LITERATURE REVIEW AND THEORETICAL FRAMEWORK 7 1 Literature Review
Theoretical Framework
Public debt, also known as government debt, refers to the total outstanding obligations of a country's government, including bonds and securities, often expressed as a ratio of Gross Domestic Product (GDP) It comprises external debt, which involves commitments to foreign lenders, and internal debt, representing obligations to domestic lenders As public sector debt rises, the government may resort to distorted financing measures, such as the inflation tax, to manage its debt service obligations.
Public debt as a percentage of GDP is commonly used to assess a government's ability to satisfy future obligations
Research indicates that various factors, including government expenditure, GDP growth, interest rates, net foreign direct investment (FDI) inflows, and trade openness, significantly influence public debt levels.
2.2.1 Factors positively affecting Public debt
The initial explanatory variable in the model is the real GDP per capita for the year 2002, referred to as gov_exp Incorporating this variable allows for sample size control and effectively measures the progress of economic catching-up, as highlighted by Kumar & Woo (2010) This approach aligns with the findings of Checherita & Rother.
A study by Baum et al (2013) indicates that GDP significantly influences public debt across six ASEAN countries—Indonesia, Malaysia, the Philippines, Thailand, Singapore, and Vietnam—over a 21-year period from 1995 to 2015 The findings reveal that GDP growth is a crucial macroeconomic factor that impacts public debt both in the short and long term Specifically, GDP growth aids in reducing public debt as economic accumulation leads to increased investments and budget expenditures, which in turn help offset debt and facilitate loan interest payments Thus, the positive correlation between public debt and GDP growth in these countries is clearly established.
Public debt can positively influence economic growth in ASEAN countries when it is managed appropriately, as accumulated debt remains within sustainable limits Government borrowing to finance public spending boosts national productivity, particularly through debt-financed investments in infrastructure While this may increase debt ratios in the short term, the long-term benefits include enhanced productivity and accelerated economic growth.
According to Fincke & Greiner (2014) and Muhammad (2017), Vietnam and other ASEAN countries maintain a public debt-to-GDP ratio that is below the safe threshold However, exceeding this maximum level could negatively impact economic growth To prevent fluctuations in interest rates that could result in a decline in real output, it is crucial to keep public debt accumulation low (Ebi & Imoke, 2017).
Investment openness, reflected by a country's foreign direct investment (FDI) levels, indicates its capacity to attract foreign capital Increased FDI inflows lessen the government's reliance on external borrowing for investment, ultimately reducing government debt Thus, higher FDI levels have a beneficial impact on managing government financial obligations.
Trade openness measures a country's level of engagement in international trade, calculated by summing the values of exports and imports of goods and services and dividing this total by the country's gross domestic product (GDP).
A higher trade openness ratio indicates greater integration with the global economy and increased reliance on foreign markets The impact of trade openness on economic growth and public debt varies based on a country's unique characteristics and the methods used to measure trade openness.
After going through some prior research papers (Yanikkaya, 2003; Jalil and Rauf,
Research from 2021 indicates a significant positive relationship between trade openness and public debt This paper aims to explore and confirm the expectation that increased trade openness correlates with rising public debt levels.
2.2.2 Factors negatively affecting Public debt
Government spending is a crucial element of a country's gross domestic product (GDP), reflecting the total economic output It encompasses expenditures on goods and services, as well as income transfers to individuals and groups through various programs This spending can be divided into two categories: purchases of goods and services and government transfers The structure and magnitude of government spending significantly influence economic performance and social welfare, impacting resource allocation, income distribution, aggregate demand, inflation rates, public debt levels, and the quality of public services Therefore, analyzing the effects of government spending on public debt is essential.
Inflation is a common macroeconomic phenomenon, having profound effects on the economic, political, and social aspects of countries in various stages of economic
MODEL SPECIFICATION AND DATA
Methodology
1.1 Method used to derive the model
Multiple Linear Regression is a statistical method used to model the relationship between a dependent variable and multiple independent variables By employing the Ordinary Least Squares (OLS) method, we can accurately estimate the results of this linear approach.
The Ordinary Least Squares (OLS) method is widely recognized as the simplest and most prevalent technique for estimating parameters in linear regression models, as it minimizes the sum of squared residuals OLS estimates remain consistent when the model adheres to the seven fundamental assumptions of classic linear regression According to the Gauss-Markov theorem, OLS is classified as the Best Linear Unbiased Estimator (BLUE) Therefore, we have chosen to employ the Ordinary Least Squares method to develop the model for our research.
