Perspective Chapter: The Impact of Human Capital Investment on Economic Growth – Arab Countries Evidence from 2001 to 2021

Abstract

The study aimed to measure the impact of investment in human capital on economic growth in a group of Arab countries during the period (2001 to 2021) using static panel models. We used a set of independent variables to express the investment variable in human capital for Arab countries represented in the enrollment ratio in the primary stage, secondary school enrollment ratio, higher education enrollment ratio, life expectancy rate, and education expenditure. Also, we used per capita GDP as a variable representing economic growth. The study found a set of results, the most important of which is the absence of the impact of the enrollment rate in primary and secondary education on the per capita share of GDP. The study also found the presence of a significant and negative impact of the enrollment rate in higher education on the per capita share of GDP and in addition to a positive morale effect on spending on employment and education, life expectancy on per capita GDP.

1. Introduction

In recent economic literature, the importance of human capital in a country’s economic development has been emphasized. Countries and international organizations who believe in such a role have lately rekindled their interest in supporting investment in human capital to raise living standards by increasing productivity, cutting unemployment, and alleviating poverty.

Over the last decade, the Arab region’s exceptional economic expansion has not corresponded with similarly robust labor and human resource development, generating apparent worries about the region’s ability to sustain and balance growth [1, 2]. According to the results of the survey, just 38% of Arab CEOs feel there is an adequate supply of skilled indigenous labor, implying a strong reliance on expatriate recruiting. The Gulf region is the most affected by the shortage of trained labor, with a 91% dependency on expatriates. Furthermore, as Gulf CEOs have pointed out, the quality and productivity of expatriates are significantly better than that of the indigenous labor at all levels of management [3, 4].

The value of human capital may be seen in the total effects on individuals and macroeconomics. Individually, education and training, as one of the primary instruments for accumulating knowledge and practical experience, are among the most essential variables in increasing one’s earnings [5, 6].

For example, using statistical surveys, the “Mincer” model [7] was used in various studies to measure the return on education in different nations. This research showed that there is a positive association between income and educational attainment.

At the macroeconomic level, research that used macroeconomic models revealed the relevance of human capital in fostering long-term growth. In this context, the notion of human accumulation of capital was viewed as a key driver of economic progress and gross national product [8, 9].

As a result, the World Bank created a human capital initiative in 2017 that brought together governments worldwide to boost human capital investment and close gaps in this field. Other organizations, such as the World Economic Forum and United Nations agencies, have also recognized the importance of human capital and are working to develop a methodology for measuring it [10, 11, 12].

Moreover, the link between human capital and economic development takes time to build [13, 14]. In this way, all theories and models emphasize the beneficial benefits of human capital on long-run income per capita growth, which is ensured, in part, by increasing economic productivity [15].

Productivity is not everything, as Krugman [16] said, but it is practically everything in the long term. The ability of a country to enhance its quality of life over time is nearly completely determined by its ability to increase production per worker.

As a result, productivity is seen to be the most essential component in long-term economic growth. Furthermore, one of the most contentious issues among economists is the direction of causation between several macroeconomic variables. Knowing which way causation runs between two economic variables aids policymakers in making accurate and efficient decisions about such economic aggregates. Similarly, the purpose of this research is to determine the direction of causation between human capital and economic growth.

Given the global economic transformations that affect all countries of the world and that have brought about radical changes in many economic aspects, many countries seek to adapt and adapt to global developments because of their repercussions on their economies and to find solutions and alternatives to that; as these countries seek to introduce new concepts to control their economic conditions and achieve economic stability, economic growth is one of the most important indicators that reflect the economic situation of countries, which is used to compare among themselves and on the basis of which they are classified into developing and developed countries, in addition to being a tool in the hands of economic decision-makers through which solutions are developed to address imbalances in a timely manner [17].

In addition, the world has witnessed great growth in terms of awareness of the value of the human being as a goal and a means in the system of economic development, and the path to positive integration in the system of advanced economies has become subject to what can be achieved and achieved. It plays an important and pivotal role in achieving it.

