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@@ -0,0 +1 @@ +/pytwoway-0.3.21.tar.gz diff --git a/python-pytwoway.spec b/python-pytwoway.spec new file mode 100644 index 0000000..443387f --- /dev/null +++ b/python-pytwoway.spec @@ -0,0 +1,127 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pytwoway +Version: 0.3.21 +Release: 1 +Summary: Estimate two way fixed effect labor models +License: MIT License +URL: https://github.com/tlamadon/pytwoway +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/23/9f/6d148b1568ce81513a49c86beed42155b130836882b362a4eae74ad6e437/pytwoway-0.3.21.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-pandas +Requires: python3-numba +Requires: python3-paramsdict +Requires: python3-bipartitepandas +Requires: python3-scipy +Requires: python3-statsmodels +Requires: python3-pyamg +Requires: python3-qpsolvers +Requires: python3-quadprog +Requires: python3-ConfigArgParse +Requires: python3-matplotlib +Requires: python3-tqdm + +%description +`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 <https://doi.org/10.1111/1468-0262.00020>`_ +2. homoskedastic bias correction as in `Andrews, et al. <https://doi.org/10.1111/j.1467-985X.2007.00533.x>`_ +3. heteroskedastic bias correction as in `Kline, Saggio, and Sølvsten <https://doi.org/10.3982/ECTA16410>`_ +4. group fixed estimator as in `Bonhomme, Lamadon, and Manresa <https://doi.org/10.3982/ECTA15722>`_ +5. group correlated random effect as presented in the main paper +6. fixed-point revealed preference estimator as in `Sorkin <https://doi.org/10.1093/qje/qjy001>`_ +7. non-parametric sorting estimator as in `Borovičková and Shimer <https://drive.google.com/file/d/1KW0sZ4nV9bIdVhcs-UW8yW_dzUr782v5/view>`_ +If you want to give it a try, you can start an example notebook for the FE estimator here: |binder_fe| for the CRE estimator here: |binder_cre| for the BLM estimator here: |binder_blm| for the Sorkin estimator here: |binder_sorkin| and for the Borovickova-Shimer estimator here: |binder_bs|. These start fully interactive notebooks with simple examples that simulate data and run the estimators. +The package provides a Python 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/>`_. +The code is relatively efficient. A benchmark below compares `PyTwoWay`'s speed with that of `LeaveOutTwoWay <https://github.com/rsaggio87/LeaveOutTwoWay/>`_, a MATLAB package for estimating AKM and its bias corrections. + +%package -n python3-pytwoway +Summary: Estimate two way fixed effect labor models +Provides: python-pytwoway +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-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 <https://doi.org/10.1111/1468-0262.00020>`_ +2. homoskedastic bias correction as in `Andrews, et al. <https://doi.org/10.1111/j.1467-985X.2007.00533.x>`_ +3. heteroskedastic bias correction as in `Kline, Saggio, and Sølvsten <https://doi.org/10.3982/ECTA16410>`_ +4. group fixed estimator as in `Bonhomme, Lamadon, and Manresa <https://doi.org/10.3982/ECTA15722>`_ +5. group correlated random effect as presented in the main paper +6. fixed-point revealed preference estimator as in `Sorkin <https://doi.org/10.1093/qje/qjy001>`_ +7. non-parametric sorting estimator as in `Borovičková and Shimer <https://drive.google.com/file/d/1KW0sZ4nV9bIdVhcs-UW8yW_dzUr782v5/view>`_ +If you want to give it a try, you can start an example notebook for the FE estimator here: |binder_fe| for the CRE estimator here: |binder_cre| for the BLM estimator here: |binder_blm| for the Sorkin estimator here: |binder_sorkin| and for the Borovickova-Shimer estimator here: |binder_bs|. These start fully interactive notebooks with simple examples that simulate data and run the estimators. +The package provides a Python 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/>`_. +The code is relatively efficient. A benchmark below compares `PyTwoWay`'s speed with that of `LeaveOutTwoWay <https://github.com/rsaggio87/LeaveOutTwoWay/>`_, a MATLAB package for estimating AKM and its bias corrections. + +%package help +Summary: Development documents and examples for pytwoway +Provides: python3-pytwoway-doc +%description help +`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 <https://doi.org/10.1111/1468-0262.00020>`_ +2. homoskedastic bias correction as in `Andrews, et al. <https://doi.org/10.1111/j.1467-985X.2007.00533.x>`_ +3. heteroskedastic bias correction as in `Kline, Saggio, and Sølvsten <https://doi.org/10.3982/ECTA16410>`_ +4. group fixed estimator as in `Bonhomme, Lamadon, and Manresa <https://doi.org/10.3982/ECTA15722>`_ +5. group correlated random effect as presented in the main paper +6. fixed-point revealed preference estimator as in `Sorkin <https://doi.org/10.1093/qje/qjy001>`_ +7. non-parametric sorting estimator as in `Borovičková and Shimer <https://drive.google.com/file/d/1KW0sZ4nV9bIdVhcs-UW8yW_dzUr782v5/view>`_ +If you want to give it a try, you can start an example notebook for the FE estimator here: |binder_fe| for the CRE estimator here: |binder_cre| for the BLM estimator here: |binder_blm| for the Sorkin estimator here: |binder_sorkin| and for the Borovickova-Shimer estimator here: |binder_bs|. These start fully interactive notebooks with simple examples that simulate data and run the estimators. +The package provides a Python 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/>`_. +The code is relatively efficient. A benchmark below compares `PyTwoWay`'s speed with that of `LeaveOutTwoWay <https://github.com/rsaggio87/LeaveOutTwoWay/>`_, a MATLAB package for estimating AKM and its bias corrections. + +%prep +%autosetup -n pytwoway-0.3.21 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-pytwoway -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.21-1 +- Package Spec generated @@ -0,0 +1 @@ +1c64171d7fc70d23475ad2b8d5bf0a99 pytwoway-0.3.21.tar.gz |