May 22, 2007 | Special Report on Immigration
Each year, families and individuals pay taxes to the government and receive back a wide variety of services and benefits. A fiscal deficit occurs when the benefits and services received by one group exceed the taxes paid. When such a deficit occurs, other groups must pay for the services and benefits of the group in deficit. Each year, government is involved in a large-scale transfer of resources between different social groups.
Fiscal distribution analysis measures the distribution of total government benefits and taxes in society. It provides an assessment of the magnitude of government transfers between groups. This paper provides a fiscal distribution analysis of households headed by immigrants without a high school diploma. It measures the total benefits and services received by this group and the total taxes paid. The difference between benefits received and taxes paid represents the total resources transferred by government on behalf of this group from the rest of society.
The first step in an analysis of the distribution of benefits and taxes is to count accurately the cost of all benefits and services provided by the government. The size and cost of government is far larger than many people imagine. In fiscal year (FY) 2004, the expenditures of the federal government were $2.3 trillion. In the same year, expenditures of state and local governments were $1.45 trillion. The combined value of federal, state, and local expenditures in FY 2004 was $3.75 trillion.
The sum of $3.75 trillion is so large that it is difficult to comprehend. One way to grasp the size of government more readily is to calculate average expenditures per household. In 2004, there were some 115 million households in the U.S. (This figure includes multi-person families and single persons living alone.) The average cost of government spending thus amounted to $32,707 per household across the U.S. population.
The $3.75 trillion in government expenditure is not free, but must be paid for by taxing or borrowing economic resources from Americans or by borrowing from abroad. In general, government expenditures are funded by taxes and fees. In FY 2004, federal taxes amounted to $1.82 trillion. State and local taxes and related revenues amounted to $1.6 trillion. Together, federal, state, and local taxes amounted to $3.43 trillion. At $3.43 trillion, taxes and related revenues came to 91 percent of the $3.75 trillion in expenditures. The gap between taxes and spending was financed by government borrowing.
Types of Government Expenditure
After the full cost of government benefits and services has been determined, the next step in the analysis of the distribution of benefits and taxes is to determine the beneficiaries of specific government programs. Some programs, such as Social Security, neatly parcel out benefits to specific individuals. With programs such as these, it is relatively easy to determine the identity of the beneficiary and the cost of the benefit provided. At the opposite extreme, other government programs (for example, medical research at the National Institutes of Health) do not neatly parcel out benefits to individuals. Determining the proper allocation of the benefits of that type of program is more difficult.
To ascertain most accurately the distribution of government benefits and services, this study begins by dividing government expenditures into six categories: direct benefits, means-tested benefits, educational services, population-based services, interest and other financial obligations resulting from prior government activity, and pure public goods.
Direct benefit programs involve either cash transfers or the purchase of specific services for an individual. Unlike means-tested programs (described below), direct benefit programs are not limited to low-income persons. By far the largest direct benefit programs are Social Security and Medicare. Other substantial direct benefit programs are Unemployment Insurance and Workmen's Compensation.
Direct benefit programs involve a fairly transparent transfer of economic resources. The benefits are parceled out discretely to individuals in the population; both the recipient and the cost of the benefit are relatively easy to determine. In the case of Social Security, the cost of the benefit would equal the value of the Social Security check plus the administrative costs involved in delivering the benefit.
Calculating the cost of Medicare services is more complex. Ordinarily, government does not seek to compute the particular medical services received by an individual. Instead, government counts the cost of Medicare for an individual as equal to the average per capita cost of Medicare services. (This number equals the total cost of Medicare services divided by the total number of recipients.) Overall, government spent $840 billion on direct benefits in FY 2004.
Means-tested programs are typically termed welfare programs. Unlike direct benefits, means-tested programs are available only to households below specific income thresholds. Means-tested welfare programs provide cash, food, housing, medical care, and social services to poor and low-income persons.