In light of the new world order and economic developments at the global, regional, and local levels, and their repercussions on the Arab region [18], it has become necessary for Arab countries to invest in the human element and give it great importance through education, training, and qualification to form a pillar of their economies, and this is what we will try to identify through our study, through which we seek to measure the impact of investment in human capital on the economic growth of a group of Arab countries during the period (2001–2021) and to know the importance of investment in human capital in achieving economic growth in Arab countries [19].

The data were collected from multiple sources such as the Arab Monetary Fund, the World Bank, the International Monetary Fund, and the World Economic Forum.

1.1 Hypotheses of the study

To answer the sub-questions, we formulated the following hypotheses:

H1: Expenditure on developing the capabilities and skills of the human element that can increase its productivity in later periods;

H2: The theory of endogenous growth is based on dividing capital into two categories: material and human.

H3: There is a significant and positive impact of the enrollment rate in the various educational stages on economic growth in Arab countries.

1.2 The importance of the study

• The importance of investing in human capital in various countries of the world, through all their efforts to preserve and develop capital human.

• The need for Arab countries to invest in human capital, considering it one of the most important sources of economic growth, by reconsidering the programs and policies used in the educational and health system and other efforts aimed at developing the human element.

1.3 The objectives of the study

Through this study, we try to know and explore:

• The role of investment in human capital in achieving economic growth in Arab countries by shedding light on the topic from the theoretical side.

• In addition, trying to measure the impact of investment in human capital on the economic growth of a group of Arab countries during the period (2001 to 2021).

2. Literature reviews

2.1 Theoretical literature for investing in human capital and economic growth

2.1.1 A conceptual approach to investing in human capital

There are many definitions of the concept of investment in the human element, as there are many definitions by the number of economists who were interested in this topic and dealt with research and analysis, because this topic has many economic and noneconomic dimensions in which there are many different points of view, as the United Nations defined investment as total capital formation the fixed expenditure on the acquisition of new capital goods in addition to the renewals and improvements that take place on capital goods only, but also on the acquisition of documents and financial assets [20].

Furthermore, the concept of human capital is characterized by strong interlinkages with many other important concepts such as knowledge capital, social capital, and human development, but it is distinguished from them in that it focuses on the human element [21, 22].

UNICEF defined it as the stock owned by the state of the healthy population efficient and productive learners, which is a key factor in estimating their potential in terms of economic growth and the promotion of human development.

Al-Hanawi defined investment in human capital as spending on a person to increase his production skills and knowledge and thus increase the income that they can obtain in the coming periods, as Abu Ragheef and al-Aqili define it as spending on developing human capabilities, skills, and talents in a way that enables them to increase their productivity [23, 24, 25].

2.2 Three basic elements of the human capital

• Competencies: These are the set of knowledge, attitudes, behaviors, and behaviors derived from the experience necessary for a particular professional practice;

• Experiences and Experiences: These are the various public and practical experiences and expertise gained through practising the profession.

• Knowledge and Qualifications: These are the various information accumulated through training and education.

2.3 Theoretical framework for economic growth

Definition of economic growth: Opinions differed and varied in defining a comprehensive definition of economic growth that includes all its aspects. The most important of these opinions are as follows:

John Revoir defines economic growth as the gradual transformation of the economy through an increase in production and welfare so that the situation that the economy reaches is in one direction, which is the increase in economic welfare.

Simon Kuznets defines economic growth as the rise in the share of the individual or the labor component’s share of the volume of output, as the increase in the volume of output is often accompanied by a rise in the size of the population, on the per capita index of the volume of output.

Raymond Baran sees economic growth as “the increase in the available wealth and population,” while François Perot sees growth as “the increase that occurs over a period of several long periods of time for a positive indicator in a country.”

2.4 Types of economic growth

There are different types of economic growth such as:

• Expanded economic growth: This growth is represented by the fact that the increase in income takes place at the same rate as the increase in the population.

• Intensive economic growth: This type is represented in the fact that income growth exceeds population growth, resulting in a rise in per capita income and the passage from expanded growth to intensive growth, and social conditions improve.

• Automatic growth: This growth is represented by the continuous increase in real national income at a rate that exceeds the rate of population growth as a result of the interaction of economic variables in society in an automatic manner without resorting to national planning to achieve it, and this type of growth is characterized by slow and the possibility of being exposed to violent fluctuations.

