How much would family and medical leave cost workers in the US? Racial/ethnic variation in economic hardship under unpaid and paid policies

Figures & data

Table 1. Work and family situations of full-year workers by race/ethnicity.

	1	2		3
	% with a spouse/partner (Total sample)	Spouse/partner work and earning status (Full-year workers with a spouse/partner)		% of family income from spouse/partner wage (Full-year workers with a spouse/partner with earnings)
	%	% non-working spouse/partner or spouse/partner with no earnings	% working spouse/partner with earnings	Mean	SD
Hispanic	56	33	67	47	0.27
White	68	24	76	46	0.25
Black	44	23	77	49	0.24
American Indian/Alaska Native	57	25	75	50	0.33
Asian/Pacific Islander	69	29	71	45	0.24
Other/multiple race	51	22	78	50	0.29
Total sample	63	26	74	47	0.25
N (unweighted)	246, 547	164,694	164,694	123,744	123,744

Table 2. Quantile regressions estimates of wage loss relative to family income for full-year workers under unpaid v. paid FML policy by race/ethnicity.

	1	2	3	4
	Unpaid FML#	Paid FML#	Gain from paid FML#	Adjusted gain from paid FML##
Median (%)	.269	.111	.145	.145
Race/ethnicity (White)
Hispanic	−0.006	−0.010	0.013	0.002
	(0.002)**	(0.001)**	(0.001)**	(0.001)**
Black	0.040	0.012	0.035	0.018
	(0.003)**	(0.001)**	(0.002)**	(0.001)**
American Indian/Alaska Native	0.011	0.002	0.013	0.010
	(0.009)	(0.003)	(0.006)*	(0.002)**
Asian/Pacific Islander	−0.025	−0.008	−0.010	−0.010
	(0.002)**	(0.001)**	(0.001)**	(0.001)**
Other/multiple race	−0.002	−0.004	0.005	−0.002
	(0.007)	(0.003)	(0.003)*	(0.001)
Working partner status (Dual earner)
Single earner				0.074
				(0.001)**
N (unweighted)	246,547	246,547	246,547	246,287
Pseudo R-squared	0.0030	0.0021	0.0061	0.1177

* p < 0.05; ** p < 0.01

# Quantile regression with no control variables.

## Quantile regression with controls for gender, education, number of children, age, age squared, usual hours worked, occupation, industry, nativity, year and state.

Notes: Robust standard errors in parentheses. See Appendix A2 for full results.

Table 3. Quantile regressions estimates of wage loss relative to family income for full-year workers under unpaid v. paid FML policy run separately by race/ethnicity.

	1	2	3	4
	Adjusted gain from paid FML white workers##	Adjusted gain from paid FML Hispanic workers##	Adjusted gain from paid FML black workers##	Adjusted gain from paid FML Asian/Pacific Islander workers##
Median	.154	.141	.176	.131
Working partner status (Dual earner)
Single earner	0.066	0.073	0.094	0.067
	(0.002)**	(0.001)**	(0.002)**	(0.003)**
N (unweighted)	43,209	153,770	26,437	17,023
Pseudo R-squared	0.0949	0.1256	0.1331	0.1144

* p < 0.05; ** p < 0.01.

## Quantile regression with controls for gender, education, number of children, age, age squared, usual hours worked, occupation, industry, nativity, year and state.

Notes: Robust standard errors in parentheses. Full regression results available upon request.

Table 4. Descriptive analysis of Paid FML prevention of short-term economic hardship for full-year workers compared to unpaid FML.

	1		2
	After unpaid (Full-year workers with family income above 200% of the FPL)		After paid (Full-year workers who enter economic hardship under unpaid leave)
	% do not enter economic hardship	% enter economic hardship	% stay in economic hardship	% leave economic hardship
Race/ethnicity
Hispanic	74	26	36	64
White	85	15	30	70
Black	74	26	34	66
American Indian/Alaska Native	75	25	36	64
Asian/Pacific Islander	87	13	28	72
Other/multiple	79	21	34	66
Total sample	82	18	32	68
N (unweighted)	206,274	206,274	36,749	36,749

Table 5. Multinomial logit models predicting the likelihood that paid FML prevents movement into short-term economic hardship for full-year workers with family income above 200% of the FPL.

