Metadata-Version: 2.1
Name: grmpy
Version: 0.1.10
Summary: grmpy is a Python package for the simulation and estimation of the generalized Roy model.
Home-page: http://grmpy.readthedocs.io
Author: The grmpy Development Team
Author-email: eisenhauer@policy-lab.org
License: MIT
Description: grmpy is a Python package for the simulation and estimation of the generalized Roy model.
        
        # grmpy
        
        ``grmpy``  is an open-source Python package for the simulation and estimation of the generalized Roy model. It serves as a teaching tool to promote the conceptual framework of the generalized Roy model, illustrate a variety of issues in the econometrics of policy evaluation, and showcases basic software engineering practices. <br>
        Marginal Treatment Effects (MTE) can be estimated based on a parametric normal model or,
        alternatively, via the semiparametric method of Local Instrumental Variables (LIV).
        
        You can install ```grmpy``` either via pip
        
        ```
        $ pip install grmpy
        ```
        Or download it directly from our GitHub repository and install the package in editable mode
        
        ```
        $ git clone https://github.com/OpenSourceEconomics/grmpy.git
        $ pip install -e .
        ```
        
        ---
        ## Quick Start
        > Initialization File
        
        ```grmpy``` relies on an ```"initialization.yml"``` file (referred to as ``ìnit_file`` below)
        to perform both simulation and estimation.
        For example, check out these two ``init_files`` for
        [simulation and parametric estimation](https://github.com/OpenSourceEconomics/grmpy/blob/master/promotion/grmpy_tutorial_notebook/files/tutorial.grmpy.yml) as well as 
        a [semiparametric estimation](https://github.com/OpenSourceEconomics/grmpy/blob/master/promotion/grmpy_tutorial_notebook/files/tutorial_semipar.yml) setup.
        
        Below you'll find some example code you can copy to jump-start your project.  
        
        > Simulation
        ```
        import grmpy
        
        # Specify the initilaization file you want to use, e.g.:
        init_file = "ProjectFiles/simulation.yml"
        
        data = grmpy.simulate(init_file)
        ```
        > Estimation
        
        ```
        import grmpy
        
        # Specify the initilaization file you want to use, e.g.:
        init_file = "ProjectFiles/estimation.yml"
        
        # Parametric Normal Model
        rslt = grmpy.fit(init_file, semipar=False)
        grmpy.plot_mte(rslt, init_file, color="blue", semipar=False, save_plot="MTE_par.png")
        
        # Local Instrumental Variables (Semiparametric Model)
        rslt = grmpy.fit(init_file, semipar=True)
        grmpy.plot_mte(rslt, init_file, color="orange", semipar=True, nboot= 250, save_plot="MTE_semipar.png")
        ```
        
        Please visit our [online documentation](http://grmpy.readthedocs.io/) for tutorials and more.
        
        -----
        [![docs passing](https://travis-ci.org/OpenSourceEconomics/grmpy.svg?branch=master)]()
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