DP2024-01

Does the Restriction Policy ofHigh-skill Immigrants Benefit
N a t i v e Wo r k e r s ?
T a k u m a S U G I YA M A

February 2, 2024

Does the restriction policy of high-skill immigrants
benefit native workers?†
Takuma Sugiyama‡§

Abstract
To protect native workers, discussions on immigration restrictions have emerged.
However, limited studies have analyzed the economic impact of such restrictions on
native workers. Past literature demonstrated a small effect of immigration restrictions
on the labor outcomes of native workers, attributing it to capital substitution. Notably,
this analysis focused on restrictions on low-skilled immigrants. Past literature oftheoretical analysis highlighted that labor scarcity affects labor outcomes differently
based on the substitutability of labor and capital. Anticipating a distinct impact,
this paper examined the restriction of skilled immigrants exploiting the H-1B visa
restrictions after 2004. The analysis, using triple differences estimation, revealed
a significantly positive impact on labor outcomes of natives. Additionally, the visa
restrictions positively impacted capital accumulation. These results suggest that the
shortage of skilled labor supply induced capital accumulation. Nevertheless, capital
investment could not fully adjust to the lack of labor supply, resulting in improved
labor outcomes for natives.
Keywords: Immigration; Labor Economics; Labor Policy; Technological Change
JEL classification: J15; J18; J22; J31; J44; J61; O33† We thank Fumio Ohtake, Masaru Sasaki, Katsuya Takii, and the Asian and Australian Society of Labour

Economics 2022 Conference for their helpful comments and suggestions. This work was supported by JST
SPRING grant number JPMJSP2138.
‡ Research Institute for Economics and Business Administration, Kobe University Email:taku625rieb.kobe-u.ac.jp§ Graduate School of Economics, Osaka University.

11

Introduction

Immigrant influx has risen annually, potentially impacting native labor outcomes. Consequently, many countries are deliberating on immigrant restrictions to safeguard native
workers. Notably, the U.S. restricts skilled immigrants’ H-1B work visas for this purpose.
The U.K. government has a manifesto aimed at decreasing immigrant influx.
These restriction policies aim to protect the native workers, several studies revealed
that the immigrant influx negatively impacts the native labor outcomes. Numerous studies,through empirical analysis, have demonstrated that the labor supply shocks from immigration lead to a decrease in wages and employment rates (Borjas, 2003; Dustmann et al.,2017; Borjas, 2017). Moreover, the skill level of immigrants determines the substitution
between natives and immigrants and the effect of the labor supply shock (Ottaviano andPeri, 2012).
This restriction aims to eliminate labor supply shocks from immigration, anticipating
an increase in wages and employment rates for native workers. However, existing researchsuggests that these restrictions may not lead to improved labor outcomes. Clemens et al.
(2018) revealed that immigrant restrictions do not enhance native labor outcomes whenlabor scarcity induces capital investment, based on empirical analysis. Acemoglu (2010)
supported this by theoretical analysis, demonstrating that labor scarcity triggers endogenous capital investment. This result indicates that the restriction policy faults the protectionof the native workers. Nevertheless, this analysis targets agricultural immigrants. The
impact of restrictions on skilled immigrants is not revealed. Abramitzky et al. (2023) also
estimated the impact of immigrant restriction by exploiting the quota restriction in the
1920s in the United States, and they showed the restriction-induced capital intensive.
Clemens et al. (2018) lacked variation in immigrants’ skill levels and occupations
owing to the focus on Mexican seasonal farmworkers through the bracero exclusion.
Therefore, it cannot reveal the impact of restrictions on skilled and other industries. This
study addresses the gap by exploring how restrictions on skilled immigrants impact nativelabor outcomes. Acemoglu (2010) demonstrated that labor scarcity induces endogenous
technical advancement only if labor and capital are substitutable. Hence, the characteristics
of immigrants may determine the impact of restriction policies. This study empiricallyanalyzes the impact of restricting skilled immigrants.
Theoretical predictions regarding the impact on native labor outcomes are ambiguous.
When the demand for skilled natives is downward, visa restrictions enhance the nativelabor outcomes. However, in the presence of endogenous technological advances, wherelabor demand is upward or flat, the lack of skilled labor supply may not improve nativelabor outcomes. This study aims to estimate whether the effect is adequate by exploiting
the restriction of the H-1B visa restriction.
2

