This study aims to analyze the impact of the monetary and fiscal policy mix on Indonesia's economic growth during the COVID-19 pandemic in the period 2013-2023. Using the Simultaneous Regression method (Two-Stage Least Squares/2SLS), this study tests two simultaneous equations, namely the effect of exports, unemployment rate, and inflation on economic growth (GDP), as well as the effect of exchange rates (exchange rates), interest rates, and GDP on inflation. The results of the study indicate that exports and unemployment have a significant negative effect on economic growth, while inflation has a significant positive effect on GDP. Meanwhile, the exchange rate and interest rate have a significant effect on inflation, but GDP does not have a significant effect on inflation. The normality test shows that the data is normally distributed and the autocorrelation test does not detect any autocorrelation, so the model used is valid. The effectiveness of monetary policy through the exchange rate channel on economic growth was found to be positive, although not statistically significant. This finding emphasizes the importance of coordination between fiscal and monetary policies, maintaining exchange rate stability, controlling inflation, and efforts to restore the real sector and reduce unemployment to support sustainable economic growth in Indonesia. This study provides recommendations for the government and monetary authorities to strengthen policy synergy in facing economic challenges, especially during times of crisis, to ensure more effective national economic stability and recovery.

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.

This study aims to determine the effect of monetary policy on economic growth. This study uses the Vector Autoregression method by completing the assumption test and estimation on the research variables of inflation, investment, credit, interest rates and gross regional domestic product. Time series research data from 2003-2022 sourced from the Central Bureau of Statistics of North Sumatra (BPS) SUMUT with the results obtained are inflation and interest rates give the results that inflation is influenced by investment and credit, until investment affects gross regional domestic product. Then credit also affects inflation and interest rates and gross regional domestic product is influenced by investment and credit. Thus, in determining policies that encourage economic growth the government must consider a more coordinated monetary policy strategy to deal with the dynamics of strengthening interest rates, controlling inflation, can be measures that support economic stability.

This research aims to determine the influence of interest rates, consumption, investment, unemployment and renewable energy on inflation and gross domestic product (GDP) in Indonesia. The variables in this research are Interest Rates, Consumption, Investment, Unemployment and Renewable Energy as independent variables, while the variables Inflation and Gross Domestic Product (GDP) are the dependent variables. The research period is 1993 - 2023. The data analysis technique used is the Simultaneous model, with testing using Eviews 10. Based on the results of the simultaneous analysis, the variables Interest Rate, Consumption and GDP have a positive and significant effect on Inflation. Meanwhile, the Investment Variable does not have a positive and significant effect on Inflation. The Renewable Energy and Inflation variables have a positive and significant effect on GDP. Meanwhile, the unemployment variable does not have a positive and significant effect on GDP.
 

This research aims to analyze the influence of financial sector deepening and foreign exchange reserves on currency exchange rates in Indonesia, Malaysia and the Philippines. The variables in this research are exchange rate, GDP, credit interest rates, money supply, foreign exchange reserves. This research uses secondary data taken from WorldBank in 2005-2022. The data analysis technique used is the Autoregressive Distributed Lag (ARDL) panel. The research results from the ARDL model analysis show that the countries that are able to become lead indicators for KURS tariff stability are Indonesia and Malaysia. This is because all the variables or indicators in the research, namely (Foreign Exchange Reserves, GDP, JUB and Credit Interest Rates) in these countries have a significant effect on the KURS, while CDV, GDV and JUB do not have a significant effect on the KURS. in the Philippines, only the SBK variable has a significant effect on the KURS in the Philippines. If we look at short-term and long-term stability, the Unemployment Rate variable, both short-term and long-term, has a significant effect on KURS stability.

This research aims to determine Renewable Energy, Emission Intensity, Life Expectancy, and Unemployment Rate on Gross National Income (GNI) in Estonia, Finland, Germany, Hungary, and Norway. The variables in this research are Renewable Energy, Emission Intensity, Life Expectancy, and Unemployment Rate as independent variables, while the Gross National Income variable is the dependent variable. This research uses secondary data taken from the OECD from 2011-2023. The data analysis technique used is the Autoregressive Distributed Lag (ARDL) panel. The research results from the ARDL model analysis show that the country that is able to become a leading indicator for the stability of the GNI rate is only Norway. This is because all the variables or indicators in the research, namely (Renewable Energy, Life Expectancy, and Unemployment Rate), this country has a significant effect on GNI. while the Emission Intensity variable does not have a significant effect on GNI. If we look at the stability of the short run and long run, the Unemployment Rate variable, both in the short and long term, significantly controls the stability of GNI.
 
 

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.