Human Capital and Economic Growth
A Generalized Method of Moments Estimation

Le Viet Giap

BULLETIN OF SOCIAL SCIENCES AND HUMANITIESGraduate School
TOKYO INTERNATIONAL UNIVERSITY
No. 4 offprint September 20, 2019

Human Capital and Economic Growth
A Generalized Method of Moments Estimation
Le Viet Giap 1)

Abstract
This study aims to examine the relationship between human capital and economic growth.
Besides the direct impact of human capital endowments on economic growth, the study examines
the indirect effect of human capital on growth process through the interaction of human capital withthe economy’s industrial specialization. Following Barro and Sala-i-Martin (2003), the study extends
their cross-section analysis into large panel analysis using a dynamic panel GMM (Generalized Methodof Moments) technique, so-called system GMM. Results suggest that human capital and industrial
specialization are essential factors to promote a country’s economic growth. In addition, the indirect
impact of human capital on economic growth is negative. It implies that the mismatch between
structural change processes and the human capital endowments can make a negative impact on thegrowth process.
Keywords: Economic growth, Human capital, Structural change, System GMM
JEL Classification: J24; O11; O15; O47

human capital and economic growth from social

1. Introduction

scientists. Human capital is the economist’s term
representing knowledge and skills that a worker

In recent decades, there has been a growing

acquires through education, training, andnumber of empirical works regarding economic

experience. It includes the skills accumulated

growth topic. The analysis of factors of economic

not only in early childhood programs, grade

growth has been one of the fundamental subjects

school, and high school but also from collegeof extensive literature. Researchers worldwide

and on-the-job training for adults in the labor

have analyzed the effect of certain variables on

force. Workers with more education are more

economic growth. In fact, both the theoreticalproductive and innovative, therefore humanliterature and empirical studies have highlighted

capital has a direct effect on economic growth.

a number of economic, political, and social

It leads to making of new ideas and improving

determinants of economic growth. However, thisproductivity factors. In addition, human capital

study is going to focus on human capital for a

is a complex term that eschews a simple

number of reasons.

definition and measurement, and also a concept

Firstly, there is a long history of interests inthat has been investigated from a variety of̶ 32 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月

perspectives by social scientists. Finally, there

his fortune and likewise that of society”. 2) In

is an intuitive appeal to the proposition that

1897, Irving Fisher was the earliest formal

human capital accumulation ought to make ause of the term “human capital” in economics.

country richer in the long run. “Investment in

The late 1950s, this term became considerably

human capital is important for a country’s long-more popular. Studies focusing on the role ofrun economic success” (G.Mankiw, 2010).

human capital endowments in determining

However, previous studies mainly concen-

economic growth are numerous. In the study

trated on the direct effect of human capital onof Wilson (2004), an in-depth appraisal of theeconomic growth. There is a lack of studies

links between education and training in Europe

which analyze the impact of human capitaland its economic growth was found. The study

on economic growth through the process ofconcluded that the impact of investment inchanging the structure of economy. Therefore,

education and training on national economic

this study is going to figure out both thegrowth is positive and significant. Also, thedirect and indirect impacts of human capitalindirect effect of education on non-economic

on economic growth, taking into account thebenefits is also examined in the context of theinteraction of human capital with the country’s

technological, spatial, and environmental gains

industrial specialization.

to society.
Mankiw (2010) believes that investment

2. Literature review

in human capital is at least as necessary as
investment in physical capital for a country’s

2.1. Human capital

long-run economic success because human

Human capital refers to education, health,capital promotes the quality of labor force,on-the-job training, and the skills acquired

thus, increases its productivity. It is normal tothrough the interaction of people or societies.

consider that an additional school year will raise

The definition of human capital is “the skills

the productivity and efficiency of labor force,the labor force possesses and is regarded

and therefore their income will increase. In

as a resource or asset.” It encompasses the

addition, human capital is particularly importantnotion that there are investments in people

for economic growth since human capital(e.g., education, training, health, etc.) and thatconveys positive externalities. Externality is thethese investments increase an individual’s

impact of one person’s actions on the well-being

productivity. In more technical term, humanof other people. For example, a person who has

capital is defined as the aggregation of thea high-level education might create new ideas

innate abilities and the knowledge, and skills

about how to make the best goods and services.