1.2 Method to Collect and Analyze Data
This article analyzes secondary data on the factors influencing government debt in 10 ASEAN countries over a 20-year period from 2002 to 2021 Key variables examined include government expenditure, GDP growth, interest rates, net FDI inflows, inflation rates, and trade openness The data, sourced from the World Data Bank, is recognized for its high precision and reliability.
After collecting data, the team applies the Ordinary Least Squares (OLS) method to analyze it This statistical approach assesses the significance and adequacy of the model based on observations and comparable studies The optimal results obtained will subsequently inform the analysis phase of the investigation.
12 understanding of econometrics 1, macroeconomics, finance, and currency, as well as quantitative techniques using STATA-compatible software and Microsoft Word andExcel to aggregate, handle, and ultimately finish this work.
Theoretical Model Specification
Our research team opted for a multiple regression model (OLS) to assess the impact of various factors on government debt, drawing on both theoretical insights and empirical evidence from prior studies The econometric model employed is structured as follows:
GD = f ( gov exp , gdp growth , interest rate , trade , lninfl , lnforeign inv )
• Dependent variable: gov debt : Government debt (% of GDP)
This article examines the impact of various independent variables on economic performance, focusing on government expenditure as a percentage of GDP, annual GDP growth rates, real interest rates, trade openness relative to GDP, inflation rates, and net foreign direct investment inflows as a percentage of GDP Each of these factors plays a critical role in shaping the economic landscape and influencing overall growth Understanding their interrelationships can provide valuable insights into effective economic policies and strategies for sustainable development.
2.2 Population Regression Model: gov debt =β 0+β 1 × gov exp +β 2 × gdp growth +β 3 ×interest rate +β 4 ×trade+β 5 ×ln(infl)+β 6 ×ln(foreign inv )+u i
• β 1, β 2, β 3, β 4, β 5 , β 6: the regression coefficient of the independent variables
2.3 Sample Regression Model: gov debt = ^β 0+ ^β 1 × gov exp+^β 2 × gdp growth + ^β 3 ×interest rate + ^β 4 ×trade+ ^β 5 ×ln(infl)+ ^β 6 ×ln(foreign inv )+^u i
• ^ β 1, ^ β 2, ^ β 3, ^ β 4, ^ β 5 , ^ β 6: the estimators of the independent variables
Variables Variables Unit Factor names
Expected correlation with dependent variable Dependent variable gov debt % of GDP Government
Independent variable gov exp % of GDP Government
Expenditure +¿−¿ gdp growth Annual % GDP Growth +¿−¿ interest rate % Real Interest
Rate +¿ trade % of GDP Trade
Logarithm of Inflation Rate +¿ ln(foreign inv ) % of GDP
Variable Explanations
- gov debt : Government Debt (% of GDP)
Government debt, also known as public or sovereign debt, represents the financial liabilities of the government sector It arises when the government spends on essential goods and services not offered by the private sector, contributing to the nation's welfare A country's gross government debt mainly reflects borrowing that results from historical government deficits, which happen when expenditures surpass revenues.
In our research, we retrieve data from several ASEAN countries between 2002 and 2021.
- gov exp: Government Expenditure (% of GDP)
Government expenditure refers to the allocation of funds by the government for goods and services The interplay between public spending and public debt is intricate, influenced by various factors including economic conditions, tax rates, and the nature of public expenditures, which can either contribute to an increase or a reduction in public debt.
- gdp growth : GDP Growth (Annual %)
Gross Domestic Product (GDP) is defined as the total monetary value of all finished goods and services produced within a country's borders over a specific period, according to Investopedia GDP growth measures the change in this value over time, expressed as a percentage, by comparing the most recent economic output with that of the previous quarter or year This growth can significantly impact tax revenues, which are essential for managing government debt.
- interest rate : Real Interest Rate (%)
The real interest rate, as defined by Investopedia, is the interest rate adjusted for inflation, providing a clearer picture of the true cost of borrowing and the actual returns for lenders or investors It is calculated by subtracting the inflation rate from the nominal interest rate.
Real interest rate=Nominal interest rate – Rate of inflation(expected casual∨ )
The relationship between real interest rates and government debt is intricate; high real interest rates can lead to reduced government spending due to increased borrowing costs, which in turn diminishes economic growth and tax revenue, complicating debt repayment for the government Conversely, low real interest rates can have the opposite effect, facilitating easier management of government debt.
