Institutional performance and its impact on economic growth in ASEAN countries: trend and panel data analysis

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Introduction Adam Smith, Karl Marx, and John Maynard Keynes are the most dominant economists with three distinct ideas about economic philosophy emerged as global references to the field (Bowden, 2020; O’Donnell, 2022). The concept of sustainable growth regarding some theorists such as Adam Smith and Karl Marx acknowledged the boundaries of growth and demands on the environment and the Stockholm conference represented the concept of sustainable growth expending to the present involving a number of important growths (Klarin, 2018). Adam Smith investigated the dynamics of national wealth and the well-being of individuals and society (Ucak, 2015). Adam Smith considered that government policy constituted a component of the market mechanism’s control systems, even though Adam Smith had a twofold and opposing thought about the role of government or institutions in a country’s economy (Davies, 2015; Smith, Smith, 1997). Karl Marx expected that capitalism would lead to internal conflicts, causing to its demise and replacement by a new system as socialism. In a socialist economic system, the government has an important role in regulating a country’s economic activities (Davies, 2015; Muldoon, 2022). John Maynard Keynes initiated a revolution in economic thought on the importance of government intervention through public policy to regulate employment and price stability (Commendatore, 2003; Ferrari-Filho, Conceição, 2005). Refer to those investigation and study of several literatures, it can be concluded that these great economists stated the importance of government intervention in a country’s economy. Government policies in the economy stimulates an encouraging effect on economic growth, (Haug et al., 2020; Hussen, 2023; Kuznets, 1977; Salman et al., 2019). The government’s role in economic growth performance is very necessary to promote economic growth involving several economic segments through fiscal policy and government spending (Sidek, Asutay, 2020). Several studies exploring the impact of institutional performance on economic growth, accomplished in concerning the various countries as the object, have been conductedinthelastyears. Forinstance, researchinvestigatinginstitutionalperformance impactoneconomicdevelopmentin European Union(EU) revealedthatreputableinstitutions representing greater opportunity of economic independence and better governance towards to advanced economic growth in the EU countries, although the effect of institutions on economic growth is fluctuated over time (Bernardelli, Próchniak, Witkowski, 2021). Another previous research, investigating economic growth as of institutional performance impact in China, disclosed that China’s high-quality economic development is effectively strengthened by the institutional environment (Zhao, 2024). To enrich and continue existing research on the impact of institutional performance towards to economic growth, the researchers attempt to investigate the performance of institutions expected to contribute on economic development in Association of Southeast Asian Nations (ASEAN) countries. The ASEAN is one of the regional organizations that has experienced an optimistic economic growth in recent years. In 2022, ASEAN economy achieved a nominal GDP of US$3.6 trillion, placement the 5th largest in the world. Nominal GDP of ASEAN per capita attained at US$5395, a noteworthy 37.6% increase from 2015. ASEAN economy improved by 5.7%, sustaining an average annual growth rate of 4.4% during 2010-2022. The top 3 of largest PDP per capita (US$) is achieved by Singapore, Brunei Darussalam and Malaysia. During 2010-2022, ASEAN GDP growth rates reached between 3.5-6.1%. The highest rate is attained in 2012. The lowest rate is conquered in 2020 due to COVID-19 effect. The COVID-19 indicated a slowing impact of economic growth on various ASEAN countries. The most obvious risk is a continued economic slowdown, as measured by GDP, especially since most of ASEAN countries continue to experience negative growth (D’Aloia, Gugler, 2024). Researchers conduct a couple approach to figure out how significantly institutional performance contributes to economic growth. Those are data visualization and panel data analysis. The data visualization is implemented to provide a trend outlook of institution performance in each ASEAN member country and