Fiscal Sustainability in Some ASEAN Countries:
Evidence from a Panel Data Analysis
Nguyen Thi Thuy*
National Institute for Finance, Ministry of Finance of Vietnam
Abstract
This paper examines the issue of fiscal sustainability for a panel of eight major Southeast
Asian (ASEAN) countries for the period of 1989-2017. The paper uses both stationarity andcointegration tests to investigate whether fiscal policy in these countries conforms to theintertemporal budget constraints of their public sectors. Overall, the presence of a long-run
relationship between government revenue and expenditure is found but the size of thecointegration slope parameters between revenue and expenditure obtained from the fully
modified OLS (FMOLS) and the dynamic ordinary least squares (DOLS) are significant, lessthan unity, indicating weak form fiscal sustainability. The weak sustainability underscores theneed for commitment to longer-term fiscal discipline and justifies the ongoing efforts by the
ASEAN countries to strengthen their fiscal positions.
Keywords: fiscal sustainability, public debt, intertemporal budget constraint, stationary,
cointegration, FMOLS and DOLS.

*Corresponding author’s e-mail: nguyenthithuy1@mof.gov.vn
1

1.

Introduction
In the context of a society with limited resources, borrowing seems to be a desirable

method that allows governments to finance required expenditures. Government borrowing is
accepted as long as it is consistent with a sound fiscal policy. Maintaining sustainable fiscal
policy has been increasingly important in the scope of economists and policymakers. The
main objective of fiscal sustainability is to provide a country with the macroeconomic
stability to maintain both its budget deficit and public debt within sustainable limits (Ehrhart
and Llorca, 2008). There has been substantial growth in the literature related to fiscal
sustainability over the past few years, especially after the financial crisis that began in the
United States since 2007 and then quickly spread to the EU and the rest of the world.
Negative shocks from the crisis have exposed fiscal vulnerabilities and led to considerable
deterioration in the fiscal positions of a number of these countries, in terms of both highbudget deficits and rising government debt or even calls to other countries and internationalorganisations for assistance in the form of a bailout. Similarly, Japan’s fiscal situation hasreached a critical point with gross government debt surpassing 200 percent (OECD, 2013).
Based on these reasons, issues relating to fiscal and debt sustainability seem pertinent andimportant.
Managing fiscal sustainability prospects is also among the key macroeconomic
management issues in the ASEAN countries. The ASEAN countries now stand at the centerof the most dynamic economic region of the world, and their performance has been part of
the Asian ‘miracle’ that has been well studied by economists and policymakers the world
over (Hicklin et al., 1997). However, a unique characteristic of the ASEAN economies mostbadly damaged by the Asian financial crisis of 1997-1998 (the ASEAN-4: Indonesia,
Malaysia, Philippines, and Thailand) was that fiscal policies and public debt levels had been
relatively sound leading up to the crisis (see, among others, Makin, 1999 and Eichengreen,2002). High and persistent fiscal deficits in ASEAN countries have been a matter of concern
for policymakers and researchers. As a consequence of reforms, ASEAN countries’ fiscal
deficits and public debts are decreasing gradually but remain consistently high (see Table 1).

[Insert Table 1 about here]

Assessment of fiscal sustainability is largely dependent on how it is defined. The mostcommon way of assessing a given economy’s fiscal position is based on the intertemporal2

budget constraint for the public sector, which indicates that a fiscal policy is sustainable when
it is expected to generate sufficient net revenues in the future to repay the accumulated debt
and its service. On the other hand, a fiscal policy becomes unsustainable if the government
intends to finance its future interest expenses by issuing further debt and is unable to generateadequate revenues even via seigniorage. Theoretical approaches that are frequently used in
the literature to assess the sustainability of public policies include fiscal indicators analysis
and intertemporal budget constraint framework. The original literature on fiscal sustainability
based on the constraint approach mostly focused on advanced economies while very few
studies on the sustainability of fiscal policies have been done on developing countries. In
addition, the main analytical techniques used to analyse the sustainability of public finances
have been stationarity tests for the stock of public debt and cointegration tests between
government expenditure and government revenue. Such tests have been performed mostly for
individual countries, which sometimes poses the problem of relatively short time series. The
main advantage of panel unit root tests and panel cointegration analysis is that these methods
increase the power of these tests by including new observations by individual time series tothe panel. Afonso and Rault (2008) highlighted benefits of using panel data including better
properties of the testing procedures in comparison with more basic time series methods.
Most comparable studies have taken into account the possible cross-sectional dependence
among countries when investigating the sustainability of public finances for developed
countries from the EU, Latin America, and OECD. This study, therefore, adds to the limited
literature on developing countries using time series econometric techniques and the intertemporal government budget constraint framework.
The principal purpose of this paper is to examine the sustainability of fiscal policy in a setof eight ASEAN countries covering the period of 1989-2017 by applying recent advances inthe econometrics of non-stationary and cointegration tests. Both the individual and panel
approaches in testing sustainability are applied.
The remainder of this paper is organized as follows. The next section reviews theoreticalbackgrounds, econometric models and empirical literature on fiscal and public debt
sustainability. The following section briefly presents some stylized facts of fiscal policy for
the ASEAN countries and reports empirical tests and assessment of debt and fiscal
sustainability. Finally, Section 4 concludes with an overview of the main findings of thepaper along with the policy implications of those findings.

3

2.

Theoretical Framework of Fiscal Sustainability

2.1. The issues of sustainability
Borrowing is an important tool for both governments and private entities to financeinvestment projects in order to achieve sustainable development, as well as cover short-term
imbalances between revenues and expenditures. Government borrowing can also allow fiscal
policy to play a countercyclical role over economic cycles 1. However, high levels of public
debt are likely to be deleterious for economic growth and sustainable development(Checherita and Rother, 2010). So far, economic literature has not defined a uniquebenchmark against which to assess sustainability and various definitions of fiscal
sustainability are considered.
According to the IMF, debt sustainability is defined as a situation in which a borrower is
expected to be able to continue servicing its debts without an unrealistically large future
correction to the balance of income and expenditure. It does not include any of the following
scenarios: (i) a situation in which a debt restructuring is already needed (or expected to beneeded); (ii) a situation where the borrower keeps on indefinitely accumulating debt fasterthan its capacity to service these debts is growing (a Ponzi game) 2; or (iii) a situation inwhich the borrower lives beyond its means by accumulating debt in the knowledge that amajor retrenchment will be needed to service these debts (even if nothing in the external
environment changes). The cost of financing is a key factor influencing debt accumulation(i.e., the present value budget constraint) and thus sustainability. Sustainability thus
incorporates the concepts of both solvency and liquidity, without making a sharp demarcation
between them. Moreover, the assumption of no expectation of major corrections in income or
expenditure captures the notion that there are social and political limits to adjustment that
determine willingness (as opposed to ability) to pay, which may be especially important in asovereign context (IMF, 2002, p.4).
According to Adams, Ferrarini and Park (2010), fiscal sustainability is the state wherein
the government budget can be smoothly financed without generating explosive increases inpublic debt (or money supply) over time. When this condition is met, the budget is said to besustainable and, conversely, when the condition is not met. They also draw an explicit
distinction between static fiscal sustainability (when the government can be financed1

http://www.un.org/esa/ffd/wp-content/uploads/2016/03/2016-IATF-Chapter2E.pdf
A ‘Ponzi game’ is named after Charles Ponzi who set up a shell company in 1919 that has no business
investment in the United States. He offered investors of the company 40% return in three months by using newinvestors’ money to pay the initial investment to attract more people to invest in his company.
42