This study exploited H-1B visa restrictions to assess the impact of restricting skilled
immigrants on native labor outcomes. The U.S. restricts the cap of H-1B visas for skilled
immigrants to protect native workers, reducing the annual quota from 195,000 to 65,000
in fiscal year 2004.
This study compares native labor outcomes before 2003 and after 2004, consideringfor-profit and non-profit research institutions to estimate the impact of H-1B restriction.
The estimators are interpreted as the Triple Differences estimators.
This study has three key contributions.
First, this paper demonstrates the impact of restrictions on skilled immigrants, including labor scarcity and technical change. The complex channels and ambiguous impact of
the restriction are explored, with empirical analysis revealing a positive impact on nativelabor outcomes.
Second, the study delineates the channel through capital estimation. While the restriction policy aims to protect native workers, existing research revealed that skilled
immigrants improve native labor outcomes by fostering innovation, leading to long-term
economic growth. Evaluating the policy’s adequacy requires understanding its impact onnative labor outcomes as well as short-term effects. The study reveals a positive impact on
capital accumulation owing to the restriction of skilled immigrants, suggesting that such
restrictions do not hinder long-term economic growth.
Third, the study estimates the industry’s heterogeneity. The current empirical analysis does not elucidate the relationship between technological change and labor scarcity
in various industries. This study addresses this gap in the relationship between otheroccupations and labor scarcity using the immigrant restriction, targeting many industries.
This paper is organized as follows. The first section briefly overviews the H-1B
visa and the visa restriction, while the second section describes the data utilized forthe estimation. Subsequently, the third section analyses the restriction by the Triple
Difference. Furthermore, it estimates the capital accumulation and checks the mechanism.
Conclusions are drawn in the final section.

2

BackgroundPrevious studies highlighted a positive impact on the United States. Ghosh et al. (2014)indicated that skilled immigrants foster innovation, while Kemeny and Cooke (2017)
demonstrated that skilled immigrants enhance diversity, positively impacting individuals’
annual income. Skilled immigrants contribute to cognitive mobility, known for its positiveeffect (Borjas and Doran, 2015; Ganguli, 2015). Conversely, Fougère and Rainville. (2011)
simulated skilled immigrants’ impact using Canadian data, revealing a potential reduction3

in skilled native labor outcomes. Therefore, restriction policies may mitigate these labor
supply shocks, potentially improving labor outcomes.
In the U.S., the H-1B visa program permits skilled immigrants to enter the labormarket. Skilled immigrants can be employed for as long as three years and can extend
their stay up to six years. An immigrant must meet one of these criteria: 1. Possess a
degree higher than the United States baccalaureate or foreign equivalent; 2. Hold any
required licenses or official permissions for the occupation; 3. Have the equivalent of
the required degree for the specialty occupation acquired through education, training, andexperience. Occupations include computer system analysis and programmers, physicians,
and accounting (Citizenship and Services, 2008). The H-1B application and approval
process is as follows. Employers can submit applications to the Labor Department up tomonths before the intended employment date of the H-1B worker. The Employment andTraining Administration (ETA) approves the application within seven days if it is complete
and accurate. Subsequently, employers submit the H-1B petition with the application to
U.S. Citizenship and Immigration Services (USCIS). The employer must include information for the H-1B workers and the employer’s identification number on the application.
If the position requires the skills petitioned for, and the nonimmigrant possesses the necessary qualifications, USCIS adjudicates and approves the petition. Outside the U.S., theH-1B nonimmigrant applies to the Department of State for a visa, and upon arrival, theDepartment of State issues an H-1B visa for admission at the port of entry. Employers offer
benefits on par with those provided to the U.S. workers. They are required to pay either
the local prevailing wage or the employer’s actual wage (Office, 2006). Typically, H-1B
approvals are for Science, Technology, Engineering, and Mathematics (STEM) workers.
In 2003, 28 % worked in the Computer System Design and Related Services, and rising
to 36 % in 2004 (Citizenship and Services, 2008).
The economic impact of the H-1B program on the U.S. has garnered attention. Kerret al. (2015) demonstrated that H-1B workers increased the employment of native workers
from 1995 to 2008. Kerr and Lincoln (2010) highlighted an increase in the number ofscience and engineering workers among immigrants and patients in the U.S. owing to the
H-1B program.
The U.S. restricts H-1B visas for skilled immigrants to protect native workers. The
annual cap decreased from 195,000 to 65,000 in the fiscal year (FY) 2004. Notably, therestriction does not apply to colleges, universities, and non-profit research institutions.
Figure 1 illustrates the annual cap changes.
The restriction impacted the labor supply of skilled immigrants. Mayda et al. (2018)
showed that this H-1B visa restriction reduces the new hiring of new H-1B workers
in for-profit firms using triple difference estimation. The merit of this restriction on

