Malaysian Journal of Economic Studies 60(1): 45–67, 2023 ISSN 1511-4554

Effects of Government Expenditure on the Poverty Level:

A Nonlinear ARDL Approach
Saharudin Yusoff a
Siong Hook Law b
Norashidah Mohamed Norc
Normaz Wana Ismail d
Universiti Putra Malaysia

Abstract: The argument on the behaviour of government expenditure toward reducing

the poverty level is still controversial among economists and policymakers. This study
investigates the role of government development expenditure in alleviating poverty
in Malaysia. The study employs a nonlinear autoregressive distributed lag (NARDL)
model from 1970 to 2019 using annual time series data. The bounds test of the NARDL
specification suggests the presence of cointegration among the variables, namely the
poverty level, development expenditure, gross domestic product per capita, inflation
rate, physical capital and human capital. The empirical findings demonstrate that an
increase in development expenditure is an insignificant determinant of poverty, but
the reductions in development expenditure significantly eradicate the poverty level in
the long run. For robustness checks, the share of development expenditure on gross
domestic product is used in the estimation. The findings show that all development
expenditure has little to no impact on lowering poverty levels over the long and short
runs. The Malaysian government should therefore consider how crucial it is to allocate
public funds effectively and make sure that the emphasis on spreading development
gains across all economic sectors must have an influence on the poverty level.

Keywords: Poverty, development expenditure, NARDL, Malaysia

JEL classification: A10, B41, D31

1. Introduction
This paper investigates one of the most severe social issues every country faces:
poverty. Poverty, according to Ahmad et al. (2016), is defined as a lack of capacities and
resources to meet one’s basic needs. This unacceptable human condition could be due

a
School of Business and Economics, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.
E-mail: yusoffsaharudin@yahoo.com
b
School of Business and Economics, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia and
College of Business and Economics, University of Johannesburg, South Africa. E-mail: lawsh@upm.edu.my
(Corresponding author)
c
School of Business and Economics, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.
E-mail: norashidah@upm.edu.my
d
School of Business and Economics, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.
E-mail: nwi@upm.edu.my

Article Info: Received 2 March 2022; Revised 27 April 2023; Accepted 27 April 2023
https://doi.org/10.22452/MJES.vol60no1.3

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 45

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

to unequal wealth distribution. That means the advantages of development initiatives

and programmes are not felt equally across society. Poverty will, in general, continue
to be a global issue in this century. This field of research is especially important
considering recent crises, such as the COVID-19 pandemic, which is predicted to
increase unemployment and poverty in the country. As a result, it is critical to consider
the impact of development expenditure in alleviating poverty in Malaysia. Furthermore,
the poverty issue is one of the sustainable development goals (SDGs) that aims to end
all forms of poverty and promote prosperity.
In 2019, the United Nations (UN) challenged Malaysia’s claim that poverty had
been practically eradicated. According to the UN, official estimates are inaccurate and
do not reflect the reality on the ground. Malaysia’s official poverty rate fell from 49.3%
in 1970 to just 0.4% in 2016, which has since been revised to 5.4%, as shown in Figure
1. According to the UN, the official figures were based on antiquated criteria, with
the poverty line remaining at the same level for decades despite rising living costs.
Malaysia’s poverty line was amended to more than double to RM2,208 in July 2020, up
from RM980 previously. Since 2005, the government has not revised Malaysia’s poverty
line methodology. The World Bank applauded the decision, allowing the government
to ensure that all Malaysians can reach a new primary standard of living that is more in
line with today’s Malaysia.
According to Majid et al. (2016), Malaysia has implemented many programmes
and policies to steer its development and poverty reduction since its independence.
Therefore, the main purpose of the development plan in Malaysia is poverty eradication
and bridging the inequality gap in society. It was manifested in adopting the concept

Expenditure
300000 60

250000 50

200000 40
Percentage (%)
RM million

150000 30

100000 20

50000 10

0 0

Year

OE DE P

Figure 1. Operating expenditure (OE), development expenditure (DE) and poverty level (P) in
Malaysia (1970–2019)
Source: Economic Planning Unit and Ministry of Finance.

46 Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023

 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

Shared Prosperity Vision 2030 (2021 – 2030) RMKe-12

Sustainable Development Goals (SDGs)

Vision 2020 (1991 – 2020)

Total Development
Fully Industrialised Nation RMKe-10, RMKe-11

National Vision Policy (NVP) (2001 – 2010)

RMKe-8, RMKe-9
Building a Resilient and Competitive Nation

National Development Policy (NDP) (1991 – 2000)

Balanced Development RMKe-6, RMKe-7

National Economic Policy (NEP) (1971 – 1990) RMKe-2, RMKe-3

Growth with Equity RMKe-4, RMKe-5

Pre-NEP (1957 – 1970)

Laissez-faire / exports
Economic & rural development RMR RMKe-1

Figure 2. Major economic policies

Note: RM (Rancangan Malaysia) denotes various Malaysia Plans (from First to Twelfth).

of “growth with equity” in all development programmes and policies. Even though the
country’s poverty rate has dropped dramatically, poverty remains a serious problem.
The government must address this issue and start working on it, particularly in raising
the standard of living in society. The Shared Prosperity Vision 2030 was established to
replace the New Economic Model (NEM) with the goal of developing a high-income
economy and increasing purchasing power of the people. Major economic policies are
shown in Figure 2. Even though many development programmes and policies have
been implemented, none have been able to eradicate poverty. However, the efforts
to overcome poverty are a continuous process. Therefore, the question is whether
government development expenditure impacts Malaysian poverty reduction.

