Substitution between Immigrant and Native Farmworkers in the United States: Does Legal Status Matter?

One of the most controversial aspects of immigration is its potential impact on the labor market opportunities for natives of the host country. In the United States, there are an estimated 11 million unauthorized immigrants,

Immigrant is defined to include both authorized immigrants (i.e., lawful permanent residents [or “green card” holders], refugees, asylees, and persons on certain temporary visas) and unauthorized immigrants (i.e., immigrants lacking proper, unexpired legal documentation to work).

Immigration has an important role in the U.S. farm sector, especially within the labor-intensive fruits and vegetables industry. Since the 1940s, U.S. farmworker demographics have shifted away from native workers

The term native is used in this study to refer to two (interrelated) legal status groups: Citizen (used in the main empirical application as the nonimmigrant group) and U.S.-born (used in the supplementary analysis in Appendix B as the nonimmigrant group). There is a subtle distinction between the definitions of U.S.-born and Citizen. U.S.-born strictly refers to a U.S. citizen by birth. Citizen is a broader category that includes both U.S. citizens by birth and naturalized citizens who used to be lawful permanent residents.

Reforming federal immigration policies with improved guest worker programs and enhanced border security measures have been a controversial point of debate, particularly within the context of the agricultural sector and farmworkers. Legislators find themselves having to balance the two opposing viewpoints. On the one hand, there are concerns from the general public that a rising immigrant population may adversely affect native workers by either driving them out of U.S. farm jobs or lowering their average hourly earnings. On the other hand, there are concerns from agricultural producers that a mass deportation or exodus of foreign-born workers will leave them with an insufficient pool of farmworkers who are willing and able to do agricultural work. The challenge for future legislative efforts to reform the current immigration policies will be to balance both of these concerns. This study aims to help decision makers by answering the following questions: (a) How does the inflow of immigrants affect the employment of native farmworkers and (b) to what extent do authorized and unauthorized immigrants compete with native farmworkers? To answer these questions, we developed and used a nested constant elasticity of substitution (CES) model of agricultural labor demand to investigate the degree of substitutability among heterogeneous groups of farmworkers separated by age, skill, and legal status. Using a three-layered nested CES structure, we estimate the elasticity of substitution among unauthorized immigrant, authorized immigrant (i.e., permanent residents and immigrants with other types of work authorization), and native (including both citizens by birth and naturalized citizens) farmworkers within the same skill and age group, the elasticity of substitution across different age groups within the same skill group, and the elasticity of substitution among workers from different skill groups. We use the NAWS data from 1989 through 2012 for the empirical analysis. Although there are other data sources for farm labor employment and wages (namely, Farm Labor Survey [FLS], Current Population Survey [CPS], and Quarterly Census of Employment and wages [QCEW]), NAWS is the only national data source tracking legal immigration status of farmworkers.

This article contributes to the literature on the impact of migration on the U.S. agricultural labor markets in three ways. First, to our knowledge, this is the first study to quantify the substitutability of farmworkers with different legal status backgrounds. Second, by differentiating between authorized and unauthorized status of immigrant workers, the study fills the research gap in the empirical labor economics literature where immigrants are typically treated as one group. Third, because the agricultural sector has a distinct definition of “skill” compared to other less-skilled labor sectors, the study proposes two proxies alternative to formal education to measure the skill in agriculture: the number of years in agricultural work and the type of farmwork tasks performed. This is because the conventional formal education measure that is widely used in the literature to proxy the skill level of workers is meaningless for the agricultural sector where most farmworkers lack any formal education beyond high school.

The main finding of the study is that native farmworkers do not compete with immigrant farmworkers who are at similar age and skill levels for the same jobs. In other words, the substitution possibilities between immigrant farmworkers (both authorized and unauthorized) and native farmworkers are limited; the elasticity of substitution between these three legal status groups is estimated to be between 2.11 and 2.2 depending on the measure of skill used in the analysis.

The rest of the article is organized as follows. Section 2 introduces the background information on immigrant workers in the U.S. farm sector. Section 3 summarizes related literature. Section 4 presents the empirical estimation strategy using the nested CES framework. Data are summarized in Section 5, and the empirical results are presented in Section 6. Section 7 offers conclusions.

