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This research examines the impact of initiatives from the private sector to reach self-sufficiency in the Agricultural Sector. The researchers utilized the following independent variables: Land Ownership of Farmers, Agricultural Credit, Agricultural Exports, Raw Material Imports, and Foreign Direct Investments concerning Agricultural Output — the dependent variable. Using a Time Series Approach, data from 2005 to 2021 was utilized and tested through the Ordinary Least Squares (OLS) regression analysis. Findings have revealed that while technology and importing raw materials could drive growth, agricultural credit and land ownership heavily depend on government policies and reforms. That said, government intervention could not be isolated from the Agricultural Sector as collaborating between the private and public sectors would optimize the agricultural sector.

The ocean is one of the significant sources of livelihood in the Philippines. The blue economy refers to ocean sustainability, from biodiversity to ecosystem health maintenance. With the motive to generate income, the blue economy coincides with the concept of good stewardship of ocean resources. The blue economy is said to have the potential to boost economic growth. The study aimed to examine the effect of the blue economy on Philippine economic growth through the use of the following variables: the Fisheries sector, Maritime Transportation sector, and Tourism sector. In addition, the researchers utilized a descriptive-quantitative approach to observe the annual time series data that covered the period from 2000-2021. Using GretL as the statistical tool, the relationship between the variables was measured and correlated through an Ordinary Least Squares (OLS) regression analysis. The researchers determined that only one of the three sectors positively affect Philippine economic growth. The fisheries (F) and maritime transportation (MT) have no positive effect on Philippine economic growth, regardless of the fisheries sector being statistically significant to the real GDP. Meanwhile, the tourism sector (T) has a significant and positive correlation with Philippine economic growth.

Medical migration is a vast field that covers numerous concerns, one of which is the shortage of healthcare workers in source countries. The “push and pull” factors that influence the migration of Filipino healthcare workers can be determined, hence, this research examines how the factors affect the Filipino healthcare workers’ decision to migrate. Moreover, this research aims to help the Philippine healthcare sector in order to further promote protection and retention of local healthcare workers. Hence, providing means to support the well-earned care for the Filipino healthcare workers.

The Philippines has one of the highest income inequality rates in Southeast Asia. Empirical studies suggest that entrepreneurial activity and high unemployment produce income inequality. 26.14 million Filipinos whose per capita income is inadequate to cover their basic food and non-food needs live below the poverty line. This study examines whether entrepreneurship will help decrease income inequality and whether unemployment is related to income inequality. Time-series multiple regression model using the Ordinary Least Square is used to determine the significance of the independent variables to the dependent variable. The results indicate that entrepreneurship positively affects income inequality, yet the unemployment rate was found insignificant to the dependent variable. Changes in the unemployment rates do not affect income inequality in the Philippines. However, entrepreneurial activities can aggravate income dispersion within the income distribution. In the Philippines, income is concentrated on entrepreneurs with capital, while the low-skilled and entrepreneurs without capital experience failure. Their business endeavors may not generate the expected return on investment and earn less than salary/wage workers. Despite this, the Philippines should still pursue entrepreneurship-enhancing policies because of its potential to create employment, its contribution of value to the economy, and its engagement prominently in export trade. The Philippine Government should keep supporting entrepreneurial activities and mitigate income inequality by bolstering low-skilled entrepreneurs by giving them access to credit, education, information, and training and easing the business process.

The Tax Reform for Acceleration and Inclusion (TRAIN) policy intends to make the tax system simpler, fairer, and more efficient while also encouraging investments, job creation, and poverty reduction. This tax reform package 1 lowers personal income taxes, removes VAT exemptions, and changes the excise tax on petroleum goods and automobiles, making the tax system more equitable while simultaneously rectifying injustice. This study determines the relationship between the TRAIN Law and the increase in income on the country's consumption, savings, and unemployment rate. Using the multiple regression analysis, this study proves that TRAIN Law and the additional income positively affect consumption. The savings also has a significant positive relationship with the increase in income; however, it has a significant negative relationship with TRAIN Law. This study also shows that while the unemployment rate in the country decreases when income rises, the TRAIN law, on the other hand, relates to the increase in the unemployment rate. The results of this research suggest that the said tax reform has had a considerable beneficial impact on consumption, it has had an adverse influence on the growth rate of savings and unemployment in the country, hence in order to improve the delivery of essential services and better future social and economic results, the government should consider modifying the TRAIN Law and introducing a tax or policy that would stimulate private savings and employment.

Artificial intelligence is designed to generate technologies that potentially increase productivity and economic welfare. This study analyzes the relationship between GDP and high-technology exports, GDP per person employed, and unemployment rate in China, India, Japan, and Singapore. Recent concerns on technological unemployment claim that artificial intelligence disrupts the labor market which decreases employment over time. Using the multiple regression analysis, this study proved that Japan comparatively has better utilization of AI and labor productivity as all independent variables show significance to the GDP. Labor productivity in all countries is positively related to GDP. However, China and India showed signs of improper AI utilization as technological unemployment occurred. The unemployment rate in China is insignificant to its GDP, while India's unemployment rate is positively related to GDP, hence the jobless growth. In Singapore, the insignificance of high-tech exports to GDP is due to its lack of R&D investments these recent years. The results suggest that AI escalates growth through proper utilization trade liberalization, as exercised by Japan, as it helps the economy to be open and flexible to various free trade agreements which facilitates technological progress and enables the opening of new markets for growth and expansion, especially of artificial intelligence, which attracts and encourage foreign direct investments that will cater technology transfer, creation of new jobs, and economic growth.