Lower Unemployment Rates Research Articles

Suburbanization Processes in Sofia: Demographic, Socio-Economic and Spatial Transformation of the Agglomeration Area

The paper studies the agglomeration area of Bulgaria’s capital, Sofia. The territorial scope of the metropolitan agglomeration encompasses 7 (LAU 1) municipalities including Sofia, Bozhurishte, Elin Pelin, Gorna Malina, Kostinbrod, Slivnitsa and Svoge, and comprises 146 (LAU 2) individual settlements. The total area of Sofia agglomeration covers almost 3,550 km² (3.2% of national territory), while it had 1,359,270 inhabitants (almost 21% of national population) according to the last population census (7 September 2021). During the whole period between 2001 and 2021, Sofia agglomeration has grown in population by more than 95,000 people (7.6%). Bozhurishte, Kostinbrod and Elin Pelin, along with Sofia municipality itself, are the municipalities with the best demographic indicators within the agglomeration area. According to the typology of Webb, type 6 agglomeration settlements (migratory and natural decrease, natural > migratory) are predominant during the first subperiod (2001-2011), while type 8 (migratory increase compensates for natural decrease) has become the leading type in the second subperiod (2011-2021). Despite the increasing number of type 8 settlements, however, the population decline of Sofia city alone (19,361 people) exceeds more than twice the combined population growth of all type 8 settlements (8,929 people), and as a result – the total population number of the agglomeration declined during the second subperiod. In 2021, the GDP in Sofia agglomeration represented 43% of the national economy, while the GDP per capita in Sofia (BGN 38,891) was more than double of the national average. A significant number of the industrial sites are located in the neighbouring municipalities that fall within the agglomeration, with leading economic activities in manufacturing, transport and logistics. The distribution of FDI, however, is uneven: some 97% of them concentrated in Sofia municipality alone. Sofia agglomeration is distinguished by a relatively stable and balanced labour market, characterized by high economic activity and low unemployment rate compared to other agglomerations in the country. Together with the demographic processes, the increasing soil sealing is another evidence of the spatial expansion of suburbanization. The largest share of new soil sealing was observed in Sofia municipality itself (approximately 370 ha), followed by Elin Pelin (105 ha), Bozhurishte (46 ha) and Kostinbrod (32 ha). Based on the intensity of new constructions and population change, the so-called zone of active inbuence of the agglomeration core has been outlined. The zone is made up of settlements meeting two conditions: they have a high intensity of new constructions and they are type 8 or type 7 according to the typology of Webb in the period between 2011 and 2021. During the considered period, the northern, eastern, southern and western peripheries of the agglomeration area developed each in its own speciac way, with dieerent new construction intensity, morphological structure and inter-settlement spaces. Suburbanization processes observed in Sofia are generally comparable to those of other post-socialist European capitals in terms of historical legacies, demographic transformation, spatial dynamics, and land use shifts.

Peran Program Dumisake Terhadap Peningkatan Pendapatan UMKM dan Perekonomian Masyarakat Provinsi Jambi Masa Covid-19

The purpose of this study is to determine how the Dumisake Programme affected the MSME income and the general economy of the people living in the Province of Jambi in COVID-19. This study uses a qualitative method and is descriptive in nature. The Cooperatives Service, UMK, Jambi Province served as the research site. The Dumisake Programme, a priority programme for the Jambi Provincial Government, was used to determine the research location to examine the capital assistance programme for MSMEs. The program's goals are to enhance the regional economy, lower rates of poverty and unemployment, and ultimately improve community welfare. Through the distribution of questionnaires and in-person interviews with MSME capital assistance grantees under the Jambi Provincial Government's Dumisake Programme, primary data was gathered. Legal and regulatory records, the 2021–2026 Jambi Province RPJMD, the Strategic Plan and Work Plan of the Cooperative Service, and the Jambi Province UMK serve as research supporting data for this study. Researchers conducted direct interviews with MSME players in Jambi Province who benefited from capital support under the Dumisake Programme. Data Reduction, Data Display (Data Presentation), and Conclusion Drawing/Verification (Conclusion) were the methods used for data analysis in this study. The study's findings demonstrate that the Covid-19 Pandemic had an impact on Micro, Small, and Medium-Sized Enterprises (MSMEs) that were given support by the Jambi Provincial Government. These MSMEs considered the assistance to be highly beneficial for business development, which boosted their revenue. When it comes to helping MSME players in Jambi Province with their business growth, the Jambi Provincial Government's Economic Recovery Programme has shown to be quite beneficial in providing them with products and equipment. The assistance programme has three (three) primary objectives: achieving economic recovery; enhancing MSMEs' capacity to become resilient and independent; and putting in place efficient, transparent, effective, and targeted help channels. The Cooperatives & MSMEs Service (Government) and MSME actors are the next two players engaging in the support programme for MSME actors.