that individuals acquire and develop throughout

If these ideas enter society’s pool of knowledge

their lifetime. As an economic concept, humanin which everyone can use them, then the ideas

capital is more than two centuries old. In 1776,

are an external benefit of education. It implies

Adam Smith mentioned the idea of humanthat the return to schooling for society is higher

capital in his fourth definition of capital - “Thecompared to the return for the individual.

acquisition of talents during education, study,

Besides, some empirical researchers foundor apprenticeship, costs a real expense, which

the evidence to show that differences in theis capital in person. Those talents are part ofaverage schooling of countries are related toHuman Capital and Economic Growth A Generalized Method of Moments Estimation

̶ 33 ̶

different economic growth rates (Benos andwhere certain industries gain relative shares

Zotou, 2013). Easterly and Levine (1997)

in an economy (Krelle, 2002). In fact, many

showed that low economic growth is associatedempirical studies showed that the productivewith low schooling in the case of Sub-Saharanstructure of an economy and especially its

Africa. Moreover, several studies proved thatdynamics emerge as an important determinanthuman capital is an important factor to promoteof economic growth (Montobbio, 2002; Saviotti,

Research and Development (R&D) - refers to

2008; Teixeira and Fortuna, 2011). In Krelle’s

innovative activities undertaken in developing

study (2002), dynamic multi-sector world model

new services or products or technologies. In

was applied to examine the impact of structural

other words, the more educated the labor forcechange on economic growth. The result showedof a country is, the higher the advantages ofthat economic growth is inevitably connected

the R&D activities in terms of economic growthwith structural change. In a study related to thegot. Workers, for instance, who have high-growth experiences (Silva and Teixeira, 2011),

skill as well as high-level education, can easily

the results proved that the shift in structureabsorb new ideas and technologies alreadyaffected economic growth. All 21 countries

created by developed countries. Therefore,

in the sample had relatively similar economic

through the process of importing equipment andstructures in the late 1970s. However, thesetechnologies, human capital will promote higher

countries’ structures changed from 1979 toinvestment in physical capital (Benhabib and2003, leading to the difference in growth rate inSpiegel, 1994).

each state. Therefore, besides the importanceFurthermore, human capital also affectsof human capital accumulation, the differentials

economic growth through its interconnectionsin economic growth across countries should bewith institutions. Sianesi and Reenen (2003)

traced by structural change, and the complexity

showed that education, besides increasing

underlying their productive structures.

the productivity of the labor force, tends toIn the literature, the impact of structural

improve health levels, environmental conditions,change on economic growth has been a highlyand social cohesion. Similarly, Glaeser et al.

contentious issue. Based on evolutionary and(2004) proved that human capital accumulation

economic development related approaches,

supports economic growth because it contrib-

several studies showed a positive relationshiputes to shaping effective policies, more

between structural change and economic

political stability, and less criminal. Therefore,

growth. In contrast, studies followed supply-

investment in human capital affects not onlyside approaches based on cost disease (Baumol,on individual returns but also drives a spillover1967) believe that structural change leads toeffect that produces social benefits (Dias anda continuing decline in aggregate productivity

Tebaldi, 2012).

growth. According to Pendeder (2003), andSilva and Teixeira (2011), structural change

2.2. Structural change

in favor of specialization in more advanced

Structural change has been one of thetechnological industries leads to stimulate

major concerns in economics over the last few

economic growth because those industries candecades. The definition of structural change

create direct impacts on growth process byis that the shifts in sectoral composition

making new ideas of production that will result̶ 34 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月

in a more efficient reallocation of resources.

accumulation on output and employment growthAlso, those technological sectors can attract

in human-capital-intensive industries. Besides,

more skilled workers because they pay betterthe country with a higher level of human capitalsalary. However, according to structuralist

has the benefit to absorb new technology fromtheories, stressing economic specialization itself

other countries. Meanwhile, structural change

is not sufficient to promote economic growth,

is related to the transfer of technology fromdepending instead on the sector that dominates

developed countries to developing countries.