Currently, more than 1 million of the 11 million unauthorized immigrants in the United States work in the agricultural sector, making up nearly half of the total U.S. farmwork force (Passel and Cohn, 2016). The U.S. Department of Agriculture, Economic Research Service (USDA-ERS) estimates that more than 50% of seasonal U.S. farmworkers in the agricultural sector are foreign-born and unauthorized to work in the country (Hertz, 2015). The U.S. Department of Labor’s (DOL) National Agricultural Worker Survey (NAWS) reports similar estimates based on farmworker interviews, and suggests that more than 50% of specialty crop workers do not possess proper documentation to work legally in the United States (ETA, 2014). Fisher and Knutson (2012) argue that the actual percentage of undocumented farmworkers is higher than 50%. Emerson and Iwai (2014) report that 68.9% of immigrants working in Florida specialty crop industries are unauthorized, while Guan et al. (2015) estimate that 80% of the labor force in the Florida strawberry industry lacks proper documentation.

The U.S. farm sector is particularly sensitive to changes in the flow of migrant workers and changes to federal immigration policies because farmers mostly rely on foreign-born workers (often with questionable legal status). Historically, Mexico has been the home country for most foreign-born farmworkers in the United States (Roka and Emerson, 2002; Martin, 2003). Immigration trends have been changing in recent years and between 2009 and 2014, more Mexican-born immigrants exited than entered the United States. Worker demographics and economic growth in Mexico are two major reasons for the changes in immigration flows (Gonzalez-Barrera, 2015). Another reason behind the deceleration in Mexican immigration in the U.S. farm sector is the enhanced border enforcement efforts and the growing national debate over comprehensive immigration reform within the United States. For more than 15 years, the U.S. Congress has been embroiled in heated political debates, with a significant number of its members calling for building walls on the Mexican–U.S. border and mass deportation of unauthorized immigrants. However, recent efforts to pass legislation to reform immigration have all failed.

There is a large literature examining the effect of immigration on the nonfarm labor markets. These studies do not provide any consensus on the outcomes of native workers in host countries in terms of both magnitude and direction of the effects. For example, Borjas (2003) argues that immigration to the United States from 1980 to 2000 has depressed wages of competing workers by 3–4%. Dustmann et al. (2017) show that an inflow of Czech immigration workers leads to a moderate decline in local wages and a sharp decline in local employment for German native workers. Lewis (2005) finds that the wage effects are smaller when the analysis focuses on local rather than nationwide effects. Card (2009) concludes that immigration has had a very small effect on wage inequality among natives in the United States. Simulating the change of supply economy using a 14-sector nested computable general equilibrium (CGE) model, Watson et al. (2012) found that a reduction of the less-educated immigrant labor supply will only modestly increase the demand for less-educated native workers, while causing a reduction in the state gross domestic product (GDP) as well as the total economic output in Idaho. Cattaneo et al. (2013) found similar evidence in European countries that the inflow of immigrants over the period of 1995 through 2001 is not associated with an increase in the probability of natives being unemployed. Ottaviano and Peri (2006) argue that wage effects may even turn positive if imperfect substitutability between immigrant and native workers is taken into account. An analysis by Chassamboulli and Peri (2015) show that restricting unauthorized immigrants through increasing deportation rates or tightening border control actually raises the unemployment rate of U.S. domestic workers and weakens the U.S. domestic labor market.

The aforementioned studies analyze the impact of immigration on nonagricultural labor markets. Further, they look at immigrants as a whole rather than distinguishing between legal status groups within the broad category of immigrants. Labor studies using secondary data seldom consider immigrants’ legal status in analyses, partially because legal status is sensitive information and often not revealed in public data. The farm sector is unique in this respect. The large presence of unauthorized immigrants in the farm sector prompted the U.S. DOL to initiate the NAWS after the enactment of IRCA to estimate the size of the immigrant farm-worker population as well as their legal status. Understanding the role of legal status on farm-worker employment and wages is important for immigration policy debates (Passel, 2006; Caponi and Plesca, 2014). After a few studies published in the early 1990s about the impact of IRCA on agricultural production and labor supply (e.g., Duffield and Coltrane, 1992; Gunter et al., 1992), there has been a renewed interest in analyzing the impact of immigration policies on labor market outcomes for hired farm labor (Pena, 2010; Zahniser et al., 2012; Hertz, 2015). Pena (2010) compares earnings of authorized and unauthorized immigrant farmworkers using NAWS data between 1989 and 2006, and finds that unauthorized immigrants make 5–6% less on average than their authorized immigrant counterparts. Using the CGE model of the U.S. economy, Zahniser et al. (2012) simulate the impact of two hypothetical scenarios on the agricultural sector: increase in the employment of (temporary) authorized immigrant agricultural workers, and decrease in the total number of unauthorized workers in the United States. The first scenario would lead to a 4.4% decrease in the long-run real wages of agricultural workers, whereas a large reduction in the number of unauthorized immigrant workers across the U.S. economy would result in a 3.9–9.9% increase in real agricultural wages in the long run. Clemens et al. (2018) demonstrate that the exclusion of Mexican bracero farmworkers had little impact on the U.S. agricultural labor market.