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 47

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

Combating poverty has been a primary priority for the government, even if it needs
more stringent and comprehensive policies that include both urban and rural areas.
The government must achieve inclusive growth by putting the “people economy” at
the centre of its development strategy to become a high-income country. The multiplier
effect on poverty reduction in the country is controversial, even though government
expenditure increases every fiscal year. The World Bank (2019) claimed that Malaysia’s
poverty rate is significantly higher with rising living costs. Consequently, the research
question to be addressed in this paper is: what are the relationships between gov-
ernment development expenditure towards the rate of poverty? This study aims to
investigate the relationships between government expenditure and poverty levels in
Malaysia, utilising time series data from 1970 to 2019.
The following are the study’s contributions to the body of knowledge. First, the
results of this study can assist policymakers in developing and implementing effective
strategies for allocating government expenditure. As a result, the findings should
assist the government in developing appropriate strategic policies and public resource
allocation in government expenditure, affecting poverty levels in Malaysia. Second, from
a research standpoint, utilising the nonlinear autoregressive distributed lags (ARDL)
model by Shin et al. (2014) to investigate the long-run and short-run asymmetries in
government development expenditure and poverty level nexus.
The remainder of the paper is organised as follows. Section 2 reviews the relevant
literature, section 3 describes the empirical model, econometric approach and the data
used. Section 4 discusses the empirical results and interprets the findings. Lastly, the
conclusion wraps up the discussion.

2. Literature Review

2.1 Determinants of Poverty

Asymmetric effects of development expenditure on the poverty level are among
the most important concerns in developing economies. According to Sasmal and
Sasmal (2016), economic progress and income distribution, social capital growth and
infrastructure development, and productivity levels all contribute to the prevalence and
persistence of poverty. As a result, using the spillover effect of economic expansion to
benefit the poor is an essential method of eliminating poverty. Then there’s the direct
poverty objective when the government helps the poor directly through measures and
distribution. This opinion was supported by Manaf and Ibrahim (2017), saying that an
emerging economy can be an excellent example of poverty reduction in Southeast Asian
countries. The poverty rate has steadily decreased from 49.3% in 1970 to 5.6%. The
Malaysia Plans, National Development Policy and the New Economic Model are only
a few of the government’s anti-poverty initiatives. Many initiatives, such as the eKasih
system, FELDA and the 1AZAM programme, have aided in the eradication of poverty.
The government is now executing the 2030 Agenda to prosper together. The policies
and programmes are underpinned by strong political will and inclusiveness and attach
to national unity. Poverty eradication will remain a primary focus for the country’s long-
term development.

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 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

In addition, Milasi et al. (2016) revealed that the relationship between economic
growth and poverty reduction is significantly linked to implementing appropriate
policies and programmes. Policies and initiatives must vigorously address changes in
economic growth and diversification. Other than that, employment policies should also
be drafted to increase the skill levels and increase labour market participation rate in
the economy. Whereas Nair and Sagaran (2015) claimed that the term poverty is very
dynamic that encompasses both absolute and relative poverty. Absolute poverty is a
minimum standard of life based on a fixed income. Regarding relative poverty, those
who earn less than the median national income is considered poor.
Hassan et al. (2020) examined the impact of globalisation, governance and com-
petition on poverty in the case of 73 developing nations between 2005 and 2016.
The results were estimated using a feasible generalized least squares approach, which
confirmed that all governance indicators have a negative impact on poverty. In the
same vein, globalisation, competitiveness and development expenditures help to
reduce poverty. Poverty also refers to having less access to health care, education and
opportunities for improving one’s life. The Keynesian cross outlines the laws governing
the relationship between government development expenditures and growth. State
expenditures spur increased spending by firms and households, boosting growth.
There are two ways to interpret the bidirectional impact of education on poverty.
Firstly, public investment in human capital improves the skills and productivity of low-
income families. Second, poverty may place a significant restriction on educational
achievement.
Inegbedion and Obadiaru (2021) investigated Nigeria’s perceived causes of poverty.
It used a longitudinal survey of four perceived determinants of poverty for the years
1980 to 2019: unemployment rate, population, inflation rate and income disparity.
Stationarity and cointegration were examined using Augmented Dickey-Fuller and
Johansen’s tests. Vector error correction model was used in testing for statistical
significance of the explanatory variables. In the short term, the results showed that
both the unemployment rate and the inflation rate are significant predictors of the level
of poverty, but in the long run, only the unemployment rate is significant. On the other
hand, Taufiq and Dartanto (2020) examined the impact of education on the dynamics
of poverty in Indonesia as well as the employment mobility of informal to formal
employees (informal turnover). The analysis of the National Socio-Economic Survey
(2011–2013) found that those with higher levels of education tended to leave the
informal economy, showing that education significantly influenced this trend (Central
Bureau of Statistics of Indonesia, 2011–2013).

2.2 Development Expenditure and Poverty

The theory of the vicious circle of poverty (TVCP) states that a country is poor because
of the market’s small size (Nurkse, 1952). According to this theory, the relationship
between demand, incentives to invest and supply, which is the ability and willingness
to save, exists in undeveloped and financially unstable countries. As a result, expanding
the country’s market is vital for stimulating and nurturing the economy’s growth and
development. Nurkse believes that for a country to thrive, it must adopt a balanced

