Food Stamp Participation and Employment among Adult-Only Households David C. Ribar – The George Washington University Marilyn Edelhoch – South Carolina.

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Presentation transcript:

Food Stamp Participation and Employment among Adult-Only Households David C. Ribar – The George Washington University Marilyn Edelhoch – South Carolina Department of Social Services Qiduan Liu – South Carolina Department of Social Services

Two gaps in the FSP literature Relatively little FSP research on adult-only households Most previous research has either examined families with children, especially single-parent families, or the caseload as a whole Participation behavior among adult-only HHs is different low take-up among elderly long spells for those who do participate Adult-only HHs are also a focus of policy simplified application procedures for elderly & disabled new work requirements and time limits for able-bodied adults without dependents (ABAWDs)

Gaps in FSP research (cont.) Little research on FSP policies and procedures Benefits follow a national formula, only variation in formula is in Alaska and Hawaii Administration, however, is left to the states Policies are difficult to measure and usually only apply to select groups Hard to examine with most national data sets Would also seem to be difficult to measure within a single state; however, there are two important aspects of policy in South Carolina that can be readily measured

ABAWD policies From PRWORA, ABAWDs had to work or participate in work-related activities otherwise could only receive benefits for 3 months in any three years At their discretion, states could exempt ABAWDs living in high unemployment areas States later given discretion to exempt up to 15 percent of their ABAWD caseload South Carolina used its discretion to exempt entire counties (mostly) mix of counties changed somewhat over time all counties exempt after Oct. 2002

South Carolina Counties Exempt from ABAWD Work Requirements 1996 – 2003 EffectiveLabor Surplus AreasHigh Unemployment Areas15% Exemption Areas December 1, 1996Abbeville, Allendale, Bamberg, city of North Charlestown, Chester, Chesterfield, Clarendon, Colleton, Darlington, Fairfield, city of Florence, Hampton, Kershaw, Lee, McCormick, Orangeburg, city of Sumter, Union Barnwell, Dillon, Georgetown, Marion, Marlboro, Williamsburg March 1, 1998Aiken, Allendale, Bamberg, Barnwell, Calhoun, city of North Charlestown, Chesterfield, Clarendon, Colleton, Darlington, Dillon, Edgefield, Fairfield, Florence, Hampton, McCormick, Orangeburg, Union Chester, Georgetown, Lee, Marion, Marlboro, Williamsburg Charleston (balance of county) August 1, 1999Abbeville, Aiken, Allendale, city of Anderson, Bamberg, Barnwell, Calhoun, city of North Charlestown, Chester, Chesterfield, Clarendon, Darlington, Dillon, Fairfield, Florence, Georgetown, Hampton, Lee, McCormick, Marion, Orangeburg, Union Marlboro, WilliamsburgAnderson (balance of county), Charleston (balance of county) April 1, 2000Allendale, Bamberg, Barnwell, Chester, Chesterfield, Clarendon, Darlington, Dillon, Fairfield, Georgetown, Lee, McCormick, Orangeburg, Union Marion, Marlboro, WilliamsburgAbbeville, Aiken, Anderson, Calhoun, Charleston, Florence, Hampton April 1, 2001Allendale, Bamberg, Barnwell, Calhoun, Chester, Chesterfield, Clarendon, Darlington, Fairfield, Georgetown, Greenwood, Lee, McCormick, Orangeburg, Union Dillon, Marion, Marlboro, WilliamsburgAbbeville, Aiken, Anderson, Charleston, Florence, Hampton April 1, 2002Allendale, Bamberg, Barnwell, Calhoun, Chester, Chesterfield, Clarendon, Darlington, Georgetown, Greenwood, Lee, McCormick, Orangeburg, Union Dillon, Fairfield, Marion, Marlboro, Williamsburg Abbeville, Aiken, Anderson, Charleston, Florence, Hampton October 1, 2002Allendale, Bamberg, Barnwell, Calhoun, Chester, Chesterfield, Clarendon, Darlington, Georgetown, Greenwood, Lee, McCormick, Orangeburg, Union Dillon, Fairfield, Marion, Marlboro, Williamsburg Rest of state May 1, 2003Abbeville, city of Anderson, Barnwell, Cherokee, Chesterfield, Clarendon, Darlington, city of Florence, Georgetown, Greenwood, city of Sumter Chester, Fairfield, Laurens, McCormick, Marion, Marlboro, Orangeburg, Union, Williamsburg Rest of state

