Key Points
10 percent of low-skilled immigrants equals just 25,000 workers in 2025, or about 0.01 percent (one percent of one percent) of the total U.S. working-age population. Over the next 30 years, 750,000 immigrant workers would be converted from low to high skill, still representing just 0.35 percent of the total U.S. working-age population in 2054. The total number of immigrant workers remains unchanged.
This policy has an outsized impact on economic growth relative to the size of the policy change. We project that the HSI policy would increase GDP by 0.1 percent by 2034 and 0.4 percent by 2054, while HSI STEM policy would increase GDP by 0.3 percent by 2034 and 0.7 percent by 2054.
Both policies reduce outlays and increase revenues over the 10-year budget window ending in 2034, decreasing primary deficits by $65.3 billion under the HSI policy and $152.6 billion under the HSI STEM policy.
All education, occupation, income, and age groups gain from both policy changes. The gains also benefit low-income workers the most relative to their earnings before these policy changes. Wages for low-skill workers increase by 0.5 percent within a decade and by 1.3 percent over the long run. Future low-skill workers born today gain between $10,000 and $16,000 in lifetime value from HSI and HSI STEM, respectively.
Shifting Immigration Toward High-Skilled Workers
Under current law, total immigration is projected to increase the U.S. adult population (ages 21 and older) by 15.3 million by 2054, accounting for approximately 40 percent of growth in total adult population (see Figure 1). Based on historical trends, about 35 percent of new immigrants are expected to have a high school diploma or less, classifying them as low-skilled labor. In contrast, about 65 percent are anticipated to have some college education or higher, placing them in the high-skilled labor category. Among these high-skilled immigrants, we estimate that only about 15 percent will work in STEM occupations.
Source: Penn Wharton Budget Model
We analyze two illustrative policy changes that alter the skill composition of new immigrants while keeping the total number of projected immigrants constant. These policy changes reduce the number of low-skilled visas by 10 percent and increase the number of high-skilled visas by the same amount. The difference between the two policies is how we allocate high-skilled visas.
High-skill immigration (HSI): Additional visas are issued to high-skilled non-STEM and high-skilled STEM immigrants so that their proportions among all high-skilled immigrants remain consistent with current immigration projections.
High-skill STEM immigration (HSI STEM): All additional visas are issued to high-skill STEM immigrants.
Table 1 shows the projected number of new immigrant households entering the U.S. under current law and two illustrative policy scenarios. Between 2025 and 2054, an estimated 7.5 million low-skilled immigrants, 12.5 million high-skilled non-STEM immigrants, and 2.1 million high-skilled STEM immigrants are expected to enter the country legally through existing visa programs. By 2054, new low-skilled, high-skilled non-STEM, and high-skilled STEM immigrants will account for approximately 3.50 percent, 5.85 percent, and 1.00 percent of the total workforce, respectively.
Under the HSI and HSI STEM policies, the annual inflow of low-skilled immigrants is reduced by 10 percent, leading to a total decline of 0.75 million over the 2025 to 2054 period. By 2054, new low-skilled immigrants as a share of the workforce will decrease from 3.50 percent to 3.15 percent.
Under the HSI policy, the reduced number of low-skilled immigrants is reallocated proportionally according to the current-law distribution: 85 percent to high-skilled non-STEM and 15 percent to high-skilled STEM immigrants. This reallocation results in approximately 650,000 additional high-skilled non-STEM immigrants and 100,000 additional high-skilled STEM immigrants compared to current law. By 2054, these changes increase the new high-skilled non-STEM and new high-skilled STEM immigrants as a share of the total workforce from 5.85 percent to 6.15 percent and 1.0 percent to 1.05 percent, respectively.
