This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

« Back to Results

Low-Income Families

Paper Session

Friday, Jan. 5, 2018 2:30 PM - 4:30 PM

Pennsylvania Convention Center, 106-A
Hosted By: Society of Government Economists
  • Chair: Austin Nichols, Abt Associates

Controlling for Prices when Estimating SPM Thresholds and the Impact on SPM Poverty Statistics

Thesia I. Garner
,
U.S. Bureau of Labor Statistics
Juan D. Munoz
,
U.S. Bureau of Labor Statistics

Abstract

"The SPM thresholds produced by the BLS, subsequently used by the Census Bureau for poverty statistics, are based on a distribution of out-of-pocket expenditures for food, clothing, shelter and utilities (FCSU) by consumer units with two children. They are created using five years of Consumer Expenditure Interview Survey (CE) data and price adjusted using the All Items CPI U.S. City Average. Following this procedure, as outlined in Citro and Michael (1995), the assumption is that FCSU expenses increase or decrease within areas at the same rate; currently, the only over time adjustment has been to apply the all items CPI-U to FCSU expenditures. No one as yet has examined the impact on SPM poverty of varying prices within areas over time. Also, in none of the previous SPM research has a price adjustment in FCSU expenditures across areas been made. This lack of a spatial or inter-area price adjustment recently was highlighted in a paper by Bishop et al. (2017).

The purpose of this research is to produce SPM thresholds based on FCSU expenditures that are price adjusted within areas across time, and across areas. These adjustments are made before FCSU expenditures are ranked to derive SPM thresholds. Poverty rates are produced to examine the impact of both the within and across area price adjustments. For this study we construct FCSU commodity bundle specific CPI’s for 38 urban areas and four regions for rural areas using prices and weights from the internal BLS CPI database. The FCSU area specific CPIs are applied to consumer unit level FCSU expenditures to convert them to FCSU 2016 dollars. FCSU expenditures are further adjusted to account for differences in prices across geographic areas. We plan to test two different inter-area price adjustments. One is the same that is used by the Census Bureau to produce Area specific SPM thresholds. The other is based on BEA regional price parities for FCSU. To test the impact of FCSU commodity price adjustment and inter-area price adjustment to the thresholds, SPM poverty rates are produced.
"

Calculating a Supplemental Poverty Measure in the Survey of Income and Program Participation: Methods, Findings, and Comparisons to the Current Population Survey

Liana E. Fox
,
U.S. Census Bureau
Lewis H. Warren
,
U.S. Census Bureau
Ashley Edwards
,
U.S. Census Bureau

Abstract

"Since the first estimates of the Supplemental Poverty Measure (SPM) were produced by the Census Bureau in 2010, estimates have been derived from the Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC). However, original National Academy of Science recommendations on the implementation of a SPM called for calculating the measure from an alternate data source, the Survey of Income and Program Participation (SIPP).

Those recommendations were based on the fact that the SIPP has traditionally done a better job than the CPS ASEC in collecting income data, particularly among low-income families. However, because much of the detailed content necessary for calculating the SPM is collected through the SIPP in topical modules, limitations related to the timing and consistency of those modules throughout the panel have created formidable obstacles to calculating consistent annual SPM estimates.

This research takes advantage of the recent redesign of the 2014 SIPP Panel, which provides more consistent collection of the detailed data on family relationships, income and transfer program receipt, and medical, work-related, and tax expenses necessary to calculate the SPM. We calculate SPM estimates for 2013 as derived from the SIPP, and evaluate differences in the SPM rate— as well as differences in the incremental impact of income sources and expenses— across the SIPP and CPS ASEC for 2013.
"

Earnings, EITC, and Employment Responses to a $15 Minimum Wage: Will Low-Income Workers Be Better Off?

Fahad Fahimullah
,
District of Columbia Government
Yi Geng
,
District of Columbia Government
Bradley L. Hardy
,
American University
Daniel Muhammad
,
District of Columbia Government
Jeffrey Wilkins
,
District of Columbia Government

Abstract

This study assesses the economic and fiscal impacts of the Fair Shot Minimum Wage Amendment Act of 2016, which increases the District of Columbia minimum wage to $15 an hour. This minimum wage policy coupled with the city’s 40 percent local EITC supplement, as a package, represent one of the most aggressive labor-market policy interventions in the nation. This study estimates the short and long-term earnings, employment and EITC responses to these policies. While many minimum wage studies have relied on partial-equilibrium approaches that focus on specific subsets of the workforce (e.g. teens, restaurant workers), our study uses a computable general equilibrium (CGE) model for the city’s entire workforce. We supplement the CGE results with a policy microsimulation model using administrative tax data. We estimate that over 60,000 District residents will be impacted by these policies and will observe a total increase of about $192 million in wage income (about 19 percent), while about 2 percent of District resident workers will experience job loss. We also find that the city’s EITC recipients will lose a total of $16.4 million in federal and local EITC payments in 2021 while gaining $56.6 million in additional wages by way of the $15 minimum wage.

Building Savings for Success

Gregory Mills
,
Urban Institute
Signe-Mary McKernan
,
Urban Institute
Caroline Ratcliffe
,
Urban Institute

Abstract

Individual development accounts (IDAs) help low-income families save by matching their personal savings for specific investments, such as a first home, business capitalization, or higher education and training. The Assets for Independence (AFI) program is a federally supported IDA grant program authorized under the Assets for Independence Act of 1998. Our evaluation at two sites—Albuquerque and Los Angeles—shows that AFI is increasing low-income participants’ savings one year into the program.

This is the first evaluation of the AFI program to use a randomized controlled trial, the gold standard for measuring program effectiveness. We assess the program’s early (first-year) effects on participants’ savings, asset ownership, and economic well-being. Results show two beneficial primary effects:

- A 7 percentage point (9 percent) increase in the share of participants with liquid assets.
- A $657 median increase and $799 mean increase in liquid assets. Because we look at all liquid assets—including savings, checking, money market, and retirement accounts plus stocks and bonds—our results indicate that participants are not simply shifting savings from other types of accounts into their IDAs, but instead are creating new savings.
We also find evidence that AFI affects several secondary outcomes:

- A 34 percent reduction in hardships related to utilities, housing, or health, equivalent to one less hardship experienced.
- A 39 percent (4 percentage point) decline in the use of alternative (nonbank) check-cashing services, suggesting that AFI participation helps people enter the financial mainstream.
- A 10 percent increase in participants’ confidence in their ability to meet normal monthly living expenses.

These major first-year impact findings—that AFI participation results in more savings, less material hardship, and improved perceptions of one’s financial situation—provide empirical evidence that AFI promotes economic well-being.

While the vast majority of federal asset-building subsidies (such as the mortgage interest deduction) disproportionately benefit high-income earners, the AFI program is one of few federal efforts that actively encourages saving among low-income families. By encouraging low-income families to save, AFI can improve their short-term stability while providing a foundation for longer-term upward mobility.
Discussant(s)
David Johnson
,
University of Michigan
James Ziliak
,
University of Kentucky
Sharat Ganapati
,
Georgetown University
Takashi Yamashita
,
U.S. Bureau of Economic Analysis
JEL Classifications
  • I0 - General
  • J0 - General