4

Figure 1: Source: American Immigration Council.
studying skilled immigrants affect all occupations without non-profit research institutions.
Mayda et al. (2018) showed that the H-1B visa restriction reduced new H-1B hiring by
18-14 %. Sparber (2019) estimated the substitution between new H-1B workers andestablished H-1B workers. Foreign students often study in American undergraduate
education to be employed in the U.S. H-1B visa is one of the gateways to employment
in the United States(Kato and Sparber, 2013). Therefore, the H-1B restriction indirectlyreduced immigrant workers by this channel.
Restricting skilled immigrants carries significant implications. Existing research indicates that immigration-induced labor supply shock led to reduced wages and employment
rates (Borjas, 2003; Dustmann et al., 2017; Borjas, 2017). Conversely, the H-1B visa
restriction shifted the labor supply curve toward the leftward, anticipating an increase inwages and employment rates, given a downward-sloping labor supply curve. However,these restrictions may not improve the wages and employment rates if the positive spilloverof skilled immigrants is absent or if the labor supply is flat or upward, as technologicaladvances adjust to the shortage of labor supply(Acemoglu, 2010; Clemens et al., 2018).
This study exploited skilled immigrant restriction to estimate its impact. First, itestimated the impact of the restriction on wages and the employment rate of native workers
to clarify its impact on the labor outcomes of native workers. Second, the study analyzed
the impact of capital accumulation to distinguish channels. If the restriction negatively
impacts the wages and employment of native workers, the study cannot distinguish between
positive spillover, cognitive mobility, or technical advancement. If positive spillover
dominates, it is expected that the restriction does not affect capital accumulation. If
cognitive mobility dominates, the restriction is expected to reduce capital accumulation.
If technical advance dominates, the restriction is expected to increase capital accumulation.
5

3

Data and Empirical Strategy

This study utilizes the American Community Survey (ACS) data spanning 2001 – 2008 to
estimate the impact on wages and employment rate of native workers(Steven Ruggles andSobek, 2020). The ACS provides individual-level data on employment status, wages, andcitizenship status.
The study restricts the sample age to 18 – 64 years for the analysis of economic
impacts on the labor outcomes of natives, excluding individuals with military service orschooling. Native and immigrant individuals are distinguished based on their citizenshipstatus. Immigrants are defined as non-citizens or naturalized U.S. citizens.
Moreover, this study aggregates individual data to skill cell-industry-state level data
as follows. Individuals are grouped based on their education data. I divide the individual
into four education groups by their education: high school graduate (with less than 12
years of completed schooling), high school graduate (with 12 years of schooling), somecollege graduate (with between 13 and 15 years of schooling), and college graduate (withat least 16 years of schooling). Subsequently, the study categorizes individuals into 13
industries using IND1990 to create cell-industry-state data for each education level.1
To evaluate the impact of the restriction on capital accumulation, this study employs
the Yes-capital data (El-Shagi and Yamarik, 2019). This dataset computes state-by-state
private capital stock, serving as the source for capital stock data in the study’s analysis.
The Yes-capital data operate at the state-level. Subsequently, the study converts the datautilized in the main estimation into state-level data. The state-level immigrant rate is thencomputed as the mean value of the treated industry in the empirical analysis of the capital
investment.
Owing to the potential upward bias from reverse causality when using the immigrant
rate in the same calendar year(Smith, 2012), this study addresses this by using the immigrant rate in 2000 as the immigrant intensity of the cell. It excludes samples that do notinclude individuals in the cell in 2000. The immigrant ratio 𝑝𝑖, 𝑗,2000 is calculated in a cellgroup and skill cell-state 𝑖, industry 𝑗, in 2000. 𝑝𝑖, 𝑗,2000 = 𝐼𝑖, 𝑗,2000 /(𝑁𝑖, 𝑗,2000 + 𝐼𝑖, 𝑗,2000 ).
Table 1 provides summary statistics for state-cell level characteristics. Table 1 indicatesthat the immigrant rate in 2000 was approximately 9 %, with an average capital stock of $297 million.
This study utilizes the immigrant rate in 2000 as the variation in restriction levels for
its estimation, assuming that cells with a high immigrant rate in 2000 were more impacted
1The following 13 industries include the following: 1. Agriculture, Forestry, and Fisheries; 2. Mining;
3. Manufacturing; 4. Transportation, Communications, and Other public utilities; 5. Wholesale trade ofdurable goods; 6. Wholesale trade of nondurable goods; 7.Retail trade; 8. Finance, Insurance, and realestate; 9. Business and repair services; 10. Personal services: 11. Entertainment and recreation services;
12. Professional and related services; and 13. Public administration.