deliver more straightforward information to understand at a glance. Data visualization, applied in numerous fields, is an important aspect of data analysis (Liang et al., 2022). It can simplify information and provide a comprehensive overview. By considering of observation objects involving data of several countries and periods, this research framework is strongly appropriate to basic concept of panel data approach. The panel analysis, two-dimensional statistical method, is generally applied in various research fields such as economics, social sciences, and humanities (Aparicio, Urbano, Audretsch, 2016). The basic concept of panel data analysis in this study is a combination of time series data and cross section data represented by observation data in 22 years periods and ten member countries of ASEAN. In this panel data analysis, GDP per capita is selected as the dependent variable representing economic growth in ASEAN. Independent variables include import, and world government indicators (WGI) representing institutional performance as independent variables affecting economic growth. The GDP is a comprehensive measure of a country’s complete economic activity. Imports and exports are important components of the expenditure method for calculating GDP. Several studies have revealed that exports and imports can be used as indicators that have a positive impact on economic growth. In this study, researchers involved exports and imports as independent variables with a measure that more feasible to understand quantitatively. This procedure needs hypothesis as following, y H0: export, import and institutional performance indicators have no impact on economic growth. 288 ЭКОНОМИКА РАЗВИТЫХ И РАЗВИВАЮЩИХСЯ СТРАН Ризки С.В., Диденко Н.И. Вестник РУДН. Серия: Экономика. 2025. Т. 33. № 2. С. 285-303 image y H1: export, import and institutional performance indicators have impact on economic growth. The alpha value is selected to assess the probability of error that researchers determine in making a decision to reject or support the null hypothesis. H0 will be rejected if p-value smaller than alpha. This research purposes to disclose the performance of six institutional indicators of in a time-series trend visualization and panel data analysis. This study practices data from 2002 to 2022, where in this period there was a time when the world struggled with the COVID-19 pandemic in 2020. So that the involvement of data in 2020 can provide different results and insights from the previous studies. Materials and methods The World Bank released several institutional indicators manifested in the WGI, that will be used for the analysis of the impact of institutions on economic growth in ASEAN. The WGI is a valuable instrument for representatives, researchers, and experts concerned in comparative governance and institutional analysis (Gallegoálvarez, Rodríguez-Rosa, Vicente-Galindo, 2021; Handoyo, 2023; Sadaf et al., 2018). The WGI establishes a widespread dataset that assess the quality of public authority at the national level. The WGI structure refers to six key governance indicators: political stability and absence of violence, government effectiveness, regulatory quality, rule of law, control of corruption and voice and account. Effective management contributes to countries’ economic growth, human capital development, and social integration. The WGI is beneficial to assist researchers and analysts discover general trends in concerning of government performance across countries and over time. There are some researches investigating about institutional performance. For instance, a study examining empirically the significant institutional performance on investment flows in developing countries disclosed that Singapore is the one ASEAN country that has good governance and high government effectiveness (Buracom, 2014). Later, a study measuring the effectiveness of government performance on socioeconomic development in ASEAN countries found that ASEAN countries restraining public spending growth outperform countries with relatively large governments (Sagarik, 2017). Several methods and approaches are applied in economy field study such as panel analysis. Panel data analysis is very prevalent in the fields of economics and econometrics. For example, a study examining several intrinsic variables and extrinsic variables, including corruption and armed conflict, on economic growth in ASEAN with panel data affords the result that corruption and armed conflict have