Ensuring Time-Series Consistency in Estimates of Income and Wealth

32 Pages Posted: 10 Feb 2008

See all articles by F. Thomas Juster

F. Thomas Juster

affiliation not provided to SSRN

Joseph Lupton

University of Michigan at Ann Arbor - Department of Economics; Board of Governors of the Federal Reserve - Division of Research and Statistics

Honggao Cao

University of Michigan at Ann Arbor

Date Written: July 2002

Abstract

In the past decade, researchers have made substantial improvements to survey questions that allow them to obtain more accurate information from survey respondents about income and wealth. However, changing survey questions - even for the better - can create problems. For example, if we ask a respondent about his wealth holdings in 1992 and ask him again in 1994 but use a different and improved set of questions, we cannot be sure that changes in his wealth are real because part of the observed change can be due to the fact that we simply got better information the second time we asked. Thus, the cost of improved questions can be inconsistency in the data over time. We refer to this problem as time-series inconsistency. In this paper, we describe work that addresses this problem in the Health and Retirement Study (HRS) using data on income from financial assets. We describe a method of computation that allows us to resolve times series inconsistencies.

Suggested Citation

Juster, F. Thomas and Lupton, Joseph P. and Cao, Honggao, Ensuring Time-Series Consistency in Estimates of Income and Wealth (July 2002). Michigan Retirement Research Center Research Paper No. WP 2002-030, Available at SSRN: https://ssrn.com/abstract=1091460 or http://dx.doi.org/10.2139/ssrn.1091460

F. Thomas Juster (Contact Author)

affiliation not provided to SSRN ( email )

Joseph P. Lupton

University of Michigan at Ann Arbor - Department of Economics ( email )

611 Tappan Street
Ann Arbor, MI 48109-1220
United States

Board of Governors of the Federal Reserve - Division of Research and Statistics

20th and C Streets, NW
Washington, DC 20551
United States

Honggao Cao

University of Michigan at Ann Arbor ( email )

500 S. State Street

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