Table 3 demonstrates the importance of correctly characterizing the elasticities. Results in the table would suggest that the burden of increased immigration over these 13 years was shouldered largely by workers without a high school degree, and in particular that native workers in this category have experienced large negative wage impacts.
Table 4 shows the results once again with appropriately characterized elasticities separately for men and women. Looking first at the overall effect for U. However, the breakdowns by education are somewhat different. In particular, we find that the effect of immigration from to was to increase the wages of U.
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Table 5 can shed some light on this difference. Table 5 is similar to Table 1, which shows increased hours worked from to due to immigration, but it is broken out by gender. Among women, there have been slightly greater increases in hours in the more-educated group than in the less-educated group, whereas among men, there have been somewhat greater increases in hours in the less-educated group than in the more highly educated group.
These differences help explain why native women with lower levels of education gain due to immigration 1. The estimates presented above show that immigration from to had a modest positive effect on the overall wages of both male and female native workers 0. Within that overall change, women with less than a high school education experienced a nontrivial increase 1.
On the other hand, men with less than a high school education experienced a modest decline Table 6 uses the estimates of the relative wage impacts of immigration to quantify how much of the growth over this period in wage inequality between workers with less than a high school degree and workers with a college degree or more can be explained by immigration.
The final row shows the difference in growth rates due to immigration divided by the difference in wage growth rates—in other words, it gives the share of the difference in wage growth rates that is due to immigration. This is the measure we use of the amount of increased inequality over this period that can be attributed to immigration. For native workers, only 0. However, this overall effect masks differences by gender. Immigration decreased inequality among native women—the differences in growth rates between the two education groups would have been 7.
Among men, 0. For foreign-born workers of both genders, but particularly for women, immigration caused larger wage declines among college workers than among less than high school workers, so new immigration reduced inequality among immigrants. However, because immigration is nevertheless concentrated at the high end and low end of the overall wage distribution, increased immigration increases overall wage inequality. We find that immigration con-tributed 2. Among women, the difference in wage growth rates between the two education groups would have been 6. One question that arises in the debate on immigration and wages is the effect of immigration on the wages of young workers, especially young men with low levels of education.
Table 7 breaks down the effect of immigration on wages by age category and gender. Also note that, as is common practice in the labor economics literature, definitions of age categories are slightly different across education categories to reflect the fact that, for example, a worker with only a high school education is generally available to start work four years earlier than a worker with a college degree. The results show that in fact older native workers face bigger impacts of the increasing foreign-born workforce over this period. Native workers with 31 to 40 years of potential labor market experience age group 4 saw a modest decline of 0.
The overall pattern generally holds across education categories, in particular, for native workers without a high school degree, year olds of both genders gained due to immigration while it was middle-aged workers—workers age —who saw modest declines. These results provide no evidence that younger workers in any category are being particularly hard-hit by immigration relative to older workers. The methodology used in this paper does not allow for a breakdown of the effect of immigration on U. However, using the estimated wage effects of immigration by education and experience group, we can aggregate the results separately for white and black native workers to look at the overall impact of immigration on these two groups.
The differences in the overall effects by race will essentially reflect the fact that educational breakdowns are different for blacks and whites. Education breakdowns for for native blacks and native whites are given in Table 8. They show that native blacks have somewhat lower educational attainment than native whites, with a higher percentage of black native workers than white native workers not having a high school degree 9.
However, since as Table 4 shows the positive impact of immigration does not rise monotonically across education groups, it is not a priori obvious what the aggregate impact will be. The overall impacts by race are given in Table 9. They show that in the aggregate, immigration has essentially the same relative effect on native blacks as it has had on native whites—a small positive relative impact on wages. These results reflect the fact that there is not a great deal of variation across education categories in the relative impact of immigration on wages, so even though blacks and whites have different education breakdowns, in aggregate the effect of immigration on wages is similar.
Does the impact of immigration on wages vary with overall labor demand? Over the period from to , labor demand varied widely—in particular, from , the labor market was much stronger than it was in the later period. From , job growth averaged 2. From to , employment growth picked up somewhat, growing at an average of 1. Immigration flows, unsurprisingly, respond to the conditions of the U. Was the impact of immigration on wages different over these three periods of very different overall labor demand?
Table 10 shows the impact of immigration on wages by gender and education separately for these three periods. It should be noted that unlike the other tables in this paper, which report the impact over the entire period from , this table gives the average impact per year over each period for ease of comparison. The results show that the main effect of the different periods is felt by immigrants themselves, who faced much larger negative eff ects during the period of greater immigration in the s.