• Planned growth: It is that which occurs as a result of the planning process and the intervention of the state to push the economic variables toward growth at a rapid rate, so the effectiveness of this growth is closely related to the realism of the drawn plans and strategies, the effectiveness of implementation and follow-up to their achievement, and the flexibility of the policies followed.

• Transient growth: It occurs as a result of the presence of emergency factors that are usually external and disappears with their demise, and this type of growth does not have the character of continuity, and this growth has been known in some developing countries as a result of favorable developments in their foreign trade.

2.5 Theoretical models of economic growth

Many economic theories have been concerned with the study of economic growth, and the most important of which are as follows:

• Classical economic growth theory: It is one of the most important theories concerned itself with the study of economic growth and was developed by the economist Ricardo, who relied on the idea of increasing production by paying attention to the study of the factors affecting it, namely capital and work. This contributed to an increase in the rate of production, which leads to a high rate of economic growth [26, 27, 28].

• The neoclassical theory of economic growth: This theory is based on the possibility of continued economic growth without economic stagnation, because the growth of an economy is an interconnected, integrated, and compatible process with a mutually positive effect, whereby the growth of a particular sector pushes other sectors to grow, and economic growth depends on the number of factors of production available in society; in addition, as for the labor component, we find the theory between population variables and the size of the labor force, noting the importance of the commensurate increase in the population or in the labor force with the volume of available natural resources.

• Internal economic growth theory models: The internal growth theory establishes the positive relationship between international trade and long-term economic growth and development and benefits flow from research and development.

2.6 Applied literature for investing in human capital on economic growth

In the following, the most important previous studies that dealt with the subject of the study will be presented:

Human capital and economic development [29] in the Nigerian experience: this study aimed to measure the relationship between investment in human capital and economic growth in the state of Nigeria during the period 1982 to 2011, primary education enrollment rate, intermediate education enrollment rate, and higher education enrollment rate, in addition to the GDP variable to express economic growth.

After conducting the Johansson test and estimating the model, it was found that there is a long-term relationship between investment in human capital and economic growth, in addition to a positive significant effect on all study variables except for government spending on education and enrollment rates in primary education [30, 31].

Investment in human capital and its impact on economic growth [32] in the case of Algeria from 1970 to 2011: this study aimed to measure the impact of investment in human capital on economic growth in Algeria during the period 1970 to 2011 by measuring the contribution of a group of educational system indicators to express the investment variable in human capital represented by the number of people enrolled in different educational stages, public spending on national education [33], and outputs university education, as it was relied on the growth of real gross product to express the economic growth variable, where the model was estimated using the totally weighted least squares method (FM and OLS), and the study found a positive effect of the educational system indicators on the growth of the real gross product [29, 34].

The impact of investment in human capital on economic growth in the Syrian Republic from 2000 to 2010 [35]: the aim of the study is to measure the effect of capital investment on economic growth in Syria during the period 2000 to 2010, using the Cobb-Douglas model and the neoclassical growth models. A set of variables were used to express the investment variable in human capital represented in the growth of the labor force, the growth of the number of students registered in the different stages, the education budget percentage of the general budget in addition to the GDP, and variable to express the economic growth variable. The study found a statistically significant effect of the growth rate of the operating category and the proportion of the general budget on the growth rate of GDP, but there is no statistically significant effect of the growth rate of the number of students enrolled in the different educational stages on the rate of growth of local GDP in Syria.

The impact of education on economic growth in the case of India from 1975 to 2016 [29]: this study aimed to determine the relationship between education and economic growth in India during the period 1975 to 2016 using an autoregressive vector model.

Then, model estimation and procedures for the co-integration methodology and the Granger causality test have been reached in the study. The study indicates the absence of the effect of the enrollment rate in primary and intermediate education on economic growth, in addition to the presence of a strong impact of the enrollment rate in higher education on economic growth.

2.7 Literature review on human capital and long-run economic growth

Human capital has several meanings that change throughout time. The Organization for Economic Cooperation and Development’s definition is one that most scholars, international organizations, and institutions use (OECD). Human capital, according to the OECD [29], is described as “individual knowledge, skills, abilities, and traits that promote the production of personal, societal, and economic well-being.”

