Lower Immigration Means Lower Productivity Growth

Key Takeaways

1. Even assuming a return to baseline immigration in 2029, the current slowdown in immigration will likely have long-run impacts on business formation and productivity.

2. The number of missing new firms per year peaks in the early 2030s at between 9,000 and 16,000 (a decline of between 1.7% and 3.0%).

3. In 2075, fifty years after the policy shock, annual new employer-firm entry is still about 4,000-6,500 firms smaller (0.7-1.2%), with the long-run gap driven primarily by missing native-born descendants of missing immigrants.

4. Economywide productivity is lower by between 0.25% and 0.44% in 2052, and productivity remains lower even in 2075.

The second stage of our framework maps demographic changes into new business creation. We focus here on entry of businesses with at least one employee (“employer-firms”), putting aside single-person businesses or solo- entrepreneurs. Drawing on existing research that documents how startup rates and the sector of these new business vary across ages and immigrant status (Azoulay, Jones, Kim, and Miranda 2020, 2022), we map our population scenarios into year-by-year changes in new business creation by sector. The falling number of working-age immigrants and, eventually, their would-be native-born descendants reduces new-business formation.

Figure 3 shows the resulting annual shortfall in new employer-firm entry. Under EVW Low, about 4,100 fewer employer firms are founded in 2025; this shortfall grows to a peak of about 16,000 missing firms per year in 2032 and settles at about 6,500 per year by 2075. EVW High follows a similar pattern with about 3,300 fewer firms in 2025, a peak of about 8,900 missing in the early 2030s, and about 3,900 fewer per year by 2075. For context, the CBO January 2025 baseline implies roughly 530,000 new employer firms entering per year in the early 2030s and, at their peak, the EVW Low and High shortfalls are about 3.0% and 1.7%, respectively, of baseline employer-firm entry.

There are three main channels driving these shortfalls:

• Fewer immigrants. Immigrants start businesses much more often than natives, with Azoulay, Jones, Kim, and Miranda (2022) estimating that immigrants as a whole are 80% more likely to found an employer firm than native-born Americans. Their study does not estimate separate authorized and unauthorized immigrant entrepreneurship premia, so we conservatively apply their estimates only to authorized immigrants.2
• An older age structure.Azoulay, Jones, Kim, and Miranda (2020) show that business startup rates are highest among those in their 30s and 40s. Immigrants tend to arrive during or before these prime founding ages, so removing them shifts the working-age population older and reduces business creation.
• Fewer U.S.-born descendants. In the longer run, the children who were never born cannot start businesses. This missing-births channel drove the native-born wedge in Stage 1 and keeps the entry shortfall well above zero decades after net migration has returned to baseline.

These mechanisms ensure that current immigration policies will lower business creation for decades to come. Even though net migration returns to the CBO baseline by 2029, the missing younger immigrant cohorts age out of their prime founding years outside the U.S. and the never-born children of those missing immigrants cannot found firms in the mid-century. Even in 2075, fifty years after the policy shock, annual new employer-firm entry is still about 6,500 firms below baseline under EVW Low and about 3,900 under EVW High (about 1.2% and 0.7%, respectively, of the baseline startup rate), with the long-run gap driven primarily by missing native-born descendants of missing immigrants.

The third stage of our framework translates the Stage 2 entry shortfall into a decline in aggregate productivity growth. For ease of interpretation, Figure 4 shows the cumulative productivity shortfall under each scenario.

Under each scenario the productivity impact peaks around 2052 before slowly attenuating. Under EVW Low, the level gap grows to about 0.35% by 2040, peaks at about 0.44% around 2052, and recedes slightly to about 0.31% by 2075. EVW High follows the same pattern at smaller scale: about 0.20% by 2040, peaking at about 0.25% around 2052, and about 0.18% by 2075. In annual terms, productivity growth is lower than baseline by up to about 2.9 basis points per year under EVW Low and up to about 1.6 basis points per year under EVW High, with the largest annual gap around 2030.

Fewer new firms shift the firm age distribution (the share of employment sitting in firms of each age) toward older, slower-growing incumbents. Young firms drive disproportionate productivity growth through a mix of high-productivity entry, selective exit of low-productivity firms, and fast post-entry growth among survivors; we capture the combined effectt, and Pugsley (2018)

The annual drag in each scenario reflects three distinct effects:

• Direct entry effect. The productivity cost from having fewer age-0 firms in any given year. This channel is strong in the early years of each scenario and tracks the entry wedge from Stage 2. 
• Aging effect. The accumulating productivity cost from missing age-1, age-2, and so on firms as earlier entry cohorts propagate forward through the firm age distribution. The aging effect becomes the larger component of total drag within about a decade and accounts for the bulk of the cumulative drag at the peak. This effect grows quickly and then more slowly as the initial loss of young firms becomes an ongoing loss of both young and old firms.
• Reallocation offset. When fewer immigrant-founded firms are formed, the surviving (predominantly native-founded) firms account for a larger share of total employment, and their contribution to aggregate productivity growth carries more weight in the aggregate measure. This partially offsets the first two effects and grows over time as missing small, young firms would have aged into larger, older firms and the missing descendants channel keeps the population of businesses permanently smaller. 