	1	2	3	4
	RRR paid FML prevent hardship (compared to paid FML not prevent hardship)#	RRR paid FML prevent hardship (compared to paid FML not prevent hardship)##	RRR no hardship (compared to paid FML not prevent hardship)#	RRR no economic hardship (compared to paid FML not prevent)##
Race/ethnicity (White)
Hispanic	0.743	0.922	0.426	0.754
	(0.029)**	(0.046)	(0.014)**	(0.033)**
Black	0.826	0.888	0.443	0.621
	(0.035)**	(0.041)**	(0.016)**	(0.025)**
American Indian/Alaska Native	0.763	0.865	0.441	0.645
	(0.106)	(0.124)	(0.050)**	(0.081)**
Asian/Pacific Islander	1.068	1.116	1.236	1.311
	(0.069)	(0.084)	(0.068)**	(0.086)**
Other/multiple	0.826	0.901	0.601	0.811
	(0.099)	(0.109)	(0.063)**	(0.090)
Working partner status (Dual earner)
Single earner		0.967		0.287
		(0.036)		(0.009)**
N (unweighted)	206,274	206,061	206,274	206,061
Pseudo R-squared	0.0126	0.0917	0.0126	0.0917

* p < 0.05; ** p < 0.01.

# Multinomial logit model with no control variables.

## Multinomial logit model with controls for gender, education, number of children, age, age square, usual hours worked, occupation, industry, nativity, year and state.

Notes: Coefficients are relative risk ratios. Robust standard errors in parentheses. See Appendix A3 for full results.

Appendix A1. Economic situation of full-year working adults by demographic, family and work characteristics.

	% of sample	Annual wage income ($)		Family income ($)		% of family income from worker wages		In economic hardship
	%	Median	IQR	Median	IQR	Mean	SD	%	SE
Race
Hispanic	16	30,000	28,110	59,241	63,590	59	0.35	31	0.00
White	65	44,273	46,674	88,643	88,765	59	0.32	11	0.00
Black	11	33,454	31,148	59,932	65,818	65	0.31	24	0.00
American Indian/Alaska Native	1	32,440	31,888	63,217	65,011	61	0.41	24	0.01
Asian/Pacific Islander	6	46,567	57,060	101,002	103,995	57	0.33	12	0.00
Other/multiple race	1	35,000	36,860	71,502	80,747	59	0.37	20	0.01
Working partner status
Single earner (no working spouse/partner or no spouse/partner with earnings)	53	34,986	39,537	60,741	65,918	67	0.34	23	0.00
Dual earners (working spouse/partner with earnings)	47	45,619	45,192	104,209	89,820	51	0.28	8	0.00
Gender
Male	54	45,554	50,580	82,123	84,779	64	0.32	15	0.00
Female	46	34,419	34,754	77,236	84,091	55	0.33	17	0.00
Education
Less than high school	7	21,416	20,835	45,411	49,369	57	0.37	44	0.00
High school diploma	26	30,413	27,438	63,026	62,944	58	0.33	22	0.00
Some college	18	32,947	32,440	70,994	72,049	58	0.33	18	0.00
Associates, bachelors, or graduate degree	48	54,569	53,222	103,562	99,802	61	0.31	7	0.00
Number of children
0	54	36,400	40,464	71,771	77,616	61	0.32	13	0.00
1	19	41,184	42,962	87,172	85,706	57	0.31	15	0.00
2	17	46,560	50,276	100,000	94,405	57	0.32	18	0.00
3+	9	41,000	47,182	84,810	89,679	59	0.35	32	0.00
Age
16–25	11	20,592	21,352	59,717	74,889	52	0.35	26	0.00
26–65	83	43,000	45,315	82,181	84,389	62	0.32	15	0.00
Over 65	6	33,977	52,645	87,778	93,107	46	0.30	7	0.00
Work hours
Full-time	86	44,542	43,103	82,284	84,201	63	0.31	14	0.00
Part-time	14	13,385	15,884	63,348	83,308	37	0.33	30	0.00
Occupation
Professional	22	55,757	49,518	104,010	95,367	62	0.30	6	0.00
Executive, administrative, managerial	18	60,826	62,000	111,564	107,061	62	0.31	6	0.00
Technical, sales, administrative support	23	32,440	30,442	74,919	76,644	56	0.32	16	0.00
Service	16	22,653	22,321	52,717	62,499	55	0.35	32	0.00
Blue collar	20	35,600	30,256	64,989	61,521	63	0.32	21	0.00
Farming, fishing	1	26,000	18,523	48,005	58,965	63	0.36	37	0.02
Armed forces	1	50,000	38,650	69,949	63,716	76	0.27	17	0.01
Industry
Agriculture, forestry, fishing and hunting, and mining	19	41,951	44,656	77,271	77,156	63	0.32	16	0.00
Wholesale trade	3	46,332	45,000	85,780	87,357	64	0.29	12	0.01
Retail trade	11	27,799	30,110	66,516	73,742	55	0.33	21	0.00
Transportation and warehousing, and utilities	5	45,619	38,643	78,194	71,157	64	0.30	13	0.00
Information	2	54,665	58,715	99,499	97,694	63	0.30	8	0.01
Finance and insurance, and real estate and rental and leasing	7	50,002	52,985	100,002	102,466	60	0.31	8	0.00
Professional, scientific, and management, and administrative and, and waste management services	12	48,591	61,047	92,526	105,312	61	0.33	13	0.00
Educational services, and health care and social assistance	22	41,000	37,498	86,175	87,100	57	0.31	13	0.00
Arts, entertainment, and recreation, and accommodation and food services	8	21,259	23,126	53,036	67,522	56	0.36	32	0.00
Other services, except public administration	5	27,372	33,389	65,801	69,155	51	0.35	23	0.01
Public administration	5	55,757	44,273	97,973	81,450	66	0.28	6	0.00
Active duty military	1	50,000	38,650	69,949	63,716	76	0.27	17	0.01
Nativity
U.S. born	82	40,550	42,216	82,368	84,270	59	0.32	13	0.00
Foreign born	18	34,000	40,493	70,000	81,618	60	0.33	26	0.00
Year
2014	24	39,125	42,214	78,409	82,800	59	0.20	17	0.00
2015	25	39,537	43,592	77,956	83,075	60	0.37	17	0.00
2016	25	40,493	42,639	81,009	85,716	60	0.35	15	0.00
2017	26	40,000	43,502	82,360	87,050	59	0.35	14	0.00

