Skip to main content

Estimate two way fixed effect labor models

Project description

pytwoway

https://badge.fury.io/py/pytwoway.svg https://travis-ci.com/tlamadon/pytwoway.svg?branch=master https://img.shields.io/badge/doc-latest-blue

pytwoway is the python package associated with the following paper:

How Much Should we Trust Estimates of Firm Effects and Worker Sorting?.” 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

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 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. The online documentation is hosted here.

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 the 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}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytwoway-0.1.3.tar.gz (40.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pytwoway-0.1.3-py3-none-any.whl (45.7 kB view details)

Uploaded Python 3

File details

Details for the file pytwoway-0.1.3.tar.gz.

File metadata

  • Download URL: pytwoway-0.1.3.tar.gz
  • Upload date:
  • Size: 40.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.8.1 pkginfo/1.6.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.7.9

File hashes

Hashes for pytwoway-0.1.3.tar.gz
Algorithm Hash digest
SHA256 f705a2999eceeab942c7f088bb782ebc03bb562501430cd293f7c0cdf93e109e
MD5 8c7832f287894682b0d3b28a19279410
BLAKE2b-256 36843d99b0c932254428e53250ca7c0803962b5592fc99d0406deeee5e163a17

See more details on using hashes here.

File details

Details for the file pytwoway-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: pytwoway-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 45.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.8.1 pkginfo/1.6.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.7.9

File hashes

Hashes for pytwoway-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 3075aea084a9a7bdb5417d01cb2359349a3804f054c3f4cf9f538ffb64f8a729
MD5 666624d789d0221a25fe3121953ea94c
BLAKE2b-256 87593f61c09bf73c126bfc7e4c08e858c7a1a9e737b935b2fbc09e9033058996

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page