Determinants of Youth Unemployment in Nepal

Both developed and developing countries are facing youth unemployed problems. The main objective of the study is to identify the determinants of youth unemployment in Nepal, using secondary data. For empirical analysis, the study uses multivariate Logit regression model to identify the determinants of youth unemployment. The logistic model shows that the sample variables like time spend in farm, ever-married, communication, completed school year, training have positive relationship with probability of being youth unemployed whereas urban, house ownership, male, household size, Koshi Pradesh, Bagmati Pradesh, Gandaki Pradesh, Lumbini Pradesh, Karnali Pradesh and Sudurpaschim Pradesh have negative relationship with proability of being youth unemployed. The sample variables like as time spend in farm, completed school year, Koshi Pradesh, Bagmati Pradesh, Gandaki Pradesh, Lumbini Pradesh, Karnali Pradesh and Sudurpaschim Pradesh are significant at 1 percent level and other explanatory variable like urban, ever-married, house ownership, communication, male, training, household size are not significant but they are important determinants of youth unemployment. This study suggests that more investment on education, improve agriculture sector, emphasis on regional balance and consider the determinant factors.

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Journal
Tribhuvan Journal
Published
2024-10-20
DOI
https://doi.org/10.3126/tribj.v3i1.70806
Primary Topic
Unemployment and Economic Growth
Type
article
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article

Determinants of Youth Unemployment in Nepal

Sharda Prasad Bhattarai
Tribhuvan Journal
Unemployment and Economic Growth
article

Determinants of Youth Unemployment in Nepal

Sharda Prasad Bhattarai
article en

Abstract

Both developed and developing countries are facing youth unemployed problems. The main objective of the study is to identify the determinants of youth unemployment in Nepal, using secondary data. For empirical analysis, the study uses multivariate Logit regression model to identify the determinants of youth unemployment. The logistic model shows that the sample variables like time spend in farm, ever-married, communication, completed school year, training have positive relationship with probability of being youth unemployed whereas urban, house ownership, male, household size, Koshi Pradesh, Bagmati Pradesh, Gandaki Pradesh, Lumbini Pradesh, Karnali Pradesh and Sudurpaschim Pradesh have negative relationship with proability of being youth unemployed. The sample variables like as time spend in farm, completed school year, Koshi Pradesh, Bagmati Pradesh, Gandaki Pradesh, Lumbini Pradesh, Karnali Pradesh and Sudurpaschim Pradesh are significant at 1 percent level and other explanatory variable like urban, ever-married, house ownership, communication, male, training, household size are not significant but they are important determinants of youth unemployment. This study suggests that more investment on education, improve agriculture sector, emphasis on regional balance and consider the determinant factors.

Tribhuvan JournalVol. 3(1)
Tribhuvan University (NP)
Decent work and economic growth
Openalex Percentile: Top 78%
Unemployment and Economic Growth
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Determinants of Youth Unemployment in Nepal — Sharda Prasad Bhattarai · Tribhuvan Journal (2024) | TGRS Research Map | TGRS