The concept of substitutability is used to draw conclusions on how immigration impacts job opportunities and wages of native farmworkers, and whether natives and authorized or unauthorized immigrants compete for similar agricultural jobs. On the one hand, if immigrant labor is similar to native labor in the sense that there is a perfect substitutability between the two groups, then increased migration into the United States may have a negative effect on native farmworkers’ wages due to the competition effect between the two groups. On the other hand, if immigrants and natives within the same skill and age category are imperfect substitutes, then the competitive effects of increased immigrant inflows on natives will likely be minimal and will be concentrated among immigrants themselves (Ottaviano and Peri, 2006; Card, 2009). It is worth noting here that our theoretical framework is a partial equilibrium, one-sector approach and inter-sectoral mobility and adjustment are not considered in this framework.

Existing empirical evidence has found the role of inter-sectoral adjustments to be small (see Card [2009] for more details).

Building on the theoretical models by Card (2009), Manacorda et al. (2012), and Ottaviano and Peri (2012), we derive the following wage differential equation between native (denoted by N) and immigrant (denoted by M) farmworkers in each age (a) and skill (s) group at time t, which is a function of relative labor supply in each skill–age–time cell (refer to Appendix A for details of the theoretical framework).

where β_sat reflects the efficiency of immigrant workers relative to native workers within each skill–age–time cell. Equation (1) is a major equation of interest, from which the elasticity of substitution between native and immigrant farmworkers, σ_I, can be obtained. By the nature of the nested CES structure, when there are multiple legal status groups, σ_I would represent the degree of substitution between any two legal status groups. If native and immigrant farmworkers are perfect substitutes, there should be no statistically significant effect of changes in the relative employment of native workers with respect to immigrant farmworkers on their relative wages. In other words, 1/σ_I will be zero in cases of perfect substitutability.

Denoting the immigration (or, legal) status by I, which takes on values N and M for native and immigrant, respectively, the relative wages of skilled labor compared to less-skilled labor within the same age but different immigration group at time t can be written as

where s = {1,2} with 1 representing the skilled labor group and 2 representing the less-skilled labor group. Equation (2) is the base equation for the empirical estimation that yields negative of the inverse of elasticity of substitution between skill groups (−1σS),$$\left( -\frac{1}{{{\sigma }_{S}}} \right),$$age groups (−1σA),$$\left( -\frac{1}{{{\sigma }_{A}}} \right),$$and legal status groups (−1σI).$$\left( -\frac{1}{{{\sigma }_{I}}} \right).$$

Although there is disagreement on the exact effects immigrants have on wages and employment of native workers in the host country, the empirical evidence generally points to imperfect substitutability between immigrant and native workers in less-skilled sectors. Based on the labor market outcomes of less-skilled native workers in 120 major cities extracted from the 1970 and 1980 U.S. Censuses, Altonji and Card (1991) found that the competition between immigrants and less-skilled natives in labor markets is modest and there is little evidence that inflows of immigrants are associated with increased unemployment rates of less-skilled native workers. Card (2009) found an elasticity of substitution between immigrants and natives of 50 (estimated -1/σ_I of −0.02) using pooled time series for 124 U.S cities. Ottaviano and Peri (2012) obtained similar elasticity estimates for immigrants and natives (-1/σ_I ranging from −0.08 to −0.04) using U.S. census data. Using pooled data on British males’ wages and employment from the mid-1970s to the mid-2000s, Manacorda et al. (2012) found that immigrants and natives are imperfect substitutes in the labor markets of the United Kingdom, with a relatively small degree of substitution around 8 (estimated -1/σ_I of −0.128).