The federal government operates over 60 means-tested aid programs. The largest of these are Medicaid; the Earned Income Tax Credit (EITC); food stamps; Supplemental Security Income (SSI); Section 8 housing; public housing; Temporary Assistance to Needy Families (TANF); the school lunch and breakfast programs; the WIC (Women, Infants, and Children) nutrition program; and the Social Services Block Grant (SSBG). Many means-tested programs, such as SSI and the EITC, provide cash to recipients. Others, such as public housing or SSBG, pay for services that are provided to recipients.
The value of Medicaid benefits is usually counted in a manner similar to Medicare benefits. Government does not attempt to itemize the specific medical services given to an individual; instead, it computes an average per capita cost of services to individuals in different beneficiary categories such as children, elderly persons, and disabled adults. (The average per capita cost for a particular group is determined by dividing the total expenditures on the group by the total number of beneficiaries in the group.) Overall, the U.S. spent $564 billion on means-tested aid in FY 2004.
Government provides primary, secondary, post-secondary, and vocational education to individuals. In most cases, the government pays directly for the cost of educational services provided. In other cases, such as the Pell Grant program, the government in effect provides money to an eligible individual who then spends it on educational services.
education is the single largest component of state and local government spending, absorbing roughly a third of all state and local expenditures. The average per pupil cost of public primary and secondary education is now around $9,600 per year. Overall, federal, state, and local governments spent $590 billion on education in FY 2004.
Whereas direct benefits, means-tested benefits, and education services provide discrete benefits and services to particular individuals, population-based programs generally provide services to a whole group or community. Population-based expenditures include police and fire protection, courts, parks, sanitation, and food safety and health inspections. Another important population-based expenditure is Transportation, especially roads and highways.
A key feature of population-based expenditures is that such programs generally need to expand as the population of a community expands. (This quality separates them from pure public goods, described below.) For example, as the population of a community increases, the number of police and firemen will generally need to expand in proportion.
In its study of the fiscal costs ofimmigration, The New Americans, the National Academy of Sciences argued that if service remains fixed while the population increases, a program will become "congested," and the quality of service for users will deteriorate. Thus, the NAS uses the term "congestible goods" to describe population-based services. Highways are an obvious example of this point. In general, the cost of population-based services can be allocated according to an individual's estimated utilization of the service or at a flat per capita cost across the relevant population.
A sub-category of population-based services is government administrative support functions such as tax collections and legislative activities. Few taxpayers view tax collection as a government benefit; therefore, assigning the cost of this "benefit" appears problematic.
The solution to this dilemma is to conceptualize government activities into two categories: primary functions and secondary functions. Primary functions provide benefits directly to the public; they include direct and means-tested benefits, education, ordinary population-based services such as police and parks and public goods. By contrast, secondary or support functions do not provide direct benefits to the public but do provide necessary support services that enable the government to perform primary functions. For example, no one can receive food stamp benefits unless the government first collects taxes to fund the program. Secondary functions can thus be considered an inherent part of the "cost of production" of primary functions, and the benefits of secondary support functions can be allocated among the population in proportion to the allocation of benefits from government primary functions.
Government spent $662 billion on population-based services in FY 2004. Of this amount, some $546 billion went for ordinary services such as police and parks, and $116 billion went for administrative support functions.
This appendix documents the methods used to calculate the spending and tax figures presented in the paper. Throughout, the term "low-skill immigrant households" is used as a synonym for households headed by immigrants without a high school degree.
Data on federal expenditures were taken from Historical Tables, Budget of the United States Government, Fiscal Year 2006. Data on federal taxes and revenues were taken from Analytical Perspectives, Budget of the United States Government, Fiscal Year 2006.
State and local aggregate expenditures and revenue data were taken from the U.S. Bureau of Census survey of government finances and employment. Added information on state and local spending categories was taken from U.S. Census Bureau, Federal State and Local Governments: 1992 Government Finance and Employment Classification Manual.
Detailed information on means-tested spending was taken from Congressional Research Service, Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY 2002-FY 2004. This report provides important information on state and local means-tested expenditures from states' and localities' own financial resources as distinct from expenditures funded by federal grants in aid.
