The Impact of Government Expenditure on Economic Growth: A Study of SAARC Countries ()
1. Introduction
For decades, there has been a debate over whether government expenditure has any impact on economic growth, and It hasn’t yet been made perfectly apparent as of yet. This article provides further evidence related to this debate whether general government expenditure has any relation to economic growth from the perspective of SAARC countries. This paper emphasizes evaluating the probable relationship among the selected variables such as GDP and general government expenditure like communication, education, industry, development. The study puts light on the factors that work to the development of the growth of the country and characteristics that are not. Additionally, the components of the government spending contribute to the acceleration of the country’s economic development. It is necessary to perform several functional areas in order to come to the conclusion of the relationship among the variables. The rising government expenditure often does not always turn into better economic performance for many countries (Nurudeen and Usman, 2010) . According to the Keynesian hypothesis, it is increasing government expenditure results in accelerating economic growth. Therefore, the expenditures of the government constitute an external factor that affects aggregate production (Loizides & Vamvoukas, 2005) . On the other hand, Wagner (1883) found that higher government expenditure is a spontaneous consequence of rising GDP. However, there are a number of research studies that have been carried on both the Law and found conflicting results for different countries. Government expenditure is often focused on reducing poverty (Fan, Hazell, & Thorat, 2000) . Now it is a much-debated issue considering the relationship between these variables. It is crucial to understand whether government expenditure has contributed to economic growth in SAARC countries or it is the opposite of it.
If our policymakers and their counterparts elsewhere read this study, they will know whether or not public spending has been excessively used in the past and present to foster economic growth, or whether or not this has the potential to harm the local market as a result of either higher taxes or increased government taking on debt from overseas countries. Through this study, it is expected to uncover many unfulfilled gaps related to this issue in SAARC countries. From this point on, the primary purpose of this study is to investigate the influence that public spending has on economic development in SAARC countries during the course of the study’s time period, which spans the years 2011 to 2020. The methodology includes econometrical techniques of co-relation, Panel fixed model, and granger causality in adherence to panel data of SAARC countries; among eight members of SAARC, due to data inadequacy, I took five countries (Bangladesh, Pakistan, Sri Lanka, India, and Bhutan) to conduct the study. Here, I used data on different related studies as the input to the research study. I have used data from UNCTAD, the Ministry of Finance website of selected countries, macro trends, world bank, exchange rate. The U. K., Bangladesh bank, and other necessary documents for the successful completion of the research study. Then time series data are appropriately analyzed to reach the decision. Data analyses were conducted through regression model, correlation, granger causality and co-integration test, that is enough for the evaluation to find whether government expenditure has impact on economic growth in SAARC countries.
2. Literature Review
This section discusses the scholarly analysis of their papers. Here, we will see a breakdown of different arguments and counterarguments provided by various scholars. From the argument and counterargument that has been provided, the close relationships among the dependent and independent variables are appropriately analyzed. There have been a significant number of research papers that have been published in an effort to ascertain the correct link that exists between governmental expenditure and GDP in both emerging nations and mature economies. These research studies have used a variety of theories/concepts in the specification of the model, as well as other research methodologies, and the findings of those studies have shown that the impact of government expenditure on economic growth can go either in a negative or positive direction. These findings are very related to the economic theories provided by Keynes and Wagner, which show two different states of the impact of government expenditure on a country’s economic development. According to the Keynesian theory, economic growth in a country arises as a result of an increase in public sector expenditure. Here, government expenditure is acted as an independent variable and could be used as an influential policy variable to affect economic growth. Keynesian school of theory suggests that a proactive fiscal policy is a crucial weapon available to the governments to accelerate economic activity and economic development Shafuda & De (2020) . Furthermore, Keynesian theory argues that government spending of any kind, even if recurrent, may stimulate economic expansion. Whether or not government spending competes with private consumption and investment determines how successful fiscal policy is in stabilizing aggregate demand. When government expenditure rises without corresponding tax or fee increases, a budget imbalance emerges. A negative outcome for domestic interest rates may result from the financing of the budget deficit through the issuance of domestic debt, which would result in a reduction in private expenditure (Kandil, 2000) . A simple monetary policy to finance the budget deficit may result in the formation of inflationary expectations as a result of credit and liquidity expansion, which may result in higher nominal interest rates, thereby hurting private consumption and investment (Loizides & Vamvoukas, 2005) . To keep from running deficits, the private sector may have to fight for funds that would have gone toward investing in capital goods and buying consumer goods. Wagner (1883) on the other hand, believes that government expenditure is an endogenous factor, rather than a cause, of economic growth in his view. His hypothesis can be expressed mathematically as Gt = f (Y t), where G denotes the size of the public sector, which reflects the level of government spending, and Y denotes the rate of economic growth in a given country. With a few words added in for good measure, Wagner’s Law states that government spending increases as the economy of a country develops and grows.
