Abstract

This study seeks to test for the validity of the Solow growth model using cross-country panel data. Panel OLS analysis was adopted following an extensive review of recent and related literature with output-side of the real GDP as the dependent variable with other variables like population, capital stock and employment as the independent. However, population and capital stock are positively impacting the output with statistically significant value, while employment is not an important variable in the model even though it exhibits a negative and statistically significant effect to the output. In conclusion, the estimation result conforms the postulations of the basic Solow and augmented Solow growth model thereby validating the Solow model across-countries.

Highlights

  • One of the greatest challenges in economic growth and development policy is the persistent and significant differences and ranges of standards of living across countries

  • All the growth theories strive to account for the differences in growth experiences across countries, and why the growth changes over time

  • Growth theory analyzes the relationship between the macro-dynamics and technological change and over the years, different growth models have been developed to account for and sustain the emergence and diffusion of technical change effects and the acceleration of economic growth, employment dynamics, capital stock among others (Llerena & Lorentz, 2004)

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Summary

Introduction

One of the greatest challenges in economic growth and development policy is the persistent and significant differences and ranges of standards of living across countries. Another notable shortcoming of the Solow growth model implicitly divergence of income share from capital from the output of the estimated model and national account information. This study utilizes data from cross-country panel to study to verify the validity the Solow growth theories across countries as well as ascertain the magnitudes of population, employment and capital stock of growth.

Results
Conclusion
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