Abstract
This article examines low income in the American Jewish population. It situates the study of the Jewish poor within a broader sociological framework by utilizing general sources on poverty among Americans to identify and test a range of predictors of low income among American Jews. Using data from the National Jewish Population Survey 2000–2001, it finds six major predictors of low income: age, education, employment status, family-household type and its interaction with gender, citizenship status and Jewish denomination. Importantly, it shows that the simultaneous presence of several predictors is necessary to raise the probability of having low income above the Jewish population’s mean rate, and it builds on this finding to examine the factors that contribute to low income among Orthodox, immigrant and elderly Jews. The article also investigates social correlates and communal consequences of low income, demonstrating a pattern of poorer health, increased social service needs and diminished communal participation among the Jewish poor. It concludes with a discussion of a research agenda on economic vulnerability among American Jews.
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Notes
Jewish communal professionals, activists and researchers have more consistently turned their attention to the Jewish poor. Starting in the late 1960s, numerous articles and reports ignited communal concern about Jewish poverty and debate over its prevalence (Leshner 1967; Chenkin, undated but presumed published shortly after the 1970–1971 National Jewish Population Survey was conducted; Kaplan 1972; Rice 1972; Wolfe 1972a, b; Levine and Hochbaum 1974; Lerner 1976, 1985; Lavendar 1977; Waxman 1979; Ginsburg 1984; Huberman 1986). More recently, a series of communal reports and articles have used survey data to focus again on economic vulnerability among American Jews (Ukeles 1998; Rapfogel 2004; Ukeles and Grossman 2004; Grossman 2005; Kotler-Berkowitz 2005a; for an analysis of poverty among Canadian Jews, see Shahar and Karpman 2004). In addition, most reports from local Jewish population studies now address the issue of Jewish poverty (see, for example, Phillips 2005; Phillips and Herman 2001; Sheskin 2004, 2007; Ukeles Associates and International Communications Research 2004), as did Bubis’ (2000) communal report. While important to communal planners and policy makers who work with organizations that serve the economically vulnerable, these reports are written primarily for non-academic audiences and do not include multivariate statistical modeling common to scholarly social science.
For a critique of NJPS 2000–2001, see Kadushin et al. (2005).
For example, Buddhism or Wicca.
For further details on weighting, see the NJPS 2000–2001 Study Documentation at www.jewishdatabank.org.
Kotler-Berkowitz (2005b), Kadushin and Kotler-Berkowitz (2006), Rebhun and Levy (2006) and Klaff (2006) use the same analytic weight in their analyses. For further information on analytic weights, see the NJPS 2000-01 Data File User Guide, available for downloading from the North American Jewish Data Bank at www.jewishdatabank.org. For an alternative analytic weighting strategy, see Phillips and Fishman (2006) and Phillips and Kelner (2006).
The item non-response rate to the question on household income in the National Survey of Religion and Ethnicity 2000–2001, a survey of non-Jews conducted in conjunction with NJPS, was 16.9%, significantly below the NJPS non-response rate for this question.
See, for example, Ukeles and Grossman (2004), who use 150% of the federal poverty guidelines in their report on the Jewish poor for UJA-Federation of New York and the Metropolitan Council on Jewish Poverty.
While the NJPS question mentioned “total income,” unlike some other survey questions on income it did not prompt respondents to include income from various sources, e.g., earnings from work, investment income, or rental income.
A series of follow-up questions were asked in order to collect data about income at or below the federal poverty level, but as noted above the federal poverty standards are often considered too low to adequately analyze economic vulnerability among American Jews. For item non-respondents to the original income question, a follow-up question asked if their income was below or above $100,000, but this question cannot be used to classify people as having low income or not.
While it would have been possible to use an ordinal measure of income, doing so would have shifted the focus of the analysis to examining increasing (or decreasing) income levels, rather than isolating and predicting low income specifically.
Secular education, not religious education.
As noted in the introduction, these studies also identify age, sex and single parenthood as determinants of low income among Jews.
In her analysis of Israeli Haredim, Stadler (2002) argues that the group has reinterpreted work and economic success as obstacles to salvation. The extent to which such an explanation might apply to American Haredim is unknown, and at any rate NJPS data do not provide a way to distinguish between Haredi and modern or centrist Orthodox Jews. Berman (2000) proposes an economic club good model to explain why Israeli ultra-Orthodox men remain in yeshiva in the face of family poverty, but explicitly acknowledges the model does not account for the behavior of ultra-Orthodox communities elsewhere.