Data on Medicaid expenditures for different recipient categories were taken from the Medicaid Statistical Information System (MSIS) as published in Medicare & Medicaid Statistical Supplement, 2006. Data on the distribution of benefits and distribution of some taxes were taken from the U.S. Census Bureau's Current Population Survey (CPS)of March 2005 (which covers the year 2004). Additional data on public school attendance were taken from the October 2004 Current Population Survey. Data on household expenditure were taken from the Bureau of labor Statistics Consumer Expenditure Survey(CEX) for 2004.
Data on Medicaid expenditures in institutional long-term care facilities were taken from Medicare & Medicaid Statistical Supplement, 2006. Data on the education levels of elderly persons in institutional long-term care facilities were taken from the National Long Term Care Survey (NLTCS). Data on the number of individuals residing in nursing homes in the average month and the number of Medicaid recipients in nursing homes were taken from the 2004 National Nursing Home Survey (NNHS). Data on the number of individuals in other types of institutions were taken from Census 2000 Summary File 1. Information on illegal immigrants was taken primarily from The Size and Characteristics of the Unauthorized Migrant Population in the U.S.: Estimates Based on the March 2005 Current Population Survey, prepared by the Pew Hispanic Center.
Count of Households
The Current Population Survey (CPS) reports some 113.15 million households in the U.S. in 2004. In addition, in the average month in 2004, 1.65 million persons resided in long-term care institutions: 1.49 million were in nursing facilities, and 155,000 were in intermediate care facilities for the mentally retarded (ICF-MR). These long-term care residents were not included in the population reported in the CPS; however, because these individuals are the beneficiaries of a substantial share of Medicaid expenditure, it is important that they be included in any accounting of fiscal balances and distribution. Consequently, the 1.65 million persons in long-term care facilities were included in the present analysis; each individual in such a facility was counted as a separate household, swelling the overall count of households from 113.15 million to 114.8 million.
There are no direct data available on the share of persons in institutional care facilities who were immigrants; therefore, the low-skill immigrant share of this population was estimated in the following way. The share of adults aged 18 to 64 in nursing facilities who were low-skill immigrants was assumed to equal the low-skill immigrant share of all adults in this age range in the general population in the CPS (4.9 percent). The share of children from low-skill immigrant families residing in nursing facilities and ICF-MR was assumed to equal the share of children from low-skill immigrant families among all children in the general population in the CPS (7 percent). The share of elderly persons in nursing facilities who were low-skill immigrants was estimated by multiplying the share of elderly persons in nursing homes who lacked a high school degree (48 percent) by the share of elderly persons without a high school degree in the general population in the CPS who were immigrants (17.4 percent). This yielded an estimated low-skill immigrant share of elderly persons in nursing facilities of 8.4 percent.
Altogether, 120,00 low-skill immigrants or minor children of low-skill immigrant families were estimated to reside in long-term care facilities in FY 2004; over 90 percent of these individuals were elderly. (The calculations are shown in Appendix Table 7.) Each of these individuals was counted as a separate household, raising the number of low-skill immigrant households from 4.4 million to 4.5 million.
The 120,000 low-skill immigrants or minor children from low-skill immigrant households constituted 7.2 percent of persons in institutional care; this was higher than the share of persons in low-skill immigrant households in the general population (5.4 percent). The disproportionate number of low-skill immigrants in institutional care is due to the disproportionate number of elderly immigrant dropouts estimated to be in institutional care; the estimated high number of poorly educated elderly immigrants in institutional care is consistent with the fact that the CPS shows that a disproportionate share of Medicaid expenditures on the elderly in the general population (9.6 percent) goes to low-skill immigrant households.
The share of Medicaid expenditures going to low-skill immigrants in institutional care settings was calculated separately for eight specific sub-categories. These calculations are described in Appendices B and C.