Stratification of Urban Health Centers of Khorramabad Based on Socioeconomic Status of Households Using Factor Analysis and Cluster Analysis

Background: In numerous studies in the field of medical sciences, researchers use health centers as a frame for stratified sampling. Since socioeconomic variables play a major role in health outcomes, the present study aimed to classify urban health centers of Khorramabad in terms of the socioeconomic status of households using factor and cluster analysis. Materials and Methods: In this cross-sectional study, the statistical population included all urban areas of Khorramabad based on the population and housing census conducted by the Statistical Center of Iran. Firstly, the scatter maps of urban areas and health centers were adopted together. Thereafter, socioeconomic indexes of urban areas were calculated in seven fields, and exploratory factor analysis was used to reduce dimensions. Finally, the similar health centers in terms of factor scores were allocated to the same clusters by k-means cluster analysis using SPSS software (version 26) and were displayed on city maps using Arc GIS software. Results: Three factors identified in factor analysis explained about 73.3% of the total variance of socioeconomic indexes. Based on cluster analysis, 11 health centers were located in cluster 1 (related to lower educational attainment, poorer housing amenities, and higher rate of homelessness and divorce), 16 centers were located in cluster 2 (related to higher studying persons rate, lower marriage rate in women, lower unemployment rate, and higher residence in apartment flats) and 10 health centers were located in cluster 3 (related to higher academic graduates, more profitable jobs, and better housing amenities). Conclusion: The results of this research can be used in health studies in urban areas of Khorramabad as a basis for performing stratified sampling. Furthermore, it is recommended that authorities adopt more effective planning to improve deprived areas in cluster one.

An Intersectional Analysis of Precarity and Exploitation: Women and LGBTQIA+ Workers in Substate Neoliberal Systems

The intersection of gender and ethnicity or race lies at the root of structural discrimination and racist practices for accessing the labor market and in the workplace. This discrimination is particularly evident for women and LGBTQIA+ individuals who either belong to ethnic minorities or are migrants. However, numerous other social drivers (e.g., age, class, origins) and external factors (e.g., prejudices, gender‐based violence) further hinder their participation in the work domain and their attainment of fair labor conditions. This article explores how gender, ethnicity, and race intersect and operate with other conditions and factors to perpetuate the precarity and exploitation of women and LGBTQIA+ individuals who find themselves at the nexus of varied intersectional axes. The discussion centers around two neoliberal substate units in the Global North (South Tyrol, in Italy, and Catalonia, Spain) that register low unemployment rates and high rates of migration and that are home to historical, linguistic, and ethnic minorities. This empirical article provides for an informed debate on the lived experience of precarity and exploitation of women and LGBTQIA+ workers, and an analysis of how neoliberal substate units’ labor and gender policies could be reformed.

Enhance Kenya University Undergraduate Employability Through Team Sports Participation: University Students Athletes

Purpose: Employability is a major issue worldwide, and Kenya is increasingly looking to universities to develop employable undergraduate students. A low undergraduate unemployment rate is considered as a sign of a thriving economy, while a high unemployment rate is seen as a waste of national resources. The aim of this study was to examine how undergraduate participating in team sports in Kenya university can enhance employ ability
 Methodology: The study used a desktop approach where literature was sought from different sources. The research was carried out with consideration given to previous theoretical literature, both published and unpublished. 
 Findings: Most employers look for specific skills and attributes in job prospects in addition to academic requirements. These attributes, known as employability skills, aren't job-specific, yet they can boost undergraduate student athletes’ employability since they increase productivity and value at work also have an impact on ability to grow career wise.
 Unique contribution to theory, practice and policy: Team sports has the potential to provide marginalized and underprivileged undergraduate athletes with adequate abilities, skills, and pathways to job or social enterprise-based possibilities. Participation in team sports can bring young people together in the pursuit of universal peace and a desire to improve themselves. Hence, university management should have good organization, facilitation, and oversight should be provided by university sports management.