Strikingly, there is a large research gap in quantifying the elasticity of substitution among farmworkers from different legal status backgrounds. This measure is crucial for assessing the wage effects of immigration and immigration policy changes on the U.S. agricultural sector. Studies using the CGE models typically skip formal estimation of σ_I , and instead assume an ad hoc elasticity of substitution between farmworkers with different legal statuses. For example, Zahniser et al. (2012) set the elasticity of substitution at 5 for unauthorized and authorized (permanent resident) workers, and a higher substitution elasticity of 7.5 between U.S.-born and foreign-born permanent resident workers to simulate the impact of changes in the supply of immigrants on the U.S. agricultural sector. Watson et al. (2012) assume an elasticity of substitution of 3.5 (upper bound) and 1.3 (lower bound) between foreign-born and native workers for their general equilibrium model for Idaho economy.

Watson et al. (2012) note that they adopt these two estimates from Borjas (2003). However, Borjas’s (2003) estimates are not elasticities of substitution between immigrant and native workers. Based on Borjas (2003), 1.3 is the elasticity of substitution across different education groups and 3.5 is the elasticity of substitution across different experience groups.

To obtain substitution elasticities across different skill, age, and immigration status groups using estimates from Equation (2), we first need to have the predicted values of L_sat and L_st at hand. As shown in Equations (A2) and (A3) in Appendix A, predicting L_sat and L_st , in return, requires having estimates of σ_I and σ_A. As such, a three-step estimation procedure proposed by Manacorda et al. (2012) is used to iteratively obtain the three elasticity estimates.

Step 3: Estimating σ_S

Labor supply estimates obtained from the first and second steps can be used to reestimate Equation (2) using the following specification:

(7)lnW1atIW2atI=κ0+κ1t+da+dI−1σSlnL1tL2t−1σA(lnL1atL2at−lnL1tL2t)−1σI(lnL1atIL2atI−lnL1atL2at)$$ln\frac{W_{1at}^{I}}{W_{2at}^{I}}={{\kappa }_{0}}+{{\kappa }_{1}}t+{{d}_{a}}+{{d}_{I}}-\frac{1}{{{\sigma }_{S}}}ln\frac{{{L}_{1t}}}{{{L}_{2t}}}-\frac{1}{{{\sigma }_{A}}}\left( ln\frac{{{L}_{1at}}}{{{L}_{2at}}}-ln\frac{{{L}_{1t}}}{{{L}_{2t}}} \right)-\frac{1}{{{\sigma }_{I}}}\left( ln\frac{L_{1at}^{I}}{L_{2at}^{I}}-ln\frac{{{L}_{1at}}}{{{L}_{2at}}} \right)$$

Equation (7) allows us to obtain an estimate of the negative of inverse elasticity of substitution between different skill groups (-1/σ_S ). k₁ captures the skill-biased technological change. Equation (7) also yields a new set of estimates for σ_I and σ_A, which may serve as specification tests for estimating equations in the previous steps.

To pin down the three substitution elasticity parameters (σ_I, σ_A, σ_S) in the production function and examine the consistency of the model, we consider different nesting structures by partitioning heterogeneous workers into different combinations of skill, age, and legal status groups as illustrated in Figs. 1 and 2. In the theoretical framework, the production function considers two distinct skill groups: skilled and less-skilled workers. Although it is a well-established tradition in the literature to use formal education years in measuring skill levels of workers, the validity of this measure is questionable for crop farmworkers, who typically lack high school diploma. Therefore, we use formal education only as a supporting measure and report results based on education proxy in Appendix B. Instead, we propose two alternatives, more realistic proxies, to categorize agricultural labor into skilled and less-skilled groups: (a) the type of operational tasks that farmworkers perform and (b) the number of years working in the farm sector (i.e., the farmwork experience).

Figure 1

Figure 2

The division of age groups is relatively straightforward. Four age cohorts are considered in the empirical analysis: Teenager (14–19), young (20–39), middle-aged (40–59), and old (≥60).

We also considered an alternative case where age was truncated to only include farmworkers between the ages of 20 and 69 years old—young (20–29), middle-aged (40–59), and old (60–69). Empirical results using this alternative age classification did not differ significantly from those using the classification described above.

Legal status is an additional characteristic to differentiate heterogeneous farmworker groups. Foreign-born workers differ from native workers in several aspects, such as legal status, education, and English proficiency (Caponi and Plesca, 2014; Kaushal et al., 2016). Even considering workers within the same skill and age cohort, immigrant and native workers tend to differ in several other aspects that are relevant to the labor market. Immigrants may have different work ethics, motivations, and preferences that differentiate them from native workers. Immigrants may have comparative advantages in some tasks and occupations because of their culture-specific skill sets that native workers do not possess (Ottaviano and Peri, 2006). Furthermore, authorized immigrants may have more bargaining power in the labor market than unauthorized immigrants, although this disparity likely decreases with educational attainment (Caponi and Plesca, 2014). Based on their immigration status, we categorize farmworkers into three legal status groups: U.S. citizens (including both citizens by birth and naturalized citizens), authorized immigrants (permanent legal residents and immigrants holding other types of work authorization), and unauthorized immigrants (immigrants without proper legal documentation authorizing them to work in the United States).