Similarly, the World Bank [36] uses a virtually identical definition of human capital: knowledge, skills, and health capacities that individuals acquire throughout their lifetimes, allowing them to reach their full potential as productive members of society¹. The World Bank definition differs from the OECD definition in that it considers the health factor and relates human capital attributes to potential productivity.

Furthermore, there is much study on technology diffusion in which human capital is a critical aspect. Many pioneering scholars, like Nelson and Phelps [37], Grossman and Helpman [38], and Barro and Sala-I-Martin [39] have produced theories of human capital.

The empirical research on human capital and its impacts on economic growth is broad and difficult to list, although there are a few notable publications that are frequently quoted, including Borensztein et al. [40] and Benhabib and Spiegel [41]. Human capital impacts are primarily taken into account in endogenous growth models, both theoretically and experimentally.

With this class of models, the pioneering contributions in this modeling domain grew, particularly by Romer [42] and Lucas [43]. These models were introduced as an alternative to Solow’s and Swan’s neoclassical growth models (Solow-Swan model).

The focus on the accumulation of information and its endogenization, whether this knowledge is reflected in the form of technical advancement, ideas, or human capital, is one of the main characteristics of such models.

As an alternative to the competing neoclassical (Solow-Swan model), endogenous growth theory models were designed to endogenize the role of externalities and their contribution to understanding the persistence of the long-run per capita growth rate [29, 44]².

The latter regards such externalities, or what is supposed to be technological development, as exogenous. Indeed, in the Solow-Swan model, exogenous components dictate the steady-state growth rate, and the macroeconomic aggregates (capital, output, and consumption) expand at a constant exogenous rate of population growth, keeping the per capita corresponding numbers constant and therefore not growing [45].

As a result, the key substantive implications concerning the long term, according to Barro and Sala-I-Martin [39], are that steady-state growth rates are independent of the saving rate or the degree of technology, because of diminishing returns, a model without technological development, such as the Solow-Swan model, predicts that economies would converge to a stable state with zero per capita growth to scale.

The total factor productivity (TFP) metric assessed the percentage of increase explained by technical advancement to be higher than 50%, as reported by Jones and Romer [46], or range between 50 and 70%, as proposed by [47].

The model proved to be outmoded as well [44]. In comparison to the neoclassical Solow-Swan model, this is an “empirical” argument supporting the strength of endogenous growth models. The latter, with its conventional framework, was unable to explain the ongoing nonzero per capita growth rates in many industrialized nations and was thus chastised for overlooking long-run growth factors.

As a result, one of the most important goals of the pioneers of endogenous growth theory is to include other long-run growth factors. This involves expanding the notion of capital to include additional factors as production inputs such as human capital [8, 43], creativity, ideas, and knowledge while avoiding the premise of declining return to scale [38, 48, 49].

As a result, according to Barro and Sala-I-Martin [39], having human capital as an explicit factor of production relaxes the assumption of diminishing returns to a broad concept of capital (as in classical models) and leads to long-term per capita growth in the absence of exogenous technology, thus playing the role of such technology³.

Since then, numerous sources of growth that are directly or indirectly connected to human skills, like creativity, ideas, human capital, and R&D expenditures, have been increasingly incorporated into the production function as inputs [46, 50].

The importance of human capital, which is heavily stressed in several types of endogenous growth theory, has numerous policy consequences [51, 52, 53, 54]. Indeed, public spending policies cover a wide range of expenditures and transfers that have a direct influence on human capital, and these policies are crucial in the development and quality of human capital. These policies address a wide range of topics in health, education, and research (Research and Development, R&D).

Some of these expenditure items may have externalities that influence the productivity of other sectors that produce information, ideas, and human capital. Many economists used endogenous growth models to analyze the function of human capital in interacting with other forms of public expenditures (both flows and stocks) [55, 56, 57].

The direction of causation between various macroeconomic variables is another key question that has sparked debate among economists. Knowing which way causation runs between two economic variables aids policymakers in enacting precise and efficient policies on such aggregates. Similarly, the purpose of this research is to determine the direction of causation between human capital and economic growth. Indeed, the major study developed a consensus regarding the influence of human capital on countries’ GDP, leading to the conclusion that human capital drives economic growth.