the economy. Aditya and Acharyya (2013),

Teixeira and Fortuna (2011) indicated thatwith a sample of 65 countries for the period

though human capital has a substantial direct

1965 2005, analyze the relationship between

impact on the total factor productivity, theexport and economic growth. The study

latter’s indirect impact, by means of machinery

showed that the growth of high technology

and equipment imports, is tremendous. Throughexports contributes to the output growth; thethe technological catching-up process, countries

relationship becomes stronger for countries that

can have productive structures with more

have the share of manufacturing exports in theirtechnological content. However, in order tototal exports higher than the world average.

get successful processes, those countries needThus, a shift in specialization towards industrial

a minimum threshold of human capital since

products can enhance economic growth.

creative and innovative methods require larger

Besides the impact of structural change

stocks of human capital. Moreover, when theon economic growth, economists have alsocountry’s stock of human capital increases,

considered the relationship between humanconsumers become more talent and smart. It

capital and structural change. From themeans that they will look for ‘high-tech’ services

structuralist point of view (Justman andand goods, which also contributes to the

Teubal, 1991), human capital is consideredstructural change of an economy (Justman andas an important factor of economic growth

Teubal, 1991).

because it advances structural change. In
fact, previous studies have proved that human

3. Methodology

capital has a critically important role in theevolution of a country’s specialization because

3.1. Model and variables

structural change and the specialization ofBarro and Sala-i-Martin (2003) conducted

countries mainly depend on skills and workers’

an empirical analysis of economic growth toproductivity, factors which are closely related toanswer an interesting question whether poor

human capital. Krishna and Levchenko (2013)

economies tend to “catch up”, which means

showed that less developed countries with low

tend to grow faster than rich economies. Theylevels of human capital would specialize in lessused an empirical framework that relates thecomplex goods. High-technological sectors willreal capital growth rate to two types of variables:

tend to locate in countries with a high stock offirst, initial levels of state variables such as

human capital. In addition, using data for a large

the stock of human capital; and second, othersample of countries, Ciccone and Papaioannou

control or environmental variables. In this study,(2006) showed a significant positive impact

the model is based on the typical cross-country

on human capital levels and human capitalcatch up equation (Barro and Sala-i-Martin,

Human Capital and Economic Growth A Generalized Method of Moments Estimation

̶ 35 ̶

2003). In the dynamic framework, the equationof trade openness and the ratio of workers to

can be written by the following specification:

population, respectively.
The variables considered are as follows:

ln_Yi,t = α * ln_Yi,t–1 + β * X' i,t + μ i + ε i,t,

(1)

Real GDP per capita: To measure thedependent variable, economic growth, thewhere ln_Y i,t is the natural logarithm of realnatural logarithm of GDP per capita is used as a

Gross Domestic Product (GDP) per capita

proxy. The value for real GDP at constant 2011

treated as a dependent variable, ln_Y i,t–1 isprices (in mil.US$) is collected from the dataset

the natural logarithm of lagged dependentof Penn World Table version 9.0 (PWT 9.0).

variable and X' i,t represents a vector of variables

Also, real GDP is divided by population.

influencing economic growth, which includes

Human capital: There are many variables

human capital accumulation, structural change,

which are used as proxies of human capitaland other potential determinants. ε i,t is an i.i.d(see Appendix Table A1). For instance, some(independently and identically distributed) error

studies employed a proxy for human capitalterm with E[ε i,t] = 0 and the subscripts i and t

accumulation by primary and secondary

denote country and time period, respectively. μ ienrollment rates (Barro, 1991; Levine andis unobserved individual-specific effects that isRenelt, 1992; Dreher, 2006; Batten and Vo, 2009)

not correlated with the error term (ε i,t).

while some other studies used expenditure on

Besides human capital and structural

education and health to measure the stock ofchange, a set of other determinants of economic

human capital (Hartwig, 2012). However, thegrowth recurrently reported by previous relevant

average years of schooling of the adult are thestudies are added. In detail, the econometricmost widely used as a proxy of the stock ofmodel estimated, equation (1) can be written as:

human capital (Rajan and Zingales, 1998; Halland Jones, 1999; Temple and Womann, 2006;

ln_Yi,t = α 1ln_Yi,t–1 + β 1 ln_hci,t + β 2 strci,t+Bodman and Le, 2013; Teixeira and Queiros,

β 3 inti,t + β 4 pubi,t + β 5 invesi,t + β 6 rpopi,t +2016).

