COPYRIGHT STATEMENT: We give our consent to anyone to use this code for non-commercial and non-profit purposes only. For commercial purposes contact one of the authors.

© 2021 Andrei Sirchenko, Jochem Huismans and Jan Willem Nijenhuis. All rights reserved.

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Swopit

Ordinal responses can be generated, in a time-series context, by different latent regimes or, in a cross-sectional context, by different unobserved classes of population. We introduce a new command swopit that fits a mixture of ordered probit models with either exogenous or endogenous switching between two latent classes (or regimes). Switching is endogenous if the unobservables in the class-assignment model are correlated with the unobservables in the outcome models. We provide a battery of postestimation commands, assess by Monte Carlo experiments the finite-sample performance of the maximum likelihood estimator of the parameters, probabilities and their standard errors (both the asymptotic and bootstrap ones), and apply the new command to model the policy interest rates.

Installation instructions:

1. Download (or clone) package and store on your device (Code -> Download ZIP or Clone);
2. Set path of package in Stata Command Window using: cd "C:/yourpath";
3. Run using artificial or real dataset (both are provided).

To use on calibrated data:

We have added a calibration file with precalibrated parameters. To run this:

1. Run calibration.do from do-file editor;
2. Run applicaton.do from do-file editor, with the desired options (some examples provided);
3. Use post-estimation commands as you wish, in the do-file or Command Window.

To use on real dataset:

The two different datasets used in the paper are available. To run this:

1. Run policy_rate.dta from command window;
2. Run Empirical_example.do from do-file editor.

Folder structure

The folder structure is shown in the figure below. We first give an explanation of the files.
Swopit package contains the files as sent to Stata Journal.
A mixture of ordered probit models with endogenous switching between two latent classes model - revision.pdf the latest version of the paper, as submitted to Stata Journal
README.md this file.
readme.txt the description of the paper, authors and copyright.
Development files/Model contains all development code.
  DefModel.ado contains all model definitions.
  Empirical_example.do the do-file with the empirical example from the paper
  swopitestimates.ado contains the main estimation routines and postestimation commands.
  helpfunctest.ado contains the auxiliary functions used in optimization.
  policy_rate.dta data on policy rate changes (used in the paper).
  sim_results.xlsx simulation results.
  sim_results_bootstrap.xlsx simulation results for bootstrap.
  swopit.ado the Stata interface of the swopit command.
  swopitprobabilities.ado the Stata interface of the swopitprobabilities command.
  swopitmargins.ado the Stata interface of the swopitmargins command.
  swopitclassification.ado the Stata interface of the swopitclassification command.
  swopitpredict.ado the Stata interface of the swopitpredict command.
  swopit.sthlp swopit help file.
  swopitpostestimation.sthlp swopitpostestimation help file.
 Calibration files contains files used in debugging and for determining simulation parameters.
  application.do do-file with different examples of the command.
  calibration.do do-file which performs the calibration of parameters used in simulation.
 Simulation files contains the simulation files.
  create_sets.py creates the bash scripts used on the Lisa cluster for simulations.
  merge_matamatrix.do combines the resulting matrices to obtain simulation results.
  runsim.do runs simulations.

Swopit
│   Estimation of two-regime switching ordered probit model - revision.pdf
│   README.md
│   readme.txt
│
├───Swopit package
│       DefModel.ado
│       Empirical_example.do
│       swopitestimates.ado
│       helpfunctest.ado
│       policy_rate.dta
│       readme.txt
│       swopitclassification.ado
│       swopitmargins.ado
│       swopitpostestimation.sthlp
│       swopitpredict.ado
│       swopitprobabilities.ado
│
└───Development files
    └───Model
        │   DefModel.ado
        │   Empirical_example.do
        │   estimates.ado
        │   helpfunctest.ado
        │   policy_rate.dta
        │   sim_results.xlsx
        │   sim_results_bootstrap.xlsx
        │   swopit.ado
        │   swopit.sthlp
        │   swopitclassification.ado
        │   swopitmargins.ado
        │   swopitpostestimation.sthlp
        │   swopitpredict.ado
        │   swopitprobabilities.ado
        │
        ├───Calibration files
        │       application.do
        │       calibration.do
        │
        └───Simulation files
                create_sets.py
                merge_matamatrix.do
                runsim.do