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The Impact Of Education On Economic Growth

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The Contribution Of Education To Economic Growth: Evidence From Nepal

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By Paravee Maneejuk Paravee Maneejuk Scilit Preprints.org Google Scholar 1, 2, * and Woraphon Yamaka Woraphon Yamaka Scilit Preprints.org Google Scholar 1, 2

Received: 05 December 2020 / Edited: 2 January 2021 / Received: 5 January 2021 / Published: 7 January 2021

Education: Development News, Research, Data

This study analyzes the non-linear impact of Education, especially higher education, on economic growth in ASEAN-5 countries (eg Thailand, Indonesia, Malaysia, Singapore and the Philippines) during 2000-2018. The impact of education on economic growth is assessed through a variety of educational indicators, including public spending on higher education for individual students, enrollment rates for primary, secondary and tertiary education. Education and new indicators of unemployment rate with higher education. This study creates a non-linear regression model – a chronological regression and a panel regression – to investigate the impact of education on the economic growth of individual countries and the ASEAN-5 region, respectively. There are three main findings. First, the non-linear impact of government spending per tertiary student on economic growth has been identified for ASEAN-5. However, the impact does not follow the law of profit reduction. Second, our findings suggest that rising unemployment among highly educated workers may have a positive or negative impact on economic growth, requiring appropriate policies to address the negative impacts. Finally, secondary and tertiary enrollment rates could contribute to ASEAN-5 economic growth (both at the individual and regional levels). However, local analysis shows that the impact of higher education is doubly strong when enrollment rates are greater than a certain threshold (kink point). Therefore, we can conclude that the secondary enrollment rate has a positive effect on economic growth. However, higher education is the key to future growth and sustainability.

Economists have renewed interest in the role of human capital in economic growth in recent years. Previous studies have traditionally viewed education as a simple measure of human capital and an attempt to examine the impact of education on economic growth. While the relationship between education and growth has been widely discussed, several recent studies have focused more on higher education and tried to investigate the impact of its economic growth. This is because higher education is considered an important factor driving economic growth and competitiveness for all countries. Basic education (both primary and secondary) may be sufficient for the production of simple goods and services and allow workers to use technology in the workplace. Higher education, on the other hand, is likely to produce graduates who have the potential to innovate and become working people who help turn a country into a knowledge-based economy. Higher education provides technology and innovation and provides high-skilled workers to the labor market, thereby boosting economic growth.

Many economists have presented evidence supporting the potential impact of higher education in both developing and developing economies (e.g., 1, 2, 3]). However, a small number of studies focus on how higher education is extended and used [4, 5]. According to the literature, some previous studies measured the impact of higher education through research and development (see [6, 7, 8]). However, in this study, the relationship between higher education and economic growth was re-examined. We try to fill the literary gap by introducing a workforce with a higher education degree – a proxy for expanding higher education – in our analysis. The study also introduces a new measure of the use of higher education: Unemployment, along with higher levels of education, as we believe that the contribution of higher education to the economy may be related to employment. For graduate students. Jobs is a platform where highly skilled workers can showcase their potential for future economic growth. On the other hand, if there is no opportunity for those who invest in skills to get a good job, it can lead to loss of life.

In addition to measurement issues, this study also demonstrates how the impact of education on growth is exemplified. Most of the existing literature typically uses linear models, which can be a good estimate and theoretically consistent. However, the relationship between education and economic growth may not be linear [8]. Investigation of non-linear relationships between these two variables is very limited. Only a few studies focus on nonlinearities [9, 10, 11, 12, 13]. Recent work on this issue, Maneejuk, Yamaka, and Sriboonchitta [14] indicates that the linear model can overlook an important nonlinear relationship. Therefore, in this study, potential nonlinear relationships will be examined by kink regression.

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In the regression model, the regression function is continuous, but the slope is discontinuous at the kink point. This kink is just a turning point that occurs when there is a structural change in the relationship between variables. Our analysis shows that the impact of education through various indicators may not be linear or constant over time. The impact may increase after reaching a certain level of development or decrease due to a decrease in revenue. Thus, this study may reflect the economic prospects arising from structural changes after education indicators have reached a kink. We need to go beyond the traditional linear model to provide a new explanation of the impact of education on economic growth under different education regimes. The study also shows whether education has a positive or negative impact on economic growth. To estimate this model, range estimates were made to address the multi-line problem and sample size in our education-growth model. Discussions and reasons for using the Ridge Estimator will be explained in the next section.

The study is of particular concern to the five ASEAN countries of Thailand, Indonesia, Malaysia, Singapore and the Philippines. These five countries are considered to be the leaders of the group due to the size of GDP and the level of economic development is quite high. They have different cultures, lifestyles and languages. However, ASEAN-5 emphasizes education in promoting economic growth. Therefore, they plan to improve the education system and quality together and try to bring the level of education of all member countries to Same standard. However, the quality of education remains very different and unequal across the country. In the relevant literature, only a few studies have investigated the role of education, especially higher education in the ASEAN-5 economy. Therefore, it may be a challenge to establish evidence on this issue and draw conclusions about the impact of higher education on economic growth in the region.

The main focus of this document is to analyze the non-linear impact of higher education on economic growth in ASEAN-5. The significant contribution of our study to the existing literature is threefold. First, this study considers the expansion of higher education, along with the share of education and investment. Second, although the impact of higher education on economic growth is considered, a small number of studies have used a non-linear model to analyze this issue. While no studies have explored the impact of individual education indicators on economic growth. Therefore, this study uses a kink trend model to investigate the impact of education indicators on economic growth in ASEAN-5 countries in order to fill gaps in the literature. Third, this is the first attempt to perform a Ridge estimation to fit the kink regression model for solving data and multi-line configuration problems in our practical model.

The preparation of this document is as follows. Following the introduction, Section 2 provides a literature review on the measurement of education and its impact on economic growth. The economic approach is then explained in Section 3. Section 4 provides a description of the data. Section 5 presents the actual results and discussions. Finally, Section 6 provides policy conclusions and recommendations.

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