scholarly journals Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net

2015 ◽  
Author(s):  
Bruce Meyer ◽  
Nikolas Mittag
Keyword(s):  
Administrative Data ◽  
Program Effectiveness ◽  
Safety Net ◽  
Poverty Program

scholarly journals Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net

2019 ◽  
Vol 11 (2) ◽  
pp. 176-204 ◽  
Author(s):  
Bruce D. Meyer ◽  
Nikolas Mittag
Keyword(s):  
Administrative Data ◽  
Low Income ◽  
Program Effectiveness ◽  
Safety Net ◽  
Housing Assistance ◽  
Transfer Programs ◽  
Survey Error ◽  
Poor Households ◽  
Poverty Program ◽  
Combined Data

We examine the consequences of survey underreporting of transfer programs for prototypical analyses of low-income populations. We link administrative data for four transfer programs to the CPS to correct its severe understatement of transfer dollars received. Using survey data sharply understates the income of poor households, distorts our understanding of program targeting, and greatly understates the effects of anti-poverty programs. Using the combined data, the poverty-reducing effect of all programs together is nearly doubled. The effect of housing assistance is tripled. Correcting survey error often reduces the share of single mothers falling through the safety net by one-half or more. (JEL C83, I32, I38)

scholarly journals Efficiency, Legitimacy, and Impacts of Targeting Methods: Evidence from an Experiment in Niger

2020 ◽  
Author(s):  
Patrick Premand ◽  
Pascale Schnitzer
Keyword(s):  
Program Effectiveness ◽  
Safety Net ◽  
Cash Transfer ◽  
Transfer Program ◽  
Community Based ◽  
Means Testing ◽  
The Subject ◽  
Per Capita ◽  
The Impact ◽  
Roll Out

Abstract The methods to select safety net beneficiaries are the subject of frequent debates. Targeting assessments usually focus on efficiency by documenting the pre-program profile of selected beneficiaries. This study provides a more comprehensive analysis of targeting performance through an experiment embedded in a national cash transfer program in Niger. Eligible villages were randomly assigned to have beneficiary households selected by community-based targeting (CBT), proxy-means testing (PMT), or a formula to identify the food-insecure (FCS). The study considers targeting legitimacy and the impact of targeting choice on program effectiveness based on data collected after program roll-out. PMT is more efficient in identifying households with lower consumption per capita. Nonbeneficiaries find formula-based methods (PMT and FCS) more legitimate than CBT. Manipulation and information imperfections affect CBT, which can explain why it is not the most legitimate. Program impacts on some welfare dimensions are larger among households selected by PMT than CBT.

scholarly journals Are We Providing Enough to Those Who Have Too Little? Measuring Poverty Relief

2017 ◽  
Vol 7 (2) ◽  
pp. 331-347
Author(s):  
Karen L. Jusko ◽  
Katherine Weisshaar
Keyword(s):  
Low Income ◽  
Poverty Reduction ◽  
Program Effectiveness ◽  
Rank Order ◽  
Reduction Rate ◽  
Safety Net ◽  
Poverty Relief ◽  
State Variation ◽  
Social Transfers ◽  
Relief Ratio

This manuscript presents a new measure of safety net program effectiveness—a “poverty relief ratio”—that is based on the estimated relationship between market income and social transfers, and reports the amount of income support provided, relative to the amount required to provide for all low-income households’ basic needs. In an important advance over the standard poverty reduction rate measures, the poverty relief ratio preserves the rank order of observations across varying poverty thresholds. In this paper, we introduce this measure and demonstrate its validity by tracking major changes in federal policy and cross-state variation in safety net programs.

Working for Your Bread: The Labor Supply Effects of SNAP

2021 ◽  
Vol 111 ◽  
pp. 496-500
Author(s):  
Marianne Bitler ◽  
Jason Cook ◽  
Jonathan Rothbaum
Keyword(s):  
Moral Hazard ◽  
Labor Supply ◽  
Administrative Data ◽  
Reduction Rate ◽  
Safety Net ◽  
Tax Credits ◽  
Supplemental Nutrition Assistance Program ◽  
Assistance Program ◽  
Eligibility Determination ◽  
Nutrition Assistance

The Supplemental Nutrition Assistance Program (SNAP), the only universal US means-tested safety net program, has a low benefit-reduction rate. Thus, many SNAP recipients are working. We apply recent methods to study whether there is evidence of moral hazard among SNAP recipients. We see if individuals respond to incentives in SNAP eligibility by bunching near kink points in the budget set. While this responsiveness has been shown for various taxes and tax credits, little work has examined responsiveness of safety net program participants to kinks in their eligibility formulae. We use novel administrative data on eligibility determination and find little evidence of responsiveness around these kinks.

Outcomes Analysis for Hearing Conservation Programs

2000 ◽  
Vol 9 (2) ◽  
pp. 75-83 ◽  
Author(s):  
Thomas M. Helfer ◽  
Anne R. Shields ◽  
Kathy E. Gates
Keyword(s):  
Health Care ◽  
Cost Effectiveness ◽  
Administrative Data ◽  
Program Effectiveness ◽  
Outcomes Analysis ◽  
Conservation Programs ◽  
Data Set ◽  
Military Health ◽  
Hearing Conservation ◽  
Screening Programs

In health care, an increasing interest in accountability for outcomes, proof of quality care, and cost effectiveness is forcing many practitioners, including audiologists, in the direction of using outcomes analysis to provide proof of performance in their practices. Critical to the conduct of outcomes analysis are the selection of valid outcomes metrics and application of appropriate statistical processes. Modeling of clinical protocols is a useful exercise for developing outcomes data and data management standards. The authors describe the implications for wider use of outcomes modeling once the Health Insurance Portability and Accountability Act (HIPAA) administrative simplification law is implemented. This legislation will set up a wholly new administrative data set that has strong potential to provide outcomes metrics to a variety of Audiology practices. The modeling exercise described here was originally intended to derive assessment outcomes for evaluating hearing conservation program effectiveness in military populations from an administrative database implemented within the Military Health System starting in 1997. The outcomes modelers, however, soon realized the broader applicability of modeling techniques for other special populations and Audiology practices, particularly with the oncoming startup of HIPAA legislative mandates. The modeling exercise demonstrates a process of structuring standard health-care codes to produce outcomes data for epidemiologic and cost analyses, thereby providing better information to guide health-care practices toward improving quality and cost effectiveness. This information in time series should also provide a record of continuous quality improvement. The authors present a general hearing surveillance protocol for evaluating occupational hearing loss. The protocol is used as a specific instance to demonstrate the shaping of an outcomes metrics model. This same process can be applied more generally when used to model outcomes data from other audiology practices. Implementation of the administrative data model described here began at more than 400 Department of Defense (DOD) medical treatment facilities worldwide as of October 1, 1999. The exercise of developing similar outcomes metrics for newborn hearing screening programs, school hearing conservation programs, and other clinical and rehabilitative audiology practices in the civilian sector remains to be done.

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