−trade: Trade Openness (% of GDP)
Trade openness quantifies a nation's integration into the global economy by assessing the total of its imports and exports in relation to its GDP A higher trade openness value signifies that a larger share of the country's economic activity is connected to international trade.
Trade openness plays a multifaceted role in influencing government debt By fostering economic growth, it can enhance tax revenues and lower the debt-to-GDP ratio However, it also risks exposing countries to external shocks, which may result in budget deficits.
Inflation rate measures the increase in prices over time, resulting in a decrease in the purchasing power of money Typically expressed as a percentage, it is calculated by comparing the prices of a basket of goods and services across different time periods.
The relationship between the inflation rate and government debt is complex but generally positive for many reasons Inflation reduces the real value of debt but can
Higher borrowing costs in the future may result from investors predicting rising inflation and demanding greater nominal yields Additionally, increasing levels of debt are expected to contribute to higher inflation rates.
- foreign inv : Net FDI Inflows (% of GDP)
Net Foreign Direct Investment (FDI) inflows, as defined by the World Bank, represent the total value of direct investments made by non-resident investors in a given economy This measure encompasses all transferred assets and liabilities between resident direct investment enterprises and their direct investors.
Net FDI inflows can boost employment rates, leading to increased tax revenue and reduced government debt Conversely, elevated levels of government debt may deter foreign direct investors, making them hesitant to invest in local enterprises.
Data
World Bank: https://data.worldbank.org gov exp gdp growth interest rate trade ln(infl) ln(foreign inv )
Between 2002 and 2021, government debt exhibited a significant shift, ranging from 0 to 195.961 Similar trends were noted in government expenditures, trade openness, and interest rates In contrast, GDP growth, inflation rate, and net FDI inflows showed relatively minor fluctuations, with changes of 33.256, 5.519529, and 6.235703, respectively, between their minimum and maximum values.
4.3 Correlation Matrix between Variables and Interpretations
We analyze the correlation between the variables using command: corr gov_debt gov_exp gdp_growth interest_rate trade lninfl lnforeign_inv
Based on the table, the following patterns can be observed:
The correlation between gov debt and gov exp: r( gov debt , gov exp¿=−0.5210, which is the lowest correlation coefficient and a negative effect on the dependent variable.
The correlation between gov debt and gdp growth : r( gov debt , gdp growth ¿=0.4301, which is the highest correlation coefficient and a positive effect on the dependent variable.
The correlation between gov debt and interest rate : r( gov debt , interest rate ¿=0.2661 , which proves to be a high correlation coefficient and positive effect on the dependent variable.
The correlation between gov debt and trade: r( gov debt , trade¿=0.0112, which is a low correlation coefficient and a positive effect on the dependent variable
The correlation between gov debt and ln(infl): r( gov debt , ln(infl)¿=0.3391, which is a high correlation coefficient and positive effect on the dependent variable.
The correlation between gov debt and ln(foreign inv ): r( gov debt , ln(foreign inv )¿=−0.2105, which is a negative coefficient and negative effect on the dependent variable.
All independent variables have correlation with the dependent variable and are up to expectation Therefore, we should include all variables in the regression model.
Estimation Results, Model Testing and Statistical Inference
OLS Regression and Model Testing
We run a regression model having one dependent variable (gov_debt) and 6 independent variables (gov_exp, gdp_growth, interest_rate, lninfl, lnfor_inv, trade) on Stata 17.
Run the command reg gov_debt gov_exp gdp_growth interest_rate lninfl lnfr_inv trade, we got the result:
Source SS df MS Number of obs
F (6, 133) Prob > F R-squared Adj R-squared Root MSE
5 gov_debt Coef Std Err t P> | t | [95% conf interval] gov_exp -.413611
4 -.2965431 gdp_growth 2.150136 5008037 4.29 0.000 1.159566 3.140707 interest_rate 8144133 1647274 4.94 0.000 4885889 1.140238 lninfl 4.078184 1.1885 3.43 0.001 1.727378 6.42899 lnfor_inv -
1.1 Testing the Overall Significance Level of Model
To evaluate the overall significance of the model, we conducted p-value (F) testing at 1%, 5%, and 10% significance levels, yielding a p-value (F) of 0.0000 This value is less than 0.01, 0.05, and 0.1, indicating that the R-squared is not equal to 0 Consequently, the model demonstrates statistical significance at all three significance levels.
