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Who Married, (to) Whom, and Where? Trends in Marriage in the United States, 1850-1940. (2020). Salisbury, Laura ; Paserman, M. Daniele ; Olivetti, Claudia ; Weber, Anna E.
In: IZA Discussion Papers.
RePEc:iza:izadps:dp13811.

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  1. (2) We assign occupational status using the occupational personal wealth distribution from 1870 (Long and Ferrie 2018; Olivetti et al 2018). (3) We assign occupational status according to the occupational real estate wealth distribution from the full count 1850 decennial census, adjusting the wealth of farmers by subtracting the mean value of a farm in 1850 from the census of agriculture. (4) We use LIDO scores, which assign income by occupation-industrystate -sex-race-age using the 1950 income distribution (Saavedra and Twinam, 2018).
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  36. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor ], 2010-05-21. https://doi.org/10.3886/ICPSR02896.v3.
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  37. B Robustness Measurement of Occupational Status Our main measure of socioeconomic status is the logarithm of occupational income (the OCCSCORE variable in IPUMS). We also experiment with alternative measures of occupational status: (1) We use the 1900 occupational wage distribution (Preston and Haines 1991) with a wage for farmers calculated from the 1900 census of agriculture (Abramitzky et al, 2012; Olivetti and Paserman, 2015); we assign farm income both nationally and at the state level.
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  38. Figure 1: Trends by Woman’s Parental SES .84 .86 .88 .9 .92 Fraction 1840 1860 1880 1900 15 year birth cohort Quartile 1 (lowest) Q2 Q3 Q4 (a) Fraction of Women 30-45 Ever Married 2.9 2.95 3 3.05 Log Father-in-Law Occscore 1840 1860 1880 1900 15 year birth cohort Quartile 1 (lowest) Q2 Q3 Q4 (b) Father-in-Law’s SES Note: The top panel shows the fraction ever married by birth cohort and parents’ quartile of occupational income score. The bottom panel shows the average log occupational score of fathers of husbands aged 3045 married to wives 30-45 by the woman’s parental quartile of occupational income score. The occupational income score is imputed based on first names. Source: Authors’ calculations based on the 1% IPUMS samples (1850-1930) and a 1% extract of the 1940 Restricted Complete Count Census Data.
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  39. Figure 2: Correlation in Parental SES 0 .02 .04 .06 .08 .1 Correlation coefficient 1840 1860 1880 1900 15 year birth cohort National Northeast Midwest South Note: This figure shows the correlation in parental occupational income score between husband and wife.
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  40. Figure 3: Trends by Region of Woman’s Birth .8 .85 .9 Fraction 1840 1860 1880 1900 15 year birth cohort Northeast Midwest South (a) Fraction of Women 30-45 Ever Married 2.9 2.95 3 3.05 3.1 Log Father-in-Law Occscore 1840 1860 1880 1900 15 year birth cohort Northeast Midwest South (b) Father-in-Law’s SES Note: The top panel shows the fraction ever married by birth cohort and woman’s region of birth. The bottom panel shows the average log occupational score of fathers of husbands aged 30-45 married to wives 30-45 by woman’s region of birth. The occupational income score is imputed based on first names. Source: Authors’ calculations based on the 1% IPUMS samples (1850-1930) and a 1% extract of the 1940 Restricted Complete Count Census Data.
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  41. Figure B-1: Age and Marital Status Distribution in Census Samples 0 1000 2000 3000 4000 5000 Observations 30 35 40 45 Age Married, Spouse in Range Married, Spouse out of Range Unmarried Men, Ages 30-45 0 1000 2000 3000 4000 5000 Observations 30 35 40 45 Age Married, Spouse in Range Married, Spouse out of Range Unmarried Women, Ages 30-45 1880 Sample Age Distributions 0 2000 4000 6000 8000 10000 Observations 30 35 40 45 Age Married, Spouse in Range Married, Spouse out of Range Unmarried Men, Ages 30-45 0 2000 4000 6000 8000 10000 Observations 30 35 40 45 Age Married, Spouse in Range Married, Spouse out of Range Unmarried Women, Ages 30-45 1940 Sample Age Distributions Source: Authors’ calculations based on the 1% IPUMS samples (1850-1930) and a 1% extract of the 1940 Restricted Complete Count Census Data.
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  42. Geographic Controls Change in Q4-Q1 Gap in Spouse's Parental Log Occscore Note: Figure plots the change in the Q1-Q4 parental SES gradient in the probability of marriage (top panel) or spousal’s parental SES (bottom panel) between the cohorts observed as adults in 1880 and 1940 estimated using different controls. All control variables are interacted with a full set of cohort dummies. The Birthplace Controls specification includes a set of dummies for the woman’s state of birth interacted with cohort dummies.
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  43. Region assignment is by the wife’s region of birth. The occupational income score is imputed based on first names. Source: Authors’ calculations based on the 1% IPUMS samples (1850-1930) and a 1% extract of the 1940 Restricted Complete Count Census Data.
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  44. Schroeder, and Matthew Sobek (2010). Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota.
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  45. Source: 1% IPUMS samples (1850-1930), 1% extract of the 1940 Restricted Complete Count Census Data.
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  46. Source: 1% IPUMS samples (1850-1930), 1% extract of the 1940 Restricted Complete Count Census Data.
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  47. Source: 1% IPUMS samples (1850-1930), 1% extract of the 1940 Restricted Complete Count Census Data.
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  48. Source: 1% IPUMS samples (1850-1930), 1% extract of the 1940 Restricted Complete Count Census Data.
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  49. To obtain a ballpark estimate of ρ(yij, ykl), we need an estimate of the attenuation factor λ. We believe that it is reasonable to assume that λ is approximately on the same order of magnitude as χ. Therefore, we calculate the implied correlation assuming that λ = δχ, for values of δ ∈ {0.5, 0.75, 1, 1.25, 1.75}. We can then estimate ρ(yij, ykl) by ρ(yij, ykl) = 1 δχ2 ρ(yj, yl) (A9) We have samples of men linked between the 1850-1880 censuses and the 1880-1910 censuses.
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    In: Working Papers.
    RePEc:dtm:wpaper:64.

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