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 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

development strategy that prioritises the industrialised sector above raw materials and
basic manufacturing. As a result, establishing cooperation between the government
and the private sector regarding savings and investments is crucial for the individual
country. TVCP is projected to improve economic growth and, as a result, eliminate
poverty, particularly in undeveloped regions. From 2008 to 2013, Khasanah et al. (2016)
used panel data regression analysis to study the relationship between the government’s
spending on education, health, housing and public facilities in Indonesia. According
to the findings, all the independent factors have a link with the dependent variable.
According to the study, the allocation for health and education expenses should be
increased by 10% and 20%, respectively. Furthermore, additional funding for home
development should be made available, ultimately benefiting the poor.
From 2010 to 2014, Saad and Nor (2018) studied the impact of health spending on
economic growth in 67 low-income and middle-income countries. The countries were
divided into two groups which are low-income and middle-income, and each group was
studied separately to determine the differing effects of health spending on economic
development. The findings demonstrate a strong relationship between health spending
and economic growth for both countries, with middle-income countries having a slightly
stronger influence. As a result, for the nations to become developed countries, boosting
the health sector through raising health expenditure should be a priority.
Subsequently, Sasmal and Sasmal (2016) investigated the effect of government
spending on economic growth and poverty alleviation, focusing on emerging countries
such as India. For example, the government can enact distributive measures during
times of extreme poverty. Of course, these distributive measures will come at a cost
in terms of long-term progress. However, they will fail if attempts to eliminate poverty
are not executed with excellent governance and adequate targeting. Nonetheless,
if public spending is aimed at boosting per capita income, it will reduce poverty.
Sasmal and Sasmal employed both fixed and random effects approaches in this study.
The results showed that per capita income grows when the government spends a
higher percentage of its budget on infrastructure development, such as roads and
transportation. As a result, poverty levels will be lowered. Therefore, the study
suggested that spending on infrastructure development improved economic growth
and, as a result, aided in poverty alleviation.
Mustapha et al. (2017) examined how public spending affects poverty reduction
in the Organisation of Islamic Cooperation (OIC) and non-OIC nations. For them, all
levels of government must share responsibility and should take the issue of poverty
reduction as a priority. They used the ordinary least squares (OLS) approach to assess
the impact of education and health spending on poverty reduction in the OIC and the
rest of the globe for each of the 126 countries. It was assumed that the OIC countries
were generally free of poverty. However, the truth was that numerous OIC countries
were among the poorest in the world. Therefore, the study discovered that government
expenditure positively impacted poverty eradication in both OIC and non-OIC countries,
with gross national incomes (GNIs) essentially comparable in both. As a result, research
in many countries showed that education, health and private investment expenditure,
inward remittance, and secondary school enrolment contributed to alleviating the
poverty level.

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 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

Musaiyaroh and Bawono (2017) extended the study of acceptable strategies to

alleviate poverty challenges in the four Association of Southeast Asian Nations (ASEAN
4 – Malaysia, Indonesia, Thailand and the Philippines) through economic develop-
ment. The construction of state infrastructure was thought to support economic
growth by boosting human resource quality and implementing relevant technology. By
eliminating poverty and unemployment, infrastructure improvements can help to boost
growth. The research used the panel generalized method of moments (PGMM). The
variables were poverty, education and health infrastructure expenditure, government
expenditure, GDP per capita, the Gini index and the unemployment rate. The results
reported statistically significant implications for health care infrastructure, GDP per
capita and government expenditure in poverty reduction in the ASEAN 4. As a result,
infrastructure investment was vital for any country to stimulate economic growth and
eliminate poverty.
Using panel smooth transition regression models, Kuang et al. (2019) investigated
how financial and fiscal policies affect poverty alleviation in China. The results show
that fiscal and financial policies both have a favourable impact on reducing poverty,
and their linkages are nonlinear. Therefore, the degree of poverty should be considered
while selecting which programmes to prioritise for eliminating poverty. Specifically,
when a portfolio of policies aimed at reducing poverty is put into place, fiscal measures
should initially take precedence while the prevalence of poverty is high. Then, when the
poverty rate declines, financial help should take centre stage, and when the poverty
rate keeps down, fiscal support should be intensified.
The relationship between government spending, economic growth and poverty
alleviation in Nigeria is examined by Oriakhi (2021). It demonstrated the causality of the
bidirectional relationship between poverty reduction, total public spending, real gross
domestic product as a measure of economic growth, and natural resource rent for 38
years. The results suggest that variables have a bidirectional relationship. Each variable
contributed to distinct percentage levels and fluctuations in shocks within the variable
and in other model variables throughout time. Nigeria generally has a bidirectional
causal relationship between overall public spending and decreased poverty. The study
concludes with recommendations for increased government spending to reduce
poverty, adopting pro-growth and pro-poor policies, and a transparent and corrupt-free
system of government.

2.3 Research Gaps

The perceived poverty rate in Malaysia and other countries has attracted the attention
of researchers, thereby making empirical literature on the research problem apprecia-
ble. The aspects of the problem so far examined include determinants of poverty
(Hassan et al., 2020; Islam et al., 2017; Majid et al., 2016; Manaf & Ibrahim, 2017;
Siwar, 2016), the positive impact of public expenditure on poverty alleviation (Ahmad
et al., 2016; Kuang et al., 2019; Mustapha et al., 2017; Saad & Nor, 2018), the negative
impact of public expenditure on poverty alleviation (Khasanah et al., 2016), reducing
poverty incidence in Nigeria (Inegbedion & Obadiaru, 2021; Oriakhi, 2021) and impact
of infrastructure on poverty level (Musaiyaroh & Bawono, 2017; Sasmal & Sasmal,

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 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

2016). The results of the studies indicate a positive impact of public expenditure on
poverty alleviation (Musaiyaroh & Bawono, 2017; Sasmal & Sasmal, 2016). However,
some studies also revealed a negative impact of public expenditure on the poverty level
(Khasanah et al., 2016). While development expenditure is perceived to have significant
implications on the poverty rate, only few studies focused on development expenditure
and poverty. In addition, not many studies appear to have included inflation, physical
capital and human capital as control variables, even though they may influence the
poverty level in a country and thus trigger poverty. This study sought to fill these gaps.