β 7 demi,t + β 8 opei,t + β 9 lari,t + μ i + ε i,t,(2)

In fact, selecting a proxy of human capitalis a fundamental issue regarding studies ofwhere ln_hci,t represents the natural logarithm

economic growth and human capital. Nowadays,of the human capital index, strci,t is structural

scholars worldwide make a considerable effort

change – the share of high-tech/high knowledge-

to find a good proxy representing humanintensive industries in total employment, inti,tcapital. The dataset of Barro and Lee (BL,computed by multiplying the value of human2013) and Cohen and Soto (CS, 2007) has

capital and structural change (hc×strc) is the

been more popular to measure human capital.

variable measuring the interaction between

The BL dataset provides information abouthuman capital stock and structural change,

the average years of schooling at all levels

pub i,t is the share of public consumption in(primary, secondary, and tertiary) for 146

the gross domestic product, inves i,t is thecountries in 5-year intervals from 1950 2010.

investment rate (in physical capital), rpopi,t is

Meanwhile, the CS dataset shows information

the population growth rate, demi,t is the level ofon years of schooling across countries in every

democracy, and opei,t and lari,t are the degree

10-years between 1960 and 2000. The CS̶ 36 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月

dataset is constructed by the OECD database

Structural change: This variable refers to

on educational attainment and from surveys

long-term shifts in the sectors of an economy. To

published by UNESCO. The CS dataset has beenmeasure these shifts, employment composition

updated by Cohen and Leker (2014), so-called

data is used. In detail, these values come from

CSL dataset. The CSL gives the educational

the Groningen Growth and Development Centre

attainments of the population of 95 countries.

(GGDC) 10-Sector Database, which provides

Pen World Table (PWT) version 8 introduced

information regarding the number of employees

a human capital index based on the averagein 10 broad sectors. The variable is measured by

years of schooling from BL dataset and an

the share of high tech/high knowledge-intensive

assumed rate of return to education, based on

industries in total employment. The data is

Mincer equation (Psacharopoulos, 1994). The

divided into groups, according to the intensity

PWT dataset presents new data for humanof knowledge that each activity requires. This

capital each year across countries between

classification is based on Peneder (2007).

1950 and 2010. However, some researchers

Specifically, in this research, Manufacturing,

believe that the BL data have undesirable

Finance, Insurance, Real Estate, and Businessfeatures related to their inconsistent use ofServices sectors are considered as the highthe data source. In fact, the general difficultytech/high knowledge-intensive industries.

in constructing data on the average years

The number of employees in high tech/highof schooling in the population is to combine

knowledge-intensive industries later is divided

information from population censuses withby total employees.

information on school enrolment, in the face

Investment rate: According to most of theof difference in classification systems between

empirical studies, physical capital accumulation

censuses. Therefore, PWT 9.0 (2015), BL dataset

is measured by the investment share to GDP.

and CSL dataset were combined in compiling theHence, PWT 9.0 dataset is used to obtain thishuman capital index. They computed a humanvariable. Regarding measuring, from the value

capital index based on both series as:of capital stock, the following formula is applied
to calculate investment. It = Kt – Kt–1) * (1 – δ ),⎧ 0.134 * s
if s ≤ 4,
⎪
⎪
0.134
4
+
0.101(s–4)
if4< s ≤ 8,*φ (s)= ⎨⎪ 0.134 * 4 + 0.101 * 4 + 0.068(s–8)⎪⎩
if s > 8,(3)where It is investment in period t, Kt and Kt–1 arecapital stock at constant 2011 national prices(in mil. 2011US$) in period t and in period t-1,
respectively. δ is the average depreciation rateof the capital stock. After that, investment (I) is
divided by real GDP.

where s is the average years of schooling from

Public expenditures: This variable iseither dataset. The assumed rates of return frommeasured by public consumption to GDP ratio.