This article does not address the theoretical debate in the sociological literature on individual, cultural and structural causes of low income and poverty (Iceland 2003; Kelso 1994; Levy 1995; Modarres and Andranovich 2005). In cross-sectional survey data like NJPS, some predictors may be indicators of all three theoretical perspectives. For example, low levels of education may represent the failure of individuals to invest in education, cultural predispositions to shun education, and/or structural constraints on educational opportunities. Because NJPS data do not, in most cases, allow us to determine to what extent the predictors reflect any of these theoretical perspectives, this article remains neutral on the theoretical debate and instead focuses on the empirical analysis.
Data from the National Survey of Religion and Ethnicity 2000–2001 (United Jewish Communities 2003b), a companion survey to NJPS 2000–2001, show that just 17.2% of non-Jewish adults do not share their household with another adult, significantly less than the 40% rate among Jewish adults.
The most notable inconsistency involves differences in the base of respondents, even from question to question within the same general topic area, which often poses challenges to analyzing across variables. See the NJPS 2000–2001 Study Documentation at www.jewishdatabank.org for further details.
A broader definition of the Jewish population typically used by communal organizations—one that includes those who were born or raised Jewish but no longer consider themselves Jewish, as long as they do not claim another monotheistic religion—yields a slightly higher rate of low income among adult Jews, 14% (Kotler-Berkowitz 2005a). The broader definition also yields slightly higher rates of low income for Jewish households, and for all people in Jewish households, both adults and children. This means low income is more common among adults who have self-selected out of the Jewish population, and their families, than among those who continue to identify as Jews.
The estimate of the low-income population may also be an underestimate because NJPS 2000–2001 may have produced an underestimate of the overall Jewish population; see the methodological appendix in Kotler-Berkowitz et al. (2003) and Schulman (2003). Despite concerns about population underestimates, analysts agree that the survey can be validly used for analyzing relationships between and among variables; see Schulman (2003), Kadushin et al. (2005), and Kadushin and Kotler-Berkowitz (2006).
The odds are defined as the probability of having low income divided by the probability of not having low income. When the probability = 0.5, the odds = 1.
Among those who are married with no children, three-quarters (75.8%) report their spouse is employed either full- or part-time.
Because NJPS is a stratified and clustered sample, potential design effects on standard errors should be examined (see the NJPS 2000–2001 Study Documentation, pp. 150–151 and Appendix 14). Assuming design effects of 1.5, all of the predictor categories reported as statistically significant above remain so at the 0.95 confidence level except age 75+, college degree, homemaker, single mother, naturalized citizen and just Jewish/secular/no denomination, and all predictors remain statistically significant at the 0.90 confidence level. Assuming design effects of 1.3, all of the predictor categories reported as statistically significant above remain so at the 0.95 confidence level except homemaker and just Jewish/secular/no denomination, and all predictors remain statistically significant at the 0.90 confidence level. Calculations are available from the author.
Also using NJPS 2000–2001, Chiswick and Huang identify several of the same factors affecting the earnings of American Jewish men that I have identified as predictors of low income, including education, nativity (citizenship), marital status (family-household type) and Jewish denomination.
In a logistic regression model, the probability, p, of the predicted category of a dichotomous dependent variable is equal to 1/1 + exp(−Z), where exp is the exponential function and Z = a + b 1 x 1 + b 2 x 2 + ··· + b n x n (i.e., the linear combination of explanatory variables).
The reference categories were chosen in order to produce positive regression coefficients among predictor categories with higher levels of low income.
Low-income probabilities based on having multiple predictors of low income are not shown in Table 4. All calculations of low-income probabilities based on the regression model are available from the author.
Similar analyses could be conducted for those who identify as just Jewish/secular/no denomination, for naturalized citizens, or for any other group defined by a particular characteristic.
Note that none of the general sources on poverty that I draw on identify poor health as a determinant of poverty. Nonetheless, in an effort to be cautious in my claims, I acknowledge the potential mutual effects between poor health and low income by specifying poor health as a social correlate rather than consequence of low income.
The full models are available from the authors upon request.
Together with the 2000–2001 NJPS and NSRE, the joint 1990 NJPS and National Survey of Religious Identity could facilitate an over-time comparison between Jews and non-Jews with respect to low income.