However, except from the two hypotheses of Keynes and Wagner, The results of Solow’s (1956) neoclassical growth model show that government expenditure has no long-run influence on economic growth. The neoclassical growth models imply that fiscal policies do not result in changes in the long-run enhancement of output. The long-run growth rate, according to this theory, is determined by three factors: population growth, labor force growth, and the degree of technological advancement, all of which are determined exogenously.
Ghura (1995) conducted a study in which he used time-series data and cross-sectional data from 33 countries in Sub-Saharan Africa for the period 1970-1990, and the results revealed that there is a negative relationship between government spending and GDP.
While Ghura (1995) found that government spending on capital structures had no effect on economic growth, who utilized the same sample area and looked at the same time period (1987-1997), found the opposite to be true (1995). Finally, he suggested that these nations enhance government spending on capital structure and try to create a more advantageous economic climate for their inhabitants. Tang (2009) found support for Wagner’s Law in his research, stating that government expenditure is co-integrated with N. I., whereas this is not the case for total health expenditure. He recognized three major components of public expenditure: education, defense, and health.
The well-being, interest in instruction, water supply, streets, power are needs that can keep the economy from the initial stage to the take-off stage of monetary and economic advancement, making the federal government invest and spend some with energy, bearing in mind the final goal to establish a libertarian culture. However, the natives of the country are less willing to pay taxes. The legislature’s obstruction of care in the form of increased spending in order to keep a strategic distance from economic, social emergencies. The lack of pay imposed by the public will result in the country having a poor income since the expense of demonstrating additional offices will be paid by the administration, causing government consumption to increase rapidly.
Federal governments can counteract a slowdown in economic activity by increasing government spending and/or lowering taxes; as a result, fiscal policy is regarded as a counter-cyclical policy tool that helps to mitigate short-run fluctuations in output and employment levels (Zagler and Durnecker, 2003) .
Using an endogenous growth model, Barro (1989) asserts that government consumption expenditure is negatively related to economic growth. He goes on to say that while government consumption causes distortions, it does not give a countervailing stimulus to investment and development. Furthermore, he noted that growth has little to do with the amount of government investment spending—his research from 1990 backs up his prior conclusions. Government spending on investment and economic activity, he said, should boost GDP, whereas government consumer spending is expected to slow it down. However, in empirical studies, determining which expenditures should be classified as an investment and which as consumption is problematic.
Taking data spanning from 1995 to 2005, Alexiou (2009) investigated the Impact of a series of variables on economic growth in seven nations in the South-Eastern Europe region. Private investment, capital formation, a proxy for trade openness, and development assistance all these variables have significant and positive effects on economic growth, according to the research, but the population is increasing, but it is statistically insignificant. Finally, he believes that by creating a favorable environment, policymakers can encourage private business investment, capital formation, and trade openness in the economy Attari & Javed (2013) . In terms of developing countries, they investigated the relationship between inflation, GDP, and government spending in Pakistan, one of Asia’s emerging countries. They divided government spending into two categories in their study: current government spending and development spending. The investigation was carried out utilizing time-series data from 1980 to 2010 using a variety of econometric approaches. The results show that although the factor of government public spending is statistically insignificant, the factor of development expenditure is quite significant. It proves the positive externalities and linkages that result from government expenditure. Economic growth is not affected by inflation in the shorter term, but it is affected by government spending in the long run. Finally, they stated that many challenges are confronting developing-country governments, such as resource usage and misallocation, and that if government expenditures are used in excess, excessive capital spending becomes worthless at the margin. Alshahrani & Alsadiq (2014) conducted another investigation that found a positive relationship between variables. They looked at the impact of various types of government spending on Saudi Arabia’s economic growth. They use several econometric tools, like the Vector Error Correction Model, to see the long- and short-run effects of expenditures on development (VECM). They discovered that private domestic and governmental investments, also healthcare expenditure, increase growth in the long run, using time-series data from 1969 to 2010. A further finding of the study was that trade openness and choosing to spend in the housing sector both increase short-term output. Butkiewicz & Yanıkkaya (2008) examined the effects of government spending on economic growth using a much larger sample size, with a particular focus on how the usefulness of the government affects the efficiency of government spending.
