Abstract
This chapter develops an algorithm for the probability distribution of a respondent’s religion in microdata (including the decennial census) in which there are data on ancestry but not on religion. A frequency distribution of religion by ancestry is generated from the NORC General Social Survey and matched by ancestry groups in the 1980 U.S. decennial census. The fruitfulness of the procedure is demonstrated through an analysis of the effect of alternative measures of religion on the household’s choice of public versus private schooling for children. This method is useful to any researcher wanting to distinguish religious affiliation when only ancestry data are available. Jewish children are as likely as Protestant children to be attending public schools compared to private schools, but Catholic children are more likely than those of other religions to attend private schools.
This is a revision of the original article published in Journal of Human Resources, 34(1), Winter 1999, pp. 193–207. Co-authored with Stella Koutroumanes Hofrenning. I am responsible for the current version.
The authors appreciate comments received on an earlier draft from John Durkin, Evelyn Lehrer, and Paul W. Miller.
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Notes
- 1.
- 2.
For example, although the majority of persons of Russian ancestry in the United States are Jewish, Jews were only a very small minority (less than 1 percent) of the population of the Soviet Union prior to the recent mass emigration (American Jewish Year Book 1988, p. 344).
- 3.
Independent of this study, Lankford and Wyckoff (1992) also use the General Social Survey ancestry data to estimate the probability of being Catholic. They use this variable in their analysis of school choice, but without much discussion. Moreover, they do not use variables for other religion probabilities, do not show the implications of alternative approaches to identifying Catholics, or report the religion probabilities by ancestry.
- 4.
Census Bureau coding procedures mask any ancestry response that would reveal the respondent’s current religion or religious ancestry.
- 5.
This procedure is, therefore, distinct from the instrumental variables (IV) technique in which a predicted value from a regression equation replaces the unknown value of an explanatory variable that is endogenous or measured with substantial error.
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- 7.
More complex stratifications can be used, such as stratifying by level of schooling as well as by ancestry. Two problems arise, however. One is that cell size becomes smaller the larger the number of stratifications. The other is that one would not want to stratify by a variable that might be endogenous, such as education.
- 8.
See Chiswick and Koutroumanes (1996) for a discussion of the other variables.
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Chiswick, B.R., Hofrenning, S.K. (2020). A Method for Proxying a Respondent’s Religious Background: An Application to School Choice Decisions. In: Chiswick, B. (eds) Jews at Work. Studies of Jews in Society, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-030-41243-2_13
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