Under the HSI STEM policy, the number of high-skilled non-STEM immigrants will remain unchanged from current law. In contrast, the reduction in low-skilled immigrants will be entirely offset by an increase of 750,000 high-skilled STEM immigrants. As a result, from 2025 to 2054, 2.9 million high-skilled STEM immigrants will enter the U.S., representing a 35 percent increase compared to current law. By 2054, new high-skilled STEM immigrants as a share of the workforce will increase from 1.0 percent to 1.35 percent, while the share of new high-skilled non-STEM immigrants remains unchanged at 5.85 percent.
| 2025 | 2029 | 2034 | 2039 | 2044 | 2049 | 2054 | |
|---|---|---|---|---|---|---|---|
| Current Law | |||||||
| Low-skilled | 0.3 | 1.2 | 2.4 | 3.6 | 4.9 | 6.2 | 7.5 |
| High-Skilled non-STEM | 0.4 | 2.0 | 4.1 | 6.1 | 8.2 | 10.4 | 12.5 |
| High-Skilled STEM | 0.1 | 0.3 | 0.7 | 1.0 | 1.4 | 1.8 | 2.1 |
| High-Skill Immigration | |||||||
| Low-skilled | 0.2 | 1.1 | 2.1 | 3.3 | 4.5 | 5.6 | 6.7 |
| High-Skilled non-STEM | 0.4 | 2.1 | 4.3 | 6.5 | 8.6 | 10.9 | 13.2 |
| High-Skilled STEM | 0.1 | 0.4 | 0.7 | 1.1 | 1.5 | 1.8 | 2.2 |
| High-Skill STEM Immigration | |||||||
| Low-skilled | 0.2 | 1.1 | 2.1 | 3.3 | 4.5 | 5.6 | 6.7 |
| High-Skilled non-STEM | 0.4 | 2.0 | 4.1 | 6.1 | 8.2 | 10.4 | 12.5 |
| High-Skilled STEM | 0.1 | 0.5 | 0.9 | 1.4 | 1.9 | 2.4 | 2.9 |
Note: Numbers are rounded to the nearest 100,000.
Source: Penn Wharton Budget Model
Table 2 illustrates the economic and debt impacts of the HSI and HSI STEM policies. Under both policies, GDP, capital, wages, and consumption steadily rise, while debt declines over the 2025–2054 period as more high-skilled non-STEM and STEM workers immigrate to the U.S. By 2054, under the HSI policy, GDP and capital increase by 0.4 percent, average wages rise by 0.2 percent, and debt is 0.4 percent lower than under current law (see Table 2.A). Wage growth also drives a 0.4 percent increase in consumption.
The effects are even more pronounced under the HSI STEM policy, which results in a larger influx of STEM workers. By 2054, GDP and capital will increase by 0.7 percent and 1.0 percent, respectively; average wages will be 0.5 percent higher, and debt will be reduced by 0.8 percent compared to current law (see Table 2.B). The stronger wage growth under this policy leads to a 0.6 percent increase in consumption. Total hours worked are mostly unaffected under both policies.
The reason for these improvements is twofold. First, both policies replace lower-income immigrants with higher-income immigrants. Higher-income workers have a higher propensity to save, which increases capital, GDP, and wages. Higher incomes also produce more tax revenues, which decreases debt and further increases capital. Second, the increase in the number of high-skilled STEM workers increases TFP, positively affecting GDP, wages, and capital even further.
| 2034 | 2039 | 2044 | 2049 | 2054 | |
|---|---|---|---|---|---|
| Gross domestic product | 0.1 | 0.2 | 0.2 | 0.3 | 0.4 |
| Capital stock | 0.0 | 0.1 | 0.2 | 0.3 | 0.4 |
| Hours worked | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Average wage | 0.0 | 0.0 | 0.0 | 0.1 | 0.2 |
| Consumption | 0.1 | 0.2 | 0.2 | 0.3 | 0.4 |
| Debt held by the public | -0.1 | -0.2 | -0.3 | -0.3 | -0.4 |
| 2034 | 2039 | 2044 | 2049 | 2054 | |
|---|---|---|---|---|---|
| Gross domestic product | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 |
| Capital stock | 0.1 | 0.3 | 0.5 | 0.7 | 1.0 |
| Hours worked | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Average wage | 0.1 | 0.2 | 0.2 | 0.3 | 0.5 |
| Consumption | 0.3 | 0.4 | 0.4 | 0.5 | 0.6 |
| Debt held by the public | -0.3 | -0.5 | -0.6 | -0.8 | -0.8 |
Source: Penn Wharton Budget Model
Table 3 presents the effects of the two illustrative immigration policies on wages, consumption, and hours worked for each group, including low-skilled, high-skilled non-STEM, and high-skilled STEM workers.
