In 2017, 6.7 million children received special education services and 1.2 million children received Supplemental Security Income. Despite the reach of these two programs, little research has examined how local, state, and federal policies interact with these two program. This dissertation is comprised of three essays examining local and federal policies affecting children with disabilities. In Chapter 1, I use administrative student level records from the state of North Carolina and regression discontinuity methods, to corroborate earlier research suggesting that the youngest children in the classroom are more likely to receive special education services relative to their older peers. Children born the month before the school cutoff date are 1.75 percentage points (16%) more likely to receive special education in grade 3 relative to their peers born the month after the cutoff date. Importantly, I find that the gap in special education placement does not diminish with school tenure. In grade 12, children born the month before the cutoff date are still 3.84 percentage points (42%) more likely to receive special education services relative to their peers born the month after the cutoff date. Thus, I find evidence of a negative feedback loop in which the youngest children are placed on a lower track at the onset of their schooling, from which they generally do not recover. In Chapter 2, I document a direct pathway from receipt of special education to SSI using a two-sample fuzzy regression discontinuity design. First, using administrative records from North Carolina, I corroborate earlier findings that children born the month before the kindergarten entry eligibility cutoff date are more likely to receive special education services relative to children born the month after the school cutoff date. Next, using National Health Interview Survey respondents linked to Social Security Administration records, I document that the children born just before the cutoff date are 0.78 percentage points (or 30%) more likely to apply for and 0.55 percentage points (or 59%) more likely to receive an award for SSI between the ages of 5 and 12 relative to children born just after the school cutoff date. I find no increase in awards among groups unlikely to be affected by the relationship between school starting age and special education; these include children with physical impairments or those too young for school enrollment. Two-sample fuzzy RD estimates indicate that a 1 percentage point increase in the fraction of children receiving special education services induces a 0.16 percentage point (or 10%) increase in the fraction of children with an SSI award. Back of the envelope calculations suggest that approximately 18% of the growth in the SSI caseload can be attributed to rising rates of special education and spillovers between these two programs. In Chapter 3, I test how exposure to the Earned Income Tax Credit (EITC) affects the likelihood a child receives SSI payments between the ages of 15 and 18. Exogenous variation in exposure to the EITC is derived from the maximum credit available to the child in his state of residence each year between the ages of 0 and 18. Reduced-form estimates indicated that exposure to an additional $1,000 each year reduces the likelihood that a child receives income from SSI by 0.34 percentage points (26%). Exposure to a larger EITC between the ages of 13 and 18 has the largest impact on SSI receipt. I find no evidence that the primary channel through which the EITC reduces SSI is improved health of the child. In particular I find that exposure to a larger EITC does not reduce the likelihood a child reports a physical or cognitive impairment. Nor do I find any evidence that the primary channel through which the EITC reduces SSI participation is through increases in maternal labor supply, which may mechanically reduce the child’s eligibility for SSI.