K-Means Clustering Algorithm: A Study on Unemployment Rates in Districts/Cities in Three Highest Provinces

Unemployment is a recurring issue every year, particularly in provinces with high unemployment rates, posing economic and social challenges. West Java, Riau Islands, and Banten are identified as the three provinces with the highest unemployment rates, exceeding 8% in the year 2022. Hence, this study aims to delve into the unemployment scenario in these provinces, considering various influencing factors drawn from relevant previous research. The primary objective of this research is to obtain the classification results of regencies/cities in West Java, Riau Islands, and Banten based on unemployment indicators. The findings reveal four clusters: Cluster 1 comprises 13 regencies/cities with the lowest unemployment rates, Cluster 2 includes 4 regencies/cities with low unemployment rates, Cluster 3 consists of 13 regencies/cities with moderate unemployment rates, and Cluster 4 encompasses 12 regencies/cities with high unemployment rates.

Comparison of male and female non-refugee immigrants with psychosis: clinical, sociodemographic, and migration-related differences and impact on stress.

To compare social, clinical, and migration-related factors between male and female immigrants with psychotic disorders and to determine the association between these variables and stress in the last year. We administered the Holmes and Rahe Social Readjustment Scale to evaluate psychological stress in 99 non-refugee immigrants (26 women, 73 men) who presented ≥ one psychotic episode (ICD-10 criteria). We compared the two groups in terms of sociodemographic, clinical, cultural, and migration-related variables. A multivariable analysis using a linear regression model (stepwise method) was performed to evaluate potential associations between these variables and stress. Women were more likely to be married and divorced, had less access to welfare payments, and lower unemployment and homeless rates than men. The most common psychiatric diagnosis was psychosis not otherwise specified with more women being affected (61.5% in women vs. 45.2% in men), but the diagnosis of schizophrenia was more common in men (38.4% vs 15.4%). Both groups exhibited very high levels of stress in the past year (mean total distress score > 300). In women, stress was significantly associated with age at first migration and be a racialized person. By contrast, among men stress was significantly associated with language barrier and comorbidity with a physical disorder. The results of this study reveal important differences between men and women immigrants. These findings underscore the importance of understanding how gender-specific roles and social expectations intersect with the timing and nature of migration to influence stress levels differently in immigrant women and men with psychotic disorders.

Cryptocurrency interest in geographical regions with high unemployment rates

Purpose- In regions with high unemployment rates, individuals often face economic uncertainty and may seek alternatives to traditional financial systems. In such circumstances, some individuals may turn to alternative investments and financial instruments, with cryptocurrencies such as Bitcoin being among them. The value of these cryptocurrencies is often volatile due to their speculative nature, which can lead investors to take on more significant risks. While this situation can result in substantial gains, it can also lead to significant financial losses. The primary use of cryptocurrencies is generally for investment purposes. Since cryptocurrencies are digital, they operate entirely in a virtual environment. The loss or theft of the digital password in the virtual space means the loss of the wallet. Security in cryptocurrencies is very weak. The lack of government guarantees and legal infrastructure globally poses certain threats to investors, making cryptocurrencies carry a higher risk compared to other investment instruments. This study will investigate the regional relationship between cryptocurrency interest and unemployment rates. The aim is to determine whether individuals living in geographical areas with high unemployment rates show more interest in cryptocurrencies compared to those in other geographical regions. Methodology- In line with the research objective, Google search engine data for the past 10 years has been analyzed using content analysis methodology. A query has been conducted to determine in which regions of Turkey cryptocurrency names are most frequently searched, and a comparison has been made on a provincial level across all 81 provinces. Additionally, considering the unemployment data provided by the Turkish Statistical Institute (TUIK), regions with high and low unemployment rates have been identified. Subsequently, an investigation has been carried out to determine whether there is any correlation between regional Google searches and unemployment rates in these areas. Findings- When examining the findings from the perspective of unemployment, it has been observed that the regions where cryptocurrency names are most frequently searched align with areas having the highest unemployment rates, while the least searched areas correspond to regions with lower unemployment rates. Among the 10 provinces with the highest unemployment rates, 8 of them are included in the list of 10 provinces with the highest Bitcoin search frequency. Similarly, 8 out of 10 provinces with the lowest employment rates are also listed among the 10 provinces with the highest Bitcoin search frequency. Furthermore, among the 10 provinces with the lowest per capita gross domestic product (GDP), 7 of them are included in the list of 10 provinces with the highest Bitcoin search frequency. Conclusion- As a result of the relationship analyses conducted in the research, it has been observed that in Turkey, regions with high unemployment rates, low employment rates, and low Gross Domestic Product (GDP) have a higher frequency of Bitcoin searches compared to other regions. Keywords: Cryptocurrency, unemployment, bitcoin JEL Codes: P44, E24, E44

