This study investigates the impact of interest rate effectiveness, inflation, and exchange rates on economic growth in Indonesia between 2014 and 2023. Using a simultaneous equation model and the Two-Stage Least Squares (TSLS) estimation technique, the research analyzes the interrelationships among key macroeconomic indicators. The results show that exports and investment significantly influence GDP, whereas the exchange rate and money supply have no notable effect. Furthermore, GDP growth is identified as a significant determinant of investment, while interest rates and inflation are found to be statistically insignificant. The diagnostic tests confirm that the regression model satisfies the classical assumptions of normality and absence of autocorrelation. These findings highlight the importance of promoting exports and enhancing investment to support Indonesia’s sustainable economic development. Policymakers are encouraged to focus on trade performance and investment climate, as these factors have a stronger direct impact on growth compared to inflation and interest rates during the observed period.

This study aims to analyze the variable contribution of the interaction of monetary policy variables (COURSE, GDP, INFLATION, CONSUMPTION and INTEREST). This study uses secondary data or time series from the first quarter of 2014 to the first quarter of 2024. The data analysis model in this study is the Structural Vector Autoregression (SVAR) model and sharpened with Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) analysis. The results of the SVAR analysis show that the past variable (t-1) contributes to the current variable both to itself and other variables and from the estimation results it turns out that there is a reciprocal relationship between variables where all variables, namely monetary policy variables (GDP, INFLATION, CURRENCY, CONSUMPTION and INTEREST) contribute to each other.

This research aims to look at the relationship between Fintech Innovation, Financial Inclusion, Green Finance, and Balance of Trade in Indonesia. Financial technology innovation is experiencing very rapid development. Green Finance or a sustainable green economy itself can be interpreted as anything that can be enjoyed not only now but for the long term into the future which ultimately aims to improve the Indonesian economy and play a positive role in the growth of the trade balance. The research method in this research is using the VAR method. The VAR model is a model that is used without emphasizing the problem of exogeneity of the variables used in the analysis. The VAR model makes it easy to provide answers and provide empirical and more complex evidence of the long-term reciprocal relationship of economic variables that contribute to one another. The research results in this study are that the variables are related to each other.

Using a quantitative approach, this study investigates the effect of port export and import volumes on economic growth in North Sumatra and West Sumatra Provinces. Time series data from the World Bank and the Central Statistics Agency (BPS) from 2006 to 2023 are used as secondary data. The analysis uses the ARDL Panel model, which allows for analysis of data dynamics across time and regions. The results show that the three main indicators that affect economic growth (GRDP) in both provinces, both in the short and long term, are export volume, inflation, and exchange rates. In North Sumatra, export volume has a positive impact on GRDP, while import volume has a negative impact, indicating a risk of dependence on imports. Controlled inflation also has a positive impact, while the exchange rate shows a diversion. Policy recommendations are expected to improve global competitiveness and exchange rate stability through coordination of fiscal and monetary policies, support for the Export Capacity Building Program and MSMEs through the Regional Comprehensive Economic Framework (RCEP), and export diversification to reduce dependence on certain commodities. This study emphasizes that policies that are responsive to changes in trade at the national to international levels are an important foundation for stabilizing sustainable economic growth.

The banking industry has a very important role in a country's economy. One of the things related to the banking sector is operational activities towards the environment. The increasing environmental damage that occurs is a form of human indiscipline in managing natural resources. Therefore, efforts that banks can make to implement environmentally friendly practices in their operational activities are green banking by considering the 5P aspects, namely People, Planet, Partnership, Peace and Prosperity. Even though banks do not contribute directly to environmental pollution, sectors that carry out business activities cannot possibly operate if they do not have capital to finance their operations and one of the financial institutions that provides capital in the form of financing is banks. So, indirectly banks play an important role in environmental sustainability. This research aims to investigate the impact of green banking on financial inclusion and the growth of Islamic banking in Indonesia. The data analysis method employed is the Seemingly Unrelated Regression (SUR) method. The research approach is associative/quantitative, utilizing secondary data obtained and processed from annual reports and sustainability reports available on the official websites of the respective companies. Additionally, references from scientific journals and previous studies on selected Islamic banks are used. The sample includes PT. Bank Central Asia Sharia Tbk, PT. Bank KB Bukopin Syariah Tbk, PT. Bank Mega Syariah Tbk, PT. Bank Muamalat Indonesia Tbk, PT. Bank Panin Dubai Syariah Tbk, and PT. Bank National Retirement Savings Account Sharia Tbk, covering the period from 2019 to 2023.

This research aims to analyze the effectiveness of the mixed economic model in controlling financial system stability in 7 emerging market countries. Where the monetary policy variables are the money supply and interest rates. Then the microprudential variables are Return On Equity and Return On Assets, the macroprudential variables are Capital Adequacy Ratio and Non Performing Loans. The financial system stability variables are the inflation level and exchange rate. The data analysis model in this research is the Simultaneous model. This research uses secondary data or time series, namely from 2019 to 2023. This analysis is significant for controlling the financial system by ensuring the data meets normality assumptions through the Jarque-Bera test, which allows for more precise financial planning and risk management decisions. The absence of autocorrelation effects, as proven in the residual test, also strengthens the reliability of the model in understanding market trends. The Two-Stage Least Squares method in simultaneous regression analysis provides in-depth insight into the relationship between economic variables such as the inflation rate and the exchange rate, supporting effective economic policy making. Understanding the elasticity of key variables to the inflation rate and exchange rate is also important for optimizing risk control strategies and financial resource allocation.