Abstract
Using a difference-in-differences framework and micro data from the Current Population Survey-Merged Outgoing Rotation Group Files (1999 to 2004), this paper estimates the impact that the 9-11 terrorists attacks had on the U.S. labor market outcomes of individuals with nativity profiles similar to the terrorists. We find that shortly after the attacks, the employment-population ratios and hours worked of very young (ages 16 to 25) Muslim men fell. By 2004, most losses had begun to dissipate. The employment-population ratios and hours worked of older Muslim men experienced little deterioration. We find no effect of the U.K.’s July 2005 London bombings on the labor market outcomes of U.S. Muslims.
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Notes
According to U.S. Equal Opportunity Commission (Washington, DC 20507) between 9/11/2001 and 12/11/2002, 705 charges were filed under Title VII with Process Type Z.—CAIR Annual Report 2002. For additional background, see for example, Baker et al. (2003), Braakmann (2009, 2010) Human Rights Watch (2002), Leonard (2003), Lindkvist (2002), Moore (2002), Shryock (2002), Suleiman (1999) and U.S. Census Bureau (2003).
Lawyers Committee for Human Rights (www.lchr.org); September 2003 Report. “Assessing the New Normal: Liberty and Security of the Post-September 11 United States”. Also, see Hate Crime Report (2001).
Approximately 35 million non-immigrants were required to register with immigration authorities. Non-immigrant adult males from the following countries were called in for the program: Iran, Iraq, Libya, Sudan and Syria, Afghanistan, Algeria, Bahrain, Eritrea, Lebanon, Morocco, North Korea, Oman, Qatar, Somalia, Tunisia, United Arab Emirates, and Yemen, Pakistan, Saudi Arabia, Bangladesh, Egypt, Indonesia, Jordan and Kuwait.
Our findings on the relative decrease in earnings of the target groups are consistent with Kaestner et al. (2007).
Kaestner et al. (2007) regress earnings for employed individuals. For their hours-worked regressions, they include all individuals setting hours equal to zero for men who were not employed. We do the same in the OLS regressions but for the quantile earning regressions, we include all men assigning log of earnings equal to zero if not employed. This is done to avoid the sample selection bias occurring in the mean regression.
The recession that began in March 2001 is potentially one such confounding factor. Estimation of the pre- and post-9/11 changes in outcome using only the target-group (i.e., Muslims) sample may generate a negative coefficient simply because of the business-cycle downturn.
To control for industry of work, nine major industry dummy variables were used. To control for occupations we constructed 10 major occupation groups. However, we use percentage of group members working in the respective occupation to control for occupational variations instead of using occupation dummies. Exclusion of this variable does not significantly affect the difference in differences effect.
We follow the specifications of Kaestner et al. (2007) here. We find coefficients of the time-trend variables always negligible and statistically insignificant. Models with month dummy variables yielded similar results.
In the case of probit, the interaction effect is estimated by taking the average of difference-in-differences of the predicted probabilities.
Kaushal et al. allowed the effect of 9-11 to differ according to an index of hate crime/discrimination against Arabs and Muslims. They used three measures of 9-11 related hate crime or discrimination: number of hate crime/discrimination incidents reported in a state; number of hate crime/discrimination incidents per Arab population in a state; and number of hate crime/discrimination incidents per state population. They estimated the results using all three indices and found the effects of all of them to be statistically insignificant. Due to the insignificant effects and the limited nature of the data, we do not include the indices in the analyses.
To verify whether the DD effects of 9-11 dissipated by year 2004, and whether the July 2005 Bombings in the U.K. affected U.S.-Muslims’ labor market outcomes, we extend our data up to year 2008.
Allen and Nielsen (2002) find that after 9/11, the single most predominant factor in determining who was to be a victim of an attack or infringement was their visual identity as a Muslim. This was found to be the case across reports from all 15 EU member states. In addition, there were seven reported cases of murders of Sikh men between September 2001 and February 2005. Sikhism is a religion, which in no way is affiliated to Islam. All of the cases appear to be hate-crimes.
Detroit Arab American Study-2003, University of Michigan; ICPSR Study No.: 4413; CAIR Annual Reports on Civil Rights Violations.
Non-immigrant adult males from the following countries were called in for the special registration program: Iran, Iraq, Libya, Sudan, Syria, Afghanistan, Algeria, Bahrain, Eritrea, Lebanon, Morocco, North Korea, Oman, Qatar, Somalia, Tunisia, United Arab Emirates, Yemen, Pakistan, Saudi Arabia, Bangladesh, Egypt, Indonesia, Jordan and Kuwait. The CPS-MORG files do not separately identify Algeria, Libya, Somalia, Sudan, Tunisia and Eritrea. However, they identify immigrants from North Africa, which consists of Algeria, Egypt, Libya, Morocco, Sudan, Tunisia and Western Sahara.
The “Rest of Africa” which includes Somalia and Eritrea is dropped from the data. This is done to make sure that none of the comparison groups contains immigrants from the special registration program.
Algeria, Libya and Tunisia cannot be identified separately but they are geographically included in North Africa. Some North African countries were not brought under Special Registration program. For the In-Between and the Narrow Groups, we dropped the “rest of North Africa” as identified by CPS.