Under the HSI policy, wages for low-skilled workers increase by 1 percent by 2054 (see Table 3.A), while wages for high-skilled workers increase only slightly. Although higher TFP raises wages for all groups, the reduction in low-skilled labor supply drives a more significant wage increase for low-skilled workers because of their increased scarcity and their complementarity with high-skilled labor. In contrast, the increase in high-skilled non-STEM and STEM workers, combined with the reduced availability of low-skilled workers, offsets the TFP-driven wage gains for high-skilled workers.
Table 3.B highlights the stronger wage effects under the HSI STEM policy. With a larger influx of STEM workers and a greater boost to TFP, wage growth is more pronounced across all groups. By 2054, wages for low-skilled workers are projected to be 1.3 percent higher than under current law, while wages for high-skilled non-STEM and high-skilled STEM workers increase by 0.4 percent and 0.3 percent, respectively.
For both policies, changes in consumption closely follow wage trends. Consumption increases among low-skilled workers by between 0.9 and 1.2 percent by 2054, while high-skilled workers’ consumption increases by no more than 0.5 percent. Average hours worked decrease slightly more for low-skilled than high-skilled workers, but those declines are never greater than 0.2 percent.
| 2034 | 2039 | 2044 | 2049 | 2054 | |
|---|---|---|---|---|---|
| Wages | |||||
| Low-skilled | 0.4 | 0.5 | 0.7 | 0.8 | 1.0 |
| High-Skilled non-STEM | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 |
| High-Skilled STEM | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 |
| Consumption per Capita | |||||
| Low-skilled | 0.3 | 0.5 | 0.6 | 0.7 | 0.9 |
| High-Skilled non-STEM | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| High-Skilled STEM | 0.0 | 0.1 | 0.1 | 0.1 | 0.2 |
| Average Hours Worked | |||||
| Low-skilled | -0.2 | -0.2 | -0.2 | -0.2 | -0.1 |
| High-Skilled non-STEM | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| High-Skilled STEM | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2034 | 2039 | 2044 | 2049 | 2054 | |
|---|---|---|---|---|---|
| Wages | |||||
| Low-skilled | 0.5 | 0.7 | 0.9 | 1.1 | 1.3 |
| High-Skilled non-STEM | 0.1 | 0.1 | 0.2 | 0.3 | 0.4 |
| High-Skilled STEM | 0.0 | 0.1 | 0.1 | 0.2 | 0.3 |
| Consumption per Capita | |||||
| Low-skilled | 0.4 | 0.6 | 0.8 | 1.0 | 1.2 |
| High-Skilled non-STEM | 0.1 | 0.1 | 0.2 | 0.2 | 0.3 |
| High-Skilled STEM | 0.1 | 0.1 | 0.2 | 0.3 | 0.5 |
| Average Hours Worked | |||||
| Low-skilled | -0.1 | -0.2 | -0.2 | -0.2 | -0.2 |
| High-Skilled non-STEM | 0.0 | 0.0 | 0.0 | -0.1 | -0.1 |
| High-Skilled STEM | -0.1 | -0.1 | -0.1 | -0.2 | -0.2 |
Source: Penn Wharton Budget Model
Table 4 presents the conventional deficit effects of both policies. Outlays decline slightly in both scenarios, primarily due to a reduced number of low-skilled workers relying on income security programs such as Medicaid and SNAP. Over the 2025–2034 period, outlays decrease by $12.3 under the HSI policy and by $13.9 under the HSI STEM policy.
At the same time, revenues increase significantly due to higher tax collections driven by rising incomes. Under the HSI policy, revenues grow by $53.1 billion, while the HSI STEM policy generates an even larger revenue increase of $138.7 billion.