1.2 Testing the Significance Level of Each Independent Variable
At the significance level 5%, if an independent variable has P-value < α=0.05, it means that this independent variable affects the dependent variable.
From the Table 4.1, we got the result:
Variable P-value Affect/do not affect dependent variable (gov_debt)
H0: Model has no omitted variables
Run the ovtest command in STATA for the model which has 6 independent variables, we got the result:
Result: P-value = 0.1725 > α=0.05 → Accept H0 → Model has no omitted variables.
Testing the Model’s Defect
Using the command vif in STATA, we got the result:
As we can see, the value of VIF of each independent variable is lower than 10, implying that the set of data does not face multicollinearity problem.
Testing Breusch-Pagan/Cook-Weisberg for heteroskedasticity
H0: model does not exist heteroskedasticity
Run the command hettest, we got the result:
Re sult: P-value=0.7358> α=0.05 → Accept H0 → Model does not exist heteroskedasticity.
2.3 Testing Normal Distribution of the Residuals
The normality test assesses the likelihood that a random variable in a dataset follows a normal distribution Our team utilized the Skewness and Kurtosis tests to evaluate the distribution of our selected variables.
The normality test helps to determine how likely it is for a random variable underlying the data set to be normally distributed.
Using the command predict u, residuals and sktest u, we got the result:
Result: P-value=0.0822 > α=0.05 → accept H0 → the residuals follow normal distribution
The OLS estimator can be biased when autocorrelation exists in the data, as it leads to violations of underlying assumptions Therefore, it is essential to detect autocorrelation and take appropriate corrective measures to ensure accurate results.
Using the command xtserial gov_debt gov_exp gdp_growth interest_rate trade lninfl lnforeign_inv, we collected the result:
From the result, we can observe that the model exists autocorrelation So, we used the FGLS method in order to fix this defect by using the command xtgls:
So, the model can be accepted because:
All independent variables influence the dependent variable
Model is statistically significance level at 5%
Do not have omitted variables
Do not have multicollinearity error
Do not have heteroskedasticity error
Sample Regression Model and Results Interpretation
According to the estimated result from Stata using OLS method, we obtained the SRF as below: gov debt #.47154−0.4136112× gov exp +2.120136× gd p growth +0.8144133× interest rate +0.1280802× trade+
Explain the general result from the table 4.1
F(6,133)= 29.24 shows the value of F-test with 6 factors and 133 degrees of freedom
Explained sum of squares (ESS) indicates how much of the variation in the dependent variable gov_debt that the model can explain: ESS= 29591.5449 with degree of freedom is k-1=6
Residuals sum of squares (RSS) shows how much of the variation in the dependent variable that the model cannot explain: RSS"431.6785, degree of freedom is n-k3
Total sum of squares (TSS) shows how much variation there is in the dependent variable of the model: TSSR023.2234, degree of freedom is n-19
The R-squared value of 0.5688 indicates that 56.88% of the variation in government debt is accounted for by the six independent variables included in the model, while the remaining variation may be influenced by other factors not considered in this regression analysis Although this figure is not particularly high, it is sufficient to justify further examination of the data.
The analysis reveals that a 1% increase in government expenditure relative to GDP results in a decrease of 0.4136% in government debt, assuming other factors are constant Conversely, a 1% annual increase in GDP growth correlates with a 2.1201% rise in government debt Additionally, a 1% rise in real interest rates leads to a 0.8144% increase in government debt Lastly, a 1% increase in the inflation rate is expected to significantly impact government debt levels.
A 4.08% change in government debt correlates with fluctuations in GDP Specifically, a 1% increase in foreign investment leads to a significant decrease in government debt by approximately 7.04% of GDP Additionally, a 1% rise in trade openness results in a modest increase of 0.13% in government debt as a percentage of GDP.
Conclusion
An analysis of public debt in ASEAN countries from 2002 to 2021 highlights the intricate relationship between economic, political, and global influences During this period of significant economic growth and external challenges, the evolution of public debt was influenced by diverse factors that differed across the region.