Psacharopoulos (1994) are applied. The result

The public consumption data is collectedof combining is that PWT 9.0 gives informationfrom PWT 9.0. Barro and Sala-i-Martin (2003)

yearly for 150 countries throughout 65-year-

believe that a higher value of the government

period from 1950 to 2014. Therefore, the Humanconsumption ratio links with a lower steady-state

Capital Index from PWT 9.0 is used to measurelevel of output per effective worker. Therefore,

the stock of human capital in the study.

it leads to a lower growth rate for given values

Human Capital and Economic Growth A Generalized Method of Moments Estimation

̶ 37 ̶

of the state variables. Afonso and Jalles (2014)

ment on economic growth. Meanwhile, thealso showed that government expenditures hadlabor force variable is measured by the ratio ofnegative effects when they analyzed the impact

workers to population.

of fiscal composition on long-term growth in thecase of OECD countries.

A list of variables with their corresponding
description and the source is in the Appendix

Population growth rate: This factor is an(Table A2), as well as the list of countries

important determinant of economic growth. In

included in the sample (Table A3). The sample

the neoclassical growth model, the population

includes 38 countries (10 Asian countries, 7

growth rate has a negative effect on the steady-European countries, 10 American countries,

state ratio of capital to the worker. In addition,and 11 African countries). The model isa high population growth rate also reflects

estimated for a long period from 1960 to 2014.

greater resources devoted to child-rearing

Besides, this dataset includes a wider range(Barro, 2003). Thus, it is expected that there isof the levels of economic development anda negative effect of population growth rate on

human capital compared to previous studies,

economic growth.

therefore, the results will reveal the relationship

Democracy: This variable is calculated

between human capital and economic growth

based on two indexes provided by Freedom

comprehensively. Last but importantly, theHouse (Political Rights Index and Civil Liberties

expected conclusions from the study mightIndex). These data began the early 1970s,

confirm even more strongly the effect of human

therefore, another dataset (Bollen, 1990) is

capital on economic growth in comparison withadded to calculate the democracy variable. The

other studies.

variable has been adjusted to a zero-to-one
scale, with zero represents the highest freedom,

3.2. Generalized method of moment estima-

and one is the lowest. This variable is included

tionin the model to analyze the impact of the quality

Several econometric problems may ariseof institutions and governability of a country on

from the estimating equation (1). First of all,economic growth. The role of governability andthree variables (human capital, structural

institutions in the process of economic growthchange, and economic growth) may have ahave been the source of considerable researchbilateral causal relationship. Therefore, theeffort. In fact, these effects of the quality ofendogeneity problem with the empirical model

institutions and governability on growth are

may arise inevitably. Moreover, as can be seenquite ambiguous. Thus, through these variables,from equation (1), the dependent variable, thatthe study is going to figure out the impact ofis dynamic, depends on its own past values.

the quality of institutions and governability of a

Therefore, the lagged dependent variable iscountry on economic growth. We examine thecorrelated with the error term. It means that

hypothesis that that freer and fairer countries

the regressors are potentially endogenous andtend to have higher economic growth rates.

will not produce a consistent estimate of a

The level of trade openness is calculated

coefficient. That problem renders the traditionalby the ratio of exports plus imports to GDP.

“fixed effects” and “random effects” panel

Considering the variable, the study aims toestimators inconsistent.

analyze the effect of the trade regime environ–

In order to mitigate the endogeneity problem

̶ 38 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月

with the explanatory variables, Arellano andAs mentioned before, one of the immediate

Bond (1991) proposed the use of instrumental

problems in applying OLS to this model is thatvariables to deduce the generalized method of

the lagged dependent variable is correlated

moments (GMM) of corresponding momentwith fixed effects in the error term, which gives

conditions, so-called difference GMM. The

rise to “dynamic panel bias” (Nickell, 1981).

basic idea of the method is eliminating the

It means that the regressors are potentiallyindividual fixed effect by proceeding with theendogenous and will not produce a consistent

first difference of regression equation in the firstestimate of the coefficient. Hence, it is inevitable

place. Following that, the lagged variable will be

to use the instrument to deal with the equationconsidered as the corresponding instrumental(1). Here, Δ ε i,t is not serially correlated, and thevariable of the endogenous variables in the

explanatory variables are weakly exogenous.

