Does years of schooling matter for economic growth at different development levels? New evidence from China

In recent years several studies have emphasized the importance of human capital for economic development. However, many of these studies have not incorporated the different stages of development to which the economies are found. In this sense, different degrees of proximity to the technological frontier induce the results of economic policy, so that the global aspects affecting the performance of economies. For this, our research examined the impacts of education policy on the rate of technological progress and the economic growth of countries according to the degree of proximity to the frontier. The most backward economies are demanding more on structural investments in relation to strategic investments in ST&I. In the same direction, other studies such as Vandenbussche, Aghion and Megh (2006) and For this, we constructed a Schumpeterian growth model incorporating on productivity, two sources of improvements adopted by firms: the components of imitation and innovation. The stock of skilled labor is allocated in the innovation activities by firms. Unlike, the stock of labor is unskilled allocated to departments for implementation of management standards and planning, ie, imitation strategies by firms. Each monopolist entrepreneur seeks to maximize its utility function that is defined by expected consumption less costs of hiring skilled labor force and unskilled. Under conditions of maximization are built two demand functions for each factor. The demand of the monopolist entrepreneur in each sector of intermediate inputs is divided in hiring skilled labor and unskilled. The demand function for factor unskilled depends positively on the distance to frontier , ie, to the backward economies, the trade-off between ST & I and investments on technological opportunities (basic infrastructure), becomes the more significant as the distance increases. For the most advanced sectors, the demand for skilled labor can offer a enhanced-growth in relation to the most backward sectors. To measure the stock of skilled and unskilled, were used average years of schooling within each education level: unskilled labor -average years of schooling in primary and secondary level; skilled labor -the average years of schooling in higher education or tertiary level. This database is provided by Barro and Lee (2000) and is built considering the five years between 1960-2000. The estimated model consisted of the xx regression of ln(TFP), ln(GDP per worker) and the growth rates of GDP per worker with the years of schooling lagged (t-1) and the interaction between schooling and the coefficient of technological gap lagged (t-1). The regressions were estimated with panel data using various computational methods of estimation. Early estimates show that years of schooling of the primary and secondary education contribute to the accumulation of GDP per worker and TFP when the economy is further away from the technological frontier. The estimated parameters showed statistical significance and expected signs with the hypothesis of the investigation. Since the schooling years of higher education (tertiary) have an increased effect of GDP per worker and TFP when the economy approaches the frontier.

The paper investigates the relationship between human capital and economic growth in Morocco during the period from 1965 to 2015. In order to test this relationship we estimated a growth function using firstly the Johansen multivariate cointegration test and the Granger causality test. Secondly, we used the method of the Bayesian Model Averaging (BMA) that takes into consideration the uncertainty related to the specification of the model studied. In the theoretical literature, the difficulty of measuring human capital is often stressed. In order to overcome this problem, we use four proxies of human capital: first, we employ the average years of schooling. Second, we use the index of the gap in life expectancy between Morocco and developed countries. Third, we integrate the qualitative aspects of education and health by constructing two composite indicators of human capital using Principal Component Analysis (PCA) method.The main results of regression analysis confirm that in the specification of determinants of GDP per worker the average years of total schooling, the life expectancy index and the indicator of quality of health affect positively and significantly level of GDP per worker. However, in the specification of determinants of the growth of the GDP per worker, we found there is no proxy of human capital that affects significantly the growth of the GDP per worker.In addition, the results of Granger causality test show that only the indicator of quality of health that cause the GDP per worker. As well, these results show that the average years of total schooling and the indicator of quality of education cause the growth of GDP per worker. We suggest that the Moroccan authorities should make additional efforts to raise the level of quality of human capital especially in the health sector and increase the productivity of both public and private investment.

