Metadata-Version: 2.1
Name: pytwoway
Version: 0.1.0
Summary: Estimate two way fixed effect labor models
Home-page: https://github.com/tlamadon/pytwoway
Author: Thibaut Lamadon
Author-email: thibaut.lamadon@gmail.com
License: UNKNOWN
Description: pytwoway
        --------
        
        .. image:: https://badge.fury.io/py/pytwoway.svg
            :target: https://badge.fury.io/py/pytwoway
        
        .. image:: https://travis-ci.com/tlamadon/pytwoway.svg?branch=master
            :target: https://travis-ci.com/tlamadon/pytwoway
        
        `pytwoway` is the Python package associated with the following paper:
        
        "`How Much Should we Trust Estimates of Firm Effects and Worker Sorting?. <https://www.nber.org/system/files/working_papers/w27368/w27368.pdf>`_" 
        by Stéphane Bonhomme, Kerstin Holzheu, Thibaut Lamadon, Elena Manresa, Magne Mogstad, and Bradley Setzler.  
        No. w27368. National Bureau of Economic Research, 2020.
        
        The package provides implementations for a series of estimators for models with two sided heterogeneity:
        
        1. two way fixed effect estimator as proposed by Abowd Kramarz and Margolis
        2. homoskedastic bias correction as in Andrews et al
        3. heteroskedastic correction as in KSS (TBD)
        4. a group fixed estimator as in BLM
        5. a group correlated random effect as presented in the main paper
        
        .. |binder| image:: https://mybinder.org/badge_logo.svg 
            :target: https://mybinder.org/v2/gh/tlamadon/pytwoway/HEAD?filepath=docs%2Fnotebooks%2Fpytwoway_example.ipynb
        
        If you want to give it a try, you can start the example notebook here: |binder|. This starts a fully interactive notebook with a simple example that generates data and runs the estimators.
        
        The code is relatively efficient. Solving large sparse linear models relies on using `pyamg <https://github.com/pyamg/pyamg>`_. This is the code we used to estimate the different decompositions on the US data. 
        
        The package provides a python interface as well as an intuitive command line interface. Installation is handled by `pip` or `conda` (TBD). The source of the package is available on github at `pytwoway <https://github.com/tlamadon/pytwoway>`_. The online documentation is hosted  `here <https://tlamadon.github.io/pytwoway/>`_.
        
        Quick Start
        -----------
        
        To install from pip, run::
        
            pip install pytwoway
        
        
        To run using the command line interface::
        
            pytw --my-config config.txt --fe --cre
        
        
        Example config.txt::
        
            data = file.csv
            filetype = csv
            col_dict = "{'fid': 'your_firmid_col', 'wid': 'your_workerid_col', 'year': 'your_year_col', 'comp': 'your_compensation_col'}"
        
        
        Citation
        --------
        
        Please use following citation to cite pytwoway in academic publications:
        
        Bibtex entry::
        
          @techreport{bhlmms2020,
            title={How Much Should We Trust Estimates of Firm Effects and Worker Sorting?},
            author={Bonhomme, St{\'e}phane and Holzheu, Kerstin and Lamadon, Thibaut and Manresa, Elena and Mogstad, Magne and Setzler, Bradley},
            year={2020},
            institution={National Bureau of Economic Research}
          }
        
        
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