difference equation. However, the lagged levels

Therefore, the dynamic panel GMM estimatorof the regressors are poor instruments for first-

conducts the following moment conditions based

differenced regressors. Hence, it is reasonable

on difference estimator for the equation (1);to apply the augmented version - “system GMM”
(Arelllano and Bover, 1995; Blundell and Bond,

E[lnYi,t–z(ε i,t – ε i,t–1)] = 0 for t = 3,……T, z ≥ 21998). The Arellano-Bover/Blundell-Bondestimators augment Arellano-Bond estimator

E[X' i,t–z (ε i,t – ε i,t–1)] = 0

for t = 3,……T, z ≥ 2

by making an additional assumption that thefirst differences of instrument variables areallows an introduction of more instruments
and can improve the statistical efficiency
dramatically. In other words, the system GMM
estimator uses the level equation to obtain asystem of two equations: one difference and one
in levels. By adding the second equation, theWhich can be written in following matrix
form as;⎡0⎢yi1 0 0 … 0 …
⎢
0⎢ 0 yi1 yi2 … 0 …
M= ⎢⎢⎢⎣ 0 0 0 … yi1 … yi,T–z

⎡
⎢
⎢
⎢
⎢
⎢
⎢
⎣

uncorrelated with fixed effect. This assumption

additional instruments can be obtained. Thus,
the variables in levels in the second equation

Here, M is the instruments matrix

are instrumented with their own first difference.

corresponding to the endogenous variables,

This usually increases statistical efficiency.

where yi,t–z refers to lnYi,t–z for the equation (4).
However, the efficiency and consistency

In equation (1),of the first-differenced estimator are criticized
ln_Yi,t = α * ln_Yi,t–1 + β * X' i,t + μ i + ε i,tin terms of bias and imprecision. Therefore,E(μ i) = E(ε i,t) = E(μ i ε i,t) = 0

to reduce potential biases and imprecision,
Blundell and Bond (1998) suggested using

Considering the first difference to remove theindividual specific effect, we can rewrite (1) as

system GMM that combines a system in the
difference estimator with the estimator in thelevel. The difference operator in the equation

Δ(ln_Yi,t) = α * Δ(ln_Yi,t–1) + β * Δ X' i,t + μ i+
Δ ε i,t(4)(3) uses the same instrument as above, and the
instruments for levels are the lagged differenceHuman Capital and Economic Growth A Generalized Method of Moments Estimation

̶ 39 ̶

of the explanatory variables. The intuition

2002). Given the shortcoming associated withhere is that the difference in the explanatory

the Sargen test and the fact that the Hansen test

variables and the country-specific effects areis the most adopted in practice, Hansen test is

uncorrelated. Thus the stationary properties are:chosen to check the validity of the instruments.
Secondly, Arellano and Bond (1991) also

E[lnYi,t+p μ i] = E[lnYi,t+q μ i] and E[X' i,t+p μ i)] =developed a test for a phenomenon that would

E[X' i,t+q μ i)] ∀ p and q

render some lags invalid as instruments, namely,
autocorrelation in the idiosyncratic disturbance

The additional moment conditions for thelevels areterm, ε i,t. Of course, the full disturbance (μ i
+ ε i,t) is presumed auto-correlated because it
contains fixed effects (μ i), and the estimators

E[ΔlnYi,t–1 (μ i + ε i,t)] = 0

are designed to eliminate this source of trouble.

E[Δ X' i,t–1 (μ i + ε i,t)] = 0

If the ε i,t are themselves serially correlatedof order 1, which make them potentiallyNow, this study applies the system GMM

invalid instruments after all. For instance,

estimation method for the dynamic panel

y i,t–2 may be endogenous to ε i,t–1 in the error

data model to get more robustness of theterm in differences. To test for autocorrelation

result. However, GMM cannot be establishedwithout the fixed effects, the Arellano-Bond

as a consistent method of estimation unlesstest is applied to the residuals in differences.

there is no autocorrelation in the disturbanceEspecially, in this study, the Arellano-Bond tests

term. Hence, after running the regression, it isfor the first-order (AR(1)) and the second-ordernecessary to conduct some tests for checking(AR(2)) serial correlation in the first-differenced

estimators.

residuals are used to test for autocorrelation.