a statistically significant and negative connection with economic growth in ASEAN countries (Aziz, Sundarasen, 2015). Thus, a study investigating the role of institutions on economic growth in ASEAN countries from 1995 to 2017 applied a dynamic panel estimator revealed that institutional strength plays a significant and positive role in economic growth (Haini, 2020). In addition, research investigating the impact of institutions on economic growth in ASEAN with panel data of 10 member countries in the period 2002-2018 ECONOMIES OF DEVELOPED AND DEVELOPING COUNTRIES 289 Rizki S.W., Didenko N. 2025. RUDN Journal of Economics, 33(2), 285-303 image resulted that voice and accountability, regulatory quality, and the rule of law have a significant influence on economic growth (Sari, Prastyani, 2021). 1. Trend graph visualization. The WGI has been used since 1996 with six governance indicators by hundreds of countries around the world. Cumulative indicators are constructed with hundreds of individual underlying variables derived from a variety of data sources that reflect opinions about governance from a diverse range of qualified and expert respondents. The WGI reflects comparisons of governance across countries and over time (Kaufmann, Kraay, Mastruzzi, 2011). To reveal institutional performance in simply technique, researchers conducted a visualization method in this study. There are several guidelines for effective data visualization in scientific publications purposing to transfer information effectively to readers and enhance communication of research outcomes (Midway, 2020). Efficient and effective data visualization techniques aim to discover more interesting visualizations building on reference visualizations (Qin et al., 2020). In general, data visualization can be simplified into three stages such as collecting data, recognizing patterns and understanding the data. Table 1 displays a description of the institutional performance indicators that will be used as independent variables in this study. Type of WGI indicators Table 1 WGI indicators Definition Political stability and absence of violence It measures the supposed probability of political variability and/or politically driven violence, counting terrorism. The value is between about -2.5 to 2.5. Government effectiveness It reveals the insights of the public and civil services quality and the its detachment level from political demands, the policy development quality and the legitimacy of the government’s assurance to implementing policies. The value is reaching about -2.5 to 2.5. Regulatory quality It reflects an observation of the government capacity to develop and enforce comprehensive policies and regulations facilitating and promoting private expansion. The score is ranging around -2.5 to 2.5. Rule of law It discloses assessments of the agent’s confidence and trust level instead in the society regulations, the agreement implementation quality, assets rights, the police and courts, and the possibility of crime and violence. The score is approaching between -2.5 and 2.5. Corruption Control It investigates understandings of the degree to which public authority is utilized for private advantage, involving minor and significant corruption types of government authority by privileged interests. The score is ranging from -2.5 to 2.5. Voice and Accountability It represents acuities about the level of citizen participation in selecting a government with freedom of appearance, association independence, and an unrestricted media. The score is ranging from -2.5 to 2.5. Source: World Bank1. image 1 World Bank. Retrieved July 12, 2024 from https://www.worldbank.org/en/publication/ worldwide-governance-indicators 290 ЭКОНОМИКА РАЗВИТЫХ И РАЗВИВАЮЩИХСЯ СТРАН Ризки С.В., Диденко Н.И. Вестник РУДН. Серия: Экономика. 2025. Т. 33. № 2. С. 285-303 image 2. Panel data method. The use of panel data model analysis is popular in economics and econometric. The core advantage of panel data analysis is considering and controlling for individual effects and heterogeneity as well as time. It can provide valuable insight into the relationships between independent and dependent variables. The data structure consists of a time-series of annual data over 21 years and a crosssection of data from 10 ASEAN member countries. The use of statistical application and software is needed to simplify complex data calculations and provide accurate results. Excel application is used to display the trends of the variables