Semestre 2

A comprehensive course on R software tailored for econometric analysis covers the essentials of using R for economic data analysis, starting with the setup of R and RStudio, and an introduction to R syntax. It emphasizes data types, structures, and manipulation specific to econometric datasets, alongside techniques for efficiently importing and exporting economic data. The course focuses on data cleaning and preparation to tackle common issues in economic data sets, such as handling missing values and time series data. A significant portion is dedicated to exploratory data analysis, employing descriptive statistics and visualization to uncover trends and relationships in economic indicators. It advances into statistical analysis and econometric modeling, including regression analysis, panel data analysis, and causality tests, equipping students with the skills to perform rigorous economic research. Programming fundamentals in R, such as writing functions and loops, are integrated with econometric applications to automate analysis tasks. Advanced topics may cover dynamic reporting with R Markdown for sharing econometric findings and using specialized libraries for advanced econometric techniques. Practical projects applying econometric methods to real-world economic data are included to bridge theory with practice, all while guiding students towards further resources and communities for ongoing development in econometric analysis with R.