Calculating Aggregate Federal, State, and Local Spending
Aggregate federal expenditures at the sub-function level were taken from Historical Tables, Budget of the United States Government, FY 2007. These data are presented in Appendix Table 1. State and local aggregate expenditures were based on data from the U.S. Bureau of Census survey of government.
Two modifications were necessary to yield an estimate of the overall combined spending for federal, state, and local government. First, some $408 billion in state and local spending is financed by grants in aid from the federal government. Since these funds are counted as federal expenditures, recording them again as state and local expenditure would constitute a double count. Consequently, federal grants in aid were deducted from the appropriate categories of state and local spending.
A second modification involves the treatment of market-like user fees and charges at the state and local levels. These transactions involve direct payment of a fee in exchange for a government service: for example, payment of an entry fee at a park. User fees are described in the federal budget in the following manner:
[I]n addition to collecting taxes…the Federal Government collects income from the public from market-oriented activities and the financing of regulatory expenses. These collections are classified as user charges, and they include the sale of postage stamps and electricity, charges for admittance to national parks, premiums for deposit insurance, and proceeds from the sale of assets such rents and royalties for the right to extract oil from the Outer Continental Shelf.
In the federal budget, user fees are not counted as revenue, and the government services financed by user fees are not included in the count of government expenditures. As the Office of Management and Budget states:
[User charges] are subtracted from gross outlays rather than added to taxes on the receipts side of the budget. The purpose of this treatment is to produce budget totals for receipts, outlays, and budget authority in terms of the amount of resources allocated governmentally, through collective political choice, rather than through the market.
In contrast, Census tabulations of state and local government finances include user fees as revenue and also include the cost of the service provided for the fee as an expenditure. The most prominent user fees treated in this manner in the Census state and local government financial data are household payments to public utilities for water, power, and sanitation services.
But market-like, user fee payments of this type do not involve a transfer of resources from one group to another or from one household to another. In addition, government user fee transactions do not alter the net fiscal deficit or surplus of any household (defined as the cost of total government benefits and services received minus total taxes and revenues paid) because each dollar in services received will be matched by one dollar of fees paid. Finally, determining who has paid a user fee and received the corresponding service is very difficult.
For these reasons, this paper has applied the federal accounting principle of excluding most user fees from revenue tallies and excluding the services funded by the fees from the count of expenditures to state and local government finances. This means that user charges and fees were removed from both the revenue and expenditure tallies for state and local government. As noted, the inclusion or exclusion of these user fees has no effect on the fiscal deficit figures for low-skill immigrant households presented in this paper.
Appendix Tables 2A, 2B, and 2C show the deductions of federal grant in aid and user fee expenditures that yielded the state and local expenditure totals used in this analysis.
Estimating the Allocation of Direct and Means-Tested Benefits
In most cases, the dollar cost of direct benefits and means-tested benefits received by low-skill immigrant households was estimated by the dollar cost of benefits received as reported in the Census Bureau's Current Population Survey (CPS). One problem with this approach is that the CPS underreports receipt of most government benefits. This means that the aggregate dollar cost of benefits for a particular program as reported in the CPS is generally less than the actual program expenditures according to government budgetary data.
To be accurate, any fiscal analysis must adjust for benefit underreporting. This has been done in prior studies; for example, the National Academy of Sciences study of the fiscal costs ofimmigration, The New Americans, made an adjustment for such underreporting.
The current analysis adjusts for underreporting in the CPS with a simple mathematical procedure that increases overall spending on any given program to equal actual aggregate spending levels and increases expenditures on low-skill immigrant households in an equal proportion. Let:
Etx = total expenditures for program x reported in the CPS;
Elx = expenditures for program x for low-skill immigrant households reported in the CPS;
Ebx = total expenditures for program x according to independent budgetary sources; and
Hl = number of low-skill immigrant households in the CPS.
The share of expenditures reported in the CPS received by low-skill immigrant households would equal Elx/Etx. The actual expenditures allocated to low-skill immigrant households would be estimated to equal (Elx/Etx) times Ebx.