GDP, on the other hand, plays an essential role in increasing the quantity and quality of human capital. Higher GDP is more likely to devote resources to sectors that directly influence human capital, such as education⁴ and health, as assessed by government spending in these areas [59]. Other expenditures and investments in capacity building and training, as well as research and development⁵, are expected to support human capital levels and quality. In conclusion, GDP is expected to have direct feedback effects on human capital, resulting in a reversal of causality.

Reverse causality is a phenomenon that throws econometric calculations for a loop. Furthermore, GDP acts as a passthrough for the impacts of various economic and institutional policies on GDP.

Indeed, human capital is influenced by a variety of external elements (geography, institutions, and culture), as well as economic and institutional policies, as outlined by Chang-Tai and Klenow [47] in Figure 1.

Figure 1.

The set of external factors affecting human capital. Source: Prepared and compiled by the author based on the outputs of [46].

3. Methods and data sources

3.1 The method and tools used

Relying on an econometric model in order to determine the impact of investment in human capital on economic growth in the Arab countries which is represented by the static panel model is the appropriate model for analyzing the study data.

3.2 Study sample

The study sample consists of 11 Arab countries, namely Algeria, Tunisia, Morocco, Mauritania, Bahrain, Egypt, Palestine, Jordan, Oman, Kuwait, and Qatar, where these Arab countries were selected according to the availability of data for the study variables during the period 2001 to 2021, as shown in Table 1.

Arab countries sample
Algeria	Morocco
Tunisia	Mauritania
Bahrain	Egypt
Palestine	Jordan
Oman	Kuwait
Qatar	—

Table 1.

Samples of Arab countries.

Source: Prepared and compiled by the author.

3.3 Study variables

Based on previous studies and on the availability of data for countries, during the study period from 2001 to 2021, we used a set of variables, which can be defined as follows:

Dependent variable (GDP-P): Represented by the per capita GDP at current prices in US dollars to express economic growth.

Independent variables: A set of variables were relied upon to express the investment in human capital, which are as follows:

PRM: the percentage of enrollment in the primary stage (out of total education);

SEC: the percentage of secondary school enrollment (out of total education);

TER: the percentage of enrollment in higher education (out of total education);

LER: total life expectancy at birth (total in years);

GEN: spending on education (in current US dollars).

4. Results and discussion

We will first present the results of the study, based on the analysis description of the variable and the correlation of the variables through the correlation matrix that shows the extent of the correlation of the variables between them, and then we present the most important results of estimating the panel model and the differentiation tests.

Descriptive analysis of variables: The descriptive analysis of the variables represented in Table 2 shows the following:

	GDP-P	PRM	SEC	TER	LER	GEN
Arithmetic mean	11726.48	99.26444	77.82675	26.27317	79.09375	2.74E+07
Mediator	3899.307	99.77680	76.8554	22.27926	75.09200	1.76E+09
Highest value	97068.11	126.3591	116.8016	62.68352	79.98300	1.87E+10
Lowest value	496.7562	48.16188	15.07116	2.896840	63.86600	36,254,822
Standard deviation	19050.07	14.75140	26.60266	13.176260	6.341174	2.80E+07

Table 2.

Descriptive statistics for the variables.

Source: Prepared and compiled by the author based on the outputs of Eviews10.

The per capita GDP in the Arab countries has reached its lowest levels during the period 2001 to 2021, and it reached a value of 496.7562 US dollars in Mauritania in 2002, while the highest level was recorded at 97068.11 in the State of Qatar in 2012.

The highest value of the enrollment rate at the primary level was recorded 126.3591 out of the total education in Algeria in 2013, which indicates the spread of awareness and desire for education, in addition to free education, which gave citizens an opportunity to enroll in education. Enrollment in the secondary stage of the total education was recorded in the State of Kuwait at 116.8016 in 2005, and the lowest value recorded was estimated at 15.07116 in Mauritania in 2002, while the highest value of the percentage of enrollment in higher education was recorded in the State of Kuwait at 62.68352 in 2016, which indicates the development of its infrastructure and infrastructure. In addition to the value of the granted university degree and its compatibility with the labor market, the lowest value was recorded in Mauritania, where it reached 2.896840 in 2002.

