rename to EstimatingMicroDSOPs

README.md

@@ -1,15 +1,15 @@
-# SolvingMicroDSOPs
+# EstimatingMicroDSOPs
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/SolvingMicroDSOPs/HEAD)
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/econ-ark/EstimatingMicroDSOPs/HEAD)
 
 To reproduces all the results in the repository first clone this repository locally:
 
 ```
 # Clone this repository
-$ git clone https://github.com/econ-ark/SolvingMicroDSOPs
+$ git clone https://github.com/econ-ark/EstimatingMicroDSOPs
 
-# Change working directory to SolvingMicroDSOPs
-$ cd SolvingMicroDSOPs
+# Change working directory to EstimatingMicroDSOPs
+$ cd EstimatingMicroDSOPs
 ```
 
 Then you can either use a local virtual env(conda) or [nbreproduce](https://github.com/econ-ark/nbreproduce) to
@@ -19,7 +19,7 @@ reproduce to the results.
 
 ```
 $ conda env create -f environment.yml
-$ conda activate solvingmicrodsops
+$ conda activate estimatingmicrodsops
 # execute the script, select the appropriate option and use it to reproduce the data and figures.
 $ python do_all.py
 ```

code/README.md

@@ -1,7 +1,7 @@
 # Description
 
 1. The "Stata" directory is a clone of the corresponding directory in the original online version
-   of the `SolvingMicoDSOPs` project, available at http://econ.jhu.edu/people/ccarroll/Topics/SolvingMicroDSOPs.zip
+   of the `SolvingMicoDSOPs` project, available at http://econ.jhu.edu/people/ccarroll/Topics/EstimatingMicroDSOPs.zip
     * That directory is being added here to clarify the origin of the SCFdata.txt file
 1. Original Matlab and Mathematica code to solve the model here is also available in that zip archive
 

code/do_all.py

@@ -1,5 +1,5 @@
 """
-Run all of the plots and tables in SolvingMicroDSOPs.
+Run all of the plots and tables in EstimatingMicroDSOPs.
 
 To execute, do the following on the Python command line:
 
@@ -13,14 +13,14 @@
 ------------
 
 This example script allows the user to create all of the figures and tables
-modules for SolvingMicroDSOPs.StructuralEstimation.
+modules for EstimatingMicroDSOPs.StructuralEstimation.
 
 This is example is kept as simple and minimal as possible to illustrate the
 format of a "replication archive."
 
 The file structure is as follows:
 
-./SolvingMicroDSOPs/
+./EstimatingMicroDSOPs/
     calibration/        # Directory that contain the necessary code and data to parameterize the model
     code/               # The main estimation code, in this case StructuralEstimation.py
     figures/            # Any figures created by the main code

code/estimark/agents.py

@@ -1,6 +1,6 @@
 """
 Demonstrates an example estimation of microeconomic dynamic stochastic optimization
-problem, as described in Section 9 of Chris Carroll's SolvingMicroDSOPs.pdf notes.
+problem, as described in Section 9 of Chris Carroll's EstimatingMicroDSOPs.pdf notes.
 The estimation attempts to match the age-conditional wealth profile of simulated
 consumers to the median wealth holdings of seven age groups in the 2004 SCF by
 varying only two parameters: the coefficient of relative risk aversion and a scaling

code/estimark/calibration/estimation_parameters.py

@@ -1,5 +1,5 @@
 """
-Specifies the full set of calibrated values required to estimate the SolvingMicroDSOPs
+Specifies the full set of calibrated values required to estimate the EstimatingMicroDSOPs
 model.  The empirical data is stored in a separate csv file and is loaded in setup_scf_data.
 """
 
@@ -26,7 +26,7 @@
 # line below fixes it properly ('feature not a bug') and remove all this text.
 
 # ---------------------------------------------------------------------------------
-# - Define all of the model parameters for SolvingMicroDSOPs and ConsumerExamples -
+# - Define all of the model parameters for EstimatingMicroDSOPs and ConsumerExamples -
 # ---------------------------------------------------------------------------------
 
 exp_nest = 1  # Number of times to "exponentially nest" when constructing a_grid

code/estimark/calibration/setup_scf_data.py

@@ -1,5 +1,5 @@
 """
-Sets up the SCF data for use in the SolvingMicroDSOPs estimation.
+Sets up the SCF data for use in the EstimatingMicroDSOPs estimation.
 """
 
 from estimark.calibration.estimation_parameters import (

code/estimark/estimation.py

@@ -1,6 +1,6 @@
 """
 Demonstrates an example estimation of microeconomic dynamic stochastic optimization
-problem, as described in Section 9 of Chris Carroll's SolvingMicroDSOPs.pdf notes.
+problem, as described in Section 9 of Chris Carroll's EstimatingMicroDSOPs.pdf notes.
 The estimation attempts to match the age-conditional wealth profile of simulated
 consumers to the median wealth holdings of seven age groups in the 2004 SCF by
 varying only two parameters: the coefficient of relative risk aversion and a scaling

code/stata/doAll.do

@@ -3,7 +3,7 @@
 set linesize 200
 
 * make paths
-global basePath  "/Volumes/Data/Notes/NumericalMethods/SolvingMicroDSOPs/Latest"
+global basePath  "/Volumes/Data/Notes/NumericalMethods/EstimatingMicroDSOPs/Latest"
 global stataPath "Code/Stata"
 global logPath   "Code/Stata"