6

Table 1: Descriptive statistics
StatisticN

Employment
Weekly wage
Immigrant rate
Treat
High Intensive

22,89020,25922,89022,89022,890CapitalPost
Immigrany rate
Immigrany rate high intensive

408
408
408
408

Mean

St. Dev.

Labor variable:−0.238
0.178
6.410
0.518
0.093
0.145
0.140
0.347
0.476
0.499
Capital variable:
297.094 362.157
0.625
0.485
0.098
0.078
0.112
0.090

Min

Max

−2.079
3.030
0.000
0
0

0.000
9.582
1.000
1
1

23.091
0
0.005
0.003

2,464.009
1
0.376
0.406

Source: Labor American Community Survey conducted by IPUMS and the Yes-capital
data. The sample is native individuals, age 18–65, and in the labor force. The outcome
variables are the logarithm of the weekly wage and the logarithm of the employment rate.
The unit of Capital is a million dollars.
by the restriction after 2004. To assess the validity of this assumption, this study examined
the relationship between the change in the immigrant rate after 2004 and the rate in 2000
in the restricted cell. Figure 2 illustrates a downward relationship between the change in
the immigrant rate and the rate in 2000. This plot suggests that cells with a high immigrant
rate in 2000 decreased after 2004 owing to the restriction of the H-1B visa.
The H-1 B applicant rate for individuals with less than a Bachelor’s degree is approximately 2%. The study employed the triple-difference estimation as follows: considering
cells with less than a Bachelor’s degree as the control group, this study estimated thefollowing equation to explore the impact of restriction on the wages and employment of
native workers:
𝑦𝑖, 𝑗,𝑒,𝑡 = 𝛽 × 𝑝𝑖, 𝑗,𝑒,2000 × 1′𝑖, 𝑗,𝑒,𝑡 + 𝜃 𝑖 𝑗 𝑒 + 𝜃 𝑡 + 𝜖𝑖, 𝑗,𝑒,𝑡 ,(1)where 1′𝑖, 𝑗,𝑒,𝑡 is indicator function that equals one when the education level 𝑒 is higher thana Bachelor’s degree in an H-1B restricted industry, and after 2004. 𝑦𝑖, 𝑗,𝑒,𝑡 represents laboroutcomes (the mean log of weekly wage or employment rate). Under the parallel trend
assumption, this estimator is interpreted as the continuous DiD estimation. 𝜃 𝑖 𝑗𝑟 and 𝜃 𝑡represents fixed effects for cell group, state 𝑖, education level, and industry 𝑗, calendar
year 𝑡, respectively. This estimation only considers the labor substitution between native
workers and immigrants in the same education level and industry (Ottaviano and Peri,
7

Figure 2: Source: American Comunirty Survey conducted by
IPUMS. The sample comprises native individuals aged 18–65
year in the labor force. The point demonstrates the relationshipbetween the change in immigrant rate after 2004 and the rate
in 2000 in the restricted cell, specifically focusing on individuals with education levels of more than a college degree andexcluding those in the education or public industry.

8

2012).
When the labor demand curve is downward, the immigrant influx reduces the natives’labor outcome. Conversely, the immigrant restriction raised the labor outcomes of natives.
In this case, 𝛽 in equation (1) is positive. However, theoretical models incorporating
technological change may induce a flat-labor demand, wherein the restriction does notincrease native wages. Therefore, the theoretical analyses render it ambiguous whether 𝛽
in equation (1) is positive or negative from the theoretical analyses. The study estimated𝛽 using the triple differences method and interpreted it as the impact of the restriction on
the labor outcomes of natives.