The public debt landscape in ASEAN countries from 2002 to 2021 has been shaped by various complex factors Key macroeconomic variables, including GDP growth rates, inflation, and trade openness, significantly influenced public debt levels Strong GDP growth typically enhanced tax revenues and credit access, promoting debt sustainability, while high inflation raised the servicing burden, especially for nations reliant on external financing Additionally, fiscal policies and government spending played critical roles; excessive expenditure on non-productive sectors strained public finances, highlighting the importance of prudent fiscal management and efficient public spending External factors, such as global economic conditions and foreign aid, also affected debt dynamics, with economic downturns increasing borrowing costs, while foreign assistance offered financial relief and debt reduction opportunities for some countries.
As ASEAN nations progress, it is crucial to leverage lessons from the past two decades to guide future policy decisions Balancing economic growth, fiscal stability, and social development presents a significant challenge The region should enhance successful debt management strategies and economic resilience while tackling the distinct issues of each member country A cooperative approach to regional economic collaboration and governance will empower ASEAN nations to effectively address global uncertainties and pursue sustainable development, all while managing public debt responsibly.
While our research report provides valuable insights, it has notable limitations Primarily, it focuses solely on ASEAN countries, which may restrict the applicability of the findings to other regions or populations Additionally, the analysis is based on a limited time frame, potentially compromising the accuracy and relevance of the results.
The analysis highlights the current state of affairs and identifies long-term patterns, but it overlooks demographic factors that could provide valuable insights into the relationship between macroeconomic conditions and public situations Additionally, the use of the OLS approach is limited by our understanding, as a comparison of various methods could yield more accurate results It is also recommended that more specialized data analysis software be utilized for a thorough examination of the collected data Finally, there may be other influencing factors not addressed in this study that affect government debt in ASEAN nations from 2002 to 2021.
Recommendations
Public debt poses a significant challenge for ASEAN countries, highlighting the urgent need for a strategic approach to alleviate its impact Elevated public debt levels can hinder economic growth, restrict fiscal flexibility, and heighten susceptibility to financial crises.
In this essay, we will explore several recommendations for the ASEAN area to effectively decrease its public debt, ensuring long-term fiscal stability and sustainable economic development.
Implementing strict budgetary discipline is crucial for reducing government debt Prioritizing essential spending, imposing rigid budget limits, and cutting unnecessary or ineffective projects are essential actions Additionally, minimizing bureaucratic hurdles, enhancing transparency in public spending, and optimizing government operations will maximize resource allocation and reduce waste By adopting a disciplined financial approach, the government can effectively manage its finances and curb further debt accumulation.
Fostering sustainable economic growth is essential for reducing national debt By encouraging investment, boosting productivity, and supporting innovation, the government can increase revenue and decrease reliance on borrowing Promoting entrepreneurship and supporting small and medium-sized enterprises (SMEs) can enhance the economy, create jobs, and raise tax revenues Furthermore, attracting foreign direct investment (FDI) through favorable policies and incentives can significantly bolster the economy and aid in debt reduction.
The Vietnam government should look for ways to raise tax income in order to reduce the country's national debt This can be accomplished through enhancing tax collecting
To ensure a fair distribution of the tax burden, the government should consider implementing a progressive tax system alongside 27 methods aimed at expanding the tax base and curbing tax evasion and avoidance Additionally, leveraging technology and digital platforms can enhance tax administration by simplifying processes, reducing compliance costs, and improving revenue collection efficiency.
Rationalizing governmental expenditures is essential for reducing public debt, requiring the government to assess funded programs and identify cost-cutting opportunities without compromising essential services This process may involve reevaluating subsidies, updating ineffective social welfare initiatives, and streamlining public procurement procedures By reallocating resources to areas with greater growth potential and societal impact, the government can optimize public finances and contribute to debt reduction.
Effective debt management techniques are crucial for long-term public debt reduction Governments should prioritize borrowing to finance profitable ventures and successful infrastructure projects Responsible borrowing practices, including monitoring debt maturity profiles and diversifying funding sources, are essential for maintaining a healthy debt profile Additionally, implementing robust risk management and debt monitoring frameworks can ensure debt sustainability and mitigate the adverse effects of volatile financial markets.
Reducing public debt is essential for Vietnam's long-term fiscal stability and sustainable economic growth The government can effectively decrease public debt by enhancing fiscal discipline, promoting economic growth, strengthening tax revenues, rationalizing public expenditures, and adopting prudent debt management practices A long-term strategy for debt reduction is vital, balancing fiscal consolidation with investments in key sectors that drive development With a comprehensive and well-executed plan, Vietnam can achieve a more prosperous and financially resilient future.
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