The data set includes over 100 industrialized and developing countries, and the model is estimated using the Seemingly Unrelated Regression (SUR) technique. The results showed that overall expenditures had a negative growth effect, but the results varied depending on the sample. In developing countries with weak governments, consumption expenditures were found to be negatively related impact on growth, while capital expenditures were found to have a positive impact on these countries. Their argument is that this is owing to ineffectual governments in developing countries, which discourage private investment, thereby forcing public investment to take the place of the private investment. To boost growth, they recommend that emerging countries limit their governments’ consumption expenditure and invest in infrastructure. This part of the analysis showed the findings of several scholars in the research background on the given topic, which is the matter of discussion in this whole analysis.
Nurudeen and Usman (2010) looked at government spending and economic development in Nigeria, which is still a developing country. Based on Keynesian and endogenous growth models, they developed their model using co-integration and error correction methods, as well as time-series data for the period 1979-2007, to test their hypothesis. In their research, they discovered that recurrent spending, capital spending, and overall education spending all have negative effects on economic growth. Increasing government spending on transportation and communication, on the other hand, leads to increased economic growth. From 1950 to 2004, a panel data set of 182 countries was used to reexamine the causal association between public spending and economic development. Wu et al. (2010) published the paper with the broadest sample and the longest time frame, reexamining the causal association between public spending and economic development. They discovered that, regardless of how government spending, as well as economic growth, is measured, the results substantially supported both Wagner’s Law and the theory that government expenditure is beneficial to economic growth.
Pham (2008/09) , in his study, covers the years 1990 to 2008 and evaluates the effects of government spending on GDP growth in China, Hong Kong (China), Malaysia, and Singapore. The Panel fixed model is used to achieve this. According to the findings of the study, there is a significant positive relationship between government spending on economic progress and GDP, which supports the idea. Furthermore, the evidence presented in this research demonstrates that government spending has a long-term impact on GDP growth in China, Malaysia, Hong Kong (China), and Singapore. Combining the two bivariate and multivariate systems, Sevitenyi & Bello (2012) investigated the relationship between government spending and economic growth. The Toda-Yamamoto Enhanced Granger Causality test and a co-integration technique were used in the econometric analysis. The findings of the Johansen multivariate co-integration test demonstrated that the static variables had no long-run association. The Impact of governmental and private investment expenditure on economic growth was studied by Ramirez & Nazmi (2003) . They came to the conclusion that government investment had a favorable and considerable impact on output growth. At the same period, public investment had a statistically equal influence on economic growth as private capital spending. However, public investment contributed to output growth at the cost of lower investment, indicating a sizeable crowding Impact. According to this research, a reduction in government capital spending could damage economic growth.
On the basis of this literature, we come to this outcome that the Impact of government expenditure on the economic growth of a country can either be positive or negative. All this literature either supports the Keynesian theory or Wagner’s Law.
We will now conduct this research to evaluate their findings based on SAARC countries’ perspectives.
3. Research Methodology
The study took on a correlational research design. Correlational research designs include the study of relationships between variables without the use of any kind of experimental manipulation or control. A correlation represents the strength and direction of a linear connection between two or more variables. The direction of a connection might be either positive or negative.
3.1. Research Design
The purpose of this empirical study is to assess the contribution of government spending to GDP growth. The research relied heavily on secondary sources of information due to its focus on economic issues. There are two types of variables such as dependent and independent variables. The dependent variable is dependent on the outcome of the independent variable. In this study, GDP is the dependent variable, as we know GDP is the expression of economic growth of a country, and general government expenditure such as development expenditure, transport facilities as communication expenditure, Industry development, and education expenditure) are regarded as the independent variable.