To check GMM estimator, as suggested by

Because the first differences of independently

Arellano and Bond (1991), Arellano and Boverand identically distributed idiosyncratic errors(1995), and Blundell and Bond (1998), twowill be serially correlated, rejecting the null

specification tests are used. Firstly, the Sargan

hypothesis of no serial correlation in the first-

and Hansen test for the joint validity of thedifferenced error at the order one does not

instruments is standard after GMM estimation.

imply that the model is misspecified. However,

The validity of the moment condition can berejecting the null hypothesis at higher orders

directly tested by Sargan and Hansen tests. The

implies that the moment conditions are notnull hypothesis of Sargan and Hansen test isvalid.

that all instruments as a group are exogenous(thus, for the instruments to be valid one should

4. Empirical results

not reject the null hypothesis). However, thebehavior of the Sargan test statistic is only well-

The dynamic panel estimation results

known when disturbances can be assumed

are presented in Table 1, which reports theas homoskedastic (Iqbal and Daly, 2014).

regression result using System GMM estimators.

Moreover, the Sargan test may have low power

In detail, the dynamic panel data estimation forto reject the null hypotheses, the instruments

the coefficients corresponding to each variable

are valid when the sample size is small (Bowsher,is provided. The results of three tests (Hansen̶ 40 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月

TABLE 1. RESULTS OF DYNAMIC PANEL-DATA ESTIMATION, SYSTEM GMM

test, AR(1) and AR(2) tests) are also reported

faster than other countries. The result suggests,

in the Table. First of all, the test for the first-

as postulated in the literature, that countries

order serial correlation in the residuals AR(1)with a higher human capital grow faster in theshows that the null hypothesis of no first-

considered periods (1960 2014). This conclusion

order serial correlation is rejected with P-value

meets the expectation that a higher stock of

0.000. Meanwhile, the test of the second-

human capital improves the workforce’s skills,

order serial correlation AR(2) reveals that all

which has a positive impact on its productivity

estimations have no problem of second-order(Bodman and Le, 2013). Moreover, the coefficient

serial correlation since AR(2) test statistic isof structural change is a positive sign withunable to reject the null of the second-order

statistical significance. It suggests that theserial correlation (P-value 0.179). In addition,

countries where structural change contributes

the Hansen test for over-identification indicatesto increasing the share of knowledge-intensive

the null hypothesis of exogenous instruments is

activities required high skills, on average, tend

not rejected with the p-value of 1.000.

to grow faster. Hartwig (2012) and Zagler (2009)

As can be seen from Table 1, the coefficient

showed that knowledge-intensive activities

estimation of the lagged GDP per capita variable

employ individuals with higher skills andis strongly significant, positive, and lower than 1.

knowledge because they are more productive

It conveys the typical conditional convergenceand capable of enhancing the emergence of new

result, in which countries with low initial GDP

products and processes. Therefore, the growth

per capita levels present, on average, higher

rates of countries that observe increases ingrowth rates.

specialization in high-level industries tend to be

As for human capital, this variable shows ahigher.

significant positive effect on economic growth.

The result with System GMM shows that

It means that countries which have a higher

human capital also has an indirect impact on

stock of human capital endowment will develop

economic growth via productive specialization.

Human Capital and Economic Growth A Generalized Method of Moments Estimation

̶ 41 ̶

The estimation of the moderating effectthe conclusion of Barro’s (1991) study. Barroof human capital on structural change isbelieved that the high investment rate has asignificantly negative. Regardless of humanpositive impact on economic growth since highcapital having a significant positive direct

physical capital formation contributes positively

impact on economic growth, its indirect impact

to the productivity of production factors. In

via the productive structure in favor of high-brief, economies with a high level of investment

level industries is negative. By analyzing thetend to grow faster than others. In addition,case of 38 countries within sample throughout

the study suggests that the ratio of workers to

55-year-period from 1960 to 2014, the study

population has a positive impact on economic

suggests that economic growth is explained by

growth. Finally, based on a more heterogeneous

the dynamics of human capital (education) andsample that includes a wide range of levels ofby the declining share of knowledge-intensive

economic development, this study fails to findactivities (‘high-level’). It seems to prove that

evidence showing that population growth rate,in the sample and transition economies, thethe level of trade openness, and the democracy

matching between an adult population withvariable matter for economic growth.

high educational attainment and structural

5. Conclusionschange towards a specialization in knowledge/
technology-intensive activities does notcontribute to higher economic growth.