As a result, primary deficits over the 2025-34 period decline by $65.3 billion under the HSI policy and by $152.9 billion under the HSI STEM policy. When accounting for dynamic effects, the reductions amount to $57.0 billion under the HSI policy and $145.2 billion under the HSI STEM policy.
| Provision | 2025 | 2026 | 2027 | 2028 | 2029 | 2030 | 2031 | 2032 | 2033 | 2034 | 2025 - 2034 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| High-Skill Immigration | |||||||||||
| Outlays | -0.3 | -0.5 | -0.7 | -1.0 | -1.1 | -1.4 | -1.5 | -1.7 | -1.9 | -2.0 | -12.3 |
| Revenues | 1.0 | 2.1 | 3.0 | 3.9 | 4.7 | 5.7 | 6.7 | 7.6 | 8.5 | 9.8 | 53.1 |
| Primary Deficit | -1.4 | -2.6 | -3.8 | -4.8 | -5.8 | -7.1 | -8.2 | -9.4 | -10.4 | -11.8 | -65.3 |
| High-Skill STEM Immigration | |||||||||||
| Outlays | -0.4 | -0.6 | -0.9 | -1.1 | -1.3 | -1.6 | -1.7 | -1.9 | -2.1 | -2.3 | -13.9 |
| Revenues | 4.8 | 8.0 | 10.8 | 12.4 | 13.7 | 15.3 | 16.5 | 17.3 | 19.0 | 20.8 | 138.7 |
| Primary Deficit | -5.2 | -8.6 | -11.7 | -13.4 | -15.0 | -16.9 | -18.3 | -19.2 | -21.1 | -23.1 | -152.6 |
| Memorandum: | |||||||||||
| Increase or decrease (-) in primary deficit with dynamic effects, High-Skill Immigration | -2.2 | -3.1 | -4.1 | -4.7 | -5.2 | -5.5 | -3.0 | -9.3 | -9.6 | -10.4 | -57.0 |
| Increase or decrease (-) in primary deficit with dynamic effects, High-Skill STEM Immigration | -6.2 | 5.4 | -13.1 | -15.1 | -15.6 | -17.3 | -18.3 | -19.1 | -22.3 | -23.8 | -145.2 |
Source: Penn Wharton Budget Model
Dynamic distributional analysis considers how a policy affects households across the income and age distribution, including the unborn (represented by a negative age index at the time of the reform). It asks how much, on average, households in each (income, age) bucket value the proposed policy change over their entire lifetime, represented as a one-time transfer at the time of the policy change. Dynamic distributional analysis is the standard in academic research, where conventional analysis is rarely used due to several key limitations that dynamic analysis addresses.
Tables 5.A and 5.B report policy “equivalent variations” for the two policies reported in Table 2 and break down the results by type of worker. A positive equivalent variation means that the person would be better off under the policy reform; a negative equivalent variation means that the person would be worse off under the policy reform. For example, as shown in Table 5.A.A, a low-skilled household aged 60 at the time of the policy change and with a gross income in the highest 20th percent of the income distribution receives $9,665 of value from the HSI policy. Put differently, this household is indifferent between adopting this policy and receiving a one-time payment of $9,665 without this policy change.
While all education, occupation, income, and age groups benefit from the HSI policy, Table 5.A shows that low-skilled workers generally experience greater gains than high-skilled non-STEM workers. With less low-skilled immigration, low-skilled workers’ wages increase more than those of high-skilled workers, contributing to the improvement in welfare. The benefits tend to increase the longer a household is exposed to the policy change, with future generations seeing the largest gains while those nearing retirement benefit the least. Retirees benefit from slightly higher interest rates.
While benefits generally increase by quintile income, low-skilled workers are an exception. Many households in this group rely heavily on means-tested income security programs such as Medicaid or SNAP. Although higher TFP drives wage growth, it can also reduce eligibility for these benefits, partially offsetting the gains from higher earnings.
As Table 5.B illustrates, the HSI STEM policy generally provides greater benefits across all education, occupation, income, and age groups compared to the HSI policy. The benefits that households receive from the HSI STEM policy are, on average, twice as large as those from the HSI policy.
Note: "Gross Income" refers to each household's income in the year of the policy change. We categorize households not yet in the labor force (ages 20 and younger) by their gross income in the year they enter the labor force. We calculate the gross income distribution across all groups of workers. Empty cells in panel A indicate that no low-skilled workers have incomes at that level.
Source: Penn Wharton Budget Model
An overview of our heterogeneous-agent overlapping-generations dynamic model (OLG) is provided in our 2024 publication “Policy Options for Reducing the Federal Debt: Spring, 2024” (available here). Over the next two years, PWBM will release additional details about our model to make our framework more accessible to academics, experts, and policy advocates.
