Abstract
Religious women work less than their non-religious counterparts. Is this because they want to work less or because patriarchal social norms limit their choices? To address this question, we estimate the employment happiness premium, which we define as the happiness gain associated with being employed, for men and women belonging to six world religions and for the non-religious. Our results indicate that the employment happiness premium is higher for men than for women for every world religion and that the gender gap in the employment happiness premium varies significantly across religions. Next, we ask whether the gender gap in the employment happiness premium can explain the gender gap in employment. That is, is it plausible that preferences explain employment patterns across religions and genders? We find that preferences plausibly explain the gender employment gap for Buddhists, Orthodox Christians, and the non-religious. In contrast, they explain less than half the observed gender employment gap for Hindus, Muslims, Catholics and Protestants. Our findings are consistent with a significant role for patriarchal social norms in constraining female employment in these religious traditions.
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Notes
Religion is also closely associated with other dimensions of stratification and social economic inequality. See Keister and Sherkat (2014) for a broad discussion of religion and inequality.
Forsythe and Korzeniewicz (2000) and Foroutan (2008) find that Islam and Hinduism are associated with particularly strong traditional gender roles. Relative to other religions, these two religions are also associated with higher fertility (McDonald 2000; Mishra 2004), lower female education (Cooray and Potrafke 2011; Dollar and Gatti 1999; Norton and Tomal 2009) and lower female employment (Foroutan 2007; Psacharopoulos and Tzannatos 1989).
The literature on culture and gender inequality addresses, inter alia, the influence of inherited values (Fernández and Fogli 2009), historical plough use (Alesina et al. 2013), gendered language (Davis and Reynolds 2018; Gay et al. 2013, 2015; Hicks et al. 2014; Mavisakalyan 2015), and individualism (Davis and Williamson 2018).
See, for example, Oswald and Powdthavee (2008), Alesina et al. (2004), and Louis and Zhao (2002) on gender, Cohen (2002), Clark and Lelkes (2005), and Helliwell (2003, 2006) on religious belief and participation, and Meier and Stutzer (2006), Weinzierl (2005), and Bardasi and Francesconi (2004) on employment. Stevenson and Wolfers (2009) find that the female happiness premium is declining in the US. Dolan et al. (2008) review the happiness literature.
Here, Orthodox refers to Orthodox Christian. People who believe in Orthodox are mainly from post-communist societies.
To further confirm that our data are composed of national representative samples, we compare the dominant religion for each country in our sample with the one reported in the US Central Intelligence Agency (CIA) Factbook and find that they are the same.
For all the regressions on employment, we estimate Probit models as well for a robustness check. We find that our OLS results are in large consistent with the results from Logit models: the variables of our interest are still significant at 5% level and the sign is the same.
Cameron and Miller (2015) provide a guideline on how to cluster standard errors for empirical studies. The authors argue that it is necessary to cluster standard error when the model errors for observations within the same cluster are correlated, but cross clusters are not correlated. In practice, generally, standard errors are clustered at a higher geographical level. They also recommend to use cluster-robust standard errors when the number of clusters is large.
Note that the coefficients on individual religious affiliation should be interpreted as capturing the average employment effect of a given religious affiliation across countries, reflecting, for example, average religious values and beliefs for that religion for individuals in our global sample. In particular, our empirical approach will not identify international variation in the values and beliefs of adherents to a particular religion, such as Roy (2004) and Foroutan (2015) argue exist for Muslims in Western and Arab countries.
For a robustness check, we also estimate another specification in which we control for a full set of female-employed-dominant religion interactions. Therefore, we end up with six interactions and each indicates a different religious society. In such specification, we differentiate the EHP for Catholic women living a Muslim society from that for Catholic women living in a Protestant society. We find that the results on EHP are quite similar to results obtained from Eq. (3) and thus we didn’t present them here.
As we discussed earlier, \(\gamma_{1}\) is estimated using a two-step generated regressor approach and its OLS standard error is biased. As a result, our Wald test statistics will be biased if we use the variance–covariance matrix obtained from the OLS estimation. To conduct a valid Wald test, ideally, we would like to replace the OLS standard error with bootstrap standard error when calculating the test statistics. However, empirically, it is difficult to manually conduct the test by replacing the variance–covariance matrix. Therefore, in practice we use the bootstrap simulation to compute the p value for our statistical inference. We randomly draw a sample with replacement and compute a Chi square statistics and repeat this process 1,000 times. Then we obtain a distribution of the test statistics. We compare each statistic with the critical values of the chi-square distribution at a 5% significance level (Since we conduct a two-tailed test, it is 2.5% level of significance on each tail). The p value is equal to the number of times that our test statistics are greater than the critical value out of 1,000 replications.
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Acknowledgements
We wish to thank Roger Hoerl, Lori Marso, Ann Owen, Steven Schmidt and participants in the Symposium on Religion, Social Conflict and Social Cohesion, the Union College Economics Seminar, and the Southern Economic Association Meetings for useful comments on earlier drafts of this paper. Any remaining errors are our own.
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Davis, L., Gao, J. Preferences or Patriarchy: Why Do Religious Women Work Less?. Soc Indic Res 147, 287–310 (2020). https://doi.org/10.1007/s11205-019-02152-6
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DOI: https://doi.org/10.1007/s11205-019-02152-6