The average per household benefit from the program received by low-skill immigrant households would equal:
(Elx/Etx) times (Ebx /Hl)
For example, if the CPS reported that low-skill immigrant households received 10 percent of food stamp benefits and the total expenditures on food stamps according to budgetary data were $20 billion, low-skill immigrant households would be estimated to receive $2 billion in food stamp benefits. If there were 4 million low-skill immigrant households, the average food stamp benefit per low-skill household would equal $2 billion divided by 4 million households, or $500.
The key assumption behind this underreporting adjustment procedure is that low-skill immigrant households underreport receipt of welfare and other government benefits at roughly the same rate as the general population. For example, if receipt of food stamps is underreported by 15 percent in the CPS for the overall population, the adjustment procedure assumes that the sub-group of low-skill immigrant households in the CPS would also underreport food stamp receipt by 15 percent. The average level of food stamp benefits among low-skill immigrant households as reported in the CPS is then adjusted upward by this ratio to compensate for the underreporting. Since there is no evidence to suggest that low-skill immigrant households underreport government benefits to the Census at a rate different from that of the general population, this procedure appears valid as an estimating technique.
Estimating the Allocation of education Expenditures
The average cost of public education services was calculated in a somewhat different manner since the CPS reports whether an individual is enrolled in a public school but does not report the cost of education services provided. Consequently, data from the Census survey of governments were used to calculate the average per pupil cost of public primary and secondary education in each state. The total governmental cost of primary and secondary schooling for each household was then estimated by multiplying the number of enrolled pupils in the household by the average per pupil cost in the state where the household resides.
This procedure yielded estimates of total public primary and secondary education costs for low-skill immigrant households in the CPS and for the whole population in the CPS. Adjustments for misreporting in the CPS were made according to the procedures outlined above. Public costs for post-secondary education were allocated in a similar manner.
Estimating the Allocation of Medical Expenditures
There is often confusion concerning the calculation of the cost of Medicaid and Medicare benefits by the Census. The Census makes no effort to determine the costs of medical treatments given to a particular person. Instead, it calculates the average cost of Medicaid or Medicare benefits per person for a particular demographic/beneficiary group. For example, per capita Medicaid costs for children are very different from those for the elderly. The Census assigns the appropriate per capita Medicaid or Medicare costs to each individual who reports coverage in the CPS according to the individual's beneficiary class: for example, elderly, children, non-elderly able-bodied adults, and disabled adults.
Allocation of Medicaid expenditures is complicated by the fact that a significant portion of those expenditures goes to persons in long-term care institutions who are not counted in the CPS. In the average month in 2004, some 1.65 million persons resided in long-term care institutions; about 62 percent of these individuals received Medicaid assistance. The first step in allocating Medicaid expenditures is to determine the share of expenditures going to institutionalized and non-institutionalized persons within each of four primary recipient categories: elderly, children, non-elderly disabled adults, and non-elderly able-bodied adults. The procedures for determining this are presented in Appendix C. Once the separation of institutional and non-institutional Medicaid expenditures has been determined, the low-skill immigrant share of Medicaid spending in the general/non-institutional population can be determined for each of the recipient categories directly from CPS data.
For persons in institutions, additional sources of information are used in the estimates according to procedures described in Appendix B. In general, the analysis assumes that for each recipient category, the share of Medicaid expenditure going to immigrants without a high school degree will equal the low-skill immigrant share of Medicaid expenditures for the same recipient category in the general/non-institutional population as measured in the CPS.
In FY 2004, some $46 billion in Medicaid funds was spent on elderly individuals in nursing homes and other institutional long-term care facilities, of which nearly 60 percent was spent on Medicaid recipients without a high school degree; of the spending going to elderly residents without a high school degree, an estimated 22.7 percent went to immigrants without a high school degree. (See Appendix C.)
Estimating the Allocation of Population-Based Services
Wherever possible, this analysis has allocated the cost of population-based services for low-skill immigrant households in proportion to their estimated utilization of those services. For example, the proportionate utilization of roads andhighways by low-skill immigrant households was estimated, in part, on the basis of their share of gasoline purchases as estimated in the Consumer Expenditure Survey (CEX).
