earnings. Findings: The empirical evidence of this study has shown a direct relationship between the education and earnings and we estimated that an increase in education of people by 1 level causes 16.64% increment in their wages on an average. Apart from the academic qualification, their experiences in the similar field have statistically significant relationship (i.e., one level increase in experience causes 11.57% increase in monthly earnings). The training dummy is found to be statistically insignificant to cause increment in earnings which is also an interesting finding of the study. Research Limitations/Implications: Due to having the low R-squared value after introducing dummies, we can suggest that there may be other quantitative and qualitative factors like ability of the individual and the contextual fact that may cause the increment in earnings, which can be the future scope of this study. Practical Implications: Two major implications of this empirical study are: firstly, this will help policymakers while allocating the budget in education sector and secondly, encourage people towards higher education. Originality/Value: This is an original research and also examines the discrepancies in earning caused by gender, marital status, and area of living and work. Key Words: Secondary Data, Multivariate Regression, Inferential Analysis, Monthly Earnings, and Education.
Authors and Affiliations
Hari Gopal Risal, C. P. Gupta
Keywords
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