Introduction/Main Objectives: Education serves as a driving force for the transformation of society to break the cycle of poverty. This study examines the relationship between average years of schooling and per capita household expenditure in Kalimantan Tengah Province in 2020. Background Problems: The method of estimating a regression model that is assumed to follow a certain form of regression equation such as linear, quadratic and others is called parametric regression. However, researchers often encounter difficulties in determining the model specification through data distribution, so the method used is nonparametric regression. Novelty: This research uses a quantile-based approach to explore how the impact of education on per capita expenditure varies across different levels of household education. This provides a more nuanced understanding of the relationship, showing not just whether education matters, but how its influence changes at different levels of educational attainment. Research Methods: The relationship between average years of schooling and per capita household expenditure is modeled using a quantile regression model with the constrained B-Splines method. Finding/Results: Based on the established classification, it can be concluded that an increase in the average years of schooling among household members tends to have a greater impact on raising per capita expenditure.

The fiscal relation between central and local governments is one of the main institutional forms that have affected economic growth of China since its reform and opening up. This article examines its impact on China’s economic growth from the viewpoint of financial budgeting and further analyses the mechanism how economic growth and financial structure of local and central governments influence each other. This article describes the interaction of local and central fiscal entities in China throughout the whole period of its economic growth from 1978 till 2014. Dividing it into the first sub-period (1978–1992), the second (1993–2001) and the third (2002–2014), it explains peculiar features of the relationship between public finance and economic growth in China. In the first period (1978–1992) since the fiscal system of China was designed to strengthen the centralized budgetary control, local governments had to rely much on the extra-budgetary finances. They gained extra-budgetary income from their investment on township enterprises, which also generated economic growth on the local level. In 1993, facing the decline in GDP growth due to the squeeze of the extrabudgetary fund, central government loosened restrictions of the sale of land by local governments to raise extra-budgetary revenues. This provided the local government with new resources, and formed a new mechanism of “land finance” to promote economic growth. This mechanism opened the way to a bubble economy, particularly associated with the rise of land and housing prices, as well as the cost of China’s economy. Thus, the root cause of the present slowdown of China’s economy is not cyclical one, but the institutional structure, mainly the special local/central fiscal relationship and its interaction with economic growth.

This study explores the impact of individual internet usage, foreign direct investment, and average years of schooling on economic growth in the ASEAN region during the period 2014-2020. The panel regression analysis method was employed to analyze secondary data obtained from the World Bank and UNDP. The results of the fixed-effects regression model indicate that the variables of individual internet usage (IUI) and foreign direct investment (FDI) have a positive and significant impact on economic growth, while the average years of schooling (MYS) do not have a significant impact. These findings are consistent with previous research findings indicating that internet usage and foreign direct investment significantly contribute to economic growth in the region. However, the average years of schooling do not have a significant influence on economic growth in this study's context. The study shows that internet usage and foreign direct investment have a significantly positive impact on economic growth in ASEAN, while the average years of schooling do not have a significant effect. These findings imply that economic development policies in ASEAN should focus on enhancing technology infrastructure and investment environments, as well as reevaluating the education system.

This study seeks to examine the impact of educational variables, which are components of the GDI, on economic growth. The research aims to determine the extent of the influence of gender inequality in education, represented by the variables of average years of schooling and school expected rates, as well as the percentage of the population receiving higher education in West Java, and to analyze the achievements of gender equality in education in West Java during the 2019-2023 period. This research employs a quantitative data analysis technique using the Generalized Method of Moments (GMM), covering 27 regencies/cities in West Java Province. The data used in this study is secondary data collected from the West Java Central Statistics Agency for the period 2019-2023. The results of the study show that the ratio of average years of schooling and the ratio of higher education have a significant negative impact on per capita income. Meanwhile, the ratio of expected years of schooling has a positive but insignificant effect on per capita income. Additionally, the achievement of gender equality in West Java has reached 90% of the targeted goal. Therefore, achieving equal gender equality across all areas of West Java remains a challenge for the government to continue reducing the existing disparities.