When an estimate of proportionate utilization was not possible, the cost of population-based services was allocated on a uniform per capita basis. Some population-based services, such as airports, will be used infrequently by low-skill immigrant households; in these cases, the cost of the service for low-skill immigrant households was set at zero or at an arbitrary low level.
Allocation of the Costs of General
Government and Administrative Support Services
Allocation of the costs of general government services such as tax collections and legislative functions presents difficulties since there is apparently no one who directly benefits from those services. Most taxpayers would regard IRS collection activities as a burden, not a benefit; however, while government administrative functions per se do not benefit the public, they do provide a necessary foundation that makes all other government benefit and service programs possible. A household that receives food stamp benefits, for example, could not receive those benefits unless the IRS had collected the tax revenue to fund the program in the first place.
It seems reasonable to integrate proportionally the cost of government support services into the cost of other government functions that depend on those services. Following this reasoning, the expenditures for general government and administrative support have been allocated among households in the same proportions that total direct benefits, means-tested benefits, education, and population-based services are distributed among households.
Estimating the Allocation of Financial Obligations Relating to Past Government Activities
Year by year, throughout most of the post-war period, U.S. taxpayers have not paid for the full cost of benefits and services provided by government. A portion of annual costs is passed on to be paid in future years. Government costs are shifted to future years through two mechanisms.
First, when government expenditure exceeds revenue, the government runs a deficit and borrows funds. The cost of borrowing is passed to future years in the form of interest payments and repayments of principal on public debts.
Second, when a government employee provides a service to the public, part of the cost of that service is paid for immediately through the employee's salary, but the employee may also receive government retirement benefits in the future in compensation for services provided in the present. Expenditures on public-sector retirement systems are thus, to a considerable degree, present payments in compensation for services delivered in the past.
interest payments on government debt are largely fixed by past government borrowing; an immigrant's entry into the U.S. does not cause interest payments to increase. While direct benefits, means-tested benefits, public education, and population-based services all will tend to increase as additional low-skill immigrants take up residence in the U.S., interest on government debt and similar obligations are largely unaffected in the intermediate-term future by increases in the number of immigrants. For that reason, this report does not include interest on the debt and similar costs in the primary net tax burden calculations presented in this paper. This is consistent with methods employed by the National Academy of Sciences in its assessment of the fiscal costs of immigrants in The New Americans.
Estimating the Distribution of Pure Public Goods
Government pure public goods include expenditures on defense, veterans, international affairs, scientific research, and part of spending on the environment, as well as debt obligations relating to past public good spending. The total cost of pure public goods was divided by the whole U.S. population to determine an average per capita cost.
The fact that an immigrant enters the U.S. and benefits from governmental public good expenditures does not increase costs or diminish the utility of public goods spending for other taxpayers. Because of this, the low-skill immigrant share of public goods spending has not been included in the net tax burden calculations presented in this paper. This is consistent with methods employed by the National Academy of Sciences in its assessment of the fiscal costs of immigrants in The New Americans.
Estimating the Distribution of taxes and Other Government Collections
The distribution of federal and state income taxes was calculated from CPS data. The Census imputes tax payments into the CPS based on a household's income and demographic characteristics and the appropriate federal and state tax rules; however, since income is underreported in the CPS, this means that imputed taxes will also be too low. Thus, the imputed tax payments in the CPS were adjusted to equal the aggregate income tax revenues reported in government budgetary documents. (Federal revenue totals were taken from Analytical Perspectives, Budget of the U.S. Government, Fiscal Year 2006. State and local tax and revenue data were taken from the U.S. Census survey of governments.)
The procedures for adjusting for the underreporting of income taxes were the same as those used to adjust for underreporting of expenditures. For example, for federal income tax, let:
Tt = total income tax reported in the CPS;
Tl = total income tax for low-skill immigrant households reported in the CPS;
Tb = total income tax according to independent budgetary sources; and
Hl = number of low-skill immigrant households in the CPS.