4

Results

In this section, the study estimates H-1B visa restrictions on both labor outcomes andcapital accumulation. Firstly, I estimated the impact of restrictions on wages and theemployment rate of native workers. Secondly, I test the impact of the restriction on capital
accumulation. Finally, I test the robustness of the announcement effect and industrial
heterogeneity.
First, this study empirically analyzed the impact of immigrant restrictions on the laboroutcomes of native workers. Table 2 presents the results for Equation (1). The estimation
indicates a positive effect beyond the immigration inflow. Standard errors, clusteredby state and education level, accompany the results. The third row corresponds to theparameter of interested 𝛽 in Equation (1).

Column 1 demonstrates the impact of the H-1B restriction on weekly wages, with 𝛽
at 0.649, which is 1% significant. Column 2 illustrates the impact on the employment
rate, with a value of 𝛽 of 0.125, which is 1% significant. The estimation results revealed
that the restriction protected the native workers and increased the labor outcomes. The
results differ from the estimated results of Clemens et al. (2018), and this difference
merges from the substitutability of skilled immigrant and capital (Acemoglu, 2010). Chen
(2015) found that restrictions of skilled immigrants increased the literacy of immigrants,suggesting heightened substitutability after the restrictions. However, the impact on laboroutcomes was predominantly influenced by the negative supply shock.
Based on Borjas (2003); Aydemir and Borjas (2007); Edo and Rapoport (2019), thestudy calculates the elasticity of substitution by the equation (1 − 𝑝𝑖𝑡 ) × 𝛽, where 𝛽 denotes
a total impact of the immigrant influx on the wage of natives. From Column 2 of Table
2, the total impact in treatment groups is obtained as 𝛽 = 0.649 by parameters of 𝑝𝑖𝑡
9Table 2: The result of the OLS Regression
Dependent variable:
Weekly wage

Employment

(1)

(2)

Treat

0.564∗∗∗(0.022)0.167∗∗∗(0.007)

Immigrant rate × Treat

0.649∗∗∗(0.203)0.125∗∗(0.054)

20,259
0.266
0.158
∗∗∗
3,195.084 (df = 2; 17668)

22,8900.112−0.001
1,285.907∗∗∗ (df = 2; 20299)

Observations
R2
Adjusted R2
F Statistic∗ p<0.1; ∗∗ p<0.05; ∗∗∗ p<0.01
Note:
Source: American Comunirty Survey conducted by IPUMS. The sample is native individuals, age 18–65, and in the labor force. The outcome variable is the logarithm of theweekly wage and the logarithm of employment rate. All regressions include state, industry,and education-fixed effect and year-fixed effect. Standard errors clustered by state.

(first row) and 𝑝𝑖𝑡 × 1. The wage elasticity from the average immigrant in each skill cell,
denoted as 𝑝 = 0.093, is calculated as (1 − 𝑝) 2 × 𝛽 ≃ 0.82 × 0.649 ≃ 0.534. This indicatesthat a 10 % increase in the number of immigrants in a specific state-skill group in 2000
is associated with a 5.34 % increase in the weekly wage of native workers in the samegroup. Additionally, the employment elasticity regarding immigrants is approximately
0.10%. The elasticity regarding immigrants in the pre-period is positive for both weekly
wages and employment rates.
Next, the study conducts an event study to identify the impact of immigration restrictions on native labor outcomes over time and to test the parallel trend assumption. If theparallel trend assumption is violated, the estimation results are biased.
The study estimates the following equation:
𝑦𝑖, 𝑗,𝑡 =∑︁𝛽𝑡 × 𝑝𝑖, 𝑗,2000 × 1′𝑖, 𝑗,𝑡 + 𝜃 𝑖 𝑗 + 𝜃 𝑡 + 𝛾𝑖, 𝑗,𝑡 .

