
**Replication Notes for "Solving Problems in the Panel Regression Model for
**Truncated Dependent Variables: A Constrained Optimization Method"

**General Instruction:
**The follwong contains replication notes for all reported findings in the main text.
**Replace "your directory" with your directory path where the files are stored.  


**Section 1 Introduction
**14 models in Fordham and Walker's (2005) ISQ article
**Stata is applied 

1. Open "Replication_fwisq.txt" in the "Replication_fwisq" directory.
2. Run all the commands in "Replication_fwisq.txt".

**Section 2.1 Boundary Violations
**Hypothetical Cases of Boundary Violations
**Matlab is applied

1. Use the "Hypocase" directory. 
2. Run "ofb.m" in the Matlab environment.

**List of Hypothetical Cases

1. Use the "Hypocase" directory. 
2. Open "List of Hypocases.xlsx".  

**Section 2.3 Model Specification
**Maximual and Minimal Values of Dummy Variables
**Matlab is applied

1. Use the "Hypocase" directory. 
2. Run "dummyvalue.m" in the Matlab environment.

**List of Maximual and Minimal Values of Dummy Variables

1. Use the "Hypocase" directory. 
2. Open "List of Dummycases.xlsx".  

** Section 4 Applying Constrained Optimization to the Panel Regression
**Model I-V in Table 1-3
**Table 1 is executed in Stata
**Table 2 is executed in Matlab
**Table 3 is executed in Matlab

**Model 1
1. Use the "Xtreg" directory. 
2. Run all the commands in "replication_Hansford_Gomez.txt".
3. Run "xtregbv.m" in the Matlab environment.

**Model 2
1. Use the "Fixmin" directory. 
2. Run all the commands in "stata_fixmin.txt".
3. Run "fixminreg.m" in the Matlab environment.

**Model 3
1. Use the "LS1" directory. 
2. Run "LSxtreg.m" in the Matlab environment.

**Model 4
1. Use the "ML1" directory. 
2. Run "ML1xtreg.m" in the Matlab environment.

**Model 5
1. Use the "ML2" directory. 
2. Run "ML2xtreg.m" in the Matlab environment.