The share of taxes paid by low-skill immigrant households as reported in the CPS would equal Tl /Tt. The actual expenditures allocated to low-skill immigrant households would be estimated to equal (Tl /Tt ) times Tb.
The average paid per low-skill household would equal:
(Tl /Tt ) times (Tb/Hl)
State income taxes were adjusted for underreporting according to the same formula.
Employees were assumed to pay both the "employee" and "employer" share of FICA taxes. Allocation of FICA taxes was estimated based on the distribution reported in the CPS, adjusted for underreporting in the manner described above.
The incidence of federal and state corporate profits tax was assumed to fall 70 percent on workers and 30 percent on owners of capital. The workers' share was allocated according to the distribution of earnings in the CPS; the owners' share was allocated according to the allocation of property income in the CPS.
Sales and excise taxes were assumed to fall on the consumer; tax payments were estimated based on the share of total consumption of relevant commodity or commodities in the Consumer Expenditure Survey (CEX). For example, since the CEX reported that households headed by persons without a high school degree consumed 18.2 percent of the sales of tobacco products, these same households were estimated to pay a corresponding 18.2 percent of all excise and sales taxes on tobacco products. Additional information on specific taxes is provided below.
Estimating Consumption by Low-Skill Immigrant Households
Many tax and expenditure calculations in this paper require an estimate of consumption of various items by low-skill immigrant households based on CEX data. An earlier version of this analysis measured the fiscal impact of all households headed by persons without a high school degree (both immigrants and non-immigrants). Measuring the consumption of these households was easy because the CEX identifies households according to the education level of the household head; however, the CEX does not report the immigration status of the head of the household.
The present paper circumvents this problem by using low-skill Hispanic households in the CEX as a proxy group to estimate the consumption of low-skill immigrant households. There is considerable overlap between low-skill Hispanic households (meaning households headed by Hispanics without a high school degree) and low-skill immigrant households. It seems reasonable, therefore, to assume that the consumption of various goods as a percentage of income is similar between the two groups. For example, if food consumption as a share of income for Hispanic households headed by persons without a high school degree is known from the CEX, a similar figure can be estimated for low-skill immigrant households after adjusting for modest differences in income between the two groups.
The consumption of various goods by low-skill immigrant households was therefore estimated by taking the aggregate consumption of that good by low-skill Hispanic households and multiplying by the ratio of aggregate low-skill immigrant income to low-skill Hispanic income in the CPS. For any consumption good1 let:
CTCEX = Total Dollar Value of Consumption of Item1 in CEX for Whole Population;
CLH1 =Total Dollar Value of Consumption of Item1 in CEX by Low-Skill Hispanic Households;
CLI1 = Derived Total Dollar Value of Consumption of Item1 by Low-Skill Immigrant Households;
YLH = Total Income of Low Skill Hispanic Households in CPS;
YLI = Total Money Income of Low Skill Immigrant Households in CPS.
CLI1 = YLI times CLH1 /YLH
The low-skill immigrant share of total consumption of the good would equal:
It might be argued that, despite the considerable overlap between low-skill immigrant households and households headed by Hispanics without a high school degree, the procedure outlined above overestimates the consumption of low-skill immigrants because immigrants are likely to send a substantial portion of their income back to their native country in remittances, whereas non-immigrants of similar education status will spend all of their income in the U.S. If this argument is correct, it would mean that the fiscal deficit estimates in this paper are somewhat too low. If low-skill immigrant households consume less than this model estimates, amount of government services received and consumption taxes paid by low-skill households would be reduced. But the drop in tax payments would be substantially larger than the reduction in benefits. For example, if the consumption level of low-skill immigrant households was 20 percent below the level assumed in this report, this would result in a $900 per household drop in taxes paid but only a $240 drop in benefits received.