An alternative classification using birthplace (i.e., U.S.-born vs. foreign-born) is presented in Appendix B.

Before proceeding to the estimation of the conceptual model introduced in the previous section, we first describe the key variables constructed for the empirical analysis. Data from the NAWS, an employment-based random sampled survey of seasonal hired crop workers, are used in this study. NAWS is the only national survey that collects data on U.S. hired farmworkers’ immigration status as well as their demographic characteristics and detailed employment information through face-to-face interviews. We use the portion of the NAWS data that is open to the public and available online from the DOL website.

Data are available at www.doleta.gov/naws/

with missing wage rate information, the sample size reduces to 52,527 individual farmworkers or 565 age–skill–immigration cells, covering the period from 1989 through 2012.

The NAWS uses a stratified multistage sampling design to account for seasonal and regional fluctuations in the level of employment in crop agriculture. The sampling design involves first obtaining a random selection of employers from a universe list compiled mainly from public agency records. Once the random sample of employers is identified, then a random sample of workers is chosen for each employer. The interviewers, who are bilingual and generally work in pairs, approach workers directly to set up interview appointments in their homes or other agreed-upon locations outside the farm. In 2008–2009, 92% of the approached workers agreed to be interviewed for NAWS. NAWS methodology has been adapted to maximize response from this hard-to-survey population. Interviewers speak with workers in English or Spanish, as necessary. All interviewers are bilingual and bicultural. The NAWS questionnaires are available in both Spanish and English. In addition to anonymity, interviewers ensure that potential respondents know that they are not associated with any enforcement agency, such as the Immigration and Customs Enforcement agency. These measures increase the likelihood of obtaining truthful answers to some key questions regarding legal status and employment (DOL, 2019).

In this section, we discuss the estimates of key parameters and elasticities from different skill measures and nesting structures. We primarily focus our discussions on nested CES Models A and B (Figs. 1 and 2), where farmworkers are grouped into citizen, authorized immigrant, and unauthorized immigrant categories at the lowest nesting level, and skill levels are approximated by task type (nested CES Model A) and farm experience (nested CES Model B), respectively (Tables 3 and 4). The model where skill level is approximated by formal education is reported in Table B1 in Appendix B. Additional supplementary results using the alternative immigration grouping by birthplace (i.e., U.S.-born vs. foreign-born) and three skill proxies are presented in Table B2 in Appendix B.

The large share of unauthorized immigrant workers in the farm labor force has made immigration policy a major issue for the U.S. agricultural sector. As debates for immigration reform continue, policy makers find themselves having to address agricultural employers’ concerns about finding and keeping the labor they need while also making sure that any changes to the flow of immigrant farmworkers do not negatively impact the economic opportunities of native farmworkers. Therefore, whether native farmworkers are substitutes for immigrant farmworkers in the United States is an important question with significant implications for the design of immigration policies. If immigrant and native farmworkers are perfect substitutes in employment, then public pressure will likely drive policy to enact legislation that protects U.S. citizens and stems the flow of immigrant workers. If, however, immigrant and native farmworkers are imperfect substitutes, then the inflow of foreign-born farmworkers would not be harmful to economic gains of native farmworkers. In the second case, legalization of undocumented immigrant farmworkers or bringing in temporary foreign workers through federal visa programs, such as the H-2A guest workers program, could potentially benefit agricultural employers by complementing the population of existing domestic farmworkers.

