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*  "Education, Wage Dynamics, and Wealth Inequality"
*   Written by Heejeong Kim at Concordia University
*   E-mail: heejeong.kim@concordia.ca
*   last updated: Feb-08-2021
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1. Empirical Analysis
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Estimating wage processes uses two different software
Between-group wage dispersion is estimated using STATA
Withing-group wage dispersion is estimated using MATLAB 
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Step 1. Run "BetweenDispersion.do" in STATA to estimtate the between-group wage dispersion.
               This will generate two .csv files below that will be used in Minmum Distance Estimation.
               res_edu_coomon.csv -  for common wage shock process
               res_edu_bench.csv     -  for skill-specific wage shock process

Step 2. To estimate skill-specific wage shock processes
   	 1) Move both .csv files generated in Step 1 into "MinimumDistanceEstimation" folder.
    	 2) Run "Main_estimation.m" to estimate common wage shock process and skill-specific wage shock processes.
          	 
              The estimated results will be saved seperately in:
		 momsize_common.mat  - for common	
		 momsize_skilled.mat      - for skilled workers
		 momsize_unskilled.mat - for unskilled workers


2. Quantitative Analysis
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The quantitative model is solved using Fortran90, compiled in Microsoft Visual Studio.
	main_Jan2021.f90 : main file for the program
	mod_Jan2021.f90 :  subroutines 
	tauchen.f90 : Tauchen algorithm to discretize continuous shock processes
	kindset.f90:  specify the data type

The model is solved on a PC with two Intel Xeon CPU E5-2640 2.40GHz processors (40 logical cores) and 64GB RAM.
With OpenMP, the running time for the benchmark case is around 10 minutes.