A Short Period Sraffa-Keynes Model for the Evaluation of Monetary Policy

ABSTRACT This paper develops a short period, one sector, Sraffa-Keynes model that can be used for the evaluation of various recommendations outlined in the Post Keynesian monetary policy literature. The model is characterised by the principle of effective demand, Sraffa or target-return pricing (which integrates the determination of key distributive variables and allows for short run cyclical variation in prices), conflict inflation, endogenous money and a basic approach to monetary policy in the Smithin–Wray tradition of fixing the policy rate to achieve low or specified rates of unemployment. The model is calibrated to the Australian economy and subjected to two standard macroeconomic shocks, a demand shock and a cost shock. After each shock, the economy returns to long period equilibrium characterised by the achievement of the target rate of return, desired capacity utilisation and Sraffian prices of production. Active monetary policy that targets employment, reduces the depth and duration of recessions in this model compared to a ‘park-it’ approach but at the cost of increased volatility in income distribution. Flexible prices (where firms respond to the additional costs of running the capital stock at other than full capacity) are shown to have similar effects to monetary policy.

Analysis of Leading Sectors in Driving the Economy of Majene Regency

West Sulawesi is the province with the lowest unemployment rate in Indonesia. Majene is a regency in West Sulawesi with increasing economic growth. This research aims to analyze the typology and leading sectors in Majene regency. This research uses the LQ, Shift Share, and Klassen Typology analysis methods. The data used is secondary data in the form of GRDP of Majene regency and West Sulawesi province for 2018-2022 which is sourced from the Central Statistics Agency (BPS). The analysis is carried out by determining the base sector, then determining the progressive sector, and finally formulating a sector typology using the Klassen Typology. The research results show that those included in the leading sectors are the mining sector, electricity and gas procurement, transportation, accommodation provision, information, financial services, real estate, government administration, educational services and other services. This sector has the potential to be developed. It is hoped that the results of this research can become the basis for an economic development strategy by looking at the potential of each sector typology

The Role of Ease of Doing Business in Attracting Foreign Direct Investment in the SADC Region

This study seeks to analyze the role of ease of doing business in attracting foreign direct investment in the SADC region. The main goal of the study is to present new findings to corroborate whether ease of doing business factors are a significant and positive stimulus for Foreign Direct Investment (FDI). The study also proves to the role of ease of doing business to boost foreign direct investment in the SADC Region to enhance economic growth amid indications that foreign direct investment (FDI) streams in the SADC Region are diminishing rather than other economic communities all through the world, regardless of SADC’s endeavours to encourage an empowering environment for FDI. The research also verifies some hindrances such as negative gamble discernments, a troublesome business environment, and pervasive corruption as key elements given for SADC’s inability to attract and keep up with FDI. The study used panel data and therefore applied a Pooled Ordinary Least Squares (OLS) regression or a fixed effects model. The results revealed that gross fixed capital formation, political stability, corruption and gross domestic product were statistically significant towards FDI inflows into the SADC region. The study recommended that the SADC region should develop responsible foreign capital regulation which offers incentives for localized investment and lower unemployment rate by producing jobs and real income that can be used to either fuel economic growth or be saved in financial institutions.

A Revisionist View of Labor Market Dynamics in Türkiye

Reported unemployment and labor force participation rates do not account for demographic changes in the labor force. However, unemployment and labor force participation rates vary by gender and age group. Changes in the relative shares of these groups in the labor force will affect both labor market measures. Here we adjust both measures for age by gender to calculate an alternative age-adjusted unemployment rate and an age-adjusted labor force participation rate for Türkiye between 1988 and 2022. Two findings for women stand out particularly. Had the age composition of women not changed, the unemployment rate for women in 2022 would have been over three percentage points higher. Likewise, women’s labor force participation rate in 2022 has declined relative to what it would have been had the age composition remained constant since the late 1980s. The demographic change that kept the actual unemployment rates for women lower has been the increase in the labor force share of prime age women, which is the age group that historically has the lowest unemployment rate. Effect on labor force participation rate is driven by a fall in the participation of women aged 15-24.

