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194 changes: 75 additions & 119 deletions working_cohorts_cps.do
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Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
#delimit ;
/* EPOP rates by age and gender for prime age individuals,
by 5-year birth cohorts

Expand All @@ -18,130 +17,87 @@ marst
popstat
empstat
*/
use "cps_00120.dta", clear;
clear all
use cps_00120

/* This is as close as we can get to birth year using CPS data (which lack
explicit birth year, as found in Census/ACS). ASEC is mostly fielded
in March, so this is correct for most people. */
gen birthyr = year - age -1;
gen finalweight = asecwt ;
/* Deal with the mystery negative weights in some early CPS samples */
replace finalweight = 0 if finalweight <0;
/* Normalize weights for 2014 ASEC */
replace finalweight = finalweight * 3/8 if hflag ==1;
replace finalweight = finalweight * 5/8 if hflag ==0;

/* Limit the sample to birth years and ages of interest */
keep if birthyr>=1945;
keep if age>=25 & age<=54;
gen birthyr5 = ceil((birthyr-1944)/5);

/* Limit to civilians */
keep if popstat==1;

/* Generate employed indicator variable */
gen employed = empstat==10 | empstat==12;

/* Calculate mean employment rates by age/sex/cohort */
collapse (mean) employed [pweight=finalweight], by(birthyr5 age sex);

/* Convert to percents for better graph display */
gen pct_employed = employed *100;
label define percents 0 "0%" 10 "10%" 20 "20%" 30 "30%" 40 "40%" 50 "50%"
60 "60%" 70 "70%" 80 "80%" 90 "90%" 100 "100%";
label values pct_employed percents;

/* Create empty local for adding graphs later */
local graphs = "";

/* Loop over cohorts */
forval val = 1(1)10{;
/* Manually label cohorts for now */
if `val'==1{;
local text = `"1945-1949"';
};
if `val'==2{;
local text = `"1950-1954"';
};
if `val'==3{;
local text = `"1955-1959"';
};
if `val'==4{;
local text = `"1960-1964"';
};
if `val'==5{;
local text = `"1965-1969"';
};
if `val'==6{;
local text = `"1970-1974"';
};
if `val'==7{;
local text = `"1975-1979"';
};
if `val'==8{;
local text = `"1980-1984"';
};
if `val'==9{;
local text = `"1985-1989"';
};
if `val'==10{;
local text = `"1990-1994"';
};

/* Label men and women in the first graph */
if `val'==1{;
graph twoway
(line pct_employed age if birthyr5 ==`val' & sex==1, lcolor(`"24 105 109"'))
(line pct_employed age if birthyr5 ==`val' & sex==2, lcolor(`"219 112 41"')),
yscale(r(50 91))
ylabel(50(10)90, valuelabels)
xtitle("")
xscale(r(25 54))
ytitle("")
xlabel(25(5)50)
plotregion(margin(zero))
text(60 45 `"Born `text'"', size(large))
text(88 33 `"Men"', size(large) color(`"24 105 109"'))
text(58.8 34 `"Women"', size(large) color(`"219 112 41"'))
name(birthyr5_employed_`val', replace)
subtitle(`"Percentage employed"', justification(left) margin(b+1 t-1) bexpand)
note(`"Source: Civilians in CPS households from 1968-2018 IPUMS CPS ASEC samples (cps.ipums.org), @graykimbrough"',
margin(l-12 t+2 b-2));
};
else{;
graph twoway `graphs'
(line pct_employed age if birthyr5 ==`val' & sex==1, lcolor(`"24 105 109"'))
(line pct_employed age if birthyr5 ==`val' & sex==2, lcolor(`"219 112 41"')),
yscale(r(50 91))
ylabel(50(10)90, valuelabels)
xtitle("")
xscale(r(25 54))
ytitle("")
xlabel(25(5)50)
plotregion(margin(zero))
text(60 45 `"Born `text'"', size(large))
name(birthyr5_employed_`val', replace)
subtitle(`"Percentage employed"', justification(left) margin(b+1 t-1) bexpand)
note(`"Source: Civilians in CPS households from 1968-2018 IPUMS CPS ASEC samples (cps.ipums.org), @graykimbrough"',
margin(l-12 t+2 b-2));
};