This study aims to examine both theRegarding the control variables, thedirect and indirect impacts of human capitalcoefficient of public expenditure is a negativeon economic growth, taking into account thesign. Therefore, high public consumption caninteraction of human capital with the country’s

make a negative effect on economic growth.

industrial specialization in 38 countries over the

Our results confirm the idea that high public

period 1960-2014. Following Barro and Sala-i-consumption can create market distortions,

Martin (2003), the study extended their cross-inefficiencies, and crowding-out, that negatively

section analysis into large panel analysis using aaffect economic growth. Moral-Benito (2012)

dynamic panel GMM technique, so-call systemsuggested that a low level of government share

GMM. The main findings of this study are as(public expenditure) would promote economic

follows:

growth since it reduces distortions in theFirst of all, the study showed that theeconomy. This result supports the finding of

human capital endowment has an important

seminal studies (Barro, 1991) as well as more

influence on economic growth even though

recent studies (Dreher, 2006; Batten and Vo,

the set of data which includes a wider range

2009; Afonso and Jalles, 2014). Furthermore,of levels of economic development and human

we found that a high investment rate is related

capital. The study demonstrates unequivocallyto higher economic growth. As can be seen

the fundamental role of formal educationalfrom the Table, the coefficient of investment

attainment, reflected in improved qualifications

has a significantly positive impact in explaining

and higher skills. Some recent studies havethe variation of GDP per capita. This evidence

doubted on the merits of ‘average years of

is in line with the results of Dreher (2006),

education’ in explaining the long-term growthBatten and Vo (2009). Also, this result meetsof countries. For instance, Delgado et al.

̶ 42 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月(2012) believe that in empirical research, theinto the productive system, thus, generates

significance of schooling depends on the sample

disappointing economic returns for this latterof observations or the specification of theset of countries. This outcome is supported bymodel. They suggested that the average years

the evidence gathered by Jaoul-Grammare andof schooling may not provide a more reliable

Guiroment (2009), which analyzed the impact

measure of human capital. However, using theof education on economic growth. That study

Human Capital Index (Penn World Table 9.0)

proves that an increase in mismatches between

to measure the stock of human capital, thiseducation and structural change leads to an

study provides evidence showing that years

unfavorable effect on economic growth.

of schooling is still an effective measurement

Some policy implications arise from theof human capital. Secondly, this study also

study. The results suggest that to promote

contributes to the scientific literature on

economic growth, countries should contemplate

the relationship between economic growth

an investment in human capital throughand structural change. The result suggests

education. Furthermore, governments shouldthat structural change is a critical factor ininvest more in technology/knowledge-intensive

economic growth. Moreover, the study confirms

activities generating high value-added to thethat increasing specialization in knowledge/

economies such as manufacture, financial,technology-intensive industries accelerates

computers, business services, and education. In

the economic growth of countries. Thirdly,

addition, the important point needs to highlight

our findings demonstrate that the mismatchthat the educational offer and system need to

between structural change processes and themeet the market demands. The aim will be tohuman capital endowments of countries canpromote the matching between skilled labormake a negative influence on economic growth.

and economic activities that require these

It is a possibly unexplored issue as far as humansame qualifications. Finally, I acknowledge thecapital and structural change interaction. The

limitation of this study and leave it for further

lack of industrial structures that cannot properly

research to analyze deeper the effect of theintegrate the highly-educated individuals

interaction term on economic growth.

Notes1) College of Economics, Hue University, Vietnam,
Corresponding author: Email: levietgiap@
gmail.com - lvgiap@hce.edu.vn

2) Smith A (2003; orig, publ 1776) “An Inquiry
into the Nature and Causes of the Wealth of
Nation”.

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Appendix
TABLE A1. LIST OF EMPIRICAL STUDIES RELATED TO HUMAN CAPITALTABLE A2. LIST OF VARIABLES USED̶ 46 ̶人文・社会科学研究

東京国際大学大学院第4号

2019 年 9 月

TABLE A3. LIST OF COUNTRIES IN THE SAMPLE