Forecasting CPI Inflation with Hierarchical Recurrent Neural Networks
This Repository contains implementation of novel model we suggested in our paper.
- Hierarchical GRU
In addition as a contribution for further research we provide he data set used in this work, which is taken from the BLS after parsing and pre-processing.
The data could be found on data/cpi_us_dataset.csv note: this is a sample from the all data
A brief description of the data set:
The data set contains the following columns:
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Date (differs by month)
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Category- item name
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Category id- item unique id
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Price- Seasonally adjusted CPI-U for the given month
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Weight- Relative importance of the item from the total aggregated index (=100)
*Indent- The hierarchy level (total aggregated index has indent 0, lowest level is 8)
*Parent- Parent’s item name
*Parent ID- Parent’s item ID
In order to run the code please make sure all Prerequisites are met (Pandas==0.22 in particular)
Prerequisites
pip install -r requirements.txt
To execute the code please run one of the following
- hierarchical_gru.py