used in this study. A statistical software commonly used by statistics researchers in data analysis is R Studio. It is an open-source software with some advantages such as the legality of using safe software and updating packages. R Studio is a low-risk software for conducting and analyzing data improving its services continually (Henningsen, Henningsen, 2019). The calculation involves GDPC as dependent variable and export, import, political stability, government effectiveness, regulatory quality, rule of law, corruption control, and voice and accountably as independent variables. The more detail information is represented in Table 2 as following. List of dependent and independent variables Table 2 Name of variable s Denotation of variables GDPC GDP per Capita Exp representing total value of goods and services provided to the rest of the world (%GDP) Imp representing total value of goods and services provided to the rest of the world (%GDP) PSAV political stability with score between -2.5 to 2.5 GE government effectiveness with score between -2.5 to 2.5 RQ regulatory quality with score between -2.5 to 2.5 RL rule of law with score between -2.5 to 2.5 CC corruption control with score between -2.5 to 2.5 VA voice and accountability with score between -2.5 to 2.5 Source: compiled by S.W. Rizki, N.I. Didenko. There are several stages of data analysis in panel data analysis. The stages procedure is directed as following, 1. Data standardization is needed before accomplishment calculations because of the diff in measurement scales of the data to be used. ECONOMIES OF DEVELOPED AND DEVELOPING COUNTRIES 291 Rizki S.W., Didenko N. 2025. RUDN Journal of Economics, 33(2), 285-303 image The standardization technique aims to simplify comparisons between data originating from variables with diff scales. The most common approach to standardization is to use the Z-score by formula as following: image Z = X X , cr image where X = real value of data; X = average value of data; σ = deviation standard of data; A positive Z-score value indicates that the data is above the mean and a negative value indicates that the data is below the mean. 2. Chow test is conducted to fi out whether the panel data regression technique with the fi eff method is better than the panel data model regression without dummy variables or the common eff method. The null hypothesis is the same intercepts, or in other words the right model for panel data regression is common eff and the alternative hypothesis is that the intercepts are not the same or the right model for panel data regression is fi eff Therefore, the hypothesis can be represented as following, H0: common effect model H1: fixed effect model 3. Hausman test is led to determine whether there are random eff in the panel data model. The random eff suppose that the entity with the errors does not correlate with the predictive variables. Thus, the hypothesis can be denoted as following, H0: random effect H1: fixed effect 4. Breusch-Pagan Lagrange Multiplier test is directed to assess whether there is a time or individual eff or even none in the model. The Breusch Pagan method for the random eff signifi test is based on the residual value. The Lagrange Multiplier test is not conducted if the Chow test and the Hausman test indicate that the most appropriate model is the fi eff approach. This test is needed if Chow test and the Hausman test indicate common eff and random eff model. Thus, the hypothesis can be denoted as following, H0: no time or individual effect H1: time or individual effect An alpha value symbolizing an error probability is selected for all hypothesis to make a decision. If p-value is smaller than alpha, so the null hypothesis will be rejected. Formula of panel data regression is presented as following GDPC = θ + θ Exp + θ Imp + θ PSAV + θ GE + θ RQ + it 0 1 it 2 it 3 it 4 it 5 it + θ RL + θ CC + VA + e , 6 it 7 it it it where θ , θ , θ , θ , θ , θ , θ , θ are parameter coefficient and e is error. 0 1 2 3 4 5 6 7 it 292 ЭКОНОМИКА РАЗВИТЫХ И РАЗВИВАЮЩИХСЯ СТРАН Ризки С.В., Диденко Н.И. Вестник РУДН. Серия: Экономика. 