3.2. Data Collection Method
For this study, time-series data from 2011 to 2020 was used. Annual data has been taken from UNCTAD, Ministry of Finance website of selected countries, macro trends, world bank, exchange rate. The U.K., Bangladesh bank, and other required documents for the successful completion of the research study. The analysis is based on time-series data at the national level on the casual relationship between gross domestic product and government expenditure for SAARC countries.
3.3. Data Analysis Procedure
Data will be analyzed through the regression model of the statistical analysis technique. Statistical regression analysis is a collection of statistical techniques that are used to estimate association between the dependent and one or more independent variables in statistical analysis. By using a regression analysis, this method of predictive modeling is one of the many approaches to modeling that investigates the connection that exists between a dependent variable and one or more independent variables (predictor). Forecasting, modeling time series, and determining the variable-to-variable cause-and-effect connection are all possible applications of this methodology.
With the help of the following equation, we will draw our conclusion:
Here, Y (dependent variable) is the GDP, independent variables:
X1 = Development expenditure
X2 = Education expenditure
X3 = Communication expenditure
X4 = industry expenditure
For different values of X1, X2, X3, and X4, the value of Y will be determined. Here, b1, b2, b3, and b4 are the coefficient of the independent variables.
The values of Y are dependent on X1, X2, X3, and X4, respectively.
Using ordinary least squares, we will be able to identify the independent influences of each explanatory variable on the variable that is being explained.
4. Empirical Analysis and Result Discussion
4.1. Regression Model
To conduct the study, the study used Eviews software and numeric data from the selected countries.
The numeric study’s variables have been completed here.
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The coefficient, standard error, adjusted R squared, and other essential variables are all well defined in this regression study. I’ll start with the dependent variables and then go on to the independent variables. Again, GDP is the dependent variable, while development expenditure, education expenditure, communication expenditure, industry expenditure are independent variables. The coefficient analysis revealed that all of the coefficients are positive in all situations, showing that the dependent and independent variables have a positive connection except Industry. According to the coefficient analysis, if the independent variables rise, so does the dependent variable, and vice versa. As a result, the data is well-fitting to the model. R squared reveals how well the independent factors can influence the dependent variable. Here, in Table 1 regression test, the R squared of the linear regression was determined to be 98.44 percent, meaning that the independent variable can explain 98.44 percent of the dependent variable. The remaining 1.56 percent is related to the model’s error term. This indicates the selected model is justified; there is no need to include another variable as an independent variable. For the most part, it is permissible to have a t-value more than two and less than two. The higher the t-value, the more confident we are in the coefficient’s ability to predict the outcome of an experiment. Here, in Table 1 regression test t value is good which indicates coefficient’s ability to predict the outcome of an experiment. Again, all the variable’s probability results can be seen that are highly significant. Moreover, all the regression coefficients are statistically significant.
4.2. Granger Causality Test
The variables for the granger causality test were chosen as before. The dependent variable is GDP, while the independent variables are general government spending.
Through the granger causality test in Table 2, the result show that probability of development expenditure to communication, communication to development, GDP to communication, communication to industry expenditure, development expenditure to GDP, Industry to development expenditure and development expenditure to Industry is lower than 0.05 hence, statistically significant. So the study rejects the null hypothesis. So the result in Table 2 shows that development expenditure granger causes communication expenditure, communication
R-squared 0.984492; Adjusted r-squared 0.9834.
expenditure granger causes the Development expenditure, GDP granger causes communication expenditure, communication granger causes industry expenditure, development expenditure granger causes GDP, industry expenditure granger causes development expenditure, and development expenditure granger causes Industry. Same test done by (Lahirushan & Gunasekara, 2015) based on nine Asian Countries demonstrates that there is a causal relationship between public expenditure and economic growth, as well as a causal relationship between economic growth and public expenditure, as both null hypotheses can be rejected at the 5% level of significance.
4.3. Pedroni Residual Co-Integration Test
The Pedroni approach’s residual-based panel co-integration test is used in this work. The results of the Pedroni co-integration test between government spending and GDP are shown in the table below. There is a 5% co-integration between government spending and GDP, according to the Panel PP stat. The null hypothesis of no co-integration is discarded since the probability value is less than 0.05. At the same time, the Group PP-stat result implies that at a 5% level, there is a co-integration between government spending and economic growth.
