I'm trying to make a forecasting model for goods prices in an economy (trying to forecast inflation).
Dataset: has 300 goods prices % monthly variations for last 6 years. And also added $n$ macroeconomic variables time series.
- Input: Last 12 variation of 300 goods prices + 12 variations of $n$ macroeconomic variables
- Output: Next variation for 300 goods prices (only one step).
I was thinking about using a LSTM model, but I don't know if the dimensionality will be a problem or if there are better models or some kind of recommended data pre processing.