Notes: Unweighted N = 246,547 for all analyses except nativity (N = 246,287).

Appendix A2. Quantile regressions estimates of wage loss relative to family income for full-year workers under unpaid v. paid FML policy by race/ethnicity.

	1	2	3	4
	Unpaid FML#	Paid FML#	Gain from paid FML#	Adjusted gain from paid FML##
Median (%)	.269	.111	.145	.145
Race/ethnicity (White)
Hispanic	−0.006	−0.010	0.013	0.002
	(0.002)**	(0.001)**	(0.001)**	(0.001)**
Black	0.040	0.012	0.035	0.018
	(0.003)**	(0.001)**	(0.002)**	(0.001)**
American Indian/Alaska Native	0.011	0.002	0.013	0.010
	(0.009)	(0.003)	(0.006)*	(0.002)**
Asian/Pacific Islander	−0.025	−0.008	−0.010	−0.010
	(0.002)**	(0.001)**	(0.001)**	(0.001)**
Other/multiple race	−0.002	−0.004	0.005	−0.002
	(0.007)	(0.003)	(0.003)*	(0.001)
Working partner status (Dual earner)
Single earner				0.074
				(0.001)**
Gender (Male)
Female				−0.015
				(0.000)**
Education (Less than high school)
High school diploma				0.003
				(0.002)
Some college				0.002
				(0.002)
Associates, bachelors, or graduate degree				−0.002
				(0.002)
Number of children (No children)
1				−0.015
				(0.000)**
2				−0.021
				(0.000)**
3+				−0.021
				(0.001)**
Age
Age				0.006
				(0.000)**
Age squared				−0.000
				(0.000)**
Usual hours worked
Usual hours worked				0.002
				(0.000)**
Occupation (Professional)
Executive, administrative, managerial				−0.008
				(0.000)**
Technical, sales, administrative support				−0.007
				(0.001)**
Service				−0.010
				(0.001)**
Blue collar				0.010
				(0.001)**
Farming, fishing				0.019
				(0.003)**
Armed forces				0.027
				(0.002)**
Industry (Agriculture, forestry, fishing and hunting, and mining)
Wholesale trade				0.004
				(0.002)**
Retail trade				−0.009
				(0.001)**
Transportation and warehousing, and utilities				0.003
				(0.001)**
Information				−0.001
				(0.001)
Finance and insurance, and real estate and rental and leasing				−0.002
				(0.001)**
Professional, scientific, and management, and administrative and, and waste management services				−0.005
				(0.001)**
Educational services, and health care and social assistance				0.000
				(0.001)
Arts, entertainment, and recreation, and accommodation and food services				−0.003
				(0.002)
Other services, except public administration				−0.013
				(0.001)**
Public administration				0.014
				(0.001)**
Nativity (U.S. born)
Foreign born				0.003
				(0.001)**
Survey year (2014)
2015				0.001
				(0.001)
2016				−0.001
				(0.001)
2017				−0.003
				(0.001)**
N (unweighted)	246,547	246,547	246,547	246,287
Pseudo R-squared	0.0030	0.0021	0.0061	0.1177

*p < 0.05; **p < 0.01.

