RauhValladaresEsteban2023.jl

This package provides all codes to replicate the main exhibits of On the Black-White Gaps in Labor Supply and Earnings over the Lifecycle in the US by Christopher Rauh and Arnau Valladares-Esteban.

The user needs to download the raw data from the National Longitudinal Survey of the Youth 1979 and store it in the folder stata/ following the naming details in stata/main.do.

produce_exhibits.jl

Execute this file to produce all the figures and tables displayed below and reported in the paper.

As a reference, using the following CPU:

Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
Address sizes:                      39 bits physical, 48 bits virtual
CPU(s):                             8
On-line CPU(s) list:                0-7
Thread(s) per core:                 2
Core(s) per socket:                 4
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              158
Model name:                         Intel(R) Core(TM) i7-7700 CPU @ 3.60GHz
Stepping:                           9
CPU MHz:                            800.036
CPU max MHz:                        4200.0000
CPU min MHz:                        800.0000
BogoMIPS:                           7200.00
Virtualisation:                     VT-x
L1d cache:                          128 KiB
L1i cache:                          128 KiB
L2 cache:                           1 MiB
L3 cache:                           8 MiB
NUMA node0 CPU(s):                  0-7

Running the following OS:

Linux 5.4.0-166-generic #183-Ubuntu SMP Mon Oct 2 11:28:33 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux

The total execution time for produce_exhibits.jl is of around 4 hours.

Model Documentation

Figure 1: Employment, hours worked, cumulative experience, and annual earnings over the lifecycle by Black and White men

Table 1: Test of parallelism in earnings experience profiles between Black and White men

See stata/main.do.

Figure 2: Mean annual earnings over the lifecycle for Black and White men that do not experience any non-employment spell

Figure 3: Distribution of AFQT deciles by race

Figure 4: Hourly earnings conditional on working by race for AFQT deciles over the lifecycle

Table 2: Regressing hourly earnings conditional on working on race and cumulative labor market experience for AFQT deciles 1-5

The PDF cannot be displayed in the GitHub README file. Please click here to view it: View PDF.

Figure 5: Employment rates over the lifecycle by race and AFQT deciles

Figure 6: Mean hourly wages over the lifecycle conditional on working by AFQT/ability decile (data vs. model)

Figure 7: Hours worked over the lifecycle conditional on employment for AFQT/ability groupings by race (data vs. model)

Figure 8: Employment rates over the lifecycle by AFQT/ability decile (data vs. model)

Table 5: How racial gaps respond to assigning characteristics of White men to Black men

The PDF cannot be displayed in the GitHub README file. Please click here to view it: View PDF.

Figure 9: Racial gaps over the lifecycle in the data: benchmark and counterfactual of equal initial conditions

Hourly Wage	Employment

Figure B.1: Annual (left) and hourly (right) log labor income over the lifecycle

Table B.1: Regressing hourly earnings conditional on working on race and cumulative labor market experience by AFQT deciles

The PDF cannot be displayed in the GitHub README file. Please click here to view it: View PDF.

Figure B.2: Hours worked conditional on working by race for AFQT deciles over the lifecycle

Figure B.3: Mean annual earnings over the lifecycle conditional on working for Black and White men that experience no non-employment spells, by education groups

Figure B.4: Mean annual earnings by cumulative hours worked conditional on working for Black and White men that experience no non-employment spells, by education groups

Figure B.5: AFQT score distributions by race and education (absolute)

Figure B.6: AFQT score distributions by race and education (relative)

Figure B.7: Hourly wages conditional on working for AFQT score groupings by race over the lifecycle for men without non-employment spells

Figure B.8: Mean individual fixed effect (left) and experience effect (right) for hourly wage by race and AFQT decile

Figure B.9: Distribution of individual fixed effects (left) and experience effects (right) for hourly wage by race and AFQT decile

Figure B.10: Mean hourly wages at age 23

Figure B.11: Mean hourly wages at age 23 for Blacks and Whites

Figure B.12: Yearly earnings for AFQT/ability groupings by race over the lifecycle (data vs. model

Figure B.13: Employment rates for AFQT/ability deciles 5-10 by race over the lifecycle (data vs. model

Figure B.14: Hours worked conditional on working for AFQT/ability deciles 5-10 by race over the lifecycle (data vs. model)