smoothly period by period) and dynamic fiscal sustainability (when the budget does not leadover time to explosive increases in public debt). Put another way, static sustainability refers
to the ability of the government to fund its budget period by period (funding liquidity) while
dynamic sustainability is concerned with very long-term fiscal solvency. They conclude thatboth static and dynamic fiscal sustainability are important, and threats to either or both canhave implications for macroeconomic and financial stability.
Balassone and Franco (2000) propose a number of different conditions for sustainability,from a non ever-rising tax rate to an intertemporal discounted budget constraint. One of thefirst definitions of sustainable fiscal policy is that the tax rate should not rise forever. From
Domar’s model, Balassone and Franco derive a necessary condition for sustainability, namely
an ever-growing tax ratio cannot be sustainable; or in other words, sustainability requires a
non ever-rising tax ratio.
According to Mendoza and Oviedo (2003), the term fiscal sustainability means that thepresent value of total government spending equals its revenues. Put in another way, Alvarado
et al. (2004) define as fiscally sustainable a situation that satisfies the two following
conditions: namely, (i) a country can satisfy its budget constraint and (ii) it does not keep
accumulating debt while knowing that a major future adjustment will be needed in order toservice its debt. Theoretically, fiscal sustainability implies that the observed net stock of thegovernment's financial liabilities is consistent with fiscal solvency considerations (Mendoza
and Oviedo, 2003).
Given the intertemporal budget constraint, Buiter (1985) suggests that a fiscal policy issustainable if it maintains the ratio of government net worth to GDP at the present level.
Similarly, Blanchard et al. (1990) define a sustainable fiscal policy as a policy such that thedebt-to-GNP ratio eventually converges back towards its initial level after some excessive
variation. In other words, for a fiscal policy to be sustainable, after having accumulated debt
in the past, the government must run primary surpluses in the future. Similar definitions are
given by Gunter (2003) and Burnside (2003) who define sustainability to mean that a country
can meet its current and future debt service obligations in full without recourse to debt relief,
rescheduling or accumulation of arrears. Also, Ko and Morita (2015) define government debt
as sustainable in so far as the debt hovers at some level.
The definition based on the intertemporal budget constraint is the most widely accepted
and most analytical discussions of fiscal sustainability take as their starting point a
representative agent model in which the government must satisfy both an intertemporal5budget constraint and, in every period, a static budget constraint. According to Hakkio andRush (1991), the government budget constraint for a given period t can be written as:(1)
where Gt is primary government expenditure which excludes interest payments, Rt isgovernment revenue, Bt is government debt, rt is the real interest rate and then (1+ rt) Bt-1 isthe interest payment on the debt. The budget constraint implies that the total government
expenditure (the left-hand side of Equation 1) must be equal to the government revenue andnew borrowings in period t (the right-hand side of Equation 1). Rewriting Equation 1, one
can get the following equation:(2)
in which, (Gt - Rt) is the primary deficit. Assuming that the real interest rate is stationary,with mean r and defining, Equation 2 can be expressed as(3)

Or alternatively,

Rewriting Equation 4 for the subsequent periods of t+1, t+2, t+3… and recursively
solving that equation leads to the following intertemporal budget constraint 3:

As discussed by Hamilton and Flavin (1986) and Hakkio and Rush (1991), the crucial
element in the intertemporal budget constraint is the second term of the right-hand side ofEquation 5 which must equal to zero in order to rule out the possibility that the government
issues new debt to finance its deficit. Following Afonso and Rault (2008), a sustainable fiscal
policy should ensure that the present value of the stock of public debt goes to zero in infinity,
which implies that debt will not grow faster than the real interest rate. In this case, it presents
the absence of Ponzi games and the fulfilment of the intertemporal budget constraint. To
achieve such of condition, the government needs to achieve budget primary surpluses withpresent value equal to the current value of the public debt.
3

The variables of the present value budget constraint are also defined as a percentage of GDP (see, e.g., Hakkio
and Rush, 1991, Goyal et al. 2004; Payne et al. 2008; Afonso and Rault, 2007 and Tronzano, 2013)6

2.2. Assessment of fiscal sustainability
There are a number of methods to evaluate fiscal policy sustainability; however acommon practice in the literature is basically to look at historical fiscal data to examine if
government debt follows a stationary process or if there is cointegration between government
revenue and government expenditure.
Based on the Equation 5, two complementary definitions of fiscal sustainability that set
the background for empirical testing can be presented:
First, the value of public current debt must be equal to the sum of future primary
surpluses:

And second, the present value of public debt must approach zero in infinity:

Based on these above formulations, in order to test empirically the no-Ponzi gamecondition, it is possible to test the stationarity of the first difference of the stock of public debt
using unit root tests. Another approach assessing fiscal policy sustainability is throughcointegration tests. The implicit hypothesis concerning the real interest rate, with mean r, isalso stationarity. We re-use the auxiliary variable G’t = Gt + (rt – r) Bt-1, and the additional
definition GGt = Gt +rt Bt-1, the intertemporal budget constraint can also be written as

and with the absence of Ponzi games, GGt and Rt must be cointegrated variables oforder one for their first differences to be stationary.
It is assumed that R and G’ are stationary variables at the first difference level. It alsomeans that the series R and G’ in levels are I(1). In order to hold the Equation 8, its left-handside will also have to be stationary. If GG and R are integrated of order 1, these two variables
should be cointegrated with cointegration vector (1,-1) for the left-hand side of Equation 8 to
be stationary.

7Consequently, the sustainability of the intertemporal government budget constraint can bemeasured by the cointegration regression between government revenue and expenditure as
the following equation:(9)This approach enables us to examine the stability of fiscal deficit. If the null of no
cointegration, the hypothesis that the two I(1) variables are not cointegrated, is rejected, this
implies that government revenue and expenditure are cointegrated. In this case, the series of
the residual ut must be stationary and does not contain a unit root.
There are several conclusions concerning the intertemporal budget constraint. Hakkio andRush (1991) point out that if there is cointegration between government revenue andexpenditure with 0 < b ≤ 1, then the condition that prevents a Ponzi game situation issatisfied. In this mode, the value of b is defined as the degree of sustainability. If 0 < b < 1,
we have ‘weak’ sustainability; meanwhile b = 1 presents ‘strong’ sustainability orsustainability in the strict sense. In economic terms, ‘weak’ sustainability means that the
government responds to the increase in public debt but the adjustments are not equal to thegrowth of public expenditure. As a result, we may see an unsteady increase of fiscal deficit
and public debt. Afonso (2004) also demonstrates that three cases may happen: (i) when there
is no cointegration, the fiscal deficit is not sustainable; (ii) when there is cointegration with b= 1, the deficit is sustainable and (iii) when there is cointegration with b < 1, government
expenditures grow faster than government revenues and the deficit may not be sustainable.
However, Quintos (1995) states that 0 < b ≤ 1 would be a necessary and sufficientcondition for the fiscal sustainability, and the presence of a cointegration relationshipbetween Rt and GGt is also a sufficient condition for fiscal sustainability. In this case, thegovernment may spend more than it raises, which will consequently impose high risk ofincreasing fiscal deficit or having to offer a higher interest rate when it puts its debt on themarket. Thus, this situation seems to be not in accordance with the possibility that the
government might market its debt in the long-run (Carrion-i-Silvestre, 2014).
2.3. Literature review
Since the early 1990s, there has been an important emergence of empirical literature
dealing with the issue of debt sustainability. The econometric literature testing the present
value budget constraint focuses on the time series properties of government expenditures andtax revenues, budget deficits and the level of public debt. As mentioned above, the empirical8