2025. Т. 33. № 2. С. 285-303 image Institutional performance on trend The WGI has a very important role in supporting the economic growth of a country. It can be a reference in determining government policies having an impact on improving the progress of society and the economic growth of a country. Researchers summarize the trends of the six institutional indicators performance in 10 ASEAN member countries in the period 2002-2022 pointing to describe the state of public governance in ASEAN countries. Figure 1 shows Singapore and Brunei Darussalam have the highest score around 1 which means those countries has strong political stability. It describes that the mentioned countries have the best quality of public services and credibility to implement and commit government’s policies. Myanmar, Philippines, Indonesia, Thailand and Cambodia gained mostly negative score indicating low political stability during 21 years. Myanmar’s score has decreased in the last years around -2.2 in 2022. The political situation in Myanmar is very unstable and a state of military emergency is still in effect image Figure 1. Trend of political stability score in ASEAN countries in 2002-2022 Source: Worldwide Government Indicators2. Figure 2 explains that Singapore has the strongest government effectiveness with score about 2 followed by Brunei Darussalam and Malaysia with score round 1. Thailand, Philippines, Viet Nam and Indonesia are in the medium level at around 0. Cambodia and Lao PDR gained round -1. The last, Myanmar reached the weakest score approximately -2. Figure 3 shows that Singapore gained the highest score around 2, in the meantime Myanmar has the weakest score. It represents that government of Singapore image 2 Worldwide Government Indicators. Retrieved July 29, 2024 from https://data.worldbank.org/ indicator/PV.EST?skipRedirection=true&view=map ECONOMIES OF DEVELOPED AND DEVELOPING COUNTRIES 293 image Rizki S.W., Didenko N. 2025. RUDN Journal of Economics, 33(2), 285-303 have the strongest capability to formulate and implement comprehensive policies and regulations that permit and encourage private sector expansion and indicating that Myanmar has weak abilities for private sector development. Brunei Darussalam, Malaysia, Thailand, Philippines, Cambodia, Viet Nam, Indonesia and Lao PDR reached score between -1 and 1. This means that these eight countries have done quite well in attracting the private sector to support economic growth but are still struggling to expand private sector growth image Figure 2. Trend of government effectiveness score in ASEAN countries in 2002-2022 Source: Worldwide Government Indicators3. image Figure 3. Trend of regulatory quality score in ASEAN countries in 2002-2022 Source: Worldwide Government Indicators4. image 3 Worldwide Government Indicators. Retrieved July 29, 2024 from https://data.worldbank.org/ indicator/GE.EST?skipRedirection=true&view=map 4 Worldwide Government Indicators. Retrieved July 29, 2024 from https://data.worldbank.org/ indicator/GE.EST?skipRedirection=true&view=map 294 ЭКОНОМИКА РАЗВИТЫХ И РАЗВИВАЮЩИХСЯ СТРАН Ризки С.В., Диденко Н.И. Вестник РУДН. Серия: Экономика. 2025. Т. 33. № 2. С. 285-303 image image Figure 4. Trend of rule of law score in ASEAN countries in 2002-2022 Source: Worldwide Government Indicators5. Figure 4 signifies that Singapore has the strongest score on the rule of law, meaning Singapore has a strong belief in following the rules of society and the courts, and a low incidence of crime and violence. Malaysia and Brunei Darussalam reached positive score near 1. Thailand, Philippines, Indonesia and Viet Nam have score between -1 and 0. Lao PDR, Cambodia and Myanmar are in the lowest level under -1, which means the level of public compliance to the law is very low. It implements that there are a high probability of crime and violence image Figure 5. Trend of corruption control score in ASEAN countries in 2002-2022 Source: Worldwide Government Indicators6. image 5 Worldwide Government Indicators. Retrieved July 29, 2024 from https://data.worldbank.org/ indicator/RL.EST?skipRedirection=true&view=map 6 Worldwide Government Indicators. Retrieved July 29, 2024 from https://data.worldbank.org/ indicator/CC.EST?skipRedirection=true&view=map ECONOMIES OF DEVELOPED AND DEVELOPING COUNTRIES 295 image Rizki S.W., Didenko N. 2025. RUDN Journal of Economics, 33(2), 285-303 Figure 5 reflects that Singapore government has the best capability to control corrupt behaviour. Malaysia and Brunei Darussalam have a fairly good ability to control corruption levels with scores above zero. The remaining countries performs under 0. Myanmar touched the lowest score at the 1st decade. It acclaims that those countries must conduct evaluations in order to improve control and reduce the level of corruption image Figure 6. Trend of voice and accountability score in ASEAN countries in 2002-2022 