Reactiveness and inclusiveness as the characteristics of regional labour markets regarding the situation of young people

Having observed the growing number of transnational shocks affecting the national and regional economies, it is worth assessing the condition of regional labour markets, primarily in the con -text of the situation of young people, who for many years have been one of the most vulnerable groups in the labour market. The problem of non-inclusiveness of the labour markets regarding young workers affects both markets presenting high unemployment rates and highly responsive to economic shocks, and also those featuring low youth unemployment rates and stable economic conditions. The article defines models of regional labour markets with regard to the situation of young people in terms of their reactivity of youth labour markets to economic shocks, and their inclusiveness compared to adults.

Female empowerment and crime patterns in Malaysia: A non-linear analysis

Using data from 1982 to 2020, this study evaluated the impact of female employment on violent crime in Malaysia using the non-linear ARDL technique. The study found that, in the long run, lower unemployment rates were linked to lower rates of violent crime, and increased female employment facilitated a short-term reduction in violent crime. Fewer women working resulted in a short-term rise in violent crime and, over the long term, higher rates of violent crime contributed to higher rates of jail population growth. Surprisingly, higher employment rates for women were eventually linked to higher rates of violent crime. Long-term trends showed a correlation between lower employment rates for women and greater rates of violent crime. For short-term analysis, negative economic growth was linked to a rise in violent crime, and positive economic growth could lower violent crime. These results demonstrated the complex interplay between a number of variables and violent crime rates. Thus, to successfully prevent violent crime and build safer societies, it is crucial to address socioeconomic inequalities, advance gender equality, and put into practice comprehensive methods that include community assistance, employment, education, and rehabilitation.

PERCEIVED WORKPLACE AGEISM AND OLDER WORKERS’ LABOR FORCE TRANSITIONS DURING THE GREAT RECESSION

Abstract Previous research suggests that workplace ageism increased during the Great Recession (GR). During the GR, despite having lower unemployment rates compared to younger workers, older workers took considerably longer to find jobs once they were unemployed. Yet, no study has investigated the potential role of workplace ageism in older workers’ labor force outcomes. This study examines the role of perceived workplace ageism in older workers’ labor force transitions during the GR using longitudinal data from the Health and Retirement study. I conduct a multi-period analysis and compare how the association of perceived workplace ageism with labor force transitions changed during the GR compared to pre and post-recession periods. Results from multivariate logistic regressions show that only in the GR period, both measures of perceived workplace ageism – pressure to retire before age 65 and preference for young in promotions – were associated with a higher likelihood of employment instability (b= 0.336 p< 0.05 and b= 0.340 p< 0.05), net of demographic, socioeconomic, financial, job-related and health-related factors. Moreover, older workers perceiving workplace were less likely to retire and thereby more likely to be unemployed (b= -0.667 p< 0.05). In contrast, perceived workplace ageism had no association with reducing or increasing the hours worked per week. In sum, this study provided the first individual-level evidence on the impact of perceived workplace ageism on older adults’ labor force transitions during the GR. Findings can be used to motivate additional studies on older workers’ experience during the Covid19 crisis.

Macroeconomic Fundamentals and the Volatility of Foreign Investors’ Net Purchase in Korean Stock Market

We employ the GARCH-MIDAS model to examine whether low-frequency macroeconomic variables help to explain the high-frequency volatility of the foreign investors’ net purchase in Korean stock market. The estimation results show that business cycle expansion along with high production growth, high inflation and low unemployment rate predicts high volatility in the near future. Higher interest rate and lower money growth are also likely to lead to higher volatility of foreign investors’ net purchase. We also find that domestic macroeconomic variables, relative to the US variables, have a stronger correlation with the future volatility of foreign investors’ net purchase.

코로나19는 여당 지지율을 상승시켰는가?

