Metadata-Version: 2.1
Name: greenbook-shocks
Version: 0.0.1
Summary: Estimates the Greenbook narrative shocks
Home-page: https://github.com/joe5saia/GreenbookNarrativeShocks
Author: Joe Saia
Author-email: joe5saia@gmail.com
License: UNKNOWN
Description: # GreenbookNarrativeShocks
        
        This package estimates up to date Romer and Romer Greenbook Narrative shocks, originally from
        [A New Measure of Monetary Shocks: Derivation and Implications](https://www.aeaweb.org/articles?id=10.1257/0002828042002651), 2004.
        
        # Installation
        `pip install greenbookshocks`
        
        # Usage
        The core class is the `RRGB` (Romer and Romer GreenBook) class. When this class is instantiated it
        downloads the data necessary to create the Romer and Romer Greenbook narrative shock series.
        The user needs to supply the original data appendix file from
        [Romer and Romer](https://www.aeaweb.org/articles?id=10.1257/0002828042002651), (2004)
        with the path specified by the `rrfname` argument in the class call, which defaults
        to `rrfname='RomerandRomerDataAppendix.xls'`. The user then needs to call the `estimate_shocks()` method.
        The following code exactly replicates the original shock series.
        
        ```python
        from rrgb import RRGB
        from datetime import datetime
        # Assemble Data
        rrgb = RRGB(rrfname='RomerandRomerDataAppendix.xls', rr_override=True)
        # Estimate shocks
        shocks = rrgb.estimate_shocks()
        ```
        
        The final shock series will be indexed by the meeting date. The user may then aggregate the
        series up with her preferred aggregation method.
        
        # Advanced Usage
        The original dataset used in [Romer and Romer](https://www.aeaweb.org/articles?id=10.1257/0002828042002651), (2004)
        was drawn from the text of the Greenbook itself. This package supplements this data with the Greenbook datasets
        provided by the Federal Reserve Bank of Philadelphia which is drawn from internal forecast materials prepared by
        the Federal Reserve Board of Governors staff. This dataset varies slightly from the Romer and Romer dataset. For
        earlier periods, the Romer and Romer dataset contains a few additional forecast observations which this package
        always uses. In 1972, the Philadelphia Fed dataset has additional observations. By default this package does not
        use these observations, allowing it to exactly match the original Romer and Romer dataset. If the user would like
        to use the full dataset then she may specify the `rr_override` argument as `False`, e.g. `RRGB(rr_override=False)`,
        the default behavior is True.
        
        # Custom models
        The `estimate_shocks()` method allows the user to specify the date range of the shocks, the control variables
        used in the regression, wether or not to drop ZLB periods in estimation and the model to use to form the predicted
        shocks. See the docstring for additional information.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