Using type of farm tasks performed, farmwork experience and formal education as three alternative proxies for farmworkers’ skill levels, we aggregate individual wage and employment information from the NAWS data over the period from 1989 through 2012 into different skill–age–year cells. Our study is the first in proposing task type and number of years in farmwork as two additional measures besides formal education to approximate skill groups in the agricultural sector. We use two alternative legal status classifications under which we define native versus immigrant workers. The first classification divides farmworkers into three legal status groups: citizens, authorized immigrants, and unauthorized immigrants. The second classification is based on birthplace, where native farmworkers are defined as U.S.-born farmworkers and immigrants are defined as foreign-born workers. Regardless of which definition of immigration status is used in the analysis, we find limited substitutability between immigrant and native farmworkers under all alternative skill measures. The estimated elasticity of substitution across different immigration status groups is not sensitive to our choice of skill groups and is stable across different nesting structures. Within a specific age–skill cell, the point estimate of the elasticity of substitution between immigrant and native workers is near 2 (2.11 for age–task, 2.2 for age–experience, and 2.07 for age–education cells), which is far smaller than those reported in the literature for low-skilled nonfarm sectors. The estimated elasticity of substitution suggests that there are limited possibilities to substitute between native and immigrant farmworkers (whether authorized or unauthorized). Wage differentials between native and immigrant farmworkers are most likely driven by productivity differences between these groups, suggesting that the removal of unauthorized immigrant workers from the labor market is unlikely to increase opportunities for native workers. This finding is consistent with Clemens et al. (2018) who demonstrated that the exclusion of Mexican bracero farmworkers has little effect on the labor market for U.S. domestic farmworkers. Similarly, low substitutability between native and authorized immigrant workers implies that increased inflow of authorized immigrant farmworkers through, for example, the H-2A guest worker program is unlikely to have a negative effect on the employment of U.S. citizen farmworkers.

The estimated elasticity of substitution across the four age groups varies from 1.53 to 2.61, depending on the skill measure used in the preceding nest. The estimated elasticity of substitution between less-educated and more-educated farmworkers is 2.45 and is close to that reported in the literature for nonfarm labor. The estimated elasticity of substitution between less-experienced and more-experienced farmworkers is 1.42, and the estimated elasticity of substitution between workers conducting less-skilled manual labor tasks and semi-skilled or skilled tasks is 4.81. The relatively low substitution possibilities between less- and more-experienced farmworkers are likely due to correlation between age and experience; older crop workers may not easily replace younger crop workers due to the labor-intensive nature of crop-farming tasks that require endurance. This result may have potential policy implications for employment of older, “settled” migrant farmworkers who have been in the United States for more than 10 years, on average.

Regardless of our choices of skill measures and nesting structures, our estimate for the elasticity of substitution across different legal status groups of farmworkers within a given age–skill cell proves to be robust and is consistently estimated to be around 2. The insensitivity of the substitution elasticity across different immigration status groups may indicate that immigration status is a relatively stand-alone characteristic in the nesting structure, while skill and age groups tend to be more closely interrelated. The substitution elasticities computed in this study for citizen, authorized immigrant, and unauthorized immigrant farmworkers from various age and skill groups would be better interpreted as long-run aggregate elasticities of substitution. It is worth noting that the theoretical model is static and the relative labor supply is assumed constant across time (inelastic labor supply). These elasticities should be taken with caution when evaluating local agricultural markets. Hired farm labor is mobile across states in the United States, and local agricultural markets may have unique supply and demand conditions (Fisher and Knutson, 2012). For example, a farmworker may have picked apples in Michigan before migrating down to Florida to harvest strawberries and then up to North Carolina to pick blueberries. Nonetheless, our long-run aggregate elasticity estimates still serve as a valuable reference point for the effects of immigrant farm labor on local agricultural markets.

Overall, we find little evidence that immigrant (both unauthorized and authorized) farmworkers significantly impact the employment of native farmworkers across different age and skill levels. Limited substitutability between authorized immigrant and citizen farmworkers found in this study has implications for the agricultural guest workers program and its future revisions. Given the limited substitutability of authorized immigrant farmworkers with citizen farmworkers combined with the tightening labor supply in the agricultural sector, policy makers may need to rethink the elements of the agricultural guest worker program that can hamper the inflow of authorized immigrant workforce into the U.S. agricultural sector. Providing easier access to the pool of authorized immigrant farmworkers through federal guest worker programs will help the U.S. agricultural sector stay competitive without threatening the employment opportunities of domestic (native) farmworkers. Our empirical finding that the degree of substitution between unauthorized immigrant farmworkers and citizen farmworkers is also small has similar implications for policies concerning undocumented farmworkers, including ongoing legislative debates and proposals on legalization of unauthorized agricultural workers who have been in the country for a certain period of time (e.g., the 2017 “Blue Card” proposal). The limited substitutability among unauthorized immigrant, authorized immigrant, and citizen farmworkers implies that providing current undocumented workers a path to legal status through a federal immigration reform is unlikely to have significant negative consequences for citizen or authorized farmworkers.