During the pandemic period, the world underwent significant changes not only in health and economic fields, but also in political ones. European politics also saw substantial changes in supporting rates for the ruling parties, far-right parties, and the main opposition parties. However, in exceptional situations like COVID-19, supporting rates for parties might be influenced more by the crisis itself than by party policies or economic performance. This paper aims to identify the key factors that contributed to the changes of supporting rates for the ruling parties, far-right parties, and the main opposition parties during the two waves of COVID-19 in 2020. A multiple regression analysis was conducted, with the dependent variable of supporting rates for the ruling parties, far-right parties, and the main opposition parties of 30 European countries, including EU member states(excluding Cyprus), Iceland, Norway, the UK, and Scotland, during the first wave, period of pause, and second wave of COVID-19. The independent variables are supporting rates for other parties, health factors such as COVID-19 casualties and confirmed cases, economic factors like GDP growth rate, inflation, total income, and 23 government-imposed lockdown measures of 30 European countries. The analysis revealed following findings. First, the human casualties of COVID-19 did not directly impact supporting rates of parties. The number of deaths per million was only positively correlated with an increase in support for the ruling party during the second wave, likely due to a rallying effect as the pandemic resurged. Second, among the lockdown measures, bans on outdoor activities, restaurant closures, and workplace shutdowns had an impact on the support rates for the ruling parties, far-right parties, and the main opposition parties. Countries that imposed outdoor activity bans for a longer duration experienced a decrease in support for the ruling parties, while far-right and main opposition parties’ supporting rates tended to increase. Third, economic factors continued to influence party support during the pandemic. Countries with higher GDP growth rates, higher total income, and lower unemployment rates during the first and second waves maintained higher supporting rates for the ruling parties. Additionally, during the second wave, countries with rapidly rising unemployment rates had higher supporting rates for far-right parties and the main opposition parties. Through this analysis, it became evident that supporting rates for parties in 30 European countries were influenced more by government-imposed lockdown measures and economic factors than by the direct impact of COVID-19 casualties during the pandemic spread.

Pembangunan Berkelanjutan Melalui Badan Usaha Milik Desa

The presence of village Sustainable Development Goals and village-owned enterprises is crucial to the development of regional economic activities and development as well as a major part of enabling the region to open up decent employment opportunities. The position of BUMDesa and the Sustainable Development Goals program has been regulated in legislation and local government policies. This research is descriptive research using a qualitative approach, namely a study by describing the data that researchers have collected, both data from interviews, observation and documentation during the research. Data analysis techniques used in qualitative research include transcripts of interview results, data reduction, data presentation and conclusion drawing. The results of data processing show that Ketapanrame Village has realized a sustainable development program through BUMDesa with 18 objectives of the village sustainable development program. The linkage shows such as the increasing welfare of the community, the lower unemployment rate because BUMDesa absorbs labor and partnerships almost entirely from the total number of villagers, the higher economy because almost all residents become BUMDesa partners. The level of village development is getting higher but the local government still maintains green land for food security and greening. Need for transparency of BUMDesa programs so that every citizen knows and understands entirely. Human Resources also need continuous coaching.

Labor Markets and Unemployment

As science and technology advance by leaps and bounds, they are gradually penetrating into every aspect of people's lives. Then currently, science is making giant strides in artificial intelligence growth at an astounding rate. In view of this trend, it shows with the current maturity of artificial intelligence technology, more and more low labor is replaced by machines. Based on the trend of future development above, model can be analyzed the maximum unemployment rate of the current market, and predict the relatively low future unemployment rate to help more people choose a occupation more conveniently. This article mainly analyzes some industries with the most unemployment rate and the industry with the smallest future unemployment rate through some of the readings of unemployment literature and industry unemployment data. In terms of research methods, the article's analysis is based on the multivariable linear regression model, calculation formula for unemployment rate, market hypotheses, and through the specific career data of doctor, lawyer and technician in recent years. With the total tendency to select the occupational population as the dependant variable, the occupational tax rate in US, the labor participation rate, and the risk coefficient are used as an independent variable, and the multi-linear regression model analysis is performed through data quantitative verification to calculate the actual number of people. Afterward used the unemployment population as a dependent variable, and the actual labor population is used as an independent variable, and the actual unemployment rate is derived through an unemployment calculation formula.

The impact of digitalization and economic openness on economic growth in ASEAN countries

Digitalization with the Sustainable Development Goals (SDGs) Program is an essential means of encouraging the government to operate more openly and effectively, which can increase global economic growth. This research aims to assess how education, digitalization, and trade openness affect the economic development of ASEAN. This study uses independent variables in the form of government spending on education, individual internet users, foreign direct investment and consumer price inflation. The dependent variable is economic growth. This study uses the panel data regression method, from 2001 to 2020, with a cross-section of 7 ASEAN countries (Indonesia, Malaysia, Thailand, Laos, Singapore, the Philippines and Cambodia). According to the study, the economic growth in seven ASEAN countries is significantly influenced by government expenditure on education, individual internet users, and foreign direct investment. Empirical evidence confirms that digitalization positively impacts both the economy and society, as reflected in lower unemployment rates, improved quality of life, and increased access to public services and information. Furthermore, digitalization simplifies learning about various aspects and activities related to conducting trade, thereby contributing to economic growth. The limitation of the study is that there is no categorizing between developed and developing countries with different income groups that lead to different digital technology developments.