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The EITC in rural and economically distressed areas: More bang per buck?

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Abstract

Numerous papers show that Earned Income Tax Credit (EITC) expansions have increased maternal labor supply, but little is known about how this effect differs by geography or metropolitan status. Using various datasets and exploiting several EITC expansions, I find that the EITC consistently had larger positive effects on the labor supply of unmarried mothers in rural and economically distressed areas. Among married mothers, I find small negative effects in suburban and urban areas and small positive effects in rural areas. I also replicate and extend previous EITC research to show that these effects hold for EITC expansions spanning 1975 to the 2010s.

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Fig. 1

Source: Bastian and Jones (2021)

Fig. 2

Source: Bastian and Jones (2021)

Fig. 3

Source: Bastian and Lochner (2020)

Fig. 4

Source: Bastian and Lochner (2020)

Fig. 5
Fig. 6
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Notes

  1. The latter three datasets and years are chosen to match Bastian and Michelmore (2018), Bastian (2020) and Bastian and Jones (2021).

  2. Two critiques of Kleven (2019) are that he uses a binary definition of treatment, when the 1993–1996 expansions phased in over time; and that 1975 appears to have had an effect (see his Fig. 3) and including 1978 as a “post” year (instead of just 1975–1977) would yield positive effects.

  3. Fig. 5 uses the ACS data described in the next section.

  4. The ACS variable “metro” has five values: not in metropolitan area; metropolitan status indeterminable (mixed); in metropolitan area, central/principal city status indeterminable (mixed); in metropolitan area, not in central/principal city; in metropolitan area, in central/principal city. Source: https://usa.ipums.org/usa-action/variables/METRO#description_section. With this relatively short sample period, reclassifying an area’s metropolitan status is uncommon (Johnson & Lichter, 2020)

  5. PSID sample size is too small to attempt any 2005–2017 analysis.

  6. Actually adult kids 19–23 that are full-time students, and disabled adult kids of any age, are EITC-eligible. Since I only observe a selected subgroup of these kids, I define EITC-eligible kids as age 18 or younger.

  7. The other parameter that captures this work incentive is the EITC phase-in rate, which is highly correlated with MaxEITC: regressing MaxEITC on the EITC phase-in rate, controlling for fixed effects for number of children, state, and year yields an \(R^2\) of 0.999.

  8. At the extensive margin, average tax rates—inclusive of public assistance—matter more than marginal tax rates (Heim & Meyer, 2004; Kleven & Kreiner, 2006; Eissa et al., 2008) For labor-market entrants, the EITC lowers both the marginal and average tax rate by 20–30%, roughly equal to the EITC’s phase-in rate (see Fig. 3 in Bastian and Jones (2021)).

  9. Bartik (2020) Appendix B describes how to crosswalk PUMAs (observed in ACS data) to local labor markets (the unit of geography for which “distressed” is defined). Many PUMAs lie partly in distressed areas; Fig. A.1 shows the distribution of the fraction of one’s PUMA that lies in a distressed local labor market.

  10. Using a continuous treatment variable also means that if the dose–response function is nonlinear then the estimated treatment effect is a convex combination of marginal effects (Yitzhaki, 1996) Figure A.10 in Bastian and Jones (2021) shows that the dose–response function of MaxEITC is quite linear.

  11. If anything, the employment trends are somewhat negative for mothers before the 1993 EITC expansion.

  12. The controls are number of children FE, state FE, year FE, age cubic, race FE, number of children under 5, education; interactions of year, state, and number of kids with married and education; state linear time trends, and the following annual state factors: welfare generosity for families with 1, 2, or 3 children, welfare waivers approved, welfare waivers binding, minimum wage, state GDP, sales tax rate, wage employment rate, and total employment rate. For estimates by metropolitan status, I also add a control for living in a rural, semi-urban, and urban area.

  13. Distressed area is a continuous variable between 0 and 1 capturing the fraction of one’s PUMA that is in a distressed local labor market (see footnote 9).

  14. Effects for earnings and EITC benefits still are significantly larger in rural areas, while employment and work hours are not significantly different in rural vs urban areas. Results in Table A.1 use CPS data and a wider set of years and show larger effects for all outcomes for rural versus urban mothers.

  15. The envelope theorem suggests that disutility of labor completely offsets utility from EITC benefits; however, non-convex budget sets with fixed work costs allow for positive welfare effects on the extensive margin (Heim & Meyer, 2004; Kleven & Kreiner, 2006; Eissa et al., 2008) I follow Bastian and Jones (2021) and assume behavioral benefits do not affect utility, leading to a lower-bound estimate of the MVPF.

  16. Bastian and Jones (2021) argues that each $1 in taxes paid—payroll, sales, and unemployment insurance (UI) taxes—is worth about $0.51 after future benefits—Social Security and UI claims—are accounted for. The paper also finds that public CPS data underestimates EITC benefits by about 39% (MaxEITC leads to $251 in EITC benefits using public data, but $349 using administrative data). The rural \(\hbox {FEx} = (0.51 \times 138 + 222)/(278 \times 1.39) = 0.76\). The urban \(\hbox {FEx} = (0.51 \times 100 + 162)/(255 \times 1.39) = 0.60\). If each $1 in EITC benefits is valued at $0.72, this yields a rural MVPF of \(3.0 (=0.72/(1-0.76))\) and an urban MVPF of \(1.8 (=0.72/(1-0.60))\). Bastian and Jones (2021) use administrative data and find slightly different FEx that result in an MVPF of $3.18–$4.23.

  17. Note that Table 8 in Eissa and Hoynes (2004) also shows positive effects on married mothers with very low income (in the EITC’s phase-in region).

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Acknowledgement

I am grateful for helpful comments from Dan Black, Jim Ziliak, and participants at the 2022 IIPF and 2023 ASSA conferences. Jacob Bastian was funded by the Smith Richardson Foundation.

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  1. Department of Economics, Rutgers University, New Jersey Hall, 75 Hamilton Street, New Brunswick, NJ, 08901-1248, USA

    Jacob E. Bastian

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I am grateful for helpful comments from Dan Black, Jim Ziliak, and participants at the 2022 IIPF and 2023 ASSA conferences. Jacob Bastian was funded by the Smith Richardson Foundation.

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Bastian, J.E. The EITC in rural and economically distressed areas: More bang per buck?. Int Tax Public Finance 31, 136–159 (2024). https://doi.org/10.1007/s10797-023-09798-6

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