What if there were a tool that could predict the consequences of every decision you make? While we don’t claim to have a crystal ball, for changes in policy, we have the next best thing: microsimulation models. Using two of those models, the Urban Institute recently explored the answers to a big policy “what if” question: What if Puerto Rico became a state? What would happen if all its citizens had access to government benefits just as citizens of other states?
To answer those questions, first we’ll need to understand a little more about microsimulation. Urban Institute has an extensive portfolio of microsimulation models. We can predict how a change in tax policy affects revenue. We can predict how changes to Social Security will affect future retirement benefits. We can simulate how insurers, employers, and individuals will act under different health care reform scenarios. And we have models for simulating changes in government programs, Medicaid and the Children’s Health Insurance Program, and the Affordable Care Act.
Urban Institute researchers used two of the those models—the Transfer Income Model Version 3 (TRIM3) and the Health Policy Center’s ACS Medicaid/CHIP Eligibility Simulation Model (HPC Eligibility Model)—to simulate the effects that granting Puerto Rico statehood would have on federal government benefits for island residents.
Urban’s role on this project—which was led by the Government Accountability Office (GAO)—focused on the economic consequences; our work did not touch on the political repercussions. Puerto Rican residents are currently not eligible for Supplemental Security Income (SSI) and Supplemental Nutritional Assistance Program (SNAP) benefits. They are eligible for Medicaid and CHIP, but under different policies than in the 50 states and DC. We used TRIM3 to estimate the SSI and SNAP benefits Puerto Rican citizens would receive under statehood. We used the HPC Eligibility Model to estimate their Medicaid and CHIP benefits. The findings illustrate the strengths of microsimulation models in answering “what if” questions.
Three benefits of microsimulation models
1. To answer “what if” questions, you have to have a pretty good idea of where things stand now, before any changes are made. Although this seems logical, it is not always clear that policymakers have a good sense of where things stand before introducing changes.
In the Puerto Rico case, Urban Institute researchers, with the assistance of GAO, compiled program rules that are often spread through dozens of local government agencies and countless manuals, but are well known by frontline caseworkers. Urban researchers then ensured that the starting point simulation matched current administrative data reported by program administrators. This compilation of rules and administrative data aimed at reproducing the current state of policy is itself a valuable contribution and a strength of microsimulation modeling.
2. Microsimulation models can capture how different public assistance programs interact with each other, something that can be difficult for the different agencies to do. TRIM3 shows how public assistance programs interact with each other in ways that can affect participation and benefits amounts.
In the Puerto Rico simulation, we found, somewhat surprisingly, that SNAP benefits might be lower under statehood than under Puerto Rico’s current status as a US territory, depending on modeling assumptions. Under statehood, Puerto Rico’s elderly and disabled residents can receive SSI benefits, which are much higher than the benefits they can currently receive under the island’s elderly/disabled assistance program. As a result, incomes go up and the number of people eligible for SNAP benefits goes down. TRIM3’s capability to model program interactions is one of its most important value-added benefits.
3. Microsimulation can replicate different scenarios to give users a sense of how sensitive results are to assumptions. In the case of the Puerto Rico simulations, researchers made assumptions about which Medicaid eligibility rules Puerto Rico would adopt under statehood. To explore a range of outcomes, we used TRIM3 and the HPC Eligibility Model to simulate two different scenarios: one with the mandatory minimum eligibility rules and another with select optional eligibility rules. Although it is unlikely that Puerto Rican policymakers would choose to adopt only the minimum rules (policymakers in all 50 states and DC have chosen to adopt significantly more expansive eligibility rules), the results demonstrate how much the impact of statehood depends on which eligibility rules are chosen.
For SSI, researchers simulated benefits under two different scenarios: one where Puerto Rican residents participate at the same rate as US residents (where about two-thirds of SSI-eligible people take the benefit) and one where they participate at the same rate as the five poorest states (where about three-quarters participate). Alternative scenarios give consumers of microsimulation models information about a range of policy choices and provide insights about the impacts of various policy interventions.
Urban Institute’s microsimulation models are powerful tools with numerous applications at the national, state, and local levels. They give us glimpses into alternative policy worlds, letting us predict the outcomes and answers to many “what if” questions.