/* Add previous cohort lines, at 20% opacity */
local graphs = `"`graphs'"' +
`" (line pct_employed age if birthyr5 ==`val' & sex==1,
lcolor(`"24 105 109%20"'))
(line pct_employed age if birthyr5 ==`val' & sex==2,
lcolor(`"219 112 41%20"'))"';

/* Export graphs as .png images */
graph export `"./graphs/birthyr5_employed_`val'.png"', width(1024) replace;
};
gen birthyr = year - age - 1
gen finalweight = asecwt
// Deal with the mystery negative weights in some early CPS samples
replace finalweight = 0 if finalweight <0
// Normalize weights for 2014 ASEC
replace finalweight = finalweight * 3/8 if hflag ==1
replace finalweight = finalweight * 5/8 if hflag ==0

// Limit the sample to birth years and ages of interest
keep if birthyr>=1945
keep if age>=25 & age<=54
gen birthyr5 = ceil((birthyr - 1944) / 5)

// Limit to civilians
keep if popstat==1

// Generate employed indicator variable
gen employed = empstat==10 | empstat==12

// Calculate mean employment rates by age/sex/cohort
collapse (mean) employed [pweight=finalweight], by(birthyr5 age sex)

// Convert to percents for better graph display
gen pct_employed = employed * 100
label define percents 0 "0%" 10 "10%" 20 "20%" 30 "30%" 40 "40%" 50 "50%" ///
60 "60%" 70 "70%" 80 "80%" 90 "90%" 100 "100%"
label values pct_employed percents

// colors for men (1) and women (2)
local col1 24 105 109
local col2 219 112 41

// Manually label cohorts for now
local text1 "1945-1949"
local text2 "1950-1954"
local text3 "1955-1959"
local text4 "1960-1964"
local text5 "1965-1969"
local text6 "1970-1974"
local text7 "1975-1979"
local text8 "1980-1984"
local text9 "1985-1989"
local text10 "1990-1994"

// Label men and women in the first graph
local lbl1 text(88 33 "Men", size(large) color("`col1'")) text(58.8 34 "Women", size(large) color("`col2'"))

// Loop over cohorts
forval val = 1/10 {

local g1 line pct_employed age if birthyr5 ==`val' & sex==1
local g2 line pct_employed age if birthyr5 ==`val' & sex==2

graph twoway `graphs' (`g1', lcolor("`col1'")) (`g2', lcolor("`col2'")), ///
ytitle("") yscale(r(50 91)) ylabel(50(10)90, valuelabels) ///
xtitle("") xscale(r(25 54)) xlabel(25(5)50) ///
plotregion(margin(zero)) ///
text(60 45 "Born `text`val''", size(large)) ///
name(birthyr5_employed_`val', replace) ///
subtitle("Percentage employed", justification(left) margin(b+1 t-1) bexpand) ///
note("Source: Civilians in CPS households from 1968-2018 IPUMS CPS ASEC samples (cps.ipums.org), @graykimbrough", ///
margin(l-12 t+2 b-2));

// Add previous cohort lines, at 20% opacity
local graphs `graphs' (`g1', lcolor("`col1'%20")) (`g2', lcolor("`col2'%20"))

// Export graphs as .png images
graph export `"./graphs/birthyr5_employed_`val'.png"', width(1024) replace
}

/* Use ImageMagick 'convert' command to combine all of these .png graphs
into a .gif. This command works on OS X with 'convert' installed, but
the specific command may vary, or the files can be combined using another
method. */
!/usr/local/bin/convert -delay 400 ./graphs/birthyr5_employed_1.png
-delay 250 ./graphs/birthyr5_employed_{2..9}.png
-delay 450 ./graphs/birthyr5_employed_10.png
./graphs/employed_5year_cohorts.gif;
!/usr/local/bin/convert -delay 400 ./graphs/birthyr5_employed_1.png ///
-delay 250 ./graphs/birthyr5_employed_{2..9}.png ///
-delay 450 ./graphs/birthyr5_employed_10.png ///
./graphs/employed_5year_cohorts.gif