Econometric Analysis on Tertiary Sector by Gross Fixed Capital Formation, Enrollment in Higher Education and Remittance Inflow in Nepal

This paper tries to explore the impact of tertiary sector by gross fixed capital formation and enrollment in higher education and remittance inflow in Nepal. Analytical and descriptive methods are used to examine the data in the paper. In analytical research, the dependent and control variables are evaluated using the OLS method; in descriptive research, the mean and standard deviation is used. The study examined the variables affecting GDP and evaluated the data using E-Views software. With an R-squared value of 0.991391, the model's independent variables can explain 99.14% of the variation in the tertiary sector's GDP. The R-squared value is now 0.989669 after being corrected for the number of independent variables in the model. 1.178231 is the Durbin-Watson statistic. This statistic aids in identifying the presence or absence of residual autocorrelation. There is no first-order autocorrelation if the number is close to 2. The standard errors display the accuracy of the estimated coefficients. The coefficients' statistical significance is shown by the probabilities (p-values) connected to the t-statistics. A statistically significant coefficient is one with a p-value that is less than the significance level (for instance, 0.05).

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Publication Details

Journal
Journal of Gurubaba
Published
2024-12-31
DOI
https://doi.org/10.3126/jg.v6i2.82438
Primary Topic
Economic Growth and Productivity
Type
article
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Econometric Analysis on Tertiary Sector by Gross Fixed Capital Formation, Enrollment in Higher Education and Remittance Inflow in Nepal

Ramesh Budha
Journal of Gurubaba
Economic Growth and Productivity
article

Econometric Analysis on Tertiary Sector by Gross Fixed Capital Formation, Enrollment in Higher Education and Remittance Inflow in Nepal

Ramesh Budha
article en

Abstract

This paper tries to explore the impact of tertiary sector by gross fixed capital formation and enrollment in higher education and remittance inflow in Nepal. Analytical and descriptive methods are used to examine the data in the paper. In analytical research, the dependent and control variables are evaluated using the OLS method; in descriptive research, the mean and standard deviation is used. The study examined the variables affecting GDP and evaluated the data using E-Views software. With an R-squared value of 0.991391, the model's independent variables can explain 99.14% of the variation in the tertiary sector's GDP. The R-squared value is now 0.989669 after being corrected for the number of independent variables in the model. 1.178231 is the Durbin-Watson statistic. This statistic aids in identifying the presence or absence of residual autocorrelation. There is no first-order autocorrelation if the number is close to 2. The standard errors display the accuracy of the estimated coefficients. The coefficients' statistical significance is shown by the probabilities (p-values) connected to the t-statistics. A statistically significant coefficient is one with a p-value that is less than the significance level (for instance, 0.05).

Journal of GurubabaVol. 6(2)
Openalex Percentile: Top 66%
Economic Growth and Productivity
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