2.4 Development Expenditure and Poverty in the Malaysian Context

One of the biggest issues in developing nations like Malaysia is poverty. Poor health and
malnutrition are associated with poverty, as well as a lack of control over resources and
education. As a result, according to Ahmad et al. (2016), one of the main issues of the
twentieth century is poverty. Poverty is an intolerable human condition characterised
by a lack of necessary resources and capacities because of dynamic and complex
individuals’ basic needs. Malaysia, according to Nair and Sagaran (2015), has to revisit
its previous methods for eliminating poverty and disparities across the country. They
believe that Malaysia must address both absolute and relative poverty, as well as rising
inequality. The government must adopt an urgent policy prescription, not only for
rural poverty, but also for urban poor. Prioritising income distribution is also necessary.
Income distribution improvements should occur in tandem with poverty reduction.
Besides that, a paradigm shift is necessary in conceptualised and measured poverty
in Malaysia.
Majid et al. (2016) supported Nair and Sagaran’s assertions. For them, the problem
of poverty has been greatly lessened in Malaysia. However, there is still a lot of efforts
needed to be embarked on the existence of poverty, particularly in rural communities
in some states and in the urban areas. Certainly, today’s poverty reduction policy devel-
opment and policy designation must place a greater emphasis on effective implemen-
tation. Furthermore, Siwar (2016) examined the role of good governance in Malaysia’s
poverty alleviation. Over the years, Malaysia has recorded a sustainable economic
growth with remarkable poverty alleviation. Good governance, pro-growth policies and
poverty-reduction programmes that have been implemented since the NEP and which
will now be carried over to the Shared Prosperity Vision 2030 have all played a role in
poverty reduction. Particularly, in the economic sector, good governance has resulted
in considerable improvements in the delivery of public services as well as enhanced
accountability and efficiency. Nevertheless, based on certain research that support the
“grease the wheel” theory, corruption, particularly in nations with poor governance
systems, can reduce inefficiency and make it easier for enterprises to be established.
Poverty was among the key factors that have hampered Malaysia’s economic
progress, according to Islam et al. (2017). Since the 1970s, the government has adopted
a range of measures to reduce poverty and income gaps, particularly in rural areas. As
a result, their research focused on the magnitude of poverty and income inequality in
Ipoh, Perak. The study also investigates the government’s interventions and goals for
reducing poverty and income disparity, as well as economic growth programmes. The

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 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

study offers a few suggestions and recommendations, mainly in terms of government

financial aid and education policy to the lower income group.

3. Methodology and Data

This study investigates the association between government development expenditure
and the poverty level by using the nonlinear ARDL method. The nonlinear ARDL model
is an extension of the autoregressive distributed lags (ARDL) model by Shin et al. (2014).
The model captures short and long-run asymmetry through positive and negative partial
sum decompositions of changes in the independent variable. There are four reasons to
choose nonlinear ARDL; according to Lee and Masih (2018):

(a) It enables the simulation of a cointegration relationship between the poverty

level and the development expenditure.
(b) The concept can be applied to linear and nonlinear cointegration problems.
(c) It calculates all the independent variables’ short- and long-run effects on the
dependent variable.
(d) The concept allows for alternative integration orders for data series.

The nonlinear ARDL method appears to be adequate for detecting potential asym-
metries in poverty levels, which development expenditure factors could cause. The
study adopts an alternative econometric framework, namely the nonlinear ARDL model,
because the framework is most appropriate since it allows potential long-run and
short-run asymmetries in the development expenditure and poverty level relations and
indirectly hints at the importance of fiscal policy in the country. Theoretically, it should
be anticipated that increased government expenditure will have an asymmetric impact
on the poverty rate. More economic spillover effects will encourage a greater standard
of life and eventually lower people’s poverty levels.
This technique examines long- and short-run nonlinearities by using positive and
negative partial sum decompositions of the regressors. It also quantifies the regressors’
responses to asymmetric dynamic multiplier shocks, both positive and negative. The
nonlinear ARDL technique is an asymmetric extension of Pesaran et al. (2001) well-
known linear ARDL bounds testing technique. After that, the cumulative dynamic
multipliers are graphed. As a result, the nonlinear ARDL model can capture the non-
linear or asymmetric relationship between the variables in both the short and long
terms in this study. This is how the long-run model is defined.

Pt = α0 + α1GDPPCt + α2INFt + α3Kt + α4HCt + α5DEt + et (1)

where P is poverty level, DE is government development expenditure, GDPPC is gross

domestic product per capita, INF is rate of inflation, K is physical capital, HC is human
capital, e is error term and t is time series subscript. GDPPC, K and HC are expected
to record a negative sign, and INF is a positive sign. That means the poverty level
is expected to be reduced with an increase in GDPPC, K and HC, but higher INF will
increase the poverty level. The nonlinear ARDL model allows us to determine whether
positive and negative development expenditure shocks have any impacts on short and

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 53

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

long run poverty. Equation (1) augmented with asymmetric coefficients of nonlinear
ARDL is as follows:

Pt   0  1GDPPCt   2 INFt   3Kt   4 HCt   5DEt   6 DEt  et (2)

where α(α 1, α 2, α 3, α 4, α 5, α 6) is a cointegrating vector or a vector of long run

parameters to be estimated. The asymmetric effect of development expenditure is
Pt   0 for
accounted 1GDPPC t   2P
by including INF t0positive
t the 3
Kt1GDPPC HCt t 25INF
  4changes 36KDE
DEttand t t 
the
negative DEt   6 DEt in
et t   5changes
4 HC  et
INFtt 33KKEquation
22INF HCtt(2).
44HC
tt  DEtt and
55DE 
DEtt constitute
66DE 
eett the partial sums of positive and negative changes
in the development expenditure, respectively. They are specified as follows:
t t
DEt   DEt   max(DEi , 0)
i 1 i 1