(2)𝑡≠2003

The figures depict the point estimates 𝛽𝑡 and 95 % confidence intervals around 𝛽𝑡 foreach year-specific coefficient. The reference year is 2003, representing the last year before
the H-1B restriction. Standard errors are clustered by education, state, and industry levels.
Figure 3 represents the event study for a weekly wage, and figure 4 shows for em10

Figure 3: Source: The American Community Survey conducted by IPUMS. The sample is native, age 18-65, and in thelabor force. The base year is 2002. The dots and bars represent
the point estimators and 95 confidence intervals. The outcome
variable is the logarithm of the weekly wage.

11

Figure 4: Source: The American Community Survey conducted by IPUMS. The sample is native, age 18-65, and in thelabor force. The base year is 2002. The dots and bars represent
the point estimators and 95 confidence intervals. The outcome
variable is the logarithm of the employment rate.

12

ployment rate. In both figures 3 and 4, the parameters in 2001 and 2002 are significantly
positive. Therefore, the estimation results in Table 2 may represents a lower bound. Whileacknowledging potential bias in the main estimation, the results consistently show a positive trend, and the interpretation of the estimation results remains unchanged. Thesefindings indicate that the restriction on immigrants positively impacted the native laboroutcomes in 2004, and this positive effect persisted from 2004-2008. These results alignwith the outcomes observed in the Triple Difference estimation. The positive effects wereboth immediate and sustained, extending through the year 2008.
Next, the study explores the impact of restriction on capital to analyze its mechanism
on labor outcomes. In the presence of substitutability between labor and capital, Acemoglu(2010) demonstrates that labor promotes capital substitution with a theoretical framework.
To investigate whether restrictions on H-1B visa caps drive this capital substitution, thestudy examines data on the amount of capital per state. Conversely, restrictions may
impede innovation and hinder capital accumulation(Ghosh et al., 2014; Borjas and Doran,
2015; Ganguli, 2015; Kerr and Lincoln, 2010). The study aims to estimate the impact ofskilled immigrant restrictions on capital accumulation.
Owing to the data limitation, the yes-capital data only provides state-level data. Therefore, the study computes the immigration rate in the treated occupation in 2000 𝑝𝑖,𝑜𝑐𝑐,2000 ,and conducts the DiD estimation as follows estimation equation.
𝑦𝑖,𝑡 = 𝛽 × 𝑝𝑖,𝑜𝑐𝑐,2000 × 1′𝑖,𝑡 + 𝜃 𝑖 + 𝜃 𝑡 + 𝜖𝑖, 𝑗,𝑡(3)

where 1′𝑖,𝑡 denotes an indicator function considering one calendar year is after 2004.
Table 3: The result of the OLS Regression(capital)
Dependent variable:
Capital
681.452∗∗(299.190)

Immigrant rate × Post

Observations
R2
Adjusted R2
F Statistic

408
0.213
0.082
94.509∗∗∗ (df = 1; 349)

∗ p<0.1; ∗∗ p<0.05; ∗∗∗ p<0.01
Note:
Source: Yes-capital data. All regressions include state and year-fixed effect. Standard
errors clustered by state. The unit of Capital is a million dollars.

13

Figure 5: Source: Yes-capital data. The base year is 2002. The
dots and bars represent the point estimators and 95 confidence
intervals. The unit of Capital is a million dollars.

Table 3 represents the estimation results of Equation (3). The parameter 𝛽 is positive(681) and significant at the 1 % level. This result indicates that a more restricted state
accumulated capital, aligning with findings in Clemens et al. (2018). The point estimatorindicates that a 1% increase in 2000 led to a $ 6.81 million increase in capital stock after
the restriction.
Following this, the study conducts an event study to identify the temporal impact ofimmigration restrictions on capital investment.
The study estimates the following equation:
𝑦𝑖,𝑡 =∑︁𝛽𝑡 × 𝑝𝑖,𝑜𝑐𝑐,2000 × 1′𝑖,𝑡 + 𝜃 𝑖 + 𝜃 𝑡 + 𝛾𝑖,𝑡 .