For information on the General Social Survey, see http://www.norc.org/GSS+website.
For information on the American National Election Studies, see http://www.electionstudies.org/.
For more expansive household and population estimates resulting from a broader definition of who is a Jew, see Kotler-Berkowitz (2005a).
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Acknowledgements
Findings from this research were first presented at the 2005 annual conference of the Association of Jewish Studies in Washington, DC, where I received encouraging feedback from Sylvia Barack Fishman. I thank Steven M. Cohen and Esther Wilder for their careful reading and helpful comments on earlier versions of this article. Alan Zuckerman, z”l, read and commented on this article, as he did with nearly all of my scholarly research and writing; I shall miss his generosity and good counsel. I dedicate this article to Buddy Friedman, z”l, my grandfather, teacher and good friend.
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Appendices
Appendix 1: Rates and Estimates of Low Income Among Jewish Households and People Residing in them
Table 11 provides weighted estimates for the total number of low-income households and people residing in them, as well as corresponding percentages. These estimates and percentages are for households with known income data and are based on the household weights on the NJPS data file. The table shows that there are 218,000 total Jewish households that fall under the low-income threshold, constituting 13.0% of all Jewish households. The total number of people, Jewish and non-Jewish, living in low-income Jewish households is 497,000 (13.0% of all people in Jewish households). In turn, the total low-income population is comprised of 388,000 adults (12.9% of all adults in Jewish households) and 109,000 children (13.2% of all children in Jewish households; children are defined as ages 0–17). Among the 388,000 adults living in low-income Jewish households, 310,000 are Jewish (12.9% of all Jewish adults in Jewish households, and 79.9% of all adults in low-income Jewish households). Among the 109,000 children in low-income Jewish households, 80,000 are Jewish (11.8% of all Jewish children in Jewish households, and 73.4% of all children in low-income Jewish households).Footnote 33
Appendix 2: Examining Income Non-respondents
As noted in the article, 29% of respondents did not supply income data that allow a determination of their low-income status. As a result, the true low-income rate for all Jewish adults cannot be known with certainty. However, a true low-income rate among the income non-respondents that is higher than 12.8% would pull the overall rate up; conversely, a true low-income rate among the income non-respondents that is lower than 12.8% would push the overall rate down.
One way to examine whether income non-respondents are likely to have a low-income rate above or below the overall mean level of 12.8% is to compare them against all respondents with known income data, as well as separately against those who are above and below the low-income threshold, relating to the critical categories within the six variables that predict low income in the logistic regression analysis and on the scale of characteristics that predict low income. Table 12 presents the comparisons.
An examination of the table reveals an important pattern. Income non-respondents usually fall between those above and below the low-income threshold and as a general rule they more closely resemble those who are above the threshold. Only for the proportion of elderly do income non-respondents fall equidistant from both comparison groups. Consequently, it is plausible to suggest that income non-respondents have an overall rate of low income less than the 12.8% overall rate that characterizes all respondents with known income data, and that the true overall rate for all Jewish adults—if it could be calculated—would be below 12.8%. Precisely how far below is impossible to know, but by making some assumptions, we can calculate a floor rate and other higher rates.
To calculate the floor rate, we assume that none of the income non-respondents falls below the low-income threshold (i.e., that their rate of low income is 0%), in which case the true low-income rate for all Jewish adults would be 9.1%; and the 12.8% rate reported in the text would be an overestimate of 3.7 percentage points. If we raise the assumed low-income rate among income non-respondents to one-quarter of the overall rate, 3.2%, then the true low-income rate for all Jewish adults would be 10.0%. Similarly, if we raise the assumed low-income rate among income non-respondents to half the overall rate, 6.4%, then the true low-income rate for all Jewish adults would be 10.9%; and if we again raise the assumed low-income rate among income non-respondents, this time to three-quarters of the overall mean, 9.6%, then the true low-income rate for all Jewish adults would be 11.9%. (All calculations are available from the author.)
Appendix 3: Predictors of Low-Income
Table 13 displays the distributions for each of the 12 independent variables used as predictors of low income.
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Kotler-Berkowitz, L. Poor Jews: An Analysis of Low Income in the American Jewish Population. Cont Jewry 29, 241–277 (2009). https://doi.org/10.1007/s12397-009-9021-z
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DOI: https://doi.org/10.1007/s12397-009-9021-z