t t
DEt   DEt   min(DEi , 0)
i 1 i 1

Based on the above formulation, the long-run relationship between the poverty level
and increases in development expenditure is α5, which is expected to be negative.
Meanwhile, α6 is expected to have a positive sign between the poverty level and
development expenditure, because both are expected to move in the opposite
direction. The study further posits that development expenditure increases will
result in lower long-run changes in the level of poverty as compared to the impact
of development expenditure reduction of different magnitude, i.e. α 5 > α 6. As a
result, the long-run relationship, as represented by (2), reflects asymmetric long-run
development expenditure passes through to the poverty level. Therefore, the nonlinear
ARDL equation will take the following error-correction form to estimate the short-term
coefficients:
Pt     0 Pt 1  1GDPPCt 1  2 INFt 1   3Kt 1   4 HCt 1   5DEt1   6 DEt1 

p q r s u
 i Pt 1  i GDPPCt i  i INFt i  i Kt i  i HCt i 
i 1 i 0 i 0 i 0 i 0
v
   
 ( DE   DE )  t
i t i i t i (3)
i 0

where all variables are as defined above, p, q, r, s, u and v are lag orders and α5 = –
β5/β0, α6 = –β6/β0, the aforementioned long run impacts of respective development
expenditure increases and development expenditure reduction on the level of poverty.
u 
 i 0 i measures the short-run influences of development expenditure increases on the
reduction of the poverty level and the short-run influences of development expenditure
reduction on the hike of the poverty level. Hence, in this setting, in addition to the
asymmetric long-run relation, the asymmetric short-run influences on development
expenditure changes on the poverty level are also captured. Both the long run and
short run asymmetry tests of the variables are conducted using the asymmetric
statistics of nonlinear ARDL.
Before embarking on the model’s stages, like the ARDL model, the unit root test
is required to investigate the stationarity condition of the required variables. To this
end, the study applies the widely used augmented Dickey-Fuller (ADF) and Phillips-

54 Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023

 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

Perron (PP) unit root tests for establishing the variables’ orders of integration. It is
crucial to ensure the variables are only stationary at I(0) and I(1). That is, no variables
of order two or above will integrate to avoid an erroneous F-statistic result at a later
stage. Generally, the nonlinear ARDL model involves carrying out long-run cointegration
utilising bounds testing. This approach is used to test for cointegration among the
variables based on the estimated nonlinear ARDL. At this stage, the F-statistics will be
compared to the critical values proposed by Pesaran et al. (2001) or Narayan (2005).
Then, if the estimated F-statistics are above the higher critical value, reject the null
hypothesis of no cointegration. The null hypothesis is maintained and cannot be
rejected if the F-statistic is at the lower critical value. When the F-statistics value falls
between the lower and higher critical value, the result is inconclusive. Then, there
is the matter of testing for short-run and long-run asymmetries. As a result, the null
hypothesis is H0: focused variables are symmetric, while the alternative hypothesis is H1:
focused variables are asymmetric.
In the next step, equation (3) is estimated using the standard OLS estimation
method. The general-to-specific procedure was adopted to arrive at the final speci-
fication of the nonlinear ARDL model by trimming insignificant lags. Based on the
estimated nonlinear ARDL, a test was performed for the presence of cointegration
among the variables using a bound testing approach of Pesaran et al. (2001) and Shin
et al. (2014). This involves the Wald F test of the null hypothesis, β0 = β1 = β2 = β3 = β4 =
β5 = β6 = 0. In the final step, with the presence of cointegration, an examination of long-
run and short-run asymmetries in the relations between development expenditure and
poverty level is made, and inferences are drawn.

3.1 Data
The sample period of this study is from 1970 to 2019, based on the annual datasets.
Poverty rate (P) – measured in terms of percentage over population – is obtained from
the Prime Minister’s Office’s Economic Planning Unit. Development expenditure (DE),
gross domestic product per capita (GDPPC) and inflation rate (INF) are collected from
Malaysia’s Ministry of Finance. The physical capital (K) and human capital (HC) variables
are obtained from the Penn World Table version 10 (Feenstra et al., 2015).

4. Empirical Results
Table 1 shows the descriptive statistics of all variables, namely poverty rate (P), develop-
ment expenditure (DE), human capital (HC), gross domestic product per capita (GDPPC),
inflation rate (INF) and physical capital (K). The standard deviation is lower than the
mean, reflecting that the datasets are not highly varied from the year 1970 to 2019.
The average of DE, P and INF during the same period were RM21,421 million (P: 18.39%
and INF: 3.43%), a maximum of RM56,095 million (P: 49.30% and INF: 17.33%) and
a minimum of RM725 million (P: 0.60% and INF: 0.29%), respectively. Whereas the
average of GDPPC, HC and K were RM13,330 (HC: 2.34 and K: 27.38%), a maximum
of RM43,708 (HC: 3.08 and K: 43.59%) and a minimum of RM1,087 (HC: 1.50 and K:
17.51%), respectively.

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 55

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

Table 1. Descriptive statistics

Mean Median Maximum Minimum Std. dev. Skewness Kurtosis

P (%) 18.39 10.55 49.30 0.60 16.38 0.81 2.15

DE (RM million) 21420.80 12768.00 56095.00 725.00 17869.84 0.48 1.69
HC (Index) 2.34 2.42 3.08 1.50 0.50 -0.17 1.65
GDPPC (RM) 13,329.80 7,794.50 43,708.00 1,087.00 12,552.28 0.9136 2.5349
INF (%) 3.43 2.90 17.33 0.29 2.88 2.71 12.72
K (% to GDP) 27.38 25.21 43.59 17.51 6.65 1.07 3.03

Note: P = poverty rate, DE = development expenditure, HC = human capital, GDPPC = gross domestic
product per capita, INF = inflation rate and K = physical capital.
Source: Authors’ calculation.

Table 2. Correlations

P DE HC GDPPC INF K

P (%) 1.00
DE (RM million) -0.78 1.00
HC (Index) -0.94 0.92 1.00
GDPPC (RM) -0.72 0.94 0.86 1.00
INF (%) 0.49 -0.38 -0.43 -0.36 1.00
K (% to GDP) -0.05 -0.31 -0.24 -0.29 0.18 1.00

Note: P = poverty rate, DE = development expenditure, HC = human capital, GDPPC = gross domestic product
per capita, INF = inflation rate and K = physical capital.

In Table 2, the correlation matrix among the selected macroeconomic variables

stated that P decreased with higher DE at degrees of correlation of -78%, HC -94%,
GDPPC -72% and K -5%, respectively. However, poverty increased with higher INF at
correlation coefficient of 49%.
The unit root tests are based on the results of the augmented Dickey Fuller (ADF)
and Phillips-Perron (PP) tests. The dependent variable was stationary at first difference.
The majority of regressors namely DE, HC, GDPPC and K were stationary at first
difference, while INF was stationary at level, as shown in Table 3. Thus, the research can
proceed with the nonlinear ARDL bounds test to investigate the relationships between
the level of poverty and government development expenditure. This paper focuses on
DE in asymmetry relationships to the level of poverty in Malaysia.
The Brock, Dechert and Scheinkman (BDS) independent test of non-linearity is
shown in Table 4. The BDS test is a non-parametric test designed to look at identical
and independent distributions (IID). When residuals from fitted models are employed,
the BDS test is a general test used to assess the model specification. The results show
that the selected variables have a nonlinear trend in all dimensions at a 1% significance
level, except INF, which has a nonlinear trend at a 10% significance level for m=2 and
m=5; and a 5% level of significance for m=6. The null hypothesis of linearity is rejected,
but the alternative hypothesis is accepted, implying that the variables are nonlinear.

56 Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023

 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

It is worth noting that the defined model of development expenditure and poverty
is suitable for policymaking in Malaysia. In addition, the nonlinear ARDL asymmetry
test reported in Table 5 indicates that the development expenditure variable has an
asymmetric relationship in the long run and short run, where the p-values are less than
0.05. Therefore, the nonlinear ARDL approach is appropriate to analyse the effect of
development expenditure on poverty.

Table 3. Results of unit root tests

Augmented Dickey Fuller (ADF) Phillips-Perron (PP)

Variable Constant Constant Constant Constant

without trend with trend without trend with trend

Level
P -0.2208 -3.3209* -1.4560 -3.3014*
(0.9281) (0.0768) (0.5472) (0.0780)
DE -1.8747 -2.3418 -2.4925 -2.4329
(0.3411) (0.4042) (0.1234) (0.3589)
GDPPC -1.0460 -3.3658* -1.6581 -3.3370*
(0.7291) (0.0680) (0.4458) 0.0723
INF -3.8370*** -4.3478*** -3.8662*** -4.3478***
(0.0048) (0.0060) (0.0044) 0.0060
K -2.5375 -2.6630 -2.5191 -2.5901
(0.1132) (0.2559) (0.1172) (0.2864)
HC -2.1267 -3.1373 -2.1267 -3.1373
(0.2354) (0.1094) (0.2354) (0.1094)

First Difference
P -7.7998*** – -7.6483*** –
(0.0000) (0.0000)
DE -5.4936*** – -5.4871*** –
(0.0000) (0.0000)
GDPPC -6.0968*** – -10.2445*** –
(0.0000) (0.0000)
INF -9.1477*** – -9.3716*** –
(0.0000) (0.0000)
K -5.0398*** – -4.9797*** –
(0.0001) (0.0002)
HC -6.6113*** – -6.6104*** –
(0.0000) (0.0000)

Notes: P = poverty rate, DE = development expenditure, GDPPC = gross domestic product per capita, INF =
inflation rate, K = physical capital and HC = human capital. *, ** and *** denote significance at 10%,
5% and 1% levels, respectively. Figures in parentheses are p-values.

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 57

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

Table 4. BDS independent test of nonlinearity

Variables m=2 m=3 m=4 m=5 m=6

P 0.1580*** 0.2645*** 0.3289*** 0.3719*** 0.3856***

DE 0.1811*** 0.3024*** 0.3838*** 0.4366*** 0.4741***
GDPPC 0.1976*** 0.3310*** 0.4250*** 0.4917*** 0.5400***
INF 0.0247* 0.0265 0.0401 0.0483* 0.0538**
K 0.1422*** 0.2260*** 0.2651*** 0.2808*** 0.2790***
HC 0.1711*** 0.2997*** 0.3760*** 0.4242*** 0.4561***
Notes: P = poverty rate, DE = development expenditure, GDPPC = gross domestic product per capita, INF =
inflation rate, K = physical capital and HC = human capital. *, ** and *** denote significance at 10%,
5% and 1% levels, respectively.

Table 5. Nonlinear ARDL asymmetry statistics

Long-run asymmetry Short-run asymmetry

F-stat (p-value) F-stat (p-value)

Development expenditure 5.594 (0.028)** 6.297 (0.020)**

GDP per capita 0.1614 (0.692) 0.0081 (0.929)
Inflation rate 0.8211 (0.375) 3.944 (0.060)*
Physical capital 3.074 (0.094)* 7.205 (0.014)**
Human capital 0.7224 (0.405) 0.7591 (0.393)

Note: ** and * denote significance at 5% and 10% levels, respectively.

4.1 Cointegration Test

Table 6 gives a summary of the cointegration test. In the model, the focal variable DE
has an F-statistic of 6.00. When compared to the critical values provided by Narayan
(2005) in the table below, it is evident that the F-statistic is more than the 1% upper
bound critical value (i.e., 4.88). This means there is a long run cointegration relationship
between the level of poverty and its determinants, namely DE, GDPPC, INF, K and HC,
across the sample period of 1970 to 2019. This conclusion emphasises the necessity of
accounting for asymmetry when investigating the relationship between these factors.

Table 6. Bound cointegration test

Critical value Lower bound value Upper bound value Computed F-statistics

k = 6, n = 50
1% 3.42 4.88 6.00***
5% 2.55 3.71
10% 2.17 3.22

Notes: *, ** and *** denote significance at 10%, 5% and 1% levels, respectively. Critical values are taken from
Narayan (2005), Table in the Appendix, Case III, p. 1988. K and n are the number of regressors and
observations, respectively.

58 Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023

 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

4.2 Results of Long-run Coefficients

Following the establishment of the cointegration relationship, the next step is to exam-
ine the variables for long-run and short-run asymmetries. Table 7 presents the long-run
coefficients for the nonlinear ARDL model.
Based on the findings for development expenditure, negative development expen-
diture shock has a positive coefficient and is a statistically significant determinant
of poverty in the long run. This means that the poverty level tends to drop when
development expenditure decreases. However, positive development expenditure is
an insignificant determinant of poverty. The findings reflect inefficiency in government
expenditure. The results reflect that not everyone receives aid from the government,
and the allocation does not reach the people on the ground. The results contradicted
the studies on the effectiveness of government expenditure in reducing poverty, such
as Ahmad and Masih (2017), Khasanah et al. (2016) and Sasmal and Sasmal (2016)
which showed that government expenditure recorded a negative and significant impact
on the number of poor people. Ineffective government expenditure in reducing the
poverty level in Malaysia is most probably due to too many regulations in executing the
allocation which deters the impact on the growth of the poverty level. However, some
researchers, such as Kimaro (2018), supported these findings by proving that increas-
ing government expenditure slows economic growth, resulting in a rise in Tanzanian

Table 7. Estimated long-run coefficients

Dependent variable: Rate of poverty (P)
Regressors Coefficient T-ratio
(p-value)
Intercept 28.344*** 15.995
(0.0000)
DE_POS 0.048 0.476
(0.6391)
DE_NEG 0.786*** 3.965
(0.0007)
GDPPC 0.0003 0.002
(0.9987)
INF -0.113* -1.981
(0.0608)
HC -6.594*** 5.673
(0.0000)
K -2.280*** -9.386
(0.0000)

Notes: P = poverty rate, DE = development expenditure,

GDPPC = gross domestic product per capita, INF =
inflation rate, HC = human capital and K = physical
capital. *, ** and *** denote significance at 10%, 5%
and 1% levels, respectively.

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 59

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

poverty. Tanzania’s economic status as a low-income country means it performs less

efficiently than countries with higher incomes. Inflation is negatively associated with
poverty; this indicates that the higher the inflation, poverty tends to increase. Better
human capital and physical investment are significant in reducing poverty. All control
variables have expected signs except inflation.
The model was confirmed and passed by two diagnostic tests, namely the serial
correlation and cumulative sum control (CUSUM) tests. Figure 3 presents the serial
15

10

-5

-10

-15
00 02 04 06 08 10 12 14 16 18

CUSUM 5% Significance

Figure 3. Development expenditure: CUSUM

80

60

40

20

-20

-40

-60
1 3 5 7 9 11 13 15

Multiplier for DE(+)

Multiplier for DE(-)
Asymmetry Plot (with C.I.)

Figure 4. NARDL multiplier graphs

60 Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023

 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

correlation test of the level relation model of long-run estimation for lags 2 and 4,
respectively. The p-values of chi-square statistics are greater than 0.05, which indicate
that there is no serial correlation problem. Additionally, the CUSUM statistics stability
test is plotted to ascertain the significance of trajectory at the 95% confidence bounds.
This is supported by the figure’s rejection of the null hypothesis, which leads to the
conclusion that all the regression parameters are stable. Figure 4 depicts the dynamic
multiplier plot that indicates the positive or negative effect of development expenditure
at a particular time. The negative shock has more effect on poverty as compared to
positive shock.

4.3 Result of Short Run Error Correction Model

In terms of the short run, the earlier three years’ poverty affects the current poverty,
as indicated in Table 8. Increases or decreases in development expenditure did not

Table 8. Short run error correction model

Dependent variable: ΔRate of poverty (P)

Regressors Coefficient T-ratio

(Probability)

Error correction termt–1 -0.294*** -2.913

(0.0000)
ΔPt–1 2.361*** 8.275
(0.0000)
ΔPt–2 1.679*** 6.895
(0.0000)
ΔPt–3 1.592*** 7.401
(0.0000)
ΔDE_POSt 0.409 0.985
(0.3338)
ΔDE_NEGt 0.062 0.102
(0.9194)
ΔGDPPCt 0.656* 1.752
(0.0915)
ΔINFt -0.087 -1.341
(0.1917)
ΔKt -13.311*** -3.625
(0.0012)
ΔHCt 6.456*** 2.833
(0.0000)
Notes: P = poverty rate, DE = development expenditure, GDPPC =
gross domestic product per capita, INF = inflation rate, K =
physical capital and HC = human capital. *, ** and *** denote
significance at 10%, 5% and 1% levels, respectively.

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 61

 Saharudin Yusoff, Siong Hook Law, Norashidah Mohamed Nor and Normaz Wana Ismail

significantly impact on the poverty level. One potential explanation is that development
expenditure needs some time for it to efficiently produce spillover effects in the
economy in the long run. The short-run result is possibly due to the displacement cost
theory in which increased government expenditures displace or crowd out private
sector activities, dampening growth that does not significantly impact the level of
poverty. The current physical investment is a negative and significant determinant of
changes in poverty. However, changes in human capital are a positive and significant
determinant of poverty, where the higher the human capital index, the higher the
poverty. The short-run results are always dynamic processes and therefore, inconsistent
with expected signs. The error-correction term (ECT) has a negative sign, and the
coefficient is less than one and is statistically significant. This implies that any short-run
deviation will adjust to the long-run equilibrium path. The full adjustment will occur at
100%. Therefore, 29.4% convert to 100% is 3.4, or it will take about 3.4 years to move
back to the long-run equilibrium if there is any short-run deviation.

4.4 Robustness Check

Furthermore, robustness checks are also conducted using the variable share of develop-
ment expenditure on gross domestic product. The nonlinear ARDL results confirmed
that the model passed two diagnostic tests, namely the serial correlation and CUSUM
tests. Table 9 presents the long-run cointegration result which reveals that there is
cointegration among the variables even though the government expenditure variable is
replaced by government expenditure over GDP. In the long-run estimation reported in
Table 10, the negative government development expenditure coefficient is statistically
significant at 5% level, which is similar with the findings presented in Table 7. The other
four variables are insignificant determinants of the level of poverty, as reported in
Table 10. Figure 5 shows the CUSUM statistics stability test while Figure 6 depicts the
dynamic multiplier plot that indicates the positive or negative effect of development
expenditure at a particular time. In the short run, it was reported that all variables
are also insignificant determinants of the level of poverty, and earlier poverty affects
current poverty, as presented in Table 11. Moreover, the error correction term (ECT) is
significant and this finding is consistent with the bound cointegration test.

Table 9. Bound cointegration test

Critical value Lower bound value Upper bound value Computed F-statistics

k = 6, n = 50
1% 3.42 4.88 4.05**
5% 2.55 3.71
10% 2.17 3.22

Notes: *, ** and *** denote significance at 10%, 5% and 1% levels, respectively. Critical values are taken from
Narayan (2005), Table in the Appendix, Case III, p. 1988. k and n are the number of regressors and
observations, respectively.

62 Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023

 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

Table 10. Estimated long-run coefficients

Dependent variable: Rate of poverty (P)

Regressors Coefficient T-ratio

(p-value)

Intercept 7.6449 0.7096

(0.4822)
DEGDP_POS 0.4015 0.5229
(0.6040)
DEGDP_NEG 0.1976 2.3334**
(0.0306)
GDPPC -0.3310 -0.4774
(0.6357)
INF -0.0940 -0.6803
(0.5003)
HC -3.9122 -0.6222
(0.5374)
K 0.0429 0.0349
(0.9723)

Notes: P = poverty rate, DE = development expenditure, GDPPC =

gross domestic product per capita, INF = inflation rate, HC =
human capital and K = physical capital. *, ** and *** denote
significance at 10%, 5% and 1% levels, respectively.

20
15
10
5
0
-5
-10
-15
-20
1985 1990 1995 2000 2005 2010 2015

CUSUM 5% Significance

Figure 5. CUSUM plot for development expenditure/GDP

Malaysian Journal of Economic Studies Vol. 60 No. 1, 2023 63

3

-1

-2

-3
1 3 5 7 9 11 13 15

Multiplier for DEGDP(+)

Multiplier for DEGDP(-)
Asymmetry Plot (with C.I.)
Figure 6. Nonlinear ARDL multiplier graphs

Table 11. Short run error correction model

Dependent variable: ΔRate of poverty (P)

Regressors Coefficient T-ratio

(Probability)

Error correction termt-1 -0.6179*** -4.0338

(0.0002)
ΔPt-1 0.3394* 2.0859
(0.0434)
ΔDEGDP_POSt 0.4205 0.6726
(0.5051)
ΔDEGDP_NEGt 0.3941 0.7401
(0.4635)
ΔGDPPCt -0.0301 -0.0637
(0.9495)
ΔINFt -0.0591 -0.7855
(0.4368)
ΔKt -1.0738 -0.5115
(0.6118)
ΔHCt 2.3290 0.2172
(0.8292)

Notes: P = poverty rate, DE = development expenditure, GDPPC =

gross domestic product per capita, INF = inflation rate, K =
physical capital and HC = human capital. *, ** and *** denote
significance at 10%, 5% and 1% levels, respectively.
 Effects of Government Expenditure on the Poverty Level: A Nonlinear ARDL Approach

5. Conclusion
This study investigates the relationship between government development expenditure
and the level of poverty in Malaysia using the nonlinear ARDL approach and time series
data from 1970 to 2019. The empirical results of nonlinear ARDL revealed that increase
in government development expenditure has no significant effect on poverty in the
long run. In the long run, development expenditure has a positive coefficient and is a
statistically significant determinant of poverty. This indicates that higher development
expenditure increases poverty. Therefore, based on this finding, government develop-
ment expenditure should not misuse the resources and should examine the importance
of focusing on proper allocation of fund resources in alleviating poverty. Therefore, this
research recommends that government expenditure should minimise the resources
when producing public goods and services to improve performance and reduce the
poverty level. Some of the federal government expenditures tend to weaken the private
sector and thus reduce economic growth and increase poverty level.
The government’s significant emphasis on dispersing development benefits
throughout all economic sectors must ensure that it impacts on the poverty level.
Government policies should also try to ensure that the benefits of development are
equally distributed among all the groups to ensure social harmony in a plural society.
Every project and program implemented by the government must ensure that it is
conducted in an effective manner, and any leakages must be eliminated. The govern-
ment must pursue a policy of competitiveness and development to help achieve
poverty alleviation targets. To circumvent these economic hazards, this research recom-
mends that the government should embark on a public-private-partnership (PPP) to
substitute for possible negative fiscal multiplier effects. The government should explore
the opportunities of having a stable private sector by establishing and implementing
PPP to enhance strong corporation between the two sectors. The public and private
sectors should coordinate their planning approaches based on how to best use the
resources at hand for the mutual benefit of the two sectors and the entire country.
The reduction of poverty is significantly aided by improved physical and human capital
investments. Theoretically, expenditure on development will boost labour’s capacity
and productivity in curtailing poverty. This is vital, especially in achieving the Shared
Prosperity Vision 2030. For future studies, the research can use state-level datasets to
examine the effect of government expenditure on the poverty level.

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