- After PIKing adults who provided an SSN, we used the PIKs to append first and last name from the Numident to the 1986-1990 CPS. We then took these appended these names to observations of their children, allowing us to PIK children using age, sex, and parents’ first and last names.
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- Arias, E, 2015. United States Life Tables, 2011. National Vital Statistics Reports, 64(11), pp. 1-62.
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Böhlmark, A. & Lindquist, M. J., 2006. Life-Cycle Variations in the Association between Current and Lifetime Income: Replication and Extension for Sweden. Journal of Labor Economics, 24(4), pp. 879-896.
- Behrman, J. & Taubman, P., 1985. Intergenerational Earnings Mobility in the United States: Some Estimates and a Test of Becker's Intergenerational Endowments Model. The Review of Economics and Statistics, pp. 144-151.
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- Björklund, A. & Jäntti, M., 1997. Intergenerational Income Mobility in Sweden Compared to the United States. The American Economic Review, pp. 10091018.
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- Boserup, S., Kopczuk, W. & Kreiner, C. T., 2013. Intergenerational Wealth Mobility: Evidence from Danish Wealth Records of Three Generations. Univ. of Copenhagen mimeo.
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Bourdieu, J., Ferrie, J. & Kesztenbaum, L., 2009. Vive la Difference? Intergenerational Mobility in France and the United States During the Nineteenth and Twentieth Centuries. Journal of Interdisciplinary History, 39(4), pp. 523-557.
Celhay, P. & Gallegos, S., 2015. Persistence in the Transmission of Education: Evidence across Three Generations for Chile. Journal of Human Development and Capabilities.
- Chan, T. W. & Boliver, V., 2013. Social Mobility Over Three Generations in Britain. American Sociological Review, pp. 662-678.
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- Chetty, R. et al., 2014. Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility. American Economic Review Papers and Proceedings, 104(5), pp. 141-147.
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- Clark, G., 2014. The Son Also Rises. Princeton: Princeton University Press.
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Couch, K.A. and Dunn, T.A., 1997. Intergenerational correlations in labor market status: A comparison of the United States and Germany. Journal of Human Resources, pp. 210-232.
- Federal Reserve Bank of Chicago Working Paper No. 2015-04 (June).
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- Feigenbaum, J., 2015a. A New Old Measure of Intergenerational Mobility: Iowa 1915 to 1940. Working Paper.
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- Feigenbaum, J., 2015b. Intergenerational Mobility during the Great Depression. Working Paper.
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- Ferrie, J., Massey, C. & Rothbaum, J., 2016. Changes in U.S. Intergenerational Mobility in Educational Attainment, 1895-2013. Working Paper.
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- FIGURE 1. REPORTED EDUCATION ATTAINMENT BY YEAR OF BIRTH AND CENSUS Notes: This figure plots the average years of schooling by age cohort and census sample. The 1940 Grandparent generation includes all adults 25-55 in the 1940 Census. The 1910-1040 linked sample includes all individuals in the 1910 and 1920 Censuses linked to themselves in the 1940 census.
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- FIGURE 2. DISTRIBUTION OF EDUCATION ATTAINMENT BY GENERATION Notes: This figure plots the distribution of education in each generation. In each generation, only individuals aged 25-55 are included. The Great-grandparent generation comes from the 1910 and 1920 Censuses (linked to the 1940 Census for education). The Grandparent generation is from the 1940 Census. The Parent generation is from the 1973, 79, 81-90 CPS ASEC. The Child generation is from the 2000 Long Form Census and 2001-2013 ACS.
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Goldin, C. & Katz, R. A., 2000. Education and Income in the Early Twentieth Century: Evidence from the Prairies. The Journal of Economic History, 60(3), pp. 782-818.
Goldin, C. 1998. America’s Graduation from High School: The Evolution and Spread of Secondary Schooling in the Twentieth Century. The Journal of Economic History, pp. 345-374.
Grawe, N. D., 2006. The Extent of Lifecycle Bias in Estimates of Intergenerational Earnings Persistence. Labour Economics, 13(5), pp. 551-570.
- Grusky, D. B., Smeeding, T. M. & Snipp, C. M., 2015. A New Infrastructure for Monitoring Social Mobility in the United States. Annals of the American Academy of Political and Social Science, 657(1), pp. 63-82.
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Haider, S. & Solon, G., 2006. Life-Cycle Variation in the Association between Current and Lifetime Earnings. American Economic Review, 96(4), pp. 13081320.
