Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net
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Cited by:
- Achille Lemmi & Donatella Grassi & Alessandra Masi & Nicoletta Pannuzi & Andrea Regoli, 2019. "Methodological Choices and Data Quality Issues for Official Poverty Measures: Evidences from Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 299-330, January.
- Bruce D. Meyer & Derek Wu, 2018. "The Poverty Reduction of Social Security and Means-Tested Transfers," NBER Working Papers 24567, National Bureau of Economic Research, Inc.
- Bruce D. Meyer & Derek Wu & Victoria R. Mooers & Carla Medalia, 2019.
"The Use and Misuse of Income Data and Extreme Poverty in the United States,"
NBER Working Papers
25907, National Bureau of Economic Research, Inc.
- Bruce D. Meyer & Derek Wu & Victoria R. Mooers & Carla Medalia, 2019. "The use and misuse of income data and extreme poverty in the United States," AEI Economics Working Papers 1018925, American Enterprise Institute.
- Kerstin Bruckmeier & Regina T. Riphahn & Jürgen Wiemers, 2021. "Misreporting of program take-up in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," Empirical Economics, Springer, vol. 61(3), pages 1567-1616, September.
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More about this item
Keywords
poverty; Inequality; measurement error; administrative data; survey misreporting; linked data;All these keywords.
JEL classification:
- I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
- I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
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