# Quantile regression with no control variables.

## Quantile regression with controls for gender, education, number of children, age, age squared, usual hours worked, occupation, industry, nativity, year and state

Notes: Robust standard errors in parentheses.

Appendix A3. Multinomial logit models predicting the likelihood that paid FML prevents movement into short-term economic hardship for full-year workers with family income above 200% of the FPL.

	1	2	3	4
	RRR paid FML prevent hardship (compared to paid FML not prevent hardship)#	RRR paid FML prevent hardship (compared to paid FML not prevent hardship)##	RRR no hardship (compared to paid FML not prevent hardship)#	RRR no economic hardship (compared to paid FML not prevent)##
Race/ethnicity (White)
Hispanic	0.743	0.922	0.426	0.754
	(0.029)**	(0.046)	(0.014)**	(0.033)**
Black	0.826	0.888	0.443	0.621
	(0.035)**	(0.041)**	(0.016)**	(0.025)**
American Indian/Alaska Native	0.763	0.865	0.441	0.645
	(0.106)	(0.124)	(0.050)**	(0.081)**
Asian/Pacific Islander	1.068	1.116	1.236	1.311
	(0.069)	(0.084)	(0.068)**	(0.086)**
Other/multiple	0.826	0.901	0.601	0.811
	(0.099)	(0.109)	(0.063)**	(0.090)
Working partner status (Dual earner)
Single earner		0.967		0.287
		(0.036)		(0.009)**
Gender (Male)
Female		0.879		0.807
		(0.031)**		(0.025)**
Education (Less than high school)
High school diploma		1.023		1.086
		(0.059)		(0.056)
Some college		1.058		1.245
		(0.066)		(0.068)**
Associates, bachelors or graduate degree		1.327		2.076
		(0.086)**		(0.119)**
Number of children (No children)
1		0.864		0.908
		(0.038)**		(0.035)*
2		0.846		0.736
		(0.040)**		(0.031)**
3+		0.722		0.429
		(0.038)**		(0.020)**
Age
Age		0.995		0.914
		(0.009)		(0.008)**
Age squared		1.000		1.001
		(0.000)		(0.000)**
Usual hours worked
Usual hours worked		1.006		0.996
		(0.001)**		(0.001)**
Occupation (Professional)
Executive, administrative, managerial		1.072		1.236
		(0.070)		(0.071)**
Technical, sales, administrative support		0.853		0.613
		(0.050)**		(0.031)**
Service		0.734		0.499
		(0.045)**		(0.026)**
Blue collar		0.778		0.435
		(0.049)**		(0.024)**
Farming, fishing		0.632		0.309
		(0.130)*		(0.058)**
Armed forces		0.858		0.291
		(0.150)		(0.046)**
Industry (Agriculture, forestry, fishing and hunting, and mining)
Wholesale trade		0.944		0.923
		(0.091)		(0.077)
Retail trade		0.810		0.827
		(0.050)**		(0.045)**
Transportation and warehousing, and utilities		1.123		1.142
		(0.077)		(0.069)*
Information		1.099		1.115
		(0.136)		(0.120)
Finance and insurance, and real estate and rental and leasing		1.207		1.095
		(0.092)*		(0.073)
Professional, scientific, and management, and administrative and, and waste management services		1.054		1.042
		(0.067)		(0.058)
Educational services, and health care and social assistance		1.100		0.912
		(0.066)		(0.048)
Arts, entertainment, and recreation, and accommodation and food services		0.947		0.789
		(0.069)		(0.051)**
Other services, except public administration		0.973		0.916
		(0.079)		(0.066)
Public administration		1.202		1.152
		(0.105)*		(0.090)
Nativity (U.S. born)
Foreign born		0.882		0.776
		(0.042)**		(0.033)**
Survey year (2014)
2015		0.856		0.828
		(0.045)**		(0.039)**
2016		0.883		0.904
		(0.047)*		(0.043)*
2017		0.924		0.938
		(0.049)		(0.044)
N (unweighted)	206,274	206,061	206,274	206,061
Pseudo R-squared	0.0126	0.0917	0.0126	0.0917

* p < 0.05; ** p < 0.01.

# Multinomial logit model with no control variables.

## Multinomial logit model with controls for gender, education, number of children, age, age square, usual hours worked, occupation, industry, nativity, year and state.

Notes: Coefficients are relative risk ratios. Robust standard errors in parentheses.