FSP recertification FSP eligibility is based on monthly criteria; however, these are hard to check Instead, clients need to “recertify” their eligibility either in-person or by mail regularly; states vary in their recertification intervals South Carolina distinguishes between HHs with fixed and fluctuating incomes HHs with fixed incomes need to recertify annually Prior to Oct. 2002, HHs with fluctuating incomes needed to recertify quarterly Since Oct. 2002, HHs with fluctuating incomes need to recertify semi-annually Elderly and disabled HHs with fixed incomes have easier recertification requirements than other HHs

Identification of policy effects Typically, it is difficult to identify policy effects within a single state For ABAWD policies, county variation in exemption status variation in the expected timing of effects (should appear early in a spell) can examine a psuedo-control group of older adult-only HHs For FSP recertification, effects occur relative to the start of a participation spell and thus can be seen in the spell duration pattern change in policy in Oct also, differences by initial income status

Food Stamp Caseload Trends

Data We examine administrative records for FSP spells that began after Oct. 1996; data extend through Dec Construct spells of participation or non-participation data measured to the day eliminate short breaks and short spells drop spells that were on-going as of Oct participation & non-participation spells may be repeated Covered employment construct indicator for whether case head earned more than $250 in a quarter misses some jobs – agriculture, out of state lack detailed timing information, just use quarterly indicators

Data (continued) Other personal and family controls include race, age, gender, education, marital status County measures: unemployment, population density, border county, ABAWD exemption Only examine cases without dependent children To reduce sample size, examine 1 out of every 11 cases Separate analyses conducted for HHs with and without members under age 50 (with and without potential ABAWDs) 9,264 households with members under age 50 4,550 households with no members under age 50

FSP exit hazards for different cohorts & types of households

FSP survival functions for different cohorts & types of households Spells began before 2000 Spells began after June 2002

FSP exit hazards by entry cohort and income type

FSP exit hazards by county ABAWD exemption status

Multivariate analyses Jointly estimate multivariate models of food stamp participation spells food stamp non-participation spells employment outcomes Models control for problems from omitted variables and endogenous explanatory variables Models estimated separately for HHs with and without members under age 50

Food stamp exits Hazard model for food stamp exits ln h FS (t) = A FS ′T FS (t) + δ FS E(t) + B FS ′X FS (t) + η (1) proportional hazard specification T FS (t) is a vector of duration variables, including spell duration, calendar time and recertification indicators; spell duration controls interacted with ABAWD exemption status E(t) is an indicator for employment X FS (t) is a vector of other observed explanatory variables η is an unobserved, time invariant variable; η ~ N(0, σ η 2 ) A FS, δ FS and B FS are coefficients to be estimated Employment is endogenous; assumed to be correlated with η

Food stamp re-entry Hazard model for food stamp re-entry ln h NF (t) = A NF ′T NF (t) + δ NF E(t) + B NF ′X NF (t) + μ (2) proportional hazard specification with E(t) and X NF (t) defined as before vector of duration variables, T NF (t), only includes controls for spell duration and calendar time μ is an unobserved, time invariant variable; μ ~ N(0, σ μ 2 ); correlated with η (ρ ημ ) A NF, δ NF and B NF are coefficients to be estimated Employment is again endogenous Estimation procedure allows for multiple, alternating spells of food stamp participation and non-participation

Employment Longitudinal earnings/employment model E*(t) = B E ′X E (t) + ν + ε(t), E(t) = 1 if E*(t) > 0(3) random effects probit model ν is an unobserved, time invariant variable; ν ~ N(0, σ ν 2 ); correlated with η and μ (ρ ην and ρ μν ) Equations (1)-(3) estimated jointly; because of repeated observations, numerous outcomes examined per case Gaussian quadrature used to evaluate η, μ and ν; 10 evaluations in each dimension (1000 evaluations total)

Estimation results – simulated change in ABAWD exemption status, HHs with members < age 50

Estimation results – simulated change in employment, HHs with members under age 50 Spell begins in January 1997Spell begins in July 2002

Estimation results – simulated change in emp. & age comp., HHs with no members under age 50 Spell begins in January 1997Spell begins in July 2002

Conclusions Recertification is important: more frequent recertification reduces FS participation and shortens spells ABAWD restrictions shorten FSP participation spells reduce FSP re-entry BUT have only modest effects on employment Dogs that don’t bark: policy effects appear where they are supposed to but not where they shouldn’t Employment reduces FS spells