literature has followed two different approaches to test fiscal sustainability. The first rests
mainly on a univariate-based approach or testing stationarity of the various fiscal variables;
while the second, a multivariate-based approach employs cointegration techniques andexplores the existence of a long-run equilibrium relationship between government revenue
and expenditure.
A number of papers have concentrated on the first framework of examining the stationary
properties of fiscal balance. Based on this method, if the deficit or public debt series exhibits
non-stationarity, subsequent debt will also grow without bound over time which renders
fiscal policy unsustainable. A stationary deficit means that the series is reverting to a certain
mean over time being in general close zero. If that were the case, then obviously fiscal policy
and debt would be sustainable, since deficits will be under control. Hamilton and Flavin(1986) use yearly data for the United States, covering the period 1962-1984 to investigate
whether the post-war U.S. deficits are largely consistent with the proposition that the
government budget must be balanced in present-value terms. The paper concludes that the
hypothesis of a unit root of the deficit and outstanding debt can be rejected for both processes.
However, the test results seem to be fairly weak. They reject the null hypothesis of a unit rootat 10 percent significant level and employ short time series of only 22 annual observations
which may have low power. Trehan and Walsh (1988) also use the annual data for the UnitedStates exploiting the period of 1890 - 1986. The paper focuses on the deficit inclusive ofinterest which is in contrast to recent studies using the deficit exclusive of interest. The
empirical results suggest that the government’s budget is consistent with intertemporalbudget balance. In the next paper of Trehan and Walsh (1991), they test the stationary of
public debt and deficits from 1960 to 1984 and draw the similar conclusion of fiscal
sustainability. Wilcox (1989) evaluates the sustainability of fiscal policy using the stationary
test of public debt between 1960 and 1984. The finding suggests that recent fiscal policy in
the United States has not been sustainable which contrasts with those of Hamilton and Flavin(1986).
Within the same framework, the stationary test of deficits and public debt is conducted
for other countries to see whether fiscal policy is sustainable or not. For instance, Corsetti andRoubini (1991) verify the fiscal sustainability using a large sample of 18 OECD countries forthe period 1960-1989. The results show that among the G-7 countries, public sector solvency
seems a serious issue in Italy while does not appear to be a problem in a number of OECD
countries such as Germany, Japan, France, the United Kingdom and Canada. The evidence
for the United States is mixed. Problems of sustainability of the current path of fiscal policies
9are also present in Belgium, Ireland, the Netherlands, and Greece. Buiter and Patel (1992) test
the sustainability of public sector debt in India with data for 1971–1989. They contend
overall public sector debt was unsustainable irrespective of the alternative interest rate.
Uctum and Wickens (1997), using annual data of government debt for the United States andEU countries for the period 1965-1994, find that many countries do not have a sustainable
policy.
In the second framework, cointegration tests were used to explore whether there is a longrun relationship between government revenue and expense. If such a relationship exists, thismeans that the respective government is not spending without bound and is taking into
account the amount of revenues it is generating and fiscal policy is sustainable. Hakkio andRush (1991) use quarterly values for revenues and expenditure, in 1950: II-1988: IV for theUnited States. The test results show that government spending was growing faster thangovernment revenue. It also supports the hypothesis that deficits have become a problem only
in recent years. Liu and Tanner (1995) also conducts the tests for the cointegration of interestinclusive expenditure and revenue and found that U.S. debt is sustainable. Similarly, using
quarterly data covering the period 1947: II-1992: III, Quintos (1995) finds that U.S. debt issustainable until 1980. The cointegration test is also employed for other economies. Payne(1997) examines the sustainability of budget deficits of the G-7 countries between 1949 and1994. It is revealed that in the cases of Canada, Italy, the United Kingdom, and the UnitedStates cointegration is present between revenues and expenditures. However, the estimatedcoefficients are significantly less than one which suggests ‘weak’ fiscal sustainability. For
France, Japan, and Italy the budget deficits of these countries may not be sustainable due tothe lack of cointegration. In order to investigate the causality relationship between Romanianpublic expenditure and revenue, Stoian (2008) uses the quarterly data from 1991 to 2005. The
results reveal that there is a correction mechanism which forces budgetary expenditure andrevenue to be in equilibrium over the long term and not to cause large fiscal imbalances. The
cointegration test is also applied to assess public debt and fiscal sustainability in developing
countries. For example, Bui et al. (2015) perform an analysis of Vietnam’s fiscal and public
debt sustainability. The findings demonstrate that no sustainability, as well as potential risk,
is reflected by Vietnam public debt and fiscal policy.
The empirical studies show that most of the stationarity analyses in the past were
performed for individual countries, resulting in the problem of short time series. Since formany countries available time series are insufficient for the study of many hypotheses ofinterest, unit root tests are often unable to reject the null hypothesis of no stationarity simply
10because the actual mean-reverting behaviour is slow and takes several years to complete(Krajewski et al., 2016). Recent literature deals with the cross-sectional analysis of fiscal
sustainability by applying panel data methods that have a number of advantages, asmentioned above. In recent years methods based on panel data are more commonly used toassess fiscal sustainability. Modern panel analyses of cointegration and stationarity have been
implemented. For example, Afonso and Rault (2008) apply modern panel cointegration
techniques to a structural long-run equation between general government expenditure andrevenue. The paper concludes that fiscal policy was sustainable both for the EU15 panel set,
and within sub-periods (1970-1991 and 1992-2006). Westerlund and Prohl (2010) use thepanel cointegration test on government revenue and expenditure for eight rich OECD
countries between 1997: I to 2005: IV. The results reported that the sustainability hypothesis
cannot be rejected. Similarly, Campo-Robledo and Melo-Velandia (2011) evaluate the fiscal
sustainability hypothesis for eight Latin American countries for the period 1960-2009,
including Argentina, Chile, Colombia, Ecuador, Panama, Peru, Paraguay and Uruguay using
second generation cointegration panel data models. The empirical evidence shows the weaksustainability of primary deficit for these Latin American countries. Afonso and Jalles (2012)
revisit the issue of fiscal sustainability in 18 OECD countries over the period 1970-2010,
employing the unit root and cointegration analysis, both country and panel based. They
conclude that fiscal policy has been unsustainable for many countries in the sample. In order
to assess fiscal sustainability for a selected group of ten Central and Eastern European (CEE)
countries in two periods: an inclusive full sample period (1990-2012), and a pre-crisis subsample (1990-2008), Krajewski et al. (2016) use the panel stationarity test for public debt andthe cointegration test between revenue and total expenditure, inclusive interest payments.
They find that both panel stationarity tests and the presence of panel cointegration between
revenues and expenditures support the notion of sustainability in CEE countries. However,
the estimation results show sustainability only in a weak sense, which may pose a threat to
public finances in the futures.
Very few studies on fiscal sustainability apply panel stationarity and cointegration tests
for developing Asian countries. First, Lau and Baharumshah (2005) investigate the issue offiscal sustainability by adopting families of panel unit root tests for a panel of 10 Asian
countries including India, Indonesia, Korea, Malaysia, Nepal, Pakistan, Philippines,
Singapore, Sri Lanka, and Thailand for the period 1970-2003. They find favorable evidenceof mean-reverting behaviour for the cluster of Asian-10 countries by adopting the commonlyused panel unit root technique; while using the series-specific unit root test, they found that11

four out of ten countries (Korea, Malaysia, Singapore and Thailand) are stationary,suggesting little evidence of fiscal sustainability in these Asian countries. Then, Adedeji andThornton (2010) exploit panel unit root and cointegration techniques and employed adynamic ordinary least squares (DOLS) model to distinguish between ‘strong’ and ‘weak’sustainability for five Asian countries–India, Pakistan, Philippines, Sri Lanka, Thailand–forthe period 1974-2001. The results indicate that government revenue and expenditure in apanel of these economies were non-stationary and cointegrated series. However, thecointegration coefficient is significantly less than unity, indicating ‘weak’ fiscal sustainability
and the likelihood that policy measures would be required to put public finances on a moresustainable basis. Syed et al. (2014) explore the issue of sustainability of fiscal policy for ten
Asian countries. The pool of 10 countries is further divided into a pool of SAARC countries
and a pool of IMT-GT countries 4. The results of panel cointegration between government
revenue and expenditure showed that fiscal policy is sustainable in the case of SAARC
countries whereas it is not sustainable in IMT-GT countries. Sharstri et al. (2017) examine
sustainability of public finances for five major South Asian economies namely, Bangladesh,
India, Nepal, Pakistan, and Sri Lanka for the period 1985-2014. The empirical results
demonstrate coherence with intertemporal budget constraint for these countries. However, inview of the weakly sustainable fiscal stance, the results also suggest that these countries,
except for Bangladesh, need to reinforce commitments to long-term fiscal discipline.
Table 2 summarizes the conclusions of these papers. Overall, the analysis conducted inthis paper is interesting in as much as it increases the empirical evidence focusing on the
ASEAN countries. The approach adopted in this paper has not yet been implemented inprevious studies in the case of the ASEAN countries.

[Insert Table 2 about here]
3.

Empirical Analysis

3.1. Stylised Facts and Data Overview
The sustainability of fiscal policy is evaluated for a sample of eight ASEAN countries:
Cambodia, Indonesia, Lao, Malaysia, Myanmar, Philippines, Thailand and Vietnam. The
4

Although the SAARC includes eight countries, including, Afghanistan, Bangladesh, Bhutan, India, Maldives,
Nepal, Pakistan and Sri Lanka, but due to scarcity of the data, the authors had to exclude Afghanistan and Nepal.
Therefore, henceforth the SAARC* represents all the countries in SAARC except Afghanistan and Nepal.
Furthermore, the IMT-GT includes only three countries, that is Indonesia, Malaysia, and Thailand, but theauthors added Singapore in this panel in order to increase the number of countries.
12

research uses annual data drawn from the International Monetary Fund’s World Economic
Outlook Database. The analysis conducted uses annual time series covering the period 19892017 for each of the variables. The countries are selected according to data availability. The
variables of government debt, revenue and expenditure are measured in terms of their ratio tonominal GDP. Table 3 reports the list of countries, the corresponding period and summary
statistics for these variables.