This appendix briefly outlines the new components we have integrated into our model to analyze immigration policies. These enhancements and parameters are either directly sourced from published research or have been newly estimated. The new model components include:
Incorporating STEM Workers' Contribution to Total Factor Productivity (TFP): The model now explicitly accounts for the contributions of both native and immigrant STEM workers to TFP and skill-biased productivity growth. As the STEM workforce expands, technological advancements and process efficiencies accelerate, leading to higher wages, increased investment, and stronger long-term growth.
Modeling Skill Complementarities and Substitution Effects: The basic version of our OLG model includes low and high-income workers but treats them as perfect substitutes. To better account for the different effects that natives and immigrants have on labor supply and the economy, we introduce a framework that differentiates between low-skilled, high-skilled non-STEM, and high-skill STEM workers.
The following empirical concepts are now included in our analysis:
Immigration projections: The PWBM produces immigration projections that we now use in the OLG model, including immigrants’ education and occupation groups.
Estimate of the STEM workers' contribution to Total Factor Productivity: The PWBM now incorporates empirical evidence on the relationship between TFP and the number of workers in STEM occupations. Through a linear regression analysis, we estimate a constant elasticity of TFP with respect to the number of STEM workers using data on labor supply from the Current Population Survey’s Annual Social and Economic Supplements (ASEC), estimates of the capital stock from the Bureau of Labor Statistics (BLS), and gross domestic product data from the National Income and Product Accounts (NIPA).
Parameters determining the degree of substitutability or complementarity between groups: We use estimated parameter values from economic literature to assess how low-skilled, high-skilled non-STEM, and high-skilled STEM workers interact in the labor market.
Estimates of group-specific earnings processes: Members of the different skill and occupational groups face different earnings processes, which we estimated from the Panel Study of Income Dynamics (PSID) and the CPS ASEC.
Felipe Ruiz Mazin and Felix Reichling produced this analysis under the direction of Felix Reichling and Kent Smetters. Mariko Paulson prepared the brief for the website.
Year Native-Born Foreign-Born 2025 203 49 2026 205 50 2027 206 51 2028 208 51 2029 209 52 2030 210 53 2031 211 53 2032 212 54 2033 213 55 2034 214 55 2035 215 56 2036 216 56 2037 217 57 2038 218 57 2039 218 58 2040 219 59 2041 219 59 2042 220 60 2043 221 60 2044 221 61 2045 222 61 2046 223 62 2047 223 62 2048 224 63 2049 224 63 2050 225 63 2051 225 64 2052 226 64 2053 227 64 2054 227 65
Age 0 to 20 20 to 40 40 to 60 60 to 80 80 to 100 -20 12154 10986 17399 23406 -15 12548 10819 16719 21988 -10 12297 11666 15579 20241 -5 11841 9782 14338 18565 0 11404 10136 12932 16487 5 10645 9407 11447 14486 10 9835 7909 9675 12332 15 9175 6489 7926 10040 20 9576 5640 6543 7968 25 8279 4221 4934 6348 9459 30 8818 3065 3315 5936 10334 35 8802 2461 4484 7254 11381 40 8838 6700 7037 7034 12879 45 1772 2166 4060 6017 11788 50 1094 1114 3500 5934 11221 55 1315 1537 3065 6095 11301 60 1348 1519 2217 5060 9665 65 1846 1124 1980 3703 8614 70 0 109 683 1258 3075 75 0 214 535 974 2658 80 0 158 372 744 2319 85 0 12 97 353 1381