For native workers overall, there was not large variation in the impact of immigration over the three periods, though the gains were greatest during the 90s, since immigration was higher. For workers with less than a high school education, there were some small differences: these workers experienced a modest relative decline of 0. By gender, the differences were slightly larger—male workers with a high school education or less saw a relative decline of 0. The fact that the relative effect of immigration on wages does not vary dramatically over periods of dramatically different labor demand offers some limited evidence that immigrant-flow response to labor demand in the United States helps to smooth the effects of immigration on native wages across periods of strength and weakness in the U.
Immigrant flows vary widely by state. Table C1 in Appendix C shows immigrant flows by state from to Here we examine the four states that have seen the largest increase in numbers of immigrant workers: California, Florida, New York, and Texas. California saw an increase of 1.
Because these are the four largest states, we are able to conduct an analysis separately for each of these states without running into major sample size issues. Table 11 shows the results by education category and gender for these four states.
In these high immigrant states, the overall effect of immigration is similar to the effect at the national level—small positive effects for native workers and nontrivial negative effects for earlier immigrant workers. By education category, however, there is some variation. In particular, in California and Texas, immigration has led to a decline in the relative wages of U. These effects were concentrated among men, with males without a high school education in California seeing an estimated relative wage decline of 2. Native workers without a high school education were essentially unaffected as a group in New York relative decline of 0.
In Florida, workers with less than a high school education gained 1. In sum, in these very high immigrant states, the overall relative effect of immigration is positive on native workers, around 0. Thus, on average, native workers in these high immigrant states gain somewhat more than the national average due to immigration. However, some subgroups in these high immigrant states fare worse, as described above, particularly male workers with less than a high school degree.
Their work shows that unauthorized immigrants make up a large portion of the workforce in these four states relative to other states. They estimate that in the United States in , unauthorized immigrants made up 5. However, they found that in California, for example, 9. Since, as shown in their work, unauthorized immigrants are more likely than other workers to be male and also more likely than other workers to be without a high school degree, a larger inflow of unauthorized immigrant workers, who are easily exploited by employers, may put downward pressure on the wages of similar native workers in these states, a pressure that is largely masked in estimates at the national level.
This paper has presented results in terms of percentage relative wage gains or losses due to immigration. However, because there is a great deal of variation in average weekly wages for different subgroups, a similar percentage effect of immigration on wages may have very different effects by subgroup in terms of actual dollars gained or lost. Table C2 in Appendix C gives the average weekly wages for for all of the subgroups in Table Based on average weekly wages in , along with the relative wage effect of immigration in Table 11, Table 12 gives, in dollar terms, the relative effect of immigration from to on the average weekly wages in Table 12 shows that at the national level, the effect of immigration from to on wages of native workers was modest—it raised the relative average weekly wage of native-born U.
However, the impact varied somewhat across education category and gender. Earlier immigrants, on the other hand, experienced large declines due to new immigration. For high immigration states, some of the effects on native workers were more dramatic. However, when recent developments in the national-approach methodology are incorporated, the results are very similar to those found in the area approach—that recent immigration has had little effect on the relative wages of native workers, including workers with low levels of education.
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A key finding in the results is that the workers who stand to lose the most from new immigration are those workers most substitutable for new immigrants, namely earlier immigrants. To those unfamiliar with the scholarly literature on the effect of immigration on native labor market outcomes, the findings of little relative impact on native wages may come as a surprise.
The immigrant share of total hours worked rose from 9. How is it possible that economists have been unable to find more evidence of adverse effects on native workers? An important thing to keep in mind is that the labor force is growing all the time. All else equal, more people, including more foreigners, do not mean lower wages or higher unemployment. If they did, every time a baby was born or a new graduate entered the labor force, they would hurt existing workers. But new workers do not just have supply-side impacts, they also affect demand.
Those new graduates buy food and cars and pay rent. In other words, while new workers add to the supply of labor, they also consume goods and services, creating more jobs. An economy with more people does not mean lower wages and higher unemployment, it is simply a bigger economy. However, a large influx of a particular type of worker has the potential to have a negative impact on the wages of existing workers who are also of that type; workers who are highly substitutable for new immigrants stand to lose when there is a large influx of new immigrants.