[Insert Table 3 about here]

The Asian financial crisis of 1997-1998 refers to a macroeconomic shock from capitaloutflows that subsequently contributed to currency crises experienced by most of the ASEAN
countries, including Indonesia, Malaysia, Philippines, and Thailand. In the years after thecrisis, overall budget balances measured as a proportion of GDP have deteriorated markedly
in the ASEAN economies, turning pre-crisis fiscal surpluses to deficits that remain high by
the standards of developed economies (Makin, 2005). All ASEAN countries have posted highand persistent deficits since 2000. Most notably, Malaysia’s average budget deficit was 4.3
percent of GDP during 2000-2017, followed by Cambodia of 3.7 percent of GDP, and Lao of
3.5 percent of GDP (ADB, 2018). Government debt increased significantly because ASEAN
governments actively deployed fiscal policy as a post-crisis, counter-cyclical measure toboost domestic demand in the context of a global economic slowdown. Accelerated domestic
financial liberalization also facilitated issuance of public debt instruments in home markets
over this time (Makin, 2005). The highest government debt-to-GDP ratios were recorded in
Myanmar in 2001 with 216 percent, Lao in 2002 with 99 percent and Indonesia in 2000 with
87 percent. The average government revenue-to-GDP ratio of eight ASEAN countries was
18.5 percent meanwhile the average government expenditure-to-GDP was recorded at 20.7
percent.
3.2. Testing for individual stationarity
At a first step, the standard augmented Dickey-Fuller (ADF) tests including trend and no
trend are used to preliminarily assess the stationarity of the time series of public debt. Using
the classic method proposed by Hamilton and Flavin (1986), the time series were run for bothlevels and first differences. For public debt, both I(0) and I(1), the tests indicate fiscal
sustainability. In the case of I(1), Quintos (1995) shows that it is a weak sustainability.
13

The early and pioneering work on testing for a unit root in time series was done by
Dickey and Fuller (Dickey and Fuller 1979). The tests are based on the following set-up:(10)
where ρ is a parameter to be estimated and the ut are assumed to be white noise. If≥ 1,

the series is non-stationary and the variance of Y increases with time and approaches infinity.
Otherwise, the series is stationary if< 1.

One of the most popular of these tests is the ADF test which is carried out by estimating
Equation 10 after subtracting Yt-1 from both sides of the equation to then get the following
form:
(11)
in which δ = ρ - 1. The null hypothesis H0 is δ = 0 or ρ = 1, meaning Y has a unit root orin other words, Y is non-stationary. In contrast, the alternative hypothesis H1 is δ ≠ 0 or ρ < 1which means that Y does not have a unit root or Y is stationary.
[Insert Table 4 about here]

Table 4 presents the results of the ADF tests for individual time series of debt. It can beseen that in most of the cases, government debts are non-stationary with trend and no trend,
except Thailand and Malaysia, for which the ADF tests indicate strong sustainability for bothcases of deterministic.
According to Hamilton and Flavin (1986), the stationarity of public debt is a sufficient,albeit not necessary, condition for fiscal sustainability. The absence of Ponzi game is stillsatisfied if debt is integrated of order one. For the further step, it is possible to test for the firstdifferences of the government debt series. Both I(0) and I(1) of public debt present fiscal
sustainability. In the latter case, Quintos (1995) denotes it as a weak sustainability5. Table 5
provides the results of individual ADF tests for first differences of government debt.

[Insert Table 5 about here]5

Bergman (2001) showed that sufficient condition for government solvency is that government debt is
integrated of any finite order.
14

When it comes to testing government debt at the first difference level, the results are morevaried compared to the previous case. There is some evidence for each country showing thatthe government debt time series are difference-stationary, which suggests fiscal sustainability
in a weak sense.
Bohn (2005) provides a formal proof that fiscal policy is sustainable if the time series ofpublic debt is integrated of any infinite order. It means that it is possible to test for public
debt being I(2) or even I(3) and arrive at stationary cases after differencing the available timeseries a sufficient number of times. However, such an approach appears uncertain for thefollowing two reasons. First, the number of observations may reduce after differencing thetime series. In such short samples, as those under consideration, the tests are widely known tohave low power, thus it is difficult to draw conclusions based on this method only.
Furthermore, since the order of integration is not predetermined, such an approach distorts
the final size of the test sequence (Krajewski et al., 2016).
In addition, Neaime (2004) suggests that the stationarity and cointegration-based tests ofdebt sustainability ideally should employ long time series (say 30–50 annual observations) on
various macroeconomic variables. Consequently, instead of further differencing or using a
cointegration test for the individual time series, it is better to apply panel-based methods totest for the presence of sustainability for the group of eight ASEAN countries.
3.3. Panel stationarity tests
The first step is to analyse the time series properties of the data to determine the persistenceof the revenue, expenditure and public debt series. A number of panel unit root tests
advocated by Levin, Lin and Chu (2002) (LLC), Im, Pesaran and Shin (2003) (IPS), Breitung(2000), Maddala and Wu (1999) (ADF Fisher) and Choi (2001) (PP Fisher) are used to test
the stationarity of the government debt, revenue and expenditure. Basically, these tests areextensions of the traditional ADF test. In the case of panel data, the ADF test is based on
estimating the following equation:(for i = 1, 2, …, N and t = 1, 2, …, T)(12)which is basically an extension of Equation 11 across individuals, denoted by subscript i.
The LLC and Breitung tests both assume that there is a common unit root process. Under theassumption, the null of H0: δi = δ = 0 for all i is tested against the alternative hypothesis, H1:
δi = δ < 0 for all i. Based on the null hypothesis, there is a unit root, while under thealternative, there is no unit root.
15

The IPS and the ADF Fisher and PP Fisher tests all allow the possibility of varying
autoregressive processes across individuals, and therefore uses the group-mean of individualt-statistics in statistical inference. The IPS test examines the null of H0: δ1 = δ2 =…= δN = 0(each individual time series in the panel contains a unit root) against the alternative H1: δi < 0for at least one i (at least one of the individual series in the panel is stationary). On theassumption that N cross-section units are independently distributed, the t-statistic can becomputed as an average of the individual ADF t-statistics such that
=

/N

(13)

Where tiT denotes the ith individual t-statistic for testing δi = 0 in each individual ADF
regression. In a further step, the above t-bar statistic is standardized so that it converges to a
standard normal distribution, as N increases. A key strength of this test is that δi is allowed todiffer across countries and only a fraction of panel members is required to be stationary under
the alternative hypothesis. The IPS test been widely implemented in empirical research due to
its rather simple methodology and alternative hypothesis of heterogeneity. This test assumes
cross-sectional independence among panel units (except for common time effects), but allows
for heterogeneity in the form of individual deterministic effects (constant and/or linear timetrend), and heterogeneous serial correlation structure of the error terms.
In the MWC test, the null and alternative hypotheses are as similar as those of the IPS test.
If Pi is defined as the asymptotic p-value from any individual unit root test for cross-section i,then under the null of unit root for all N cross-sections, it may have the result that:→or P has a χ2 distribution with 2N degrees of freedom.

In addition, Choi (2001) demonstrates that

where Φdenotes the standard normal cumulative distribution function.
In this paper, the estimation procedures incorporate the non-stationary panel unit-root test
proposed by Levin, Lin and Chu (2002), Im, Pesaran and Shin (2003), Breitung (2000),
Fisher-type tests using ADF and PP tests (Maddala and Wu (1999) and Choi (2001)),
conducted for both levels and first differences of government revenue, expenditure and debt.
It is also conducted for without and with a time trend. The results from the unit root tests forpanel data using a sample of eight ASEAN countries are detailed in Table 6.