Age 0 to 20 20 to 40 40 to 60 60 to 80 80 to 100 -20 3362 5404 7804 11064 15796 -15 3328 5315 7585 10826 15780 -10 3240 5005 7158 10161 14603 -5 3044 4456 6286 8854 12781 0 2750 3878 5447 7583 10891 5 2338 3376 4791 6722 9641 10 2114 2870 4113 5951 8919 15 1816 2476 3595 5116 7477 20 1789 2305 3282 4752 6997 25 1391 1931 2938 4729 7878 30 1285 1733 2552 4153 7648 35 3358 1551 2266 3988 8270 40 1881 1396 2209 4169 9563 45 1436 1308 2124 4078 10659 50 1410 1449 2079 4078 10974 55 712 825 1524 4189 11145 60 360 836 1743 3643 9970 65 148 859 1303 2750 8156 70 0 554 980 1908 5855 75 0 248 656 1066 3553 80 0 312 409 668 2742 85 0 150 426 488 1897
Age 0 to 20 20 to 40 40 to 60 60 to 80 80 to 100 -20 2232 11172 19195 22584 31555 -15 2166 10788 20768 22297 30954 -10 1976 10028 18042 21267 29508 -5 1922 9719 18039 19340 26380 0 1886 6915 12325 17489 23488 5 1675 6148 11190 15787 21257 10 1555 5877 10489 14495 18977 15 1404 5047 9253 13266 18108 20 1167 4623 8428 12143 16951 25 1873 6881 10533 11016 16957 30 3826 6561 8637 11525 17867 35 4102 6048 7298 9002 16765 40 2080 3805 5582 8189 16289 45 875 2908 5283 8626 16742 50 132 2421 3554 5345 12126 55 1980 2467 3896 6422 12927 60 1272 1587 2345 3859 9056 65 565 707 794 1295 5186 70 0 212 920 2740 6155 75 0 53 301 1255 4119 80 0 110 267 834 2954 85 0 124 326 651 2127
Age 0 to 20 20 to 40 40 to 60 60 to 80 80 to 100 -20 17025 15661 24230 32577 -15 17226 15002 22506 29420 -10 16636 15703 20685 26746 -5 15887 12982 18366 23461 0 14957 12931 16446 20450 5 13456 11752 14418 17966 10 12701 10687 12654 15641 15 11794 8810 10538 13168 20 11078 7307 8784 10778 25 11376 7167 8208 9649 13238 30 9653 4142 5704 9562 15941 35 10651 4272 6997 10237 16148 40 9746 7145 8297 9790 17651 45 1467 2302 4602 9511 19329 50 5509 4965 5843 9933 19642 55 3228 4387 5801 10078 20360 60 1619 684 4017 8929 19166 65 2512 2145 3876 7471 17126 70 0 367 1105 2209 6159 75 0 140 849 1754 4847 80 0 204 725 1304 4174 85 0 60 602 989 3413
Age 0 to 20 20 to 40 40 to 60 60 to 80 80 to 100 -20 7850 14270 19790 27015 38198 -15 7466 13484 18422 24967 35422 -10 7039 12264 16771 22577 31326 -5 6335 10519 14182 18981 26244 0 5661 9045 12162 16232 22464 5 4751 7799 10534 14176 19652 10 4227 6709 9173 12485 17631 15 3666 5876 8143 11129 15685 20 3254 5314 7372 10164 14386 25 2910 4387 6348 9640 15073 30 3728 4448 5742 8495 14486 35 6840 3986 5483 8417 15664 40 6291 3627 5185 8765 18046 45 7326 5199 5305 8784 20210 50 1506 2731 4605 8503 21178 55 1387 2090 3631 8038 21383 60 1039 1901 3565 7307 20048 65 879 1401 2588 5684 16979 70 0 269 1178 2522 9180 75 0 670 1164 2013 7555 80 0 560 1247 1665 6003 85 0 396 700 1032 4399
Age 0 to 20 20 to 40 40 to 60 60 to 80 80 to 100 -20 5996 27864 43887 50140 66159 -15 5559 26042 44973 47459 60622 -10 4870 23366 37661 43321 54586 -5 4592 21321 35487 37430 45871 0 4316 15074 25092 32351 38994 5 3814 13046 21905 28133 33970 10 3453 11825 19754 25001 29697 15 2799 9855 17039 22427 27674 20 2302 8749 15099 20194 25796 25 3516 12159 17413 18004 25226 30 7091 11934 15133 19339 27541 35 7496 8381 9436 11148 22762 40 6222 9191 11525 15884 29162 45 4879 8736 11624 16735 30797 50 3392 5008 7048 10852 24293 55 4852 6312 8172 12165 26326 60 667 1113 4508 9245 22644 65 1612 1145 1835 3310 11859 70 0 350 1664 4327 10777 75 0 364 1090 2703 8237 80 0 209 699 1834 6382 85 0 210 594 1370 4490
