A R Package to apply Machine Learning to Macro Economic Diffusion Indexes
Macroeconomics (from the Greek prefix makro- meaning “large” + economics) is a branch of economics dealing with the performance, structure, behavior, and decision-making of an economy as a whole. For example, using interest rates, taxes and government spending to regulate an economy’s growth and stability.
The main goal of the project is to help macroeconomists to obtain useful insights from a dataset as a whole with the help of useful Machine Learning Algorithms by creating it’s potential diffusion indexes. Time series analysis is an area of statistics that focuses on analyzing time-dependent data. Time series can be analyzed either descriptively or inferentially. This has led to different approaches depending on the type of information available in time-series data.
We will be using the method proposed by Stock and Watson in their paper called “Macroeconomic Forecasting Using Diffusion Indexes” published in 2002 for generating the forecasts initially and later proceed with the Machine Learning approach.
Check out the vignette for detailed process: https://github.com/Rishi0812/MacroDiffusionIndex/blob/main/vignettes/ML_for_MacroDiffusionIndexes.Rmd