Exploring the nexus between economic growth and economic performance in Nepal

  • 288 Views
  • 90 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This study aims to explore the relationship between economic growth and performance in Nepal, identifying key drivers for growth. Studying the nexus between economic growth and economic performance in Nepal is crucial for understanding how these factors interact within the nation’s specific context. Growth of gross domestic product (GDP) is represented as the primary indicator for evaluating economic performance, reflecting the overall well-being of a nation's economy. Economic performance encompasses a broader spectrum, including indicators such as employment rate, inflation, income distribution and overall economic stability. Using E-Views 10, a descriptive and analytical research approach has been applied to analyze time series secondary data from 1990–2021 using an econometric model. This study found that faster-growing economies typically experience increased jobs, higher investment, more exports, and often lower inflation. These relationships are part of a long-run equilibrium relationship. In the event of an economic shock disrupting this equilibrium, the economy tends to naturally return to the equilibrium over time. This study found that short-term causality running from lagged GDP, gross capital formation (GCF), exports, human development index (HDI), and employment ratio influence immediate GDP growth. These variables wield a short-term influence over GDP growth; for instance, a sudden surge in exports can prompt a temporary boost in economic growth. This indicates that there is a long-term sustained link between GDP growth and the independent variables rather than merely a short-term event.

view full abstract hide full abstract
    • Figure 1. Jarque-Bera normality test
    • Table 1. Variables, their description and measurement
    • Table 2. ADF test result on level series
    • Table 3. Process of selecting lag order
    • Table 4. Results of the Johansen cointegration test
    • Table 5. Vector Error Correction Model
    • Table 6. Wald test
    • Table 7. Heteroskedasticity test (Breusch-Pagan-Godfrey)
    • Table 8. Breusch-Godfrey (Serial correlation LM test)
    • Table 9. Pairwise Granger causality tests
    • Conceptualization
      Yadav Mani Upadhyaya, Khom Raj Kharel
    • Data curation
      Yadav Mani Upadhyaya, Basu Dev Lamichhane
    • Formal Analysis
      Yadav Mani Upadhyaya, Khom Raj Kharel, Suman Kharel
    • Methodology
      Yadav Mani Upadhyaya
    • Project administration
      Yadav Mani Upadhyaya, Khom Raj Kharel, Suman Kharel
    • Software
      Yadav Mani Upadhyaya, Suman Kharel, Basu Dev Lamichhane
    • Validation
      Yadav Mani Upadhyaya, Suman Kharel, Basu Dev Lamichhane
    • Writing – original draft
      Yadav Mani Upadhyaya, Khom Raj Kharel, Suman Kharel
    • Writing – review & editing
      Yadav Mani Upadhyaya, Khom Raj Kharel, Suman Kharel, Basu Dev Lamichhane
    • Funding acquisition
      Khom Raj Kharel, Suman Kharel, Basu Dev Lamichhane
    • Investigation
      Khom Raj Kharel, Suman Kharel
    • Resources
      Khom Raj Kharel, Suman Kharel, Basu Dev Lamichhane
    • Supervision
      Khom Raj Kharel, Basu Dev Lamichhane
    • Visualization
      Suman Kharel, Basu Dev Lamichhane