Domestic violence is a social problem experienced by some married women. Victims of domestic violence can experience health and mental problems and even lose hope for the future. This research aims to prove the influence of average years of schooling, economic growth, poverty, and age at first marriage on domestic violence. The number of subjects studied was all provincial areas and national data (Indonesia). The type of quantitative data (cross section) was obtained from the Central Statistics Agency, and the profile of Indonesian women in 2021. The highest level of domestic violence was experienced by 12 provinces, 19 provinces in the medium category, and 4 other provinces in the low category. The results of statistical tests (path analysis) prove that poverty can increase domestic violence, while average years of schooling, economic growth and age at first marriage have the potential to reduce domestic violence. Average years of schooling has the highest influence, followed by poverty, age at first marriage, and economic growth on domestic violence. The Government's policy priority to reduce domestic violence is to implement a 12-year compulsory education program, in addition to poverty alleviation programs

This study aims to analyze the effect of education on economic growth in Indonesia using panel data on 34 provinces from 2019 to 2023. The method used is panel data regression analysis, with independent variables including literacy rate, average years of schooling, and government spending on education. The dependent variable in this study is gross regional domestic product. The results showed that literacy rate, average years of schooling and education spending simultaneously had a significant effect on economic growth in Indonesia. Furthermore, partially, the literacy rate variable has a significant negative effect on economic growth. While the average length of schooling and education expenditure variables have a negative effect on economic growth in Indonesia. This study provides evidence that investment in education can be a catalyst for economic growth, hence the government should continue to improve the quality and access to education as a long-term strategy for sustainable economic development.

This study examines the effect of entrepreneurial activity on economic growth in MENA countries. Following the endogenous growth model, we included human capital and technology spillover variables into the analysis. Due to limited data of entrepreneurship measures in MENA countries this study employed self-employment rate as a proxy. As the level of education increases, absorptive capacity and innovation capacity of the entrepreneurs’ increase. In order to adjust for human capital, the interaction variable of self-employment and average years of schooling are used. The fixed- effect panel regression estimates that the effect of self-employment on economic growth is negative in all specifications. However, the interaction estimate of self-employment and average years of schooling are positive and significant. Our results suggest that the driving force of entrepreneurship in MENA countries is also affected by the economic necessities. On the other hand, the level of education accelerates the effect of entrepreneurial activity on economic growth.

Economic growth can be an indicator that reflects how advanced and prosperous the condition of a region can be influenced by various aspects. This study attempts to analyze the determinants of economic growth in Southeast Sulawesi Province using the identified factors, which include: (1) poverty percentage, (2) population density per km2, (3) average years of schooling, and (4) life expectancy. The research used fixed effect model estimation with panel data of 17 districts/cities in Southeast Sulawesi during 2019-2023. Based on the results of the analysis, it was found that the percentage of poverty, population density, average years of schooling, and life expectancy (AHH) simultaneously and significantly affect economic growth in Southeast Sulawesi Province. Economic growth is significantly influenced by the percentage of poverty rate, average years of schooling, and life expectancy rate (AHH). Meanwhile, population density has no significant effect on economic growth in Southeast Sulawesi. The limitation of this study is that the independent variables in the study were only able to explain 16,7 percent. For future research, the determinants of economic growth in Southeast Sulawesi can be tested by adding other variables.

Every country strives to minimize the unemployment rate as much as possible. The Open Unemployment Rate in Banten Province, which has consistently been higher than the national average, has become a serious concern. This study aims to examine the influence of the labor force participation rate, economic growth, average years of schooling, and city minimum wage on the open unemployment rate in Banten Province during the 2017-2023 period. This research utilizes Eviews 12 software with a panel data approach, combining cross-sectional and time-series data over seven years, from 2017 to 2023. The method applied in this study is the Fixed Effect Model (FEM). The data analyzed in this study are secondary data obtained from the Central Statistics Agency (BPS) of Banten Province. The research findings indicate that the labor force participation rate, economic growth, and average years of schooling have a negative and significant effect on the open unemployment rate in eight districts/cities in Banten Province from 2017 to 2023. Conversely, the city minimum wage variable has a positive but insignificant effect. Additionally, the independent variables, namely the labor force participation rate, economic growth, average years of schooling, and city minimum wage, simultaneously have a significant effect on the dependent variable, which is the open unemployment rate in Banten Province during the 2017-2023 period, contributing 76.48% to the variation in the open unemployment rate in Banten Province.