Expenditure on education recorded its highest level in Egypt with a value of 1.87E+10 US dollars in 2016, while the lowest value was recorded in Mauritania with a value of 36,254,822 US dollars in 2008.

The highest value of life expectancy was recorded in Qatar in 2017, which reflects the good living conditions in this country, while the lowest value was recorded in Mauritania in 2001.

The lowest value for the standard deviation was for the life expectancy variable out of the total years, which amounted to 6.341174, which indicates that the values of the latter are more homogeneous from one country to another if compared to other study variables.

The matrix of correlations between the model variables represented in Table 3 shows that there is a very weak correlation of per capita GDP with the enrollment rate in the primary stage of the total education amounted to 0.13252, and it has a medium direct correlation with the secondary school enrollment rate of the total education amounted to 0.481850, while A very weak direct correlation with the percentage of enrollment in higher education out of the total education, which amounted to 0.084883, and it has a medium direct correlation with the average life expectancy that reached 0.560323, and in the end, we find that it has a very weak correlation with the percentage of expenditure on education which amounted to 0.055834.

	GDP-P	PRM	SEC	TER	LER	GEN
GDP-P	1.000000	0.13252	0.481850	0.084883	0.560323	0.055834
PRM	0.13252	1.000000	0.462444	0.315635	0.467354	0.333871
SEC	0.481850	0.462444	1.000000	0.668394	0.775842	0.182905
TER	0.084883	0.315635	0.668394	1.000000	0.506044	0.352448
LER	0.560323	0.467354	0.775842	0.506044	1.000000	0.189500
GEN	0.055834	0.333871	0.182905	0.352448	0.189500	1.000000

Table 3.

Matrix of correlations between model variables.

Source: Prepared and compiled by the author based on the outputs of Eviews10 (matrix of correlations between variables).

5. Empirical models

5.1 Estimating panel models

In order to measure the impact of investment in human capital on economic growth, the three models of static panel, namely aggregation regression model, stochastic regression model, and fixed-effects model, were estimated as shown in Table 4.

Variables	Aggregate regression model	Fixed-effects model	Random-effects model
Constant	−106475.8	−134552.1	−140804.1
PRM	−290.6809	−95.50500	−109.9072
SEC	339.3213	16.85871	37.83612
TER	−655.8832	−313.7323	−333.4070
LER	1871.065	2194.663	2288.077
GEN	7.00E-07	1.41E-06	1.32E-06
R-square	R^2 = 0.450127	R^2 = 0.761412	R^2 = 0.242830
Adjusted R-square	0.440378	0.749177	0.229405
S.E. of Regression	12784.72	8559.092	8594.715
F-statistic	46.16922	62.23086	18.08794
Prob. F-statistic	0.000000	0.000000	0.000000

Table 4.

Results of estimating panel models.

Source: Prepared and compiled by the author based on the outputs of Eviews10.

The model prepared as a basis for the estimate can be formulated as follows:

$$\mathit{GDP}-P_{\mathit{it}}={\alpha }_0+{\alpha }_1\mathit{\text{PRMit}}+{\alpha }_2\mathit{\text{SECit}}+{\alpha }_3\mathit{TER}+{\alpha }_4\mathit{\text{GENit}}+{\epsilon }_{\mathit{it}}$$E1

where $\mathit{\alpha }$: the parameters of the models; ${\mathit{\epsilon }}_{\mathit{it}}$: random error limit; 29; t = 1: the time period from 2001 to 2021;11; I = 1: the syllables that are represented by a group of 11 Arab countries;

Including the number of observations: 290 = 29 * 11 = n = N * T.

5.2 Comparison between estimated models

To compare the three models, we use the following tests:

Fisher’s test: for differentiation between the cumulative regression models and the effects constant. Fisher’s constrained test is used to compare the two models of cumulative regression and fixed effects and depends on the following two hypotheses:

The null hypothesis: a cumulative regression model is appropriate.

Alternative hypothesis: A fixed-effects model is appropriate.