[Insert Table 6 about here]16

As shown in table 6, for the series of government debt at level, most of the tests, namely
IPS, MW and Breitung tests, support the null hypothesis of unit root: i.e. the government debt
is non-stationary and possesses a unit root at level. However, the null hypothesis is rejectedon the basis of 5% and 1% levels of significance by the LLC and Choi tests respectively. In
the case of small N and T, IPS (1997) suggested that t-bar test has better performance. They
proposed a cross-sectionally demeaned version of both test to be used in the case where theerrors in different regressions contain a common time-specific component. Thus, moreevidence shows that government debt in the analysed sample is not an I(0) process.
In order to test for the presence of weak sustainability, the application of the same batteryof tests to first differences of government debt is repeated. All the tests rejected the null
hypothesis at all conventional levels of significance; or in other words, the debt series weredifference-stationary, which indicates that fiscal policy in the ASEAN countries was weakly
sustainable.
For the variables of government revenue and expenditure, the presence of unit root inthese series strongly indicates that the variables are not stationary in levels. To test the orderof integration, the panel unit root tests are then applied at first difference. Based on thefurther tests, the results confirm that the variables are difference-stationary. It can beconcluded that the government revenue and expenditure-to-GDP ratios have been found to be
integrated of order 1 or I(1). All the preceding results lead to examine whether government
revenue and expenditure ratios are cointegrated in a panel perspective.
3.4. Panel cointegration test on government revenue and expenditure
Since cointegration tests typically require long samples, it is not feasible to draw
conclusions based on individual tests. Instead, it is better to implement a battery of tests forthe whole panel, consisting of our group of eight countries. Thus, the next step is to test forexistence of a long-run cointegration between government revenue and expenditure in thepanel using Pedroni (1999 and 2004) and Kao (1999), who propose a range of statistics thatcan be used to determine the presence of cointegration in heterogeneous panels. In each case,the t-statistics are constructed using the residuals from the following hypothesized
cointegrating equation:(for i = 1, 2, …, N and t = 1, 2, …, T)

17

(14)

Where a allows the cointegrating regression to include country-specific fixed effects, b is
the long-run coefficient, and u is a residual term. Under the null hypothesis of no
cointegration, the residual uit will be I(1). The structure of estimated residual is as follows:
or

(15)

where λi is the autoregressive coefficient of the residual uit from the Equation (15).
Pedroni (1999) panel cointegration test
Pedroni describes various methods of constructing statistics for testing the null hypothesisof no cointegration (λi = 1). There are two alternative hypotheses, namely the homogenous
alternative, H1: (λi = λ) < 1 for all i (in the case of panel cointegration tests based on withindimension statistics), and the heterogeneous alternative, H1: λi < 1 for all i (in the case ofgroup mean cointegration tests based on between-dimension statistics)
Based on various methods, Pedroni (1999) derives four panel cointegration statistics. The
first category of four statistics is classified as panel cointegration statistics, which presume acommon value for the unit root coefficient and are based on within-dimension statistics. It
includes a variance ratio statistic, a non-parametric Phillips and Perron type ρ-statistic, a nonparametric Phillips and Perron type t-statistic, and a Dickey–Fuller type t-statistic. The
second category of three panel cointegration statistics is defined as group mean panel
cointegration statistics, which allow for differences in this parameter and are based on
between-dimension statistics. The set includes, in this case, a Phillips and Perron type ρstatistic, a Phillips and Perron type t-statistic and finally an Augmented Dickey-Fuller type tstatistic. All these statistics are distributed as asymptotically normal.
Kao (1999) panel cointegration test
Kao’s residual panel cointegration test is based on the assumption that homogeneous
slope coefficients exists across countries (Kao, 1999). Hence, the null hypothesis of no
cointegration, H0: ρ = 1, is tested against the alternative hypothesis of stationary residuals,
H1: ρ < 1. Kao presents four DF-type statistics. The first two DF statistics are based onassuming strict exogeneity of the regressors with respect to the errors in the equation, while
the remaining two allow for endogeneity of the regressors. Kao also proposes an ADF test
statistic. The asymptotic distributions of all tests converge to a standard normal distribution
N(0, 1) and T →and N →.

Table 7 contains the test results of panel cointegration employing Pedroni (1999, 2004)
and Kao (1999) for the full period 1989 - 2017.
18

[Insert Table 7 about here]

First, for testing the cointegration between government revenue and expenditure whenneither intercept nor trend was used as deterministic specification, the null hypothesis of nocointegration was rejected by most of the statistics (10 out of 11 statistics) under the Pedroni
test. For the other two cases, the null hypothesis of no cointegration is rejected by the panel tand group t- statistics (both are non-parametric) at 5% significance level (except the case ofindividual intercept, the group PP-statistic rejects the null hypothesis at the 10% significancelevel). It was also accepted by the ρ-statistic. Pedroni (2004) carried out Monte Carlosimulations and concluded that in short samples (in this case, T=29 and N=8), panel t- andgroup t- statistics generally performed best. Thus, it is possible to conclude that the null
hypothesis of no cointegration is rejected by using Pedroni’s tests.
According to Gutierrez (2003), the author shows that Kao’s test has higher power thanPedroni’s tests when a small-T number of observations are included in the panel.
Consequently, in order to assess the robustness of the findings, Kao’s test is also
implemented. The conclusion of Kao’s test confirmed the existence of a long-run relationshipbetween government revenue and expenditure ratios for the set of ASEAN eight countries at
1% level of significance.
3.5. Estimation of cointegrating relationship
Finally, as the null hypothesis of no cointegration between the series is rejected, thecoefficient of the long-run relationship between government revenue and expenditure can be
estimated. Quintos (1995) distinguishes between a strong and a weak definition of fiscal
sustainability. Assuming that government revenue and expenditure are both I(1), strong
coefficient b is unity. Weak solvency occurs when b is less than unity. In the context ofrevenue and expenditure ratios to GDP, Hakkio and Rush (1991) and Cipollini (2001) argue
that only the strong condition is appropriate to assess fiscal sustainability as the weak
condition may be satisfied but the government still could have difficulty financing a fiscal
deficit if the expenditure-to-GDP ratio continuously exceeds the revenue-to-GDP ratio.

19With a view to estimate the parameter b in the Equation 14 6, two different methods, theFully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Squares(DOLS) are implemented. When the series are non-stationary, specific panel cointegration
techniques should be used. In the case of homogeneous and near-homogeneous panels, thecointegration can be estimated by a fully modified (FM) estimator Phillips and Hansen(1990). This method is non-parametric as it employs kernel estimators of the nuisanceparameters affecting the asymptotic distribution of the OLS estimator. It addresses thepossible issue of endogeneity of the regressors as well as the autocorrelation of residuals.
Alternatively, the DOLS procedure, proposed by Kao and Chiang (2000), Mark and Sul(1999, 2003) and Pedroni (2001), is parametric and has the advantage of computing
convenience (Bodart et al., 2011). Based on Monte Carlo simulations, Kao and Chiang(2001) concluded that the DOLS outperforms both the OLS and the FMOLS estimators infinite samples in terms of unbiased estimation. The DOLS estimator also has an additional
advantage in controlling the endogeneity in the model, as augmentation with the lead andlagged differences of the regressor suppress the endogenous feedback. Thus, the DOLS
estimation method provides a robust correction of endogeneity in the explanatory variables.
However, this paper applies both FMOLS and DOLS since the cointegrated regression model
which was composed of series having a long-term relationship between each other showeddeviating results when it was estimated by least squares method. The estimates of the longrun coefficient are reported in the Table 8.

[Insert Table 8 about here]

The results clearly suggest the existence of a long-run cointegrating relationship between
government revenue and expenditure that is statistically significant. For all four versions of
the estimations, the average of the estimated slopes is 0.889, meaning that, on average, a 1%change in government expenditure leads to a 0.889 % change in government revenue for theconsidered group of eight ASEAN countries. Note that all these cases point estimates of slope
parameters are highly significant. The close values of long-run coefficients for all estimations
confirm the robustness of the estimated results

The DOLS procedure involves running the following regression: Rit = ai + biGGit +ΔGGi,t+j + εit
where t = 1, …, T and i = 1, …, N. Equation () includes the leads and lags of ΔGGit in the cointegrating
regressions to produce asymptotically unbiased estimators which typically chosen using some info criterion.
20
6

Further Wald tests on the model reject both the null hypothesis of b = 0 and b = 1 at theconventional significant levels. A 1% increase in government expenditure causes government
revenue to increase by less than 1%, which implies that although sustainable fiscal positions
are feasible, governments in the region spend more than they receive in revenue, suggestingthat these governments must be cautious with their public finances. By extension, it also
implies that if governments spend at a lower rate compared to their ability to raise revenues in
the long-run, so that government revenue and expenditure are one-to-one, then the strongform sustainability can be confirmed and there would be no cause for alarm about the future
course of a fiscal deficit situation.
To sum up, in the case of the panel eight ASEAN countries, the empirical tests show thattwo non-stationary variables, government revenue and expenditure, are cointegrated andfiscal policy can be judged sustainable only in the weak form. This result appears broadly inaccordance with the existing literature on emerging and developing countries.
4.