(4)𝑡≠2003,where 𝑦𝑖,𝑡 means the value of investment in state 𝑖 and calendar year 𝑡.
Figure 5 shows the result of the event study. These figures plot the point estimates 𝛽𝑡
and 95 % confidence interval around 𝛽𝑡 for each year-specific coefficient. The reference
year is 2003. Standard errors are clustered by state level.
14

The parameters of 𝛽𝑡 in Equation 4 before 2004 are not significantly different fromzero, indicating the validity of the parallel trend assumption in capital estimation. Afterthe restriction, the parameters of 𝛽𝑡 in Equation 4 exhibit a consistent and increasing trendwith the increase growing each year. These findings are similar to the primary estimationof employment.
While the empirical analysis of the study focuses on short-term impacts, the results
suggest that immigrant restrictions fostered capital accumulation, akin to the impact observed with the farm-workers restriction. However, capital accumulation may not fullycompensate for the lack of skilled workers. However, the restriction elevated the laboroutcomes of native workers despite technological advances.
Finally, the study examines the robustness of the parallel trend assumption and its
applicability to immigrant-intensive industries. In both Figures 3 and 4, the reference
year parameter may be lower, with parameters for other years relatively higher. Thistendency could introduce an upward bias in the primary analysis results. For example,
the announcement effect led to an increase in immigration in 2003, resulting in a labor
supply shock that impacted wages and employment rates. To gauge robustness against thisupward bias, the study excludes the 2003-year sample and performs the same estimation
as in the main estimation. Moreover, this study assesses the industrial heterogeneity ofimmigrant intensity, considering the potential, considering the potential for a larger ordifferent impact in the industries with a lot of immigrant presence before the restriction.
To explore this heterogeneity, the study introduces a ℎ𝑖𝑔ℎ − 𝑖𝑛𝑑𝑢𝑠𝑡𝑟 𝑦 dummy when taking
the industry with the immigrant rate in 2000 above the median (𝑝 = 0.71).2 Table 4
represents the heterogeneous impact of the H-1B restriction.

Table 4 reports the results of these robustness checks. Columns 1 and 2 represent therobustness of the announcement effect, while Columns 3 and 4 illustrate the heterogeneityof the immigrant-intensive industries. Columns 1 and 2 represent that the parametervalue is lower than those in Table 2. However, the point estimators for weekly wages are
positive (0.37) and statistically significant at the 5% level. While the point estimator for theemployment rate is not significant, but remains positive. Notably, the main analysis results
may have an upward bias owing to the announcement effect. However, the positive impacts
on the labor outcomes of native workers persist robustly against this bias, particularly inthe case of wage impact.
2Immigrant-intensive industries, defined using the IND1990 variable provided by the ACS manufacturing, whole trade of durable goods, whole trade of nondurable goods, retail trade, business and repair
services, and personal services.

15

Table 4: The result of the OLS Regression(Triple-difference and ommit)
Dependent variable:
Drop 2003 samples
Immigrant-intensive Industries
Weekly wage

Employment

Weekly wage

Employment

0.522∗∗∗

0.149∗∗∗

0.486∗∗∗(0.021)(0.007)(0.031)0.155∗∗∗(0.011)0.370∗∗(0.183)0.044(0.051)Treat×Immigrant rate

0.676∗(0.345)0.093(0.073)Treat×High Intensive

0.153∗∗∗(0.043)0.024(0.015)−0.232(0.424)0.020(0.105)

20,2590.269
0.161
1,623.160∗∗∗(df = 4; 17666)

22,8900.113−0.0003646.379∗∗∗(df = 4; 20297)

Treat

Treat × Immigrant rate

Treat×Immigrant rate
×High Intensive

Observations
R2
Adjusted R2
F Statistic

17,7360.226
0.110
2,254.907∗∗∗(df = 2; 15428)

20,352
0.092−0.025909.978∗∗∗(df = 2; 18043)∗ p<0.1; ∗∗ p<0.05; ∗∗∗ p<0.01
Note:
Source: American Comunirty Survey conducted by IPUMS. The sample is native individuals, aged 18–65, and in the labor force. The outcome variable is the logarithm of
the weekly wage and the logarithm of the employment rate. The samples whose calendar
year are 2003 are dropped in Column 2 and 3. The high ind takes 1 when the industry
with the immigrant rate in 2000 above median and 0 otherwise. All regressions include
state, industry, and education-fixed effect and year-fixed effect. Standard errors clusteredby state.