Source: Worldwide Government Indicators7. Figure 6 presents almost all countries has score between 0 and -2. It means that public participation in government, freedom of expression, freedom of association, and freedom of the media are low. Indonesia and Philippine are the two countries that have most affordable scores although it is a fairly low assessment with values around zero Panel data analysis of institutional performance in ASEAN countries To summarize the overall information from the data in a simple form, descriptive statistics areneeded. Thedescriptivestatisticsareusedtoobtainaglimpseofinformation about the profile of government quality in ASEAN countries. The descriptive statistics can assist readers to understand several highlights and simplify information from the large data. The simple information of descriptive statistics is represented in Table 3 as following. image 7 Worldwide Government Indicators. Retrieved July 29, 2024 from https://data.worldbank.org/ indicator/VA.EST?skipRedirection=true&view=map 296 ЭКОНОМИКА РАЗВИТЫХ И РАЗВИВАЮЩИХСЯ СТРАН Ризки С.В., Диденко Н.И. Вестник РУДН. Серия: Экономика. 2025. Т. 33. № 2. С. 285-303 image Descriptive statistics of dependent and independent variables Table 3 Variables GDPC, $ Export, % GDP Import, % GDP PSAV GE RQ RL CC VA Mean 10597.06 64.30 58.6 -0.149 0.117 -0.033 -0.216 -0.271 -0.760 Std. Dev. 17692.77 50.42 42.57 0.932 1.015 1.004 0.892 1.001 0.681 Min 36.99 0.1 0.1 -2.212 -1.684 -2.349 -1.736 -1.673 -2.230 Max 85623.75 229 208.3 1.599 2.470 2.252 1.838 2.301 0.320 Obs. 210 210 210 210 210 210 210 210 210 Source: compiled by S.W. Rizki, N.I. Didenko. Table 3 represents a simple form of governance conditions in ASEAN countries expressed in numerical form. The descriptive analysis reveals an extreme difference between minimum and maximum values in all variables. In this case, the minimum GDPC value is $36.99 and the maximum is $85623.75, it confirms that there is a very significant difference in prosperity between ASEAN countries. Data of export and import represent a structure of demand of export and imports (% of GDP at current market prices) of goods and services from 10 ASEAN member countries completed 21 years. The maximum and minimum values of export and import revealed an extreme difference of those values. It reinforces the indications of a large prosperity gap between ASEAN member countries. This situation is quite relevant with a sharp difference exist between the maximum and minimum values of the WGI. It implies a very significant difference in government performance in each ASEAN member country. The biggest difference is in regulatory quality and the smallest is in voice and accountability. Correlation between independent variables Table 4 Variables Export Import PSAV GE RQ RL CC VA Export 1 Import 0.7251 1 PSAV -0.2434 -0.1239 1 GE 0.0931 0.0971 0.2738 1 RQ -0.0207 0.0059 0.2109 0.3429 1 RL 0.0169 0.0043 0.3802 0.5499 0.4591 1 CC 0.0424 0.2434 0.0715 0.4060 0.4476 0.3061 1 VA -0.0207 0.0562 -0.0165 -0.0223 0.4334 0.3397 0.4658 1 Source: compiled by S.W. Rizki, N.I. Didenko. ECONOMIES OF DEVELOPED AND DEVELOPING COUNTRIES 297 image Rizki S.W., Didenko N. 2025. RUDN Journal of Economics, 33(2), 285-303 Table 4 confirms that the strongest correlation between export and import gained coefficient value around 0.725151 and the weakest correlation between rule of law and import earned coefficient value about 0.004301. The strongest anti-correlation between political stability and absence of violence and export is round -0.243421. Result of special test of significance Table 5 Test Statistics p-value Chow test F statistic F = 41.746; df1 = 20; df2 = 181 2.2e-16 Hausman test Hausman test chisq = 0.00046684; df = 8 1 Breusch Pagan test LM test - two-ways effects chisq = 214.66; df = 2 2.2e-16 LM test - Individual effect chisq = 209.41; df = 1 2.2e-16 LM test - time effects chisq = 5.2424, df = 1 0.02204 Source: compiled by S.W. Rizki, N.I. Didenko. Table 5 represents several tests involved in panel regression analysis. Firstly, The Chow test is conducted to choose the better model between a common effect (as null hypothesis) or fixed effect method (as alternative hypothesis). It resulted that H0 rejected (or H1 accepted) because p - value = 2.2e - 16 > 0.05. It means that the fixed effect method is better than the common effect method with a 95% confidence level. Secondly, The Hausman test is needed to determine whether there are random effects supposing the unit