BackgroundThe accurate measurement of educational attainment is of great importance for population research. Past studies measuring average years of schooling rely on strong assumptions to incorporate binned data. These assumptions, which we refer to as the standard duration method, have not been previously evaluated for bias or accuracy.MethodsWe assembled a database of 1,680 survey and census datasets, representing both binned and single-year education data. We developed two models that split bins of education into single year values. We evaluate our models, and compare them to the standard duration method, using out-of-sample predictive validity.ResultsOur results indicate that typical methods used to split bins of educational attainment introduce substantial error and bias into estimates of average years of schooling, as compared to new approaches. Globally, the standard duration method underestimates average years of schooling, with a median error of -0.47 years. This effect is especially pronounced in datasets with a smaller number of bins or higher true average attainment, leading to irregular error patterns between geographies and time periods. Both models we developed resulted in unbiased predictions of average years of schooling, with smaller average error than previous methods. We find that one approach using a metric of distance in space and time to identify training data, had the best performance, with a root mean squared error of mean attainment of 0.26 years, compared to 0.92 years for the standard duration algorithm.ConclusionsEducation is a key social indicator and its accurate estimation should be a population research priority. The use of a space-time distance bin-splitting model drastically improved the estimation of average years of schooling from binned education data. We provide a detailed description of how to use the method and recommend that future studies estimating educational attainment across time or geographies use a similar approach.

This study analyzes the effects of education level, unemployment rate, and health level on economic growth and poverty rates in Indonesia during the 2010–2023 period. Panel data from 33 provinces sourced from the Central Bureau of Statistics (BPS) were utilized. Education level was measured by average years of schooling, unemployment by the open unemployment rate, and health by life expectancy. Economic growth was assessed using Gross Regional Domestic Product (GRDP), and poverty was measured by the poverty line. Multiple linear regression analysis with two models was employed to examine direct and mediating effects. The results indicate that education and health levels have significant negative effects on poverty and a positive effect of education on economic growth. The unemployment rate showed no significant impact on either poverty or economic growth. Economic growth was not found to significantly mediate the relationship between independent variables and poverty. These findings provide important insights into the factors influencing poverty and economic growth in Indonesia, emphasizing the role of human capital development in regional economic policies.

This study examines the impact of trade openness and human capital on economic growth in China. The Autoregressive Distributed Lag cointegration model (ARDL) and CUSUM-of-squares test are used for data duration 1990-2023. Main results of the study show that trade openness and human capital are positively correlated with economic growth. Human capital is considered one of the most profitable assets in the country's economy, While, the country’s economy does not directly affect by trade openness. To enhance economic growth, the following suggestions can be made 1) reduce Trade Barriers like Lower tariffs, quotas, and other trade restrictions to facilitate international trade. 2) Increase funding for primary, secondary, and tertiary education to raise the average years of schooling and literacy rates. 3) Implement policies that improve ease of doing business, such as reducing bureaucratic red tape and enhancing legal protections for investors.

This study examines the impact of average years of schooling on the GDP per capita change rate in Malaysia, providing empirical evidence that highlights significant insights for educational policy and economic development strategies. Utilizing Vector Autoregressive (VAR) models and Granger causality tests, this paper explores the dynamic relationships between education expenditure and GDP growth within the Malaysian context. We find that the relationship between the increase in average years of schooling and the increase in GDP per capita is positive at first, then decreases rapidly, and then increases again. Specifically, our analysis of data from 1990 to 2020 demonstrates that enhanced educational attainment contributes significantly to the labor market’s skill level, which in turn boosts economic productivity and technological innovation capacity. The study challenges the conventional view that higher educational investments lead automatically to better economic outcomes and stresses the importance of educational quality alongside quantity. By providing a detailed variance decomposition, we find that changes in schooling years explain about 15% of the variations in GDP per capita growth rates. These results underscore the critical role of education in Malaysia’s economic modernization and suggest that policy interventions should not only increase educational investments but also enhance the quality of education to maximize economic returns. Future research should further investigate the causality and interactions between educational quality and economic growth to refine educational policies effectively.