The immigrant share of total hours worked by workers with less than a high school education rose from How is it that this has not caused large negative effects on native-born workers with less than a high school education? There are two factors that largely shelter native-born workers with less than a high school education from these negative impacts. The first is their relatively high degree of substitutability with workers with a high school education. While these two types of workers are likely not perfect substitutes, the fact that their substitutability is relatively high means that the impact of an influx of less-than-high-school immigrants is not shouldered entirely by the 9.
This greatly reduces the impact on the least-educated American workers. In other words, substituting immigrant workers for native workers who have the same level of education and experience is possible, but limited due to the different characteristics of these two types of workers, including fluency in English. The workers who are the most substitutable for new immigrants are earlier immigrants, so this is the group that ends up shouldering much of the impact of new immigration, rather than native-born workers. There are a few limitations of the research presented in this paper that are important to mention.
First, this analysis looks at the effect of immigration on wages, not on employment. However, the limited effect we find of immigration on native wages suggests there is also likely a limited effect on native employment. Second, the approach used here does not allow for a separate estimation of the effect of immigration on different racial and ethnic subgroups by education level. While the empirical challenges are nontrivial, further research into the effect of immigration on non-Hispanic black U. Third, we are only able to look at the relative effect on native wages of increases in foreign-born workers.
If a foreign-born worker is not a naturalized citizen, it is impossible to determine with our data whether he or she is a permanent resident, temporary visa-holder, refugee, or undocumented worker. This unfortunately limits the policy-relevance of the research presented here, since we are unable to determine the effect of various subgroups of foreign-born workers on native labor market outcomes. Better data are needed to further investigate the effect of different types of foreign-born workers, in particular unauthorized immigrants and temporary visa holders.
Finally, this paper estimates the long-run effect of immigration on wages, assuming the economy has fully adjusted to absorb new immigrants and that the overall real wage effect of immigration is zero. It is important to note that, since it takes time for capital to adjust to increases in the labor force, a large unexpected increase in the labor force will likely depress wages temporarily, something not accounted for here. Ottaviano and Peri find, for example, a 0. Except perhaps for male U. Instead, it has generally had modest positive effects.
Declining job quality for the least-educated American workers is due to a host of factors aside from immigration, including declining unionization rates, the eroding real value of the minimum wage, and trade practices that expose U. While it remains crucial to reform our broken immigration system, a larger economic agenda that will spur growth, reduce economic insecurity, and provide broadly shared prosperity is more central to improving their economic status.
We also thank Anna Turner for excellent research assistance. The statements made and views expressed are solely the responsibility of the author. The data used are from the March supplement to the Current Population Survey, which asks detailed demographic and labor market questions about the previous year. We are using March supplement data because with these data we can compute the total hours worked in a year for each worker, which offers the most comprehensive measure of labor supply.
Note that these data do not distinguish between documented and undocumented immigrants; survey respondents are not questioned about their legal status. While undocumented immigrants are included in the survey sample, it is widely considered likely that there is higher survey non-response among undocumented immigrants than among others in the sample. In any event, we are u nable to distinguish between the effects of documented and undocumented immigrant flows on native workers.
When calculating average weekly wages, we further restrict the sample to people who report positive annual wage and salary income. To compute average weekly wages, we divide annual wage and salary income by weeks worked in a year, and calculate a mean weighted by the CPS person weight times annual hours in order to properly account for varying hours worked across workers. We compute the effect of immigration on wages using an approach outlined in Ottaviano and Peri , in which they simulate the impact of immigration on wages based on a production function structure which combines workers of different education and experience levels.
Let wDbkjt be the average weekly wage of native workers in main education group b , education subgroup k , experience group j , at time t , and similarly, let wFbkjt be the average weekly wage of immigrant workers in main education group b , education subgroup k , experience group j , at time t. Let sFbkjt be the share of total wages both immigrant and native in year t paid to immigrant workers in main education group b , education subgroup k , and experience group j.
Let sbkjt be the share of total wages in year t paid to workers in main education group b , education subgroup k , and experience group j. The percentage change in the wages of native worker with education level k and experience level j due to immigration is given by equation 25 in Ottaviano and Peri Assuming long run effects i.
Similarly, the percentage change in the wages of immigrant worker with education level k and experience level j due to immigration, assuming long run effects, is given by. All of the wage and hours terms in the above equations are calculated using CPS data as described in Appendix A. The different sets of elasticities we use, presented in Table B1 , are taken from the literature see Ottaviano and Peri and Card for detailed discussions. The intuition behind this methodology is the following: if an increase in the labor supply of group A relative to group B leads to very little decline in the wage of group A relative to group B, then the two groups are highly substitutable, and the elasticity of substitution between them is high.
