Metadata-Version: 2.1
Name: pytwoway
Version: 0.0.3
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
        Two way fixed effect models for labor in python
        
        Full documentation can be found [here](https://tlamadon.github.io/pytwoway/).
        
        Quick start:
        
        To install from pip:
        ```shell
        pip install pytwoway
        ```
        
        To run using command line interface:
        ```shell
        pytw --my-config config.txt --akm --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'}"
        ```
        
        To run in Python:
        - If you have data
        ```python
        from pytwoway import twfe_network
        tn = twfe_network.twfe_network
        # Create twfe object
        tw_net = tn.twfe_network(data, formatting, col_dict)
        # Convert long data into event study data (not necessary if the data is already in event study format):
        tw_net.refactor_es()
        # Run the bias-corrected AKM estimator:
        tw_net.run_akm_corrected(user_akm)
        # Cluster firms based on their wage CDFs (required for the CRE estimator)
        tw_net.cluster(user_cluster)
        # Run the CRE estimator
        tw_net.run_cre(user_cre)
        ```
        
        - If you want to simulate data
        ```python
        from pytwoway import sim_twfe_network
        sn = sim_twfe_network.sim_twfe_network
        # Create simulated twfe object
        stw_net = sn(sim_params)
        # Generate data
        sim_data = stw_net.sim_network()
        ```
        
        - If you want to run Monte Carlo on simulated data
        ```python
        from pytwoway import sim_twfe_network
        sn = sim_twfe_network.sim_twfe_network
        # Create simulated twfe object
        stw_net = sn(sim_params)
        # Run Monte Carlo
        stw_net.twfe_monte_carlo(N, ncore, akm_params, cre_params, cluster_params)
        # Plot results
        stw_net.plot_monte_carlo()
        ```
        
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