with the errors does not correlate with the independent variables. The results revealed that it failed to reject H0 because p - value = 1 > 0.05. It means that the random effect method is a better method to use when compared to the fixed effect method with a 95% confidence level. Lastly, because the Hausman test disclosed that the model has a random effect, it is continued with the Breusch Pagan test to determine whether there is a time or individual effect or even none in the model. Based on the results of the Breusch Pagan test all p-value less than α, it concludes that in the random effect model there are two-way effects such as cross-section and time effects. The results of the Hausmann test and the Breusch-Pagan test conclude that the model to be estimated is a random effect data model with cross-section and time effects. In brief, this research conducted a fixed model having random effect with cross-section and time effects. Then a significance test of the variables in the model is carried out in Table 6 as following. 298 ЭКОНОМИКА РАЗВИТЫХ И РАЗВИВАЮЩИХСЯ СТРАН Ризки С.В., Диденко Н.И. Вестник РУДН. Серия: Экономика. 2025. Т. 33. № 2. С. 285-303 image Variables Estimated coefficients Std. Error z-value Pr (>|z|) Intercept 0.0029714 0.0841461 0.0353 0.9718 Export 0.2333809 0.0541044 4.3135 1.607e-05 *** Import -0.3132212 0.0550479 -5.6900 1.271e-08 *** PSAV -0.0404423 0.0414292 -0.9762 0.3290 GE 0.0007504 0.0515786 0.0145 0.9884 RQ 0.2142237 0.0450639 4.7538 1.997e-06 *** RL 0.0185307 0.0531348 0.3487 0.7273 CC -0.0431136 0.0505659 -0.8526 0.3939 VA -0.0382610 0.0497207 -0.7695 0.4416 R-Squared: 0.25247 Adjusted R-Squared: 0.22272 Result of panel regression imageimage Significance codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Source: compiled by S.W. Rizki, N.I. Didenko. Table 6 The panel analysis equation by putting estimated coefficients to formula equation can be written as following, it GDPC it = 0.0029714 + 0.2333809Exp it - 0.3132212Imp 3 it - 0.0404423θ PSAV + it + 0.0007504GE it + 0.2142237RQ it + 0.0185307RL - it - 0.0431136CC it + e , it - 0.0382610VA where i denotes countries in ASEAN and t denotes years. The Table 6 gives the results for the previous hypothesis as following y H0: export, import and institutional performance indicators have no impact on economic growth. y H1: export, import and institutional performance indicators have impact on economic growth. By taking an alpha value as 0.05, H0 will be rejected if p-values less than 0.05. Based on the overall test results on Table 6, it was obtained that the p-value of the export, import and RQ variables are 1.607e-05, 1.271e-08 and 1.997e-06, respectively. Those are less than alpha 0.05, which means that the null hypothesis is rejected and alternative hypothesis is accepted. It reveals that the export per capita, import per capita and RQ variables have impact on economic growth under 95 percent confidence level. Thus, simultaneously, those independent variables have a significant effect on GDPC. The value of adjusted R-Square is 0.22272. It means that the independent variables, namely the export, import and RQ variables, are able ECONOMIES OF DEVELOPED AND DEVELOPING COUNTRIES 299 Rizki S.W., Didenko N. 2025. RUDN Journal of Economics, 33(2), 285-303 image to explain the dependent variable, that is GDPC, by 22.272%, while the remaining 77.278% is explained by other factors not mentioned in the model. R-Squared measures how much deviation in the model, the greater the R-Square means the deviation in the model is less which indicates the model is better. In this study, R square is 0.25247, and this is relatively small. To increase the R square value, more independent variables can be added in further research. Discussion Singapore achieved the highest scores in five institutional indicators: political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and corruption control, meanwhile Indonesia and the Philippines scored the highest in voice and Accountability. Brunei Darussalam and Malaysia ranked high in the five indicators following Singapore. Thailand, the Philippines, Indonesia, and Vietnam maintained a relatively high level in almost every indicator. Cambodia, Lao PDR, and Myanmar continue to struggle with governance indicator assessment. Myanmar attained the lowest level in all indicators. This is due to the unstable political situation and an effect of military emergency state. The existence of a fairly large gap in institutional performance