Where the value of the constrained (Fisher) is calculated according to the following relationship:

$$\mathbf{F}\left(\mathbf{N}-1,\mathbf{NT}-\mathbf{N}-\mathbf{k}\right)=\frac{\frac{\left({\mathbf{R}}_{\mathbf{FEM}}^2-{\mathbf{R}}_{\mathbf{PRM}}^2\right)}{\left(\mathbf{N}-1\right)}}{\left(1-\left({\mathbf{R}}_{\mathbf{FEM}}^2\right)/\left(\mathbf{NT}-\mathbf{N}-\mathbf{k}\right)\right)}$$E2

where R²FEM: fixed-effects model parameter; R²PRM: aggregate regression model coefficient of determination; K: estimated number of parameters; N: number of sample members; NT: the number of views.

Fisher scheduled value: (5–11-1290–11) F (9,275) = 1.75,5%) = Ft.

Fisher calculated value: 17.297 = ((275)/(0.761412–91)) /) /) (0.450127) (0.761412)) = F_c.

5.3 Comparison of the two values

Since the calculated value of Fisher is greater than the tabulated value, we accept the alternative hypothesis, which states that the random-effects model is appropriate, as shown in Table 5.

Test type	Test value	Probability value
Husman test	7.381059	0.1938

Table 5.

Husman test results.

Source: Prepared and compiled by the author based on the outputs of Eviews10.

5.4 Comparison between fixed- and random-effects models

To compare the two models of fixed effects and random effects, we use Husman test based on the following two hypotheses:

The null hypothesis: The random-effects model is appropriate.

Alternative hypothesis: A fixed-effects model is appropriate.

As per Table 5, the probability value reached 0.1938, which is greater than 5%, and we accept the null hypothesis, meaning that the random-effects model is appropriate.

5.5 Discussion

There is no doubt that human capital is important for development, and its beneficial impact on economic growth, which this study confirms, has been demonstrated in the empirical literature using many methodologies and variables to quantify human capital [60, 61, 62, 63]. However, due to the disparities in methodologies and effects, it is impossible to compare such impacts in terms of size in the empirical literature.

Indeed, a researcher working on the same variable may not employ the same estimating method or model, and those working on the same approaches could have utilized various measures of human capital. As a result, there are usually comparisons of samples and nations within the same research rather than with other studies in many different studies covering similar issues, which we implemented in our work by using two benchmark samples of Asian and OECD countries. Nonetheless, certain uncommon studies might be studied to compare our findings with their conclusions, which appear to be in agreement with ours.

Furthermore, in terms of returns to scale, our findings are consistent with what is predicted and demonstrated in the theory of endogenous growth models, which shows that taking human capital into account leads to higher returns to scale see the literature section ([8, 43, 55]; and many others). Returns to scale are also shown to be impacted by a country’s degree of affluence, with higher-income nations seeing stronger returns to scale in the presence of qualified and competent human resources.

Moreover, we should mention several issues with data creation that might affect the quality of any estimations in the literature, including ours. The first difficulty involves constructing the human capital variable. Thus, as described by the human capital definitions, evaluating human capital mostly entails measuring embedded soft skills and health capacities. Human capital has been measured using a variety of approaches. We utilized the one we considered, which involved the quantity of human capital adjusted for quality with sufficient observations.

The World Bank’s recent work to develop the human capital index [29] demonstrates an innovative methodology that links human capital to factors other than the rate of return on education, such as pupil health, which is considered the foundation of future human capital and expected labor productivity [64]. However, due to the small number of data (the research only began in 2017), we decided not to include this metric in our estimating technique.

As a result, in addition to investing in human capital, Arab nations are urged to contribute to improving human capital statistics by participating in international initiatives that specifically evaluate human capital quality.

Moreover, the physical capital stock is a computed variable that is commonly approached using the recurrent perpetual inventory equation, which is one of the most widely used approaches. The current stock is compared to the prior one, less the depreciated past stock, and the flow of current investments is added to the calculation. Some assumptions are required for such a recurring equation, notably for the initial point in the time series and the depreciation rate. The quality of the derived capital stock is determined by the correctness of these assumptions.

However, this is a universal issue and difficulty that all empirical literature faces, and it has the potential to change genuine elasticities values, necessitating greater caution in interpreting scientific works as well as increased attempts to improve the quality of the empirical literature.