- Hertel, F. R. & Groh-Samberg, O., 2014. Class mobility across Three Generations in the US and Germany. Research in Social Stratification and Mobility, Volume 35, pp. 35-52.
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Hertz, T., Jayasundera, T., Piraino, P., Selcuk, S., Smith, N. and Verashchagina, A., 2007. The inheritance of educational inequality: International comparisons and fifty-year trends. The BE Journal of Economic Analysis & Policy, 7(2), pp. 1-46.
- Hilger, N. G., 2016. The Great Escape: Intergenerational Mobility Since 1940. Working Paper.
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Hodge, R. W., 1966. Occupational Mobility as a Probability Process. Demography, 3(1), pp. 19-34.
Lee, C.I. & Solon, G., 2009. Trends in Intergenerational Income Mobility. The Review of Economics and Statistics, 91(4), pp. 766-772.
Lindahl, M., Palme, M., Massih, S. S. & Sjögren, A., 2015. Long-Term Intergenerational Persistence of Human Capital an Empirical Analysis of Four Generations. Journal of Human Resources, 50(1), pp. 1-33.
Lleras-Muney, A, 2005. The Relationship between Education and Adult Mortality in the U.S. Review of Economic Studies, Vol. 72, No.1: 189-221.
- Long, J. & Ferrie, J., 2012. Grandfathers matter(ed): Occupational mobility across three generations in the US and Britain, 1850-1910. Unpublished Manuscript.
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Long, J. & Ferrie, J., 2013. Intergenerational Occupational Mobility in Great Britain and the United States since 1850. American Economic Review, 103(4), pp. 1109-37.
Mazumder, B., 2005. Fortunate sons: New Estimates of Intergenerational Mobility in the United States using Social Security Earnings Data. Review of Economics and Statistics, 87(2), pp. 235-255.
Mazumder, B., 2015. Estimating the Intergenerational Elasticity and Rank Association in the U.S.: Overcoming the Current Limitations of Tax Data.
Nybom, M. & Stuhler, J., 2016. Heterogeneous Income Profiles and Life-Cycle Bias in Intergenerational Mobility Estimation. Journal of Human Resources, 51(1).
Olivetti, C. & Paserman, M. D., 2015. In the Name of the Son (and the Daughter): Intergenerational Mobility in the United States, 1850-1940. The American Economic Review, pp. 2695-2724.
- Panel A: 1940 Census-CPS Panel B: CPS-LF/ACS Panel C: LF/ACS - ACS FIGURE 2. WITHIN-PERSON DISCREPANCIES IN EDUCATION ATTAINMENT ACROSS SURVEYS Notes: The reported education difference is equal to education attainment at time ! + # minus education attainment at time t.
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Peters, E. H., 1992. Patterns of Intergenerational Mobility in Income and Earnings. The Review of Economics and Statistics, pp. 456-466.
Solon, G., 1992. Intergenerational Income Mobility in the United States. The American Economic Review, pp. 393-408.
Solon, G., 2002. Cross-country Differences in Intergenerational Earnings Mobility. The Journal of Economic Perspectives, 16(3), pp. 59-66.
- Solon, G., 2014. Theoretical Models of Inequality Transmission across Multiple Generations. Research in Social Stratification and Mobility, Volume 35, pp. 1318.
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Solon, G., 2015. What Do We Know So Far about Multigenerational Mobility? NBER Working Paper Series 21053.
- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data.
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- Source: Linked 1910/1920 Census, 1940 Census, 1973, 1979, 1981-1990 Current Population Survey Annual Social and Economic Supplements, 2000 Long Form Census, and 2001-2013 American Community Survey data. -0.001
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Stuhler, J., 2012. Mobility across Multiple Generations: The Iterated Regression Fallacy. IZA Discussion Paper No 7072.
- TABLE 4 – EDUCATIONAL MOBILITY OVER TIME (1) (2) Parent Child 1973,79,81-90 2000-2013 Grandparent 0.361*** Parent 0.363*** 1940 (0.005) 1973,79,81-90 (0.006) R 2
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- The 1940 Census contains PII that is not traditionally used to assign PIKs. We adapted the Census Bureau’s matching software to use state or country of birth, location in 1940 and 1935, and parents’ names in addition to more traditional PII such as first name, middle initial, last name, and age. To incorporate place of birth, we coded birthplace in the Numident to match the five-digit IPUMS birthplace (BPL) codes in the 1940 Census, accounting for both territories and changes in country names over time. To match on age, we calculated age on April 1, 1940 using full date of birth in the reference file and compared this to reported age in the 1940 Census.
