This portfolio showcases my academic journey through key courses in my Economics and Management Science degree. It highlights my engagement with and growing understanding of econometrics, monetary economics, macroeconomic theory, regression analysis, and business forecasting techniques.
These courses introduced me to the fundamentals and advanced concepts of econometrics, enhancing my ability to analyze economic data using statistical methods.
Key Learnings and Projects:
- ECN627 laid the groundwork in econometric techniques, focusing on linear regression models, estimation, inference, and addressing issues like heteroscedasticity and endogeneity.
- ECN702 expanded on these concepts, introducing me to more complex topics such as instrumental variable estimation, panel data models, binary choice models, and the basics of time series analysis.
Skills Developed:
- Built a solid foundation in understanding and applying econometric models.
- Gained experience in data analysis with a focus on economic applications.
- Developed proficiency in statistical software, particularly R, for econometric analysis.
This course explored the microfoundations of money through the Overlapping Generations (OLG) model, offering insights into the role of money in the economy.
Key Learnings and Projects:
- Investigated the impact of bond stock increases on capital investment decisions.
- Examined scenarios where fiscal deficits do not lead to capital crowding out.
- Analyzed the crowding out effect of fiat money on capital.
Skills Developed:
- Enhanced understanding of monetary theory and policy.
- Improved analytical skills in macroeconomic contexts.
Focused on modern macroeconomic theory, this course developed my analytical skills for studying economic growth, business cycles, and policy analysis within a dynamic framework.
Key Learnings and Projects:
- Gained insights into dynamic optimization techniques.
- Explored the application of dynamic macroeconomic models for policy analysis.
Skills Developed:
- Increased knowledge in macroeconomic analysis and modeling.
- Familiarity with dynamic optimization methods.
Introduced me to time series forecasting techniques, emphasizing the practical aspects of forecasting.
Key Learnings and Projects:
- Learned about smoothing, auto regression, and ARIMA models for forecasting.
- Undertook a forecasting project involving data acquisition, model selection, and interpretation.
Skills Developed:
- Developed skills in time series forecasting.
- Gained experience with forecasting software, particularly R.
This portfolio illustrates my dedication to understanding and applying complex economic and financial concepts. It highlights my academic growth and my ongoing journey as a learner eager to tackle challenges in economics, finance, and data analysis.