The hump shape arises from the interaction of these three channels. In the short run, the population of missing firms is dominated by the young, whose contributions to productivity growth are the largest. Over time, the incremental impacts of these direct and aging effects begin to stabilize as the firm age distribution drifts towards its new long-run shape.3

The positive entry under the “native offset” column is a reallocation effect.4 When fewer immigrant-founded firms enter the economy, the employment share of surviving (predominantly native-founded) firms rises mechanically. This channel does not imply that native-founded firms are becoming more productive, but that their contribution to aggregate productivity growth simply carries more weight because they are a larger share of employment. The gross loss from missing immigrant-founded firms minus this offset equals the net headline drag. To make this concrete: under EVW Low in 2055 the gross drag from missing immigrant-founded firms (authorized plus unauthorized) is about 0.75 percentage point, the reallocation offset is about 0.31 percentage point, and the net headline drag is about 0.44 percentage point. The same structure holds in EVW High.

Sector matters for this exercise because the age-productivity relationships estimated by ABDP vary substantially across sectors and because the sectoral footprint of immigrant-founded firms differs from the economy as a whole. To model the role of sectors we use sector-specific age-productivity profiles from ABDP, estimated separately for eleven 2-digit NAICS sectors, and we allow each of the three founder-status groups in our model (native-born, authorized foreign-born, unauthorized foreign-born) to have its own sector mix at entry. Figure 6 shows the resulting EVW Low and High cumulative drag in 2055 decomposed by founder status and sector.

Two patterns stand out in the EVW Low results. First, the unauthorized-channel drag is highly concentrated. Construction accounts for about 28% of the unauthorized channel and professional and administrative services (which includes landscaping, custodial services, etc.) for another 26%, with the two sectors together accounting for roughly 54% of the total (see table below). Second, the authorized channel is much more dispersed across sectors than the unauthorized channel, with appreciable contributions from professional services, entertainment and accommodations, education and healthcare, and retail trade.

The per-status sector mixes are constructed from two public datasets. The Census Bureau’s Annual Business Survey Characteristics of Business Owners (2023 vintage) reports the sector composition of employer-firm owners separately for the native-born and foreign-born. ABS does not record legal status, however, so we cannot use it to estimate separate authorized and unauthorized sectoral distributions. To identify these two distributions we use the American Immigration Council’s Mass Deportation report (Hubbard et al., 2024), which estimates the sector mix of undocumented entrepreneurs’ businesses via Borjas-style legal-status imputation on the American Community Survey. They find unauthorized startups are roughly 30% in construction, 19% in professional and administrative services, and 17% in general services. We assume that 10% of foreign-born employer-firm owners are unauthorized and derive the authorized-immigrant sector mix as the residual of the foreign-born mix net of the AIC unauthorized mix. The cumulative drag in 2055 changes by about 0.003 percentage points as the unauthorized-owner fraction is varied between 0.05 and 0.20, so the sector results are robust to this assumption.

Footnotes

• 1

  Our notion of unauthorized immigrants follows the Migration Policy Institute’s definition. Unauthorized includes both those who have entered illegally or overstayed and some individuals with liminal or temporary protections. Authorized is shorthand for the residual foreign-born group, including naturalized citizens, lawful permanent residents, and many temporary-status holders. See the appendix for more details.

• 2

  There are reasons to expect that unauthorized immigrants have lower employer-firm startup rates than authorized immigrants: structural barriers such as EIN requirements, banking access, and licensing; legal exposure; educational differences; and the empirical observation that unauthorized self-employment is concentrated in unincorporated, often necessity-driven activity that lies outside our employer-firm universe. Our baseline calibration accordingly sets the authorized-immigrant premium to 1.8 (matching the Azoulay et al. aggregate under the interpretation that their dataset, the Longitudinal Business Database, predominantly captures authorized founders) and the unauthorized-immigrant premium to 1.0; details and sensitivities are in Appendix A.

• 3

  A second major factor is the continued growth of the reallocation effect over time. For more discussion of this interplay and of the long run behavior of the productivity shortfall, see the appendix. 

• 4

  This native reallocation effect is a subset of the full reallocation effect calculated in Appendix B.