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- The 1986-1990 CPS did not contain first or last name. To PIK this data, we merged the CPS to the Numident using SSN. If sex and age agreed, we assigned the PIK associated with that SSN. We were able to PIK 99.5 percent of the 248,670 respondents who provided a SSN (out of 386,630 total respondents). Because we do not observe SSN for children under the age of 15, we took additional steps to increase the number of parent-child associations possible from the CPS.
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- The Census Applications Branch (CAB) within CARRA processed the 2000 Census and the 2001-2013 American Community Surveys (ACS) through the PVS. CAB assigned PIKs to these files using full name (first, last, and middle), full date of birth (month, day, and year), and street address. To assign PIKs to the 1940 Census and the 1973-1990 Current Population Surveys (CPS) Annual Social and Economic Supplements (ASEC), we modified the PVS to assign PIKs tailored to the information available on each file.
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- The CPS, 2000 Census, and ACS samples do not include imputed education.
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- The PVS follows the typical steps in record linkage: preprocessing, sorting into blocks, identifying potential matches, and resolving multiple matches. Person records are preprocessed to standardize the blocking and matching fields to ensure comparability across the census file and the reference file. Next, because the reference file is large, PVS sorts the input and reference files into blocks to create reasonably sized search spaces (Michelson and Knoblock, 2006). The PVS creates the Cartesian product of the census and reference records falling within the same block, comparing every census record to every reference record falling within the same block.
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- The PVS then scores the similarity between the census and reference records in this comparison space. 20 The average number of transactions per SSN is 2.1 (Harris, 2014).
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- The third module blocked on the first letter of first and last name. The fourth and fifth modules compared location in 1940 and 1935 observed from the 1940 Census to states where records received their SSN in the reference file. For these modules, we used the first three digits of the SSN (called the area number) to determine location of SSN issue in the reference file and allowed no more than 2 years difference between age in 1940 or 1935 and the age a person acquired their SSN. The final module blocks on county observed in 1940 and 1935 to state and county of birth observed in the reference file. We only processed person-records less than 2 years old in 1940 or 1935 through this module to ensure we did not introduce significant bias from migration. Within each module, potential matches were scored based on the similarity of first name, middle initial, last name, age, five-digit state or country of birth BPL code, and parents’ first name.
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- To fill in the gap between 1940 and 2000, we produced PIKed versions of the 1973, 1979, and the 1981-1990 CPS. We employed multiple techniques to PIK this data. For 1973, 1979, and 1981-1985 data, we used probabilistic matching techniques to assign PIKs using SSN, first name, middle initial, last name, age (or full date of birth if available), and sex. We observed SSN for a large number of observations over the age of 15. For children, we also used parents’ first names in the PIKing algorithm. We used two blocking procedures: one blocking on age and one blocking on first and last name initials.
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- Warren, J. R. & Hauser, R. M., 1997. Social Stratification Across Three Generations: New Evidence from the Wisconsin Longitudinal Study. American Sociological Review, pp. 561-572.
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- We used probabilistic matching techniques to link the 1940 Census back to the 1910 and 1920 censuses to obtain education for the Great-Grandparent generation. We used the 1920 Census in addition to the 1910 Census to reduce bias introduced by requiring survival of the GreatGrandparent generation to 1940. To link 1910 and 1920 to 1940, we used first name, middle initial (if available), last name, age, sex, and state or country of birth. We employed two blocking strategies, first blocking on place of birth then blocking on the first letter of the first and last name. We allowed a tolerance of three years in age between a 1910 or 1920 observation and a potential match in the 1940 Census. Once the probabilistic matching algorithm identified and scored all potential matches, we used only the highest-scoring, unique match.
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- We used six customized modules to PIK the 1940 Census. The first module blocked on the first three digits of the IPUMS BPL code. The second module blocked on age on April 1, 1940.
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- When the initial match between 1910/1920 and 1940 was complete, we appended education data from the 1940 census to adults in the 1910 and 1920 censuses. We then used the relationship-to-household-head variable to construct family units and identify children. These children were linked forward to the 1940 Census. To account for name-changes of women, we appended mother’s maiden names from the Numident to children in the 1940 Census using the PIKs discussed previously. Once we knew a child’s mother’s maiden name, we appended the maiden names to mothers observed in 1940 to link backwards to 1910 and 1920.
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Zeng, Z. & Xie, Y., 2014. The Effects of Grandparents on Children’s Schooling: Evidence from Rural China. Demography, 51(2), pp. 599-617.