Attitudes toward Immigration February 2010 (four dummies for white,Hispanic,black.and other) skilled immigration among differently skilled respon- in all specifications.The covariates are simply included dents is not significant. here to increase the comparability of some of the Taken together,these results reveal several striking coefficients with previous studies(Facchini and Mayda features regarding the dynamic of respondents'skill 2009:Hanson,Scheve,and Slaughter 2007;Mayda levels and immigration preferences.To give some sense 2006:Scheve and Slaughter 2001).Notice that because of the substantive magnitudes involved.we simulate the randomization orthogonalizes HSKFRAME with the predicted probability of supporting an increase in respect to Z,the exact covariate choice does not affect immigration(answers“somewhat agree”and“strongly the results of the main coefficients of interest.21 agree"that the U.S.should allow more immigration) for the median respondent(a white woman aged 45)for Results for Tests of the Labor Market all four skill levels and both immigration types based Competition Model on the least restrictive model (model five in Table 1). Figure 4 shows the results and summarizes our key Results for the tests are shown in Table 1.In the first findings for the tests of the labor market competition two columns we separately regress attitudes toward argument. highly skilled and low-skilled immigration on respon- First,in contrast to the predictions from the labor dents'skill level(measured by educational attainment) market competition model,support for both low-and and the set of covariates.Following the labor market highly skilled immigration is steeply increasing in re- hypothesis we would expect that the support for low- spondents'skill levels.This increase in the probabil- skilled (highly skilled)immigration should increase ity of supporting immigration is very large in substan- (decrease)in respondents'skill level.In contrast,we tive terms.For example,for highly skilled immigration find that the correlation between respondents'skill it ranges from .23 [.18;.26]among respondents who level and support for immigration is positive and sig- did not finish high school to.40 [.35;.45]among col- nificant for both types of immigration (columns one lege graduates (the numbers in square brackets give and two).In fact,we cannot reject the null hypothesis the.95 percent confidence interval).Furthermore.the that the effect of respondents'skill on support for in- increase is not linear,but instead is particularly pro- creased immigration is identical for highly skilled and nounced for the gap between respondents who have a low-skilled immigrants(p-value.21). college education and those who do not.This plateau The next three models implement our main exper- effect is in line with findings in some previous stud- imental tests.To identify the premium attached to ies (Chandler and Tsai 2001:Hainmueller and Hiscox highly skilled relative to low-skilled immigrants,we 2007)showing that exposure to university education use PROIMIG as our dependent variable and regress seems to be the critical contributor to the generally it on the indicator HSKFRAME that denotes whether positive relationship between education and support a respondent received the frame about highly skilled for immigration. immigrants rather than the question about low-skilled Second,regardless of the respondents'skill level immigrants.Results are shown in column three.The highly skilled immigrants are much preferred over low- high-skill frame indicator enters positive and highly sig- skilled immigrants.This finding is at odds with the ex- nificant,indicating that on average highly skilled immi- pectation from the standard model of labor market grants are strongly preferred to low-skilled immigrants. competition that highly skilled natives should oppose Column four includes the interaction of HSKFRAME inflows of highly skilled immigrants and support in- with respondents'skill level,measured by EDUCA- flows of low-skilled immigrants.On the average (i.e., TION.The interaction term enters with the expected across the four skill levels),the predicted probability negative sign,but it is statistically insignificant and the of supporting highly skilled immigration is about 0.15 point estimate is very small in substantive terms.This higher than the probability of supporting low-skilled result suggests that,in contrast to expectations based immigration and this difference is highly statistically on the labor market competition model,the premium significant. attached to highly skilled immigration does not vary Third,there seems to be no systematic variation significantly with respondents'skill level.In column in the premium attached to highly skilled immigrants five we also drop the linearity assumption regarding the across respondents'skill level.As clearly indicated by effect of respondents'skill level and replace EDUCA- the dashed lines that connect the predicted probabil- TION with our set of dummy variables that indicate the ities for each type of immigration,the step function highest level of educational attainment (SOME COL- that describes increased support for immigration with LEGE is the reference category)plus all interactions rising skill levels among respondents is quite similar with the high-skill question frame.We find that not one for the two types of immigration.The relative differ- of the interaction terms is significantly different from ences in predicted probabilities of supporting highly zero.A Wald test against the null that all interaction skilled versus low-skilled immigration are.17 [.13;.20] terms are jointly zero yields a p-value of.61,indicating for respondents who did not complete high school,.12 that the variation in the premium attached to highly [.10;.14]for high school graduates,.15 [.12;.18]for those with some college education,and.17 [.13;.21]for 21 All results are substantively identical if additional(pretreatment) college graduates.The differences are not significantly covariates (suchas martial status or geographic indicators)or no different and do not have opposite signs,as predicted covariates at all are used.Results available upon request. by the labor market competition model.The two dotted 70Attitudes toward Immigration February 2010 (four dummies for white, Hispanic, black, and other) in all specifications. The covariates are simply included here to increase the comparability of some of the coefficients with previous studies (Facchini and Mayda 2009; Hanson, Scheve, and Slaughter 2007; Mayda 2006; Scheve and Slaughter 2001). Notice that because the randomization orthogonalizes HSKFRAME with respect to Z, the exact covariate choice does not affect the results of the main coefficients of interest.21 Results for Tests of the Labor Market Competition Model Results for the tests are shown in Table 1. In the first two columns we separately regress attitudes toward highly skilled and low-skilled immigration on respon￾dents’ skill level (measured by educational attainment) and the set of covariates. Following the labor market hypothesis we would expect that the support for low￾skilled (highly skilled) immigration should increase (decrease) in respondents’ skill level. In contrast, we find that the correlation between respondents’ skill level and support for immigration is positive and sig￾nificant for both types of immigration (columns one and two). In fact, we cannot reject the null hypothesis that the effect of respondents’ skill on support for in￾creased immigration is identical for highly skilled and low-skilled immigrants (p-value .21). The next three models implement our main exper￾imental tests. To identify the premium attached to highly skilled relative to low-skilled immigrants, we use PROIMIG as our dependent variable and regress it on the indicator HSKFRAME that denotes whether a respondent received the frame about highly skilled immigrants rather than the question about low-skilled immigrants. Results are shown in column three. The high-skill frame indicator enters positive and highly sig￾nificant, indicating that on average highly skilled immi￾grants are strongly preferred to low-skilled immigrants. Column four includes the interaction of HSKFRAME with respondents’ skill level, measured by EDUCA￾TION. The interaction term enters with the expected negative sign, but it is statistically insignificant and the point estimate is very small in substantive terms. This result suggests that, in contrast to expectations based on the labor market competition model, the premium attached to highly skilled immigration does not vary significantly with respondents’ skill level. In column five we also drop the linearity assumption regarding the effect of respondents’ skill level and replace EDUCA￾TION with our set of dummy variables that indicate the highest level of educational attainment (SOME COL￾LEGE is the reference category) plus all interactions with the high-skill question frame. We find that not one of the interaction terms is significantly different from zero. A Wald test against the null that all interaction terms are jointly zero yields a p-value of .61, indicating that the variation in the premium attached to highly 21 All results are substantively identical if additional (pretreatment) covariates (suchas martial status or geographic indicators) or no covariates at all are used. Results available upon request. skilled immigration among differently skilled respon￾dents is not significant. Taken together, these results reveal several striking features regarding the dynamic of respondents’ skill levels and immigration preferences. To give some sense of the substantive magnitudes involved, we simulate the predicted probability of supporting an increase in immigration (answers “somewhat agree” and “strongly agree” that the U.S. should allow more immigration) for the median respondent (a white woman aged 45) for all four skill levels and both immigration types based on the least restrictive model (model five in Table 1). Figure 4 shows the results and summarizes our key findings for the tests of the labor market competition argument. First, in contrast to the predictions from the labor market competition model, support for both low- and highly skilled immigration is steeply increasing in re￾spondents’ skill levels. This increase in the probabil￾ity of supporting immigration is very large in substan￾tive terms. For example, for highly skilled immigration it ranges from .23 [.18; .26] among respondents who did not finish high school to .40 [.35; .45] among col￾lege graduates (the numbers in square brackets give the .95 percent confidence interval). Furthermore, the increase is not linear, but instead is particularly pro￾nounced for the gap between respondents who have a college education and those who do not. This plateau effect is in line with findings in some previous stud￾ies (Chandler and Tsai 2001; Hainmueller and Hiscox 2007) showing that exposure to university education seems to be the critical contributor to the generally positive relationship between education and support for immigration. Second, regardless of the respondents’ skill level, highly skilled immigrants are much preferred over low￾skilled immigrants. This finding is at odds with the ex￾pectation from the standard model of labor market competition that highly skilled natives should oppose inflows of highly skilled immigrants and support in- flows of low-skilled immigrants. On the average (i.e., across the four skill levels), the predicted probability of supporting highly skilled immigration is about 0.15 higher than the probability of supporting low-skilled immigration and this difference is highly statistically significant. Third, there seems to be no systematic variation in the premium attached to highly skilled immigrants across respondents’ skill level. As clearly indicated by the dashed lines that connect the predicted probabil￾ities for each type of immigration, the step function that describes increased support for immigration with rising skill levels among respondents is quite similar for the two types of immigration. The relative differ￾ences in predicted probabilities of supporting highly skilled versus low-skilled immigration are .17 [.13; .20] for respondents who did not complete high school, .12 [.10; .14] for high school graduates, .15 [.12; .18] for those with some college education, and .17 [.13; .21] for college graduates. The differences are not significantly different and do not have opposite signs, as predicted by the labor market competition model. The two dotted 70