International Journal of Social Science & Economic Research
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Title:
Empirical Analysis of the Automation-Augmented Solow Growth Model and Income Differences in the South Korean Economy

Authors:
Cho, Young-Jun

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Cho, Young-Jun
North London Collegiate School Jeju, South Korea

MLA 8
Young-Jun, Cho,. "Empirical Analysis of the Automation-Augmented Solow Growth Model and Income Differences in the South Korean Economy." Int. j. of Social Science and Economic Research, vol. 9, no. 8, Aug. 2024, pp. 2633-2650, doi.org/10.46609/IJSSER.2024.v09i08.005. Accessed Aug. 2024.
APA 6
Young-Jun, C. (2024, August). Empirical Analysis of the Automation-Augmented Solow Growth Model and Income Differences in the South Korean Economy. Int. j. of Social Science and Economic Research, 9(8), 2633-2650. Retrieved from https://doi.org/10.46609/IJSSER.2024.v09i08.005
Chicago
Young-Jun, Cho,. "Empirical Analysis of the Automation-Augmented Solow Growth Model and Income Differences in the South Korean Economy." Int. j. of Social Science and Economic Research 9, no. 8 (August 2024), 2633-2650. Accessed August, 2024. https://doi.org/10.46609/IJSSER.2024.v09i08.005.

References

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ABSTRACT:
The integration of automation into production processes is emerging as a transformative force, impacting economic growth, labor market structures, and broader economic landscapes. Prettner's automation-augmented Solow Growth Model provides a novel theoretical framework for analyzing the role of automation capital in economic production, offering insights into its effects on both economic growth and income disparities between workers and business owners. This study investigates the impact of automation on economic growth and income inequality in South Korea, applying Prettner’s automation-augmented Solow Growth Model. By incorporating automation capital into the production function, this model helps elucidate the broader economic implications of automation. South Korea, with its advanced manufacturing sector and rapid technological adoption, serves as an ideal case for examining these dynamics. Using time series data from 2011 to 2019 and the Ordinary Least Squares (OLS) method, our analysis reveals a positive correlation between automation capital and economic growth, highlighting automation's role in driving South Korea’s economic progress. While the link between automation and income inequality is less clear, the study suggests that automation has the potential to significantly influence economic structures in South Korea. This emphasizes the need for further research to fully understand these relationships and inform policy decisions.

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