16

Row 3 of Table 4 represents the 𝛽 in Equation 1. The point estimates for a weekly
wage are positive and significant at the 10% level, while the employment rate is positive
but insignificant. Row 5 of Table 4 displays the heterogeneity of the effect of the H1B restriction, while the estimators are positive but not significantly different from zero.
These results suggest that the restriction impacts on the labor outcomes are homogeneousand are not different for the intensity regarding skilled immigrant workers.
Table 5: The result of the OLS Regression(capital, heterogeneity)
Dependent variable:
Capital592.772∗∗(243.856)

Immigrant rate in high intensive × Post

Observations
R2
Adjusted R2
F Statistic

408
0.213
0.082
∗∗∗
94.292 (df = 1; 349)

∗ p<0.1; ∗∗ p<0.05; ∗∗∗ p<0.01
Note:
Source: Yes-capital data. All regressions include state and year-fixed effect. Standard
errors clustered by state. The unit of Capital is a million dollars.

Next, this study assesses the impact of capital accumulation on immigrant-intensive
industries. It computes the average immigrant rate in these industries in 2000 and estimates
Equation 3. Figure 5 shows the result. Figure 5 presents the results, indicating an impactof 593.6 at a 1% level significance level. This result suggests that the restriction on skilled
immigrants also led to increased capital accumulation in immigrant-intensive industries;
however, but at a lower level than the overall impact.
In summary, the results from Table 4 and 5 indicate robust, estimation outcomes
regarding the announcement effect. Additionally, minimal to no heterogeneity is observedin the impacts across immigrant-intensive industries.

5

Conclusion

Immigration restrictions have been discussed worldwide to protect native workers. However, few studies have analyzed the economic impact of immigration restrictions on native
workers.
17

Clemens et al. (2018) demonstrates that the Mexican Bracero Exclusion does notincrease the labor outcomes of native firm workers. Nevertheless, this analysis is limited
to seasonal agricultural workers, migrants, and natives. These results are in line with
Acemoglu (2010). Acemoglu (2010) developed a theoretical framework for labor scarcity
and capital accumulation. Acemoglu (2010) concluded that labor scarcity induces capital
accumulation, and labor scarcity does not increase labor outcomes when labor and capitalare substitutes. Otherwise, labor scarcity does not cause capital accumulation when laborand capital are complementary. Therefore, native workers may be impacted differentiallyby the characteristics of the restricted immigrants (e.g., education level).
The H-1B visa is a work visa for highly educated immigrants in the United States. To
analyze restrictions on skilled immigrants, this study empirically estimated the impact of
exploiting the limit of a maximum number of H-1B visas per year.
The study conducted the Triple differences estimation. The estimation results show thatthe H-1B restriction raised the weekly wage and employment rate. Moreover, Acemoglu(2010) suggests that labor scarcity induces capital accumulation when labor and capitalare substitutes. This study employs the Yes-capital data and estimates the relationshipbetween the 2000 immigrant rate and capital acculturation. The estimation result implies
that States with a higher rate of immigrants as of 2000 have accumulated more capital.
The estimation results of labor outcomes and capital accumulation suggest that the
H-1B visa restriction fostered capital accumulation, but the accumulation does not reduce
the labor outcomes.
The study reveals that the H-1B restriction policy improved natives’ labor outcomes.
It demonstrates the restriction fostered capital investment similar to Acemoglu (2010).
These results suggest that contrary to the farm-workers restriction, capital accumulation
could not fully adjust the impact in the case of the H-1B restriction. The results suggestthat immigrant restrictions have a different impact depending on immigrant characters,
and further empirical analyses must be studied.
Three limitations exist in this study.
First, the study only estimates the short-term impact of H-1B visa restrictions. It
reveals that the restriction of skilled immigrants fosters capital investment. This capital
investment may change product components, and this change affects the labor demand ofskilled natives in the long term.
Second, this study was limited by the supply-side change. The study analyzes thelabor demand side due to visa restrictions. However, it has not been able to analyze
the changes in demand on the firm side or the changes in output (Clemens et al., 2018).
Nevertheless, Ghosh et al. (2014) report the H-1B restriction reduced the firm’s sales. This
reduction suggests that both capital investment and output reduction could not fully adjust

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the immigrant restriction. Therefore, structural estimation and state- and industry-specificdata can be used to address this limitation.
Third, this study estimates the impact of visa restrictions on capital accumulation.
Nevertheless, owing to data limitations, the study cannot analyze heterogeneity regarding
capital characteristics. Webb (2019) demonstrates that different occupations are relevant
to robots, software, and AI. There may be a similar relationship between the industry andeach technology.

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