Conclusion and policy implications

4.1. Conclusion
This paper has closely assessed the fiscal sustainability of public finance for eight
ASEAN countries including Cambodia, Indonesia, Lao, Malaysia, Myanmar, Philippines,
Thailand, and Vietnam by exploiting the data for the period 1989-2017. Starting from thepresent value borrowing constraint of governments, the study investigates past fiscal data to
see if the government debt to GDP follows a stationary process and if there is cointegration
between government revenue and government expenditure as a percentage of GDP.
The econometric methods employed in the paper include both time series and panel datatechniques, namely (i) individual unit root tests of the government debt of each country; (ii)panel data unit root tests of the government debt and (iii) the panel data cointegration tests
proposed by Pedroni (1999, 2004) and Kao (1999). Finally, the FMOLS and DOLS models
are also applied to investigate the degree of fiscal sustainability.
Three methods have come to the same conclusion. First, the results from the individual
unit root test point to the non-stationarity of the debt series (with the exceptions of Malaysia
and Thailand) but stationarity of the first-difference debt for most countries suggesting thatthe solvency condition would be satisfied in the weak sense. Second, panel unit root tests
show that fiscal debt series were difference-stationary, which suggests that fiscal policy in the
ASEAN countries was not sustainable in a strong sense for the analysed period. On the basis
21

of panel cointegration tests, the estimation results show that government revenue andexpenditure exhibit common movements in the long run. Nevertheless, the relationshipbetween these variables is not one to one. This condition means that, although there is a longrun relationship, the cointegration coefficient is lower than unity, which means that the
governments are spending more than they are collecting. Overall, the evidences provide
broad support for a weakly sustainable fiscal policy in line with the recent literature.
The contribution of this paper is twofold. First, it has covered a larger number of
emerging and developing countries in Southeast Asia than previous studies in contributing to
the empirical literature on fiscal sustainability for ASEAN countries, a topic that has attracted
the attention of researchers and economists. Second, from a methodology point of view, amore accurate evaluation of the degree of fiscal sustainability is achieved through thecomparison of parameter estimates of the cointegrating vectors obtained from alternative
econometric methodologies. The FMOLS and DOLS estimation techniques have been used,which are robust against asymptotic endogeneity and serial correlation. Using both groupedmean and pooled FMOLS and DOLS to estimate the fiscal sustainability of countries, theresults reflect consideration about the problem of heterogeneous panel and fill some gaps inprevious studies.
This study has several areas for improvement. First, relevant to the intertemporalgovernment budget constraint, the tests of the hypothesis that the fiscal sustainability
condition holds in a country is based on historical time-series data. These tests are notdesigned to link the observed underlying sources of macroeconomic uncertainty with the
dynamics of public debt in order to provide short- and long-run, forward-looking measures ofsustainable public debt ratios (Mendoza and Oviedo, 2004). Second, it is now wellestablished that examining time series for the presence of structural breaks is an importantcomponent of any empirical analysis. Indeed, the standard unit root tests have serious power
distortions in the presence of structural breaks (Afonso, 2007). Consequently, further studies
should be undertaken on the sustainability of fiscal policy with fiscal reforms comprising a
structural break.
4.2. Policy implications
A number of important policy implications emerge from the empirical analysis. The firstand foremost policy message is that weak fiscal sustainability in the aforementioned countries
reflects government expenditures systematically higher than government revenues. This
results in high and persistent fiscal deficits, and puts upward pressure on the stock of debt. If
22fiscal policy were to be conducted in the future as it was in the past, there could still be someproblems. In order to reduce the debt to more prudent levels or maintain the debt on asustainable path, governments require a steady decline in fiscal deficits or primary budget
surpluses. To this end, governments could either raise more revenues or moderate theirexpenditure concurrently. To achieve the first option, revenue reforms could be pursued via
increasing tax rates, widening the tax base, and strengthening tax administration, as
implemented in a number of countries. For example, Thailand has a range of reform options
to gradually strengthen tax revenue, including an increase in the amount of tax revenue
collected from the VAT 7. In Lao, a number of measures to improve revenue collection andbroaden the tax base should be implemented, including enforcing compliance of tax and duty
exemptions and VAT deductibles, and focusing on large taxpayers and taxes on vehicles,
petrol, and luxury goods (ADB, 2018). On the expenditure side, reform efforts should aim atmoderating current expenditure, restructuring the spending structure, improving theeffectiveness of public expenditure and its allocation. In the Vietnamese current context, withthe high level of government expenditure to GDP and the rising proportion of recurrent
expenditure 8 , it is important to rationalize spending, adjust the diversification of public
investments under the principle of fiscal sustainability to boost economic growth, supportsocioeconomic development, and provide a more effective mechanism for strict control overpublic expenditure.
The second policy message from the analysis is that ASEAN countries need to improve
public debt management. According to the IMF (2018), average public debt in these countries
is not projected to decline significantly in the upcoming years due to an increase ininvestment demands, unexpected rises in interest rates, or sharp currency depreciations,which may severely endanger public debt sustainability in the future. Among the ASEAN
countries, the public debt to GDP ratios of Indonesia, Malaysia, and Thailand seem to havestabilized and appear more manageable; meanwhile a high and increasing public debt poses a
key risk in Lao 9 . In order to curb the rising public debt, along with fiscal reforms, Lao
authorities should strengthen the country’s public debt management and establish more

7

In Thailand, the existing VAT rate of 7 percent is relatively low in comparison with regional peers and otherparts of the world.
8
According to the World Bank (2017), from 2011-2015, Vietnam’s total state budget expenditure – including
capital outlays financed by oﬀ-budget bonds – averaged 29.2 percent. The proportion of recurrent to capital
expenditure was 70:30, compared to 65:35 from 2006-10.
9According to the IMF (2018), the ratio of public debt to GPD of Lao PDR was projected to rise from 63.58
percent in 2017 to 68.19 percent in 2020 and 69.67 percent in 2023.
23

transparent loan cycles. Furthermore, growing exposure to rollover, exchange rate, andinterest rate risks should be closely monitored in these countries.
Another important policy implication is that regional policymakers should continue togive high priority to improving or adopting fiscal rules. Fiscal rules specify numerical targets
for key budgetary aggregates such as annual government deficits, debts or spending. The goalof fiscal rules is to improve fiscal discipline and reduce government deficits and debts. The
use of fiscal rules is on average associated with improved fiscal performance (IMF, 2009) 10.
The database of fiscal rules constructed by the IMF (2017) shows that among emerging anddeveloping ASEAN countries, only Indonesia and Malaysia adopt fiscal rules 11.
Last but not least, this paper examines fiscal sustainability using the explicit government
debt, the flows of government revenue and expenditure; but it is important to note that theexistence of contingent liabilities and fiscal burdens arising from population ageing 12 arelikely to add to the vulnerability of the fiscal positions of these ASEAN countries. As a result,the need to rebuild fiscal space to deal with contingent liability shocks remains, given theworsening demographics in future.

