Additional Details¶
Output Files¶
Depending on the user’s request, the respy
package creates several output files.
Warning
There is a slight difference between the estimation parameters in the files below and the model specification. The difference is in the parameters for the covariance matrix. During the estimation we iterate on a flattened version of the upper-triangular Cholesky decomposition. This ensures that the requirements for a valid covariance matrix, e.g. positive semidefiniteness and strictly positive variances, are always met as the optimizer appraises alternative model parameterizations.
Simulation¶
- data.respy.dat
This file contains the agent choices and state experiences. The simulated dataset has the following structure.
Column Information 1 agent identifier 2 time period 3 choice (1 = Occupation A, 2 = Occupation B, 3 = education, 4 = home) 4 wages (missing value if not working) 5 work experience in Occupation A 6 work experience in Occupation B 7 years of schooling 8 lagged schooling
- data.respy.info
This file provides descriptive statistics such as the choice probabilities and the wage distributions. It also prints out the underlying parameterization of the model.
- sim.respy.log
This file allows to monitor the progress of the simulation. It provides information about the seed used to sample the random components of the agents’ state experience and the total number of simulated agents.
- sol.respy.log
This file records the progress of the backward induction procedure. If the interpolation method is used during the backward induction procedure, the coefficient estimates and goodness of fit statistics are provided.
- solution.respy.pkl
This file is an instance of the RespyCls
and contains detailed information about the solution of model such as the \(E\max\) of each state for example. For details, please consult the source code directly. It is created if persistent storage of results is requested in the SOLUTION section of the initialization file.
Estimation¶
- est.respy.info
This file allows to monitor the estimation as it progresses. It provides information about starting values, step values, and current values as well as the corresponding value of the criterion function.
- est.respy.log
This file documents details about each of the evaluations of the criterion function. Most importantly, once an estimation is completed, it provides the return message from the optimizer.
API Reference¶
The API reference provides detailed descriptions of respy
classes and
functions. It should be helpful if you plan to extend respy
with custom components.
-
class
respy.
RespyCls
(fname)¶ Class to process and manage the user’s initialization file.
Parameters: fname (str) – Path to initialization file Returns: Instance of RespyCls -
classmethod
update_model_paras
(x)¶ Function to update model parameterization.
Parameters: x (numpy.ndarray) – Model parameterization
-
classmethod