We make use of newly available data that include roughly 5 million linked household and population records from 1850 to 2015 to document long-term trends in intergenerational social mobility in the United States. Intergenerational mobility declined substantially over the past 150 y, but more slowly than previously thought. Intergenerational occupational rank–rank correlations increased from less than 0.17 to as high as 0.32, but most of this change occurred to Americans born before 1900. After controlling for the relatively high mobility of persons from farm origins, we find that intergenerational social mobility has been remarkably stable. In contrast with relative stability in rank-based measures of mobility, absolute mobility for the nonfarm population—the fraction of offspring whose occupational ranks are higher than those of their parents—increased for birth cohorts born prior to 1900 and has fallen for those born after 1940.
This paper reviews the literature in historical record linkage in the United States and examines the performance of widely used record-linking algorithms and common variations in their assumptions. We use two high-quality, hand-linked data sets and one synthetic ground truth to examine the direct effects of linking algorithms on data quality. We find that (i) no algorithm (including hand linking) consistently produces representative samples; (ii) 15 to 37 percent of links chosen by widely used algorithms are classified as errors by trained human reviewers; and (iii) false links are systematically related to baseline sample characteristics, showing that some algorithms may introduce systematic measurement error into analyses. A case study shows that the combined effects of (i)–(iii) attenuate estimates of the intergenerational income elasticity by up to 29 percent, and common variations in algorithm assumptions result in greater attenuation. As current practice moves to automate linking and increase link rates, these results highlight the important potential consequences of linking errors on inferences with linked data. We conclude with constructive suggestions for reducing linking errors and directions for future research. (JEL C45, C81, J62, N31, N32)
for their many contributions to the LIFE-M project. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
This report is released to inform interested parties of ongoing research and to encourage discussion. Any views expressed on statistical, methodological, technical, or operational issues are those of the author and not necessarily those of the US Census Bureau or the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
Since Alan Krueger’s christening of the Great Gatsby curve, there has been increased attention given to the relationship between inequality and intergenerational social mobility in the United States. Studying intergenerational mobility (IGM) requires longitudinal data across large spans of time as well as the ability to follow parents and children over multiple generations. Few longitudinal datasets meet this need. This article surveys available data and the current and potential issues surrounding the use of administrative records to vastly extend the study of IGM. First, we describe the U.S. Census Bureau’s current uses of administrative records in the linkage of households across household surveys such as the Current Population Survey (CPS), American Community Survey (ACS), Survey of Income and Program Participation (SIPP), and the decennial censuses. Then, we describe the possibilities of creating additional parent-child linkages using the SIPP linked to decennial censuses and the ACS. Last, we outline our model to create linkages across earlier census data (e.g., 1980 and 1990) and contemporary surveys.
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