From c08c604036fec64211f4a13df8eaf33381c7feff Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Mon, 15 May 2023 03:20:36 +0000 Subject: automatic import of python-pytwoway --- python-pytwoway.spec | 127 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 127 insertions(+) create mode 100644 python-pytwoway.spec (limited to 'python-pytwoway.spec') 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? `_" +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 bias correction as in `Kline, Saggio, and Sølvsten `_ +4. group fixed estimator as in `Bonhomme, Lamadon, and Manresa `_ +5. group correlated random effect as presented in the main paper +6. fixed-point revealed preference estimator as in `Sorkin `_ +7. non-parametric sorting estimator as in `Borovičková and Shimer `_ +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 `_. The online documentation is hosted `here `_. +The code is relatively efficient. A benchmark below compares `PyTwoWay`'s speed with that of `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? `_" +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 bias correction as in `Kline, Saggio, and Sølvsten `_ +4. group fixed estimator as in `Bonhomme, Lamadon, and Manresa `_ +5. group correlated random effect as presented in the main paper +6. fixed-point revealed preference estimator as in `Sorkin `_ +7. non-parametric sorting estimator as in `Borovičková and Shimer `_ +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 `_. The online documentation is hosted `here `_. +The code is relatively efficient. A benchmark below compares `PyTwoWay`'s speed with that of `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? `_" +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 bias correction as in `Kline, Saggio, and Sølvsten `_ +4. group fixed estimator as in `Bonhomme, Lamadon, and Manresa `_ +5. group correlated random effect as presented in the main paper +6. fixed-point revealed preference estimator as in `Sorkin `_ +7. non-parametric sorting estimator as in `Borovičková and Shimer `_ +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 `_. The online documentation is hosted `here `_. +The code is relatively efficient. A benchmark below compares `PyTwoWay`'s speed with that of `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 - 0.3.21-1 +- Package Spec generated -- cgit v1.2.3