Most of the 19 hijackers of the 9-11 attacks were identified to be from Middle Eastern Arab countries. None of them was identified to be from any South Asian countries, Indonesia, or North Africa (Except Egypt). News articles and other reports indicate that incidences of civil right violations occurred at lower rates against immigrants from Bangladesh, Indonesia and North African countries. The anti-terrorism programs such as mass round-ups and voluntary interviews also targeted these immigrants relatively less than the narrow group. On another note, majority of these hijackers were very young, with age below 26.
Kaestner et al. (2007) too, takes only 20 states where 80 percent of the broadest target-group population is concentrated. In our study, observations of very young target-group members were too small for the excluded states. The Davila and Mora paper includes a concentration measure instead and uses all of the U.S. states. The authors used a concentration ratio to measure visibility. However, concentration measures may not measure visibility well and increased visibility does not necessarily lead to bigger 9-11 effects. In addition, potentially important state-level differences in factors such as the economy and industry mix are captured by state dummies but not by concentration measures.
Immigrants from Mexico, Central America and the Caribbean are excluded because their educational achievement and language proficiency is not similar to other immigrants. Besides, Orrenius and Zavodni (2009) found that the relatively new immigrants from Mexico also experienced a small drop in earnings after 9-11. We find that inclusion of immigrants from these countries does not change our results.
We exclude African Americans and Latinos from comparison group 3 because some of their observable characteristics are different from those of our target groups. Non-Hispanic Whites have been used as a comparison group in previous studies such as Orrenius and Zavodny (2009), and Davila and Mora (2005). This exclusion of U.S.-born Blacks and Latinos does not change our results.
All comparison tables are available from the authors on request.
These relative changes in outcomes are unadjusted DD effects of 9-11; they can be calculated from Table 1.
For the employment regressions, the difference-in-differences of employment-ratio was predicted for each observation separately and the mean of all the difference-in-differences is reported for each age-range under each target group in Table 2. Standard errors were estimated for each prediction and the mean of those standard errors is shown in parentheses. When we use linear probability model, the DD effect stays close to 30 percentage points by year 2002.
We find no statistically significant effect on the weekly earnings of immigrants from African-Arab countries (results available from authors on request).
All quantile regression estimates are available from the authors on request.
All results using the rolling-date strategy are available from the authors on request.
We used nine intervention dates for the period from 1999 to 2004. September 2001 and January 2002 interventions yield the largest relative drops in the employment of the youngest members of the target groups. The drops are around 30 to 35 percentage points and are statistically significant. If is worth mentioning here that for the narrow target group, the unadjusted regressions show nearly 14 to 18 percentage-point relative drops in employment after 9-11 for this shorter time-window. We used a shorter time-window, 1999 through 2002. Intervention dates close to 9-11 yield bigger employment effects for 16 to 25 year old Muslims
This finding is in line with the fact that even in the wake of the July bombings, public opinion was steadily becoming more favorable towards Muslims in the USA (Pew Research Center 2005).
Restricting samples to U.S. citizens, we find 16 to 26 percentage point DD effects on earnings of men aged 16 to 64. The short run DD effects on Employment of men aged 16 to 25 stays at 20 to 23 percentage points but are not measured with precision.
We find that the earnings of the 1st generation immigrant men in the target groups decreased by 14 to 17 percentage points relative to 1st generation immigrants from non-Muslim majority countries in the year after 9-11. Relative to comparison groups 2 and 3, decrease in earnings were between 16 and 20 percentage points. This adverse effect disappears by 2004. We do not find any statistically significant relative decrease of employment of 16 to 25 year old 1st generation men. Surprisingly, the difference-in-differences effect on the employment ratio of the 16 to 64 year old 1st generation men in the narrow target group was positive 11 percentage points by year 2002. However, this advantage in employment is not found for the broader target groups.
“More Muslims Arrive in U.S., After 9/11 Dip”; Andrea Elliott, New York Times, September 10, 2006. “Tossed Out of America”; Chicago Tribune, November 18, 2003
Although the CPS survey materials and interviewers routinely provide reassurances about confidentiality to potential and actual respondents, CPS faces the problem of non-response from undocumented or otherwise fearful group of respondents. Many non-citizen Muslims probably became more likely to refuse to participate in the CPS after 9-11. If they did participate, they might not have been forthcoming about their labor market activities or a proxy respondent for the household might have omitted them from the household roster altogether. It is often assumed by the BLS that those who are likely to be missed have lower employment or their employments are more cyclically sensitive. The missed portion of the sample is reflected in the final estimates when the survey results are weighted to the population controls; the persons missed will be assigned the labor force characteristics of their counterparts who were in the sample. Therefore, if, during the recession after 9-11, employment decreased among those missed by the survey, their loss would not be reflected in the CPS.
Regression estimates from using U.S.-born men as comparison groups are available from the author on request. In regressions that included comparison groups 2 and 3, we drop citizenship status and length of stay variables to avoid multicollinearity problem.
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Rabby, F., Rodgers, W.M. Post 9-11 U.S. Muslim Labor Market Outcomes. Atl Econ J 39, 273–289 (2011). https://doi.org/10.1007/s11293-011-9281-3
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DOI: https://doi.org/10.1007/s11293-011-9281-3