As shown in Table 3, the correlation test is done to evaluate whether two or more variables are related. A statistical method that expresses how closely two variables are related linearly.
5. Findings
It was the aim of this study to examine the relationship between government expenditure and economic growth using econometrical techniques such as regression, correlation, co-integration, and Granger causality in the context of panel data for the SAARC countries of Bangladesh, Pakistan, Sri Lanka, India, and Bhutan. Each country had ten observations, for a total of 50 observations, and the period covered was from 2011 to 2020. The panel data approach was utilized in this study; as a result, to analyze the co-integration of government expenditures with economic growth in SAARC nations and the effect and causality of government expenditures on economic growth. In the first place, it is
straightforward to state that the independent variables are obviously describing the dependent variable. Because of the extensive research has also been determined that the independent variables are sufficient to explain the dependent variable. After conducting several experiments, it has been determined that variations in the independent factors produce variations in the dependent variable. In regression analysis, it can be seen that all the variable’s probability results are highly significant. Moreover, all the regression coefficients are statistically significant. The correlation result showed that GDP strongly correlates with communication, Education, Industry and development expenditure variables. For the SAARC countries, there is a unidirectional correlation between GDP to government expenditure and vice versa, showing that this analysis is consistent with Keynesian theory and Wagner’s Law. Because of the extensive research, it has also been determined that the independent variables are sufficient to explain the dependent variable. Same study done by (Lahirushan & Gunasekara, 2015) based on nine Asian countries, the empirical findings reveal that government spending has a statistically significant beneficial impact on economic growth in the Asian region. Second, in Asian countries, government expenditure and economic growth do, in fact, have a long-term link. Finally, for the Asian countries, there is a one-way causation from economic growth to government expenditure and vice versa, showing that this analysis is consistent with Keynesian theory as well as Wagner’s law.
6. Recommendation
Based on this relationship, it is suggested that increasing government expenditure will result in an increase in GDP in the same direction, whereas decreasing government expenditure will result in an increase in GDP in the opposite direction. In order to increase economic growth in the selected SAARC countries, it is suggested that increasing government expenditure will result in an increase in economic growth in the chosen SAARC countries. Other tests and findings from the Eviews results, such as the granger causality test, the pedroni tests of co-integration, and other tests, all point to the same conclusion. It is recommended that the amount of money spent on the relevant regions be increased in this situation. Despite this, it has been discovered in practice that the government’s financial resources are severely constricted. It is therefore impractical to invest large sums of money just on these sectors; rather, an ideal balance must be achieved between them. According to the situation’s priority, the highest level of government is authorized to allocate resources in accordance with that priority. Policymakers should take into account expenditures in various areas and devote the maximum amount of resources to the most critical ones first and foremost. Prioritizing the most important sectors will be vital in order to establish the most significant sectors. Because of this, an increase in government spending is planned in order to boost the economies of the SAARC countries that have been selected.
7. Conclusion
Specifically, this study looked at the long-term link between gross domestic output and government spending in the SAARC member countries. Through the use of annual data for the period 2011 to 2020, the research aimed to evaluate whether there is a long-run relationship between GDP and public spending in SAARC countries. Several areas were being worked on to bring the study to a successful conclusion. The procedures and strategies used to collect data are consistent with a quantitative research design, and secondary data were examined to reach the result. For the purpose of conducting the regression analysis, the Eviews software was employed. Data were obtained from the United Nations Conference on Trade and Development (UNCTAD), the Ministry of Finance websites of selected nations, macroeconomic trends, the World Bank, the currency rate, UK and Bangladesh Bank. In the end, the outcomes of the entire study demonstrate there is indeed a positive association between all of the variables. It is simple to assert that the independent variables provide a clear explanation for the dependent variables. Because of the extensive research has also been determined that the independent variables are sufficient to explain the dependent variable. Based on the tests and findings, it has been determined that variations in the independent factors result in changes in the dependent variable. Over this, SAARC countries should boost their government by being involved in spurring economic development. However, if public spending patterns are not effectively designed to meet the economy’s needs, it has the ability to have an enormous negative impact on the economy, with the costs being borne by the general public.