10

In fact, many countries have introduced fiscal rules. The European Union, by Treaty, established fiscal rulesin the early 1990s, with the goal of ensuring that all members would maintain sustainable fiscal policies, which
specified that countries should keep their government deficits at or below 3 percent of GDP, and thatgovernment debt should not exceed 60 percent of GDP. A number of other economies, in Europe and elsewhere,
seemed to have found fiscal rules to be helpful in achieving greater budget disciplines. According to the IMF(2017), about 80 countries currently are subject to national or supranational fiscal rules.
11
Following Schaechter et al. (2012), the database includes all rules with specific numerical targets fixed inlegislation, as well as fiscal arrangements for which the targets can be revised but are binding for a minimum of
three years. Thus, the medium-term budgetary frameworks or expenditure ceilings that provide multi-year
projections are not considered as fiscal rules because they can be changed annually. There are four main types offiscal rules, namely debt rules, budget balance rules, expenditure rules, or revenue rules according to theaggregate targeted. Debt rules set an explicit limit or target for public debt in percent of GDP. Budget balance
rules set a limit on the overall balance (including or net of capital expenditures), the structural or cyclicallyadjusted balance, and the balance ‘over the cycle’. Expenditure rules set limits on total, primary, or current
spending while revenue rules set ceilings on revenues.
12
According to ASEAN and United Nations data, with the exception of the Philippines, the proportion of people
over the age of 65 in ASEAN is expected to triple from 2015 to 2050 (ERIA, 2017).
24

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64. Schaechter, A., Kinda, T., Budina, N., Weber, A., 2012. Fiscal rules in response to thecrisis - toward the ‘next-generation’ rules. A new dataset. International Monetary
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65. Shastri, S., Giri, A.K., Mohapatra, G., 2017. Budget deficit sustainability and revenue
expenditure linkages in major South Asian economies. Eurasian Journal of Businessand Economics. 10, 19, 37-59.
66. Stoian, A., 2008. Analysing causality between Romania’s public budget expendituresand revenues. Theoretical and Applied Economics. 11, 60-64.
67. Syed, M.S., Mariani, A.M., Syed, H.S., 2014. Assessing fiscal sustainability for
SAARC and IMT-GT countries. Romanian Journal of Fiscal Policy. 5, 2(9), 26-40.
68. Trehan, B., Wash, C.E., 1988. Common trends, the government's budget constraint,
and revenue smoothing. Journal of Economic Dynamics and Control. 12, 2-3, 425444.
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Credit and Banking. 23, 2, 206-223.
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71. Uctum, M., Wickens, M., 1997. Debt and deficit ceilings and sustainability of fiscal
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72. Westerlund, J., Prohl, S., 2010. Panel cointegration tests of the sustainability
hypothesis in rich OECD countries. Applied Economics. 42, 11, 1355-1364.
29

73. Wilcox, D., 1989. The sustainability of government deficits: implications of thepresent-value borrowing constraint. Journal of Money, Credit and Banking. 21, 3,
291-306.
74. World Bank, 2017. Vietnam public expenditure review.

30

Table 1: Overall Budget Deficit and Government Debt in ASEAN Countries from 20002017
2000
2005
2010
2011 2012
Overall Budget Deficit (as percentage of GDP)
Cambodia
-2.1
-0.7
-8.8
-7.6
-6.8
Indonesia
-1.1
-0.5
-0.7
-1.1
-1.8
Lao
-4.6
-4.5
-2.2
-1.6
-1
Malaysia
-5.5
-3.4
-5.3
-4.7
-4.3
Myanmar
0.7
n/a
-4.6
-3.8
1.6
Philippines
-3.7
-2.6
-3.5
-2.0
-2.3
Thailand
-2.8
0.1
-2.9
-1.6
-2.2
Vietnam
-4.3
-1.0
-2.1
-0.5
-3.4
Government Debt (as percentage of GDP)
Cambodia
35.2
36.2
28.7
29.7
31.5
Indonesia
87.4
42.6
24.5
23.1
23.0
Lao
n/a
75.8
55.1
50.8
55.2
Malaysia
32.9
41.4
51.9
52.6
54.6
Myanmar146.6 110.4
49.6
46.1
40.7
Philippines
61.1
67.4
49.7
47.5
47.9
Thailand
57.8
45.5
39.8
39.1
41.9
Vietnam
31.4
36.5
48.1
44.7
48.4

2013

2014

2015

2016

2017

-6.9
-2.2
-5.2
-3.8
-1.4
-1.4
-0.6
-5.0

-3.8
-2.1
-3.2
-3.4
-1.1
-0.6
-1.8
-4.4

-2.6
-2.6
-3.8
-3.2
-4.3
-0.9
-1.2
-4.3

-2.7
-2.5
-4.4
-3.1
-2.6
-2.4
-0.7
-4.2

-3.1
-2.9
-5.4
-3.0
-5.7
-2.2
n/a
-3.5

31.6
24.8
54.3
56.4
33.2
45.7
42.2
52.0

31.8
24.7
58.6
56.2
29.9
42.1
43.3
55.0

30.9
27.5
58.1
57.9
34.5
41.5
42.5
57.4

29.1
28.3
58.4
56.2
35.7
39.0
41.8
59.9

30.4
28.8
63.6
54.1
33.6
39.9
41.9
58.5

Sources: ADB and IMF, 201831

Table 2: Some Empirical Evidence regarding Fiscal Policy Sustainability
Author and date

Country - Period

Time Series Study
Hamilton andU.S.
Flavin (1985)(1962-1984)

Data
Frequency
AnnualMethods

Deficit andpublic debt
stationary
Deficit andpublic debt
stationary
Public debt
stationary
Cointegration

Yes

Yes for Germany,
Japan, France, theUnited Kingdom
and Canada. No
for Italy, Belgium,
Ireland, theNetherlands, andGreece, etc. Mixed
evidence for the
U.S.
No

Trehan and Walsh(1988, 1991)

U.S. (1890-1986
and 1960-1984)

AnnualWilcox (1989)

U.S.
(1960-1984)
U.S. (1950: II1988: IV)
18 OECD
countries(1960-1989)

AnnualAnnualPublic debt
stationaryIndia(1971-1989)
U.S.
(1950-1989)
U.S. (1947:21992:3)
U.S. and EU(1965-1994)
G-7 - 1949-1994

AnnualPublic debt
stationary

Romani (19912005)
Vietnam (19902013 for debt and1985-2013 forrevenue andexpenditure)

Hakkio and Rush
(1991)
Corsetti andRoubini (1991)

Buiter and Patel(1992)
Liu and Tanner(1995)
Quintos (1995)
Uctum and
Wickens (1997)
Payne (1997)
Stoian (2008)
Bui et al. (2015)

Panel Data Studies
Lau and
10 Asian
Baharumshahcountries (1970(2005)
2003)
Afonso and Rault(2008)

15 EU Countries(1970-2006
within sub-Quarterly

Sustainability

AnnualYesNoNo

Yes (with breaks in
1982)
Yes till 1980

Quarterly

Cointegration

AnnualAnnualGovernment
debt stationary
Cointegration

AnnualCointegration

AnnualPublic debt
stationary andcointegration

No

AnnualPanelstationary

AnnualPanelcointegration

Yes when applying
commonly usedpanel unit root
techniquesYes

32

No for many
countries
Yes only for
GermanyYesperiods of 19701991 and 19922006)
Westerlund and
08 OECD
Prohl
countries(2010)(1977Q12005Q4)
Adedeji and
5 Asia Countries
Thornton (2010)(India,Pakistan, thePhilippines, Sri
Lanka andThailand)
1974-2001
Campo-Robledo
08 Latinand Melo-Velandia American(2011)
countries:
Argentina, Chile,
Colombia,
Ecuador, Panama,
Peru, Paraguay
and Uruguay(1960-2009)
Afonso and Jalles
18 OECD(2012)
countries (19702010)

Quarterly

Panelcointegration

Yes

AnnualPanelcointegration

Yes (weaksustainability)

Annual.

Panelcointegration

Yes (weaksustainability)

AnnualBoth timeseries andpanel stationary
andcointegration
Panelcointegration

No for many
countries

Syed et al. (2014)

10 Asiancountries (19902010)

AnnualKrajewski,
Mackiewicz and
Szymańska (2016)

A selected groupof tenCentral andEastern European
countries (19902012)05 major South
Asian countries(1985-2014)

AnnualPanelstationarity andcointegration

AnnualPanelcointegration

Sharstri, Giri and
Mohapatra (2017)

Yes for SAARC
countries and No
for IMT-GT
countries
Yes (weaksustainability)

Yes (weaksustainability)

Source: Author’s construction

33

Table 3: Country Coverage and Statistical Summary for Fiscal Variables, 1989-2017(as percentage of GDP)
No. ofobservations
Government Debt
Cambodia
22
Indonesia
18
Lao17
Malaysia
28
Myanmar20
Philippines
25
Thailand
22
Vietnam18
Government Revenue
Cambodia
22
Indonesia
25
Lao18
Malaysia
28
Myanmar21
Philippines
29
Thailand
23
Vietnam20
Government ExpenditureCambodia
22
Indonesia
25
Lao18
Malaysia
28
Myanmar21
Philippines
29
Thailand
23
Vietnam
20
Country

Coverage

Mean

Std. dev.

Max

Min.