assessment scores has caused a very significant difference in welfare between ASEAN countries. The important objective of ASEAN’s formation to realize supporting economic growth, cultural development, and social progress in the regional area is facing a big challenge until present. It needs to be a more effective and strict policy to achieve the joint goal. Panel data analysis reveals that export, import, and RQ contributing significantly to ASEAN economic growth, with an adjusted R-square value of 0.25247. This value is fairly insufficient, as it is less than 0.5. The result indicates that the export, import, and regulatory quality variables can explain 22.272% of the dependent variable, GDPC, with the remaining 77.278% explained by factors not identified in the model. Refers to the results of this panel data analysis, we know that the quality of regulation has a significant impact on economic growth. These results recommend that policy makers be more active in formulating regulations and implementing more optimal policies to encourage the development of the private sector. By considering the relatively slight R-squares value as 0.25247, it can be improved by adding independent variables in further research. The independent variables that can be added can refer to additional variables that can support regulatory quality such as interest rates and investment. Conclusion According to the researcher’s point of view, ASEAN has unique and interesting characteristics and descriptions to be used as research study material. There are several opinions from economic experts regarding the impact of population on economic growth, on the one hand several experts and studies state that the number of residents can have a positive impact on economic growth. However, some opinions are still not sure whether the number of residents has a positive impact on economic growth. In this study, observations in the ASEAN region provide clues that Singapore and Brunei with the smallest area and population performed very impressive economic growth with per capita income significantly above on the average GDP per capita of other ASEAN countries. In addition, these two countries have the smallest land area compared to ASEAN countries. The large area should be able to provide large natural resources that can be used as production materials and can increase export value and ultimately have a positive impact on economic growth as reflected in GDP per capita. The connecting line that could be taken from this situation is that government performance plays a very important role in managing natural resources and improving the quality of the population. From this point of view, several policies, related to how to utilize natural resources optimally and strive to improve human quality, is need to improve. Further research could involve the human development index and education quality to measuring success in efforts to build the quality of human life. In addition, interest rate and investment can be considering to be independent variables as a parameter of natural resource processing and management stimulator. This study only limits two quantitative variables, which have an impact on economic growth, namely exports and imports, as complementary variables of the institutional performance variable. In further research, other variables can be involved, such as Foreign Direct Investment between ASEAN countries as a manifestation of economic cooperation. The researcher also suggests that further research involve the Human Development Index as one of the independent variables. The addition of suggested variables is expected to provide a more detailed description of the research results and can be used as a consideration for making policies that can support economic development in ASEAN.

About the authors

Setyo Wira Rizki

Peter the Great Saint Petersburg Polytechnic University

Author for correspondence.
Email: rizki.sv@edu.spbstu.ru
ORCID iD: 0000-0003-0829-9767

PhD Student, Institute of Industrial Management, Economics and Trade

29 B Polytechnicheskaya St., Saint Petersburg, 195251, Russian Federation

Nikolay I. Didenko

Peter the Great Saint Petersburg Polytechnic University

Email: didenko.nikolay@mail.ru
ORCID iD: 0000-0001-8540-7034
SPIN-code: 3512-5410

Doctor of Economics, Professor, Institute of Industrial Management, Economics and Trade

29 B Polytechnicheskaya St., Saint Petersburg, 195251, Russian Federation

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