Conversely, if an increase in the labor supply of group A relative to group B leads to a large decline in the wage of group A relative to group B, then the two groups are not good substitutes, and the elasticity of substitution between them is low. For the aggregations by race, we weight using wage shares by race. To compute breakdowns of wage impacts by gender, we use the elasticities in Table B1 but calculate all other components separately by gender. Finally, to compute breakdowns of wage impacts for the four high-immigration states, we use the elasticities in Table B1 but calculate all other components separately by state.
The finding that high school graduates and high school dropouts are close substitutes is a new historical phenomenon. It was not true in the first half of the 20th century, when there was, instead, a big divide in production between high school graduates and those without a high school degree. Borjas, George. The economics of immigration. Journal of Economic Literature. The labor demand curve is downward sloping: reexamining the impact of immigration on the labor market.
Quarterly Journal of Economics. Native internal migration and the labor market impact of immigration. Journal of Human Resources. Borjas, George and Lawrence Katz. The evolution of the Mexican-born workforce in the United States. In Borjas, George, ed. Cambridge, Mass. How much do immigration and trade affect labor market outcomes?
Brookings Papers on Economic Activity Card, David. The impact of the Mariel Boatlift on the Miami labor market. Industrial and Labor Relation Review. Immigrant inflows, native outflows and the local labor market impacts of higher immigration. Journal of Labor Economics. Card, David, and John DiNardo.
Working Papers & Publications
Immigration and inequality. American Economic Review. Friedberg, Rachel, and Jennifer Hunt. The impact of immigrants on host country wages, employment and growth. Journal of Economic Perspectives. Friedberg, Rachel. The impact of mass migration on the Israeli labor market. Goldin, Claudia, and Lawrence F. The Race Between Education and Technology. Katz, Larry, and Kevin Murphy. Changes in relative wages supply and demand factors. A meta-analytic assessment of the effect of immigration on wages. Journal of Economic Surveys. Bonn, Germany.
Marshall, Ray. Washington, D. P83 Rueben, Kim and Sarah Gault. State and Local Fiscal Effects of Immigration.
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Urban Institute, June R84 Fiscal Policy Institute, January U6 K35 Kochhar, Rakesh. A5 K63 National Employment Law Project, Morse, Ann. M Yearbook of Immigration Statistics. REF JV Kaul, Greta. Hine, Steve and Cameron Macht. Brodey, Sam. Magan, Christopher and Tad Vezner.
Cooney, Tony. Montlake, Simon. Shah, Allie. Preston, Julia. Yang, Nancy. Hirsi, Ibrahim. Beal, Dave. State Policy Reports , Vol. Minnesota Economic Trends , September Guntzel, Jeff Severns. Supreme Court Debates , Vol. Johnson, Fawn. Cameron, Linda A. Hoyt, Joshua. Salisbury, Bill. Paul Pioneer Press , December 16, , p. Sweeney, Patrick. Paul Pioneer Press , December 9, , p. For additional reports at the Legislative Reference Library, use this Library catalog search: Immigration.
Menu House Minnesota House of Representatives. Minnesota Senate. Joint Departments, Offices, and Commissions. Schedules, Calendars, and Legislative Business. Legislative Committees. Statutes, Laws, and Rules. Search Legislature. Minnesota Legislative Reference Library. LRL Menu. Step by Step Resources. Legislative History There may be additional statutes and rules that are not listed here. A1 A45 Allen, Ryan. U62 M Blau, Francine D. Z9 C58 Chun, Randall. M6 S56 Corrie, Bruce. C67 Economic Impact of Immigrants.
Immigration to the United States
U6 E93 Fennelly, Katherine. U5 F57 Hopkins, Nathan. I47 Johnson, Ryan et al. P83 Rueben, Kim and Sarah Gault. U6 K35 Kochhar, Rakesh. M Yearbook of Immigration Statistics. S8 Significant Articles articles in reverse chronological order Kaul, Greta. Significant Internet Resources Minnesota Becoming Minnesotan: Stories of Recent Immigrants and Refugees - This Minnesota Historical Society Website presents excerpts from oral history interviews with recent MN immigrants, along with supporting information about each narrator, the communities, and immigration in general, in a format designed to be of greatest use to teachers and students in grades Green Card Voices - This Minneapolis-based nonprofit aims to foster understanding of the immigrant experience through digital storytelling.
Citizenship and Immigration Services - A division of the U.