Adjusting the Estimated taxes and Benefits for Illegal Immigrant Households
There were some 11 million illegal immigrants in the U.S. in 2004. About 9.3 million of these individuals were adults, roughly half of whom lacked a high school degree. About 90 percent of illegal immigrants are reported in the CPS. This report covers only those illegal immigrants who are reported in the CPS and does not address the remaining 10 percent not counted by the Census. Assuming that the illegal immigrant households omitted from the CPS are similar to those that are included, incorporation of the missing 10 percent of illegals might raise the aggregate net tax burden imposed by low-skill immigrant households by roughly 4 percent.
Of the 4.5 million low-skill immigrant households analyzed in this report, approximately 41 percent were headed by illegal immigrants. Households headed by illegal immigrants differ from other immigrant households in certain key respects. Illegal immigrants themselves are not eligible for most means-tested welfare benefits, but illegal immigrant households do contain some 3 million children who were born inside the U.S. to illegal immigrant parents; these children are U.S. citizens and are eligible for and do receive means-tested welfare.
Most of the tax and benefits estimates presented in this paper are unaffected by a low-skill immigrant household's legal status. For example, children in illegal immigrant households are eligible for and do receive public education. Similarly, nearly all of the data on direct and means-tested government benefits in the CPS are based on a household's self-report concerning receipt of each benefit by family members; the analysis assumes that if an illegal immigrant household reports receipt of a government benefit, that report is accurate. The fact that low-skill illegal immigrant households are less likely to receive certain types of government benefits is already reflected in lower levels of reported benefit receipt for those households in the CPS; the CPS data will accurately the reflect the limited eligibility for benefits within illegal immigrant households.
However, for two benefit programs, the earned income tax Credit (EITC) and the additional child tax Credit (ACTC), the CPS imputes receipt of benefits rather than relying on self-report of the householder. The EITC is a refundable tax Credit that provides cash to low-income working parents with children. In general, parents must be working lawfully in the U.S. to be eligible for the credit. Since the Census does not distinguish the legal status of parents and assumes that all employment is "on the books," these procedures clearly result in the assignment of EITC benefits to many illegal immigrant families who in reality receive no benefits. The present analysis adjusts for the misallocation of EITC benefits to illegal immigrant households in the CPS; it reduces the share of EITC benefits going to low-skill immigrant households in the CPS by the portion of low-skill immigrant households that are assumed to be illegal (41 percent). ACTC benefits are reduced in a similar manner.
There are also six taxes that are significantly affected by an immigrant household's legal status: the federal income tax, state income tax, FICA tax, worker's compensation tax, federal unemployment insurance tax, and state unemployment insurance tax. The value of income and FICA taxes paid by households is imputed into the CPS by Census analysts according to the household's income demographic characteristics and state of residence. The Census imputation procedures assume that all households work "on the books" and pay taxes owed; however, most analyses assume that nearly half (45 percent) of illegal immigrants work "off the books" and would not therefore pay income or FICA taxes. Any estimate of the FICA, income, workers' compensation, and unemployment insurance taxes paid by low-skill immigrant households must therefore adjust for the tax reduction effect due to the high number of illegal immigrants who work "off the books."
This paper uses an "illegal immigrant adjustment factor" to reduce the estimated tax payments made by low-skill immigrant households. The illegal immigrant adjustment factor was computed as follows: Some 41.5 percent of low-skill immigrant households are assumed to be headed by illegal immigrants; among these, some 45 percent are assumed to work "off the books." Overall, 18.7 percent (45 percent times 41.5 percent) of the income in low-skill immigrant households is assumed to be the result of "off the books" labor on which taxes are not paid. The estimated level of federal income tax, state income tax, FICA tax, worker's compensation tax, and unemployment insurance paid by low-skill immigrant households is therefore reduced by 18.7 percent.
(This procedure is likely to underestimate the level of "off the books" labor in low-skill immigrant households and overestimate the taxes paid because it seems likely that less educated illegal immigrants would be more likely to work informally and "off the books" than would better educated illegal immigrants. Consequently, the