By following the methodology of the static panel model, which corresponds to the nature of the study, three types of models were estimated, and after conducting comparison tests, it was found that the best model for the study is the random-effects model. The Arabic chosen during the study period is as follows:

• The study found the absence of the effect of both the primary school enrollment rate and the secondary school enrollment ratio of total education on the per capita GDP, which indicates that this category is not economically active and is not considered among the labor force to participate in economic growth.

• There is a significant and negative impact on the rate of enrollment in higher education and per capita GDP, which contradicts the economic theory, which states that there is a positive impact of enrollment in higher education and per capita GDP; however, it confirms the high unemployment rates among the categories of higher education graduates in addition to the lack of possibilities to translate their skills into adding value, which negatively affects the economic growth of Arab countries.

• There is a significant and positive impact of life expectancy at birth and spending on education in the Arab countries on the per capita GDP, which indicates the importance of these two variables in increasing the per capita GDP.

6. Conclusions and policy implications

Through this study entitled “The impact of investment in human capital on economic growth a benchmarking study for a group of Arab countries during the period 2001 to 2021,” we tried to measure the impact of investment in human capital on economic growth, and the study reached a set of results, the most important of which are given in the following sections.

Investment in human capital contributes to improving its productivity, which increases the benefits and benefits resulting from its work. In addition, economic growth in the Arab countries under study is negatively and morally related to the rate of enrollment in higher education, which contradicts the economic theory and reflects the deteriorating state of the higher education situation in Arab countries, and also economic growth in Arab countries during the study period is positively and morally linked with spending on education and life expectancy at birth.

Human capital is frequently viewed as a source of long-term economic growth when it is included in the endogenous growth hypothesis. It is frequently cited as one of the most important drivers of long-run growth that explains development variations among countries. For a sample of 11 Arab nations, this article showed the significant positive impact of human capital on economic growth; nevertheless, the sample of Arab countries is not widely behind in terms of human capital contribution to GDP growth.

Furthermore, this study also looked at the direction of causation between GDP and human capital, determining that while the former causes the latter, the latter has feedback effects on the former. Obviously, this has significant policy consequences. The bidirectional causation between human capital and GDP produces a feedback loop.

As a result, enhancing human capital’s contribution to long-term growth necessitates investments in critical areas that directly support human capital. Education, vocational training, health care, and research and development for creative ideas and innovations are among these areas, which have a greater impact on employees’ long-term output.

As a result, governments should prioritize such industries in their spending programs, which is likely to sharpen workers’ abilities and increase productivity, resulting in positive GDP feedback. Furthermore, technological advancements are fast-changing and modifying our reality, affecting our way of life in a worldwide competitive world.

As a result, in order to compete and succeed in such a changing environment, governments should invest in their people by improving their skills and potential knowledge, which will, in turn, lead to significant economic and societal advantages in the long term.

7. Policy recommendations

Through the results obtained, a set of recommendations was proposed which are represented as:

• The necessity of introducing amendments to the educational system of Arab countries at the level of curricula and structures.

• Attention to primary education in Arab countries is considered the first rule in which the positive energy of excellence must be inculcated in light of the great differences when compared to developed countries.

• Develop policies and future plans to reduce the Arab brain drain and provide the necessary means to work within an atmosphere that encourages them to stay to embody their skills in the service of their countries.

• Cooperation among Arab countries and the exchange of experiences to develop the human element, in addition to drawing on the experiences of the pioneering countries in the field.

Acknowledgments

The author extends their appreciation for their support for scientific research at the Palestine Economic Policy Research Institute (MAS) in Palestine to support this research and encourage the author in particular. The author also sends a special thanks and a great appreciation to the jury staff Reviewers and to the Editorial Board at IntechOpen.

Conflict of interest

The author has declared that no competing interests exist.

Author’s contribution

The Sole Author Designed, Analyzed, Interpreted and Prepared the Chapter.

Data availability statement

The data and materials that support the findings of this study are available from the corresponding author upon request. Datasets are derived from public resources and made available to the authors. Data analyzed in this study were a reanalysis of existing data, which are openly available at locations cited in the reference section.

JEL classification codes

G11, I2, I1, J3, J8, J24, N3, O47.