1996 - 20172000 - 20172001 - 20171990 - 2017
1998 - 20171993 - 20171996 - 20172000 - 2017

33.03
39.04
66.87
47.11
86.88
56.05
43.49
44.37

4.46
19.25
16.74
11.23
55.94
10.84
9.19
9.19

43.10
87.44
99.16
75.18
216.04
76.08
57.83
59.94

26.99
22.96
50.81
30.04
29.91
39.03
15.19
31.43

1996 - 20171993 - 20172000 - 20171990 - 20171997 - 20171989 - 20171995 - 2017
1998 - 2017

13.98
15.63
16.51
24.48
13.75
18.52
20.25
23.79

4.46
1.93
3.46
2.98
4.62
1.29
1.37
2.22

21.38
19.45
21.41
31.11
21.97
21.30
22.31
27.26

8.05
12.47
11.51
19.61
8.50
14.49
17.46
19.63

1996 - 20171993 - 20172000 - 20171990 - 20171997 - 20171989 - 20171995 - 2017
1998 - 2017

17.28
16.68
19.88
26.73
17.20
19.58
21.07
26.85

3.75
23.24
12.33
2.22
19.51
11.51
3.65
26.10
13.80
2.69
33.64
22.52
4.12
23.48
12.18
1.29
21.75
16.18
2.30
26.47
17.18
3.05
31.61
20.34
Source: IMF and ADB (2018)34

Table 4: ADF Tests of Government Debt for Individual Countries
Sample: 1989-2017
Total Number of Observations: 170
Intercept
Deterministict-statProb.
Cambodia-2.070037
0.2575Indonesia-2.292388
0.1856Lao-2.427962
0.1501
Malaysia-2.802939*
0.0711
Myanmar-2.335193
0.1745
Philippines-0.965896
0.7476
Thailand-4.132302***0.0047
Vietnam
0.754756
0.989Intercept and Trendt-statProb.
-2.806384
0.211-2.370906
0.3757-0.069009
0.9901-3.989171**
0.0216-1.019114
0.9136-1.898383
0.6228-5.943868***0.0005-2.569192
0.296

Note: MacKinnon values for rejection of hypothesis of a unit root at 1% level (***), 5%
level (**) and 10% level (*).

35

Table 5: ADF Tests for First Differences of Government Debt for Individual Countries
Sample: 1989-2017
Total number of observations: 170
Intercept
Deterministict-statProb.
Cambodia-3.107579*
0.0422Indonesia-1.399198
0.5497
Lao-0.900056
0.7565
Malaysia-2.811682*
0.0704Myanmar-4.466258***
0.0035
Philippines-3.959587***
0.0063Thailand-5.812275***0.0001
Vietnam-4.399768***
0.0044

Intercept and trend
t-statProb.
-3.023599
0.1504-4.273392**
0.0214-3.789246**
0.0476-2.98946
0.1538-5.173999***
0.0037-3.870347**
0.0307-5.007021***0.0037-4.533252***
0.0139Note: MacKinnon values for rejection of hypothesis of a unit root at 1% level (***), 5%
level (**) and 10% level (*).

36

Table 6: Panel Unit Root Test Result of the Fiscal Variables

Sample: 1989 – 2017
Level

First Level Difference

Public Debt

Revenue

Expenditure

Public debt

Revenue

Expenditure-1.62952**( 0.0516)-0.67103( 0.2511)

0.51035( 0.6951)
0.32519( 0.6275)-0.93293( 0.1754)-1.21735( 0.1117)-3.22932***( 0.0006)-4.37279***( 0.0000)-1.21695( 0.1118)-3.91902***(0.0000)-4.88557***( 0.0000)-5.99765***( 0.0000)

12.3304( 0.7209)

22.3212( 0.1331)

50.8125***( 0.0000)

45.0221***( 0.0001)

66.3477***( 0.0000)

21.3305( 0.1662)

32.7895***( 0.0079)

87.2074***( 0.0000)

121.538***( 0.0000)

164.287***( 0.0000)

0.62742( 0.7348)
0.17227( 0.5684)-0.47479( 0.3175)-0.20073( 0.4205)-2.54335***( 0.0055)-3.79641***( 0.0001)

1.26634( 0.8973)-1.90820**( 0.0282)-3.67637***( 0.0001)-4.50181***( 0.0000)

13.3713( 0.6454)

15.2123( 0.5091)

42.3458***( 0.0004)

28.0336**( 0.0313)

49.8148***(0.0000)

17.2856( 0.3674)

24.9326*( 0.0710)

85.5765***( 0.0000)

97.7951***( 0.0000)

159.881***( 0.0000)-0.53740( 0.2955)-0.65223( 0.2571)-2.28164**(0.0113)-2.88352***( 0.0020)-4.25704***( 0.0000)Intercept
LLC
IPS

MW-ADF20.0159
Fisher
( 0.2195)
Chi-square
Choi-PP47.0222***
Fisher Chi( 0.0001)
squareIntercept and Trend-2.00334**
LLC( 0.0226)-0.48801
IPS( 0.3128)
MW-ADF18.1544
Fisher
( 0.3149)
Chi-square
Choi-PP46.5081***
Fisher Chi( 0.0001)
square1.17676
Breitung( 0.8804)
t -statNote: *, **, *** indicates rejection of the null hypothesis of a unit root at 10%, 5% and 1%,
levels of significance. The p-values are in c.

37

Table 7: Panel Cointegration Tests, 1989-2017

Pedroni (1999, 2004) Engle-Granger Based Cointegration Test
Panel Statistic
Group Statistic
Statistic
Weighted Statistic
Statistic
Deterministic Specification: Individual Intercept
0.631852
0.672257( 0.2637)( 0.2507)
V-statistic-1.473633*-1.420397*-0.345906( 0.0703)( 0.0777)( 0.3647)
Rho-statistic-2.034499**-1.868591**-1.526736*( 0.0210)( 0.0308)( 0.0634)
PP-statistic-0.461455-0.296649
0.123717( 0.3222)( 0.3834)( 0.5492)
ADF-statistic
Deterministic Specification: Constant & Trend
0.003391-0.165520( 0.4986)( 0.5657)
V-statistic-0.586272-0.768135(
0.2788)( 0.2212)
Rho-statistic-2.110140**-2.255461**(0.0174)( 0.0121)
PP-statistic-0.309480-0.582810(
0.3785)( 0.2800)
ADF-statistic
Deterministic Specification: No Constant & Trend
1.604687*
1.004218(
0.0543)(0.1576)
V-statistic-3.778273***-4.283910***(0.0001)( 0.0000)
Rho-statistic-3.483134***-3.796752***( 0.0002)( 0.0001)
PP-statistic-2.642071***-3.211381***( 0.0041)( 0.0007)
ADF-statistic

0.390816( 0.6520)-1.990003**( 0.0233)-0.343685( 0.3655)-1.510270*( 0.0655)-3.451615***( 0.0003)-2.301851**( 0.0107)

Kao (1999) Residual Cointegration Test, Ho: No cointegrationt-Statistic-2.707225***
ADF(0.0034)
Note: ***, ** and * indicate 1%, 5% and 10% level of significance respectively. The pvalues are in parentheses.

38

Table 8: Estimation of the cointegrating coefficient
FMOLS
PooledGrouped0.897160.883913
77.0236***95.73238***(0.0000)(0.0000)1781780.777873
0.780352

Pooled
0.893314
74.7861***(0.0000)
162
0.845744Grouped
0.88272
86.20750***(0.0000)
162
0.841067b=0

77.02360***( 0.0000)

95.73238***( 0.0000)

74.78610***( 0.0000)

86.20750***( 0.0000)b=1-8.829104***( 0.0000)-12.57282***( 0.0000)-8.931473***( 0.0000)-11.45376***( 0.0000)

Estimation Method
Long-run coefficientt-statistic
No. of observations
R-squared adjusted

DOLS

Note: ***, ** and * indicate 1%, 5% and 10% level of significance respectively. The pvalues are in parentheses. Pooled estimation performs FMOLS and DOLS on the pooled
sample after removing the deterministic components from both the dependent variable andthe regressors. Grouped mean estimation computes the cross-section average of the individualcross section FMOLS and DOLS estimates.

39Annex: Data Sources

All data was taken from the International Monetary Fund’s World Economic Outlook
Database, updated on October 9th, 2018.

-

General Government Gross Debt (percent of GDP)-

General Government Revenue (percent of GDP)-

General Government Expenditure (percent of GDP)40