Reliability of industrial policies in Nepal: An empirical investigation into the role of macroeconomic indicators

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This study aims to analyze the reliability of Nepal’s industrial policies, focusing on the effects of macroeconomic variables on implementation and outcomes. This paper assesses Nepal’s industrial policies, emphasizing the need for improvements, export promotion, and human capital development while recognizing the importance of strategic planning and context-specific approaches for economic growth, stability, and development. The analytical and descriptive approaches have been applied to analyze the data by collecting secondary data sources that include official publications, which encompass 47 time series variables from 1974 to 2020. The findings provide mixed evidence for the economic impacts of liberalization, with exports and liberalization driving overall GDP growth. In contrast, other factors like economic openness, tourism, and their relationship with industrial GDP remain statistically insignificant. The paper indicates that remittances and investment have the most substantial impact on GDP, raising it by 1.86 and 1.21 units per unit increase, respectively. Exports have a moderate impact on industrial GDP (0.403 units). Export-oriented industries and tourism lack significant associations with either type of GDP. Liberalization significantly boosted both GDP and industrial GDP, with an increase of 179465.3 and 49595.62 units, respectively. Imports also jumped post-liberalization, driven by higher remittances as 1.215 units per unit increase. This study on industrial policies in developing economies, focusing on Nepal, adds valuable insights. The findings can ensure policymaking, boost economic growth, and strengthen Nepal’s industrial sector.

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    • Figure 1. Normality test of model 1
    • Figure 2. Normality test of model 3
    • Figure 3. Normality test of model 4
    • Table 1. Regression model
    • Table 2. Heteroskedasticity in economic regression
    • Table 3. Breusch-Godfrey Serial correlation LM test
    • Table 4. Multicollinearity of VIF
    • Table 5. Variance inflation factors
    • Table 6. Heteroskedasticity for residuals
    • Table 7. Godfrey serial correlation LM test for residuals
    • Table 8. Determination of R2
    • Table 9. Regression of model IV
    • Table 10. Serial correlation test
    • Table 11. Heteroskedasticity or homoscedasticity check
    • Table 12. Least squares method for industrial GDP
    • Conceptualization
      Khom Raj Kharel, Yadav Mani Upadhyaya, Basu Dev Lamichhane
    • Data curation
      Khom Raj Kharel, Shiva Raj Ghimire
    • Formal Analysis
      Khom Raj Kharel, Yadav Mani Upadhyaya, Basu Dev Lamichhane
    • Funding acquisition
      Khom Raj Kharel, Yadav Mani Upadhyaya, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Methodology
      Khom Raj Kharel
    • Project administration
      Khom Raj Kharel, Yadav Mani Upadhyaya, Basu Dev Lamichhane
    • Software
      Khom Raj Kharel, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Validation
      Khom Raj Kharel, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Writing – original draft
      Khom Raj Kharel, Yadav Mani Upadhyaya, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Writing – review & editing
      Khom Raj Kharel, Yadav Mani Upadhyaya, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Investigation
      Yadav Mani Upadhyaya, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Resources
      Yadav Mani Upadhyaya, Shiva Raj Ghimire, Basu Dev Lamichhane
    • Supervision
      Yadav Mani Upadhyaya, Shiva Raj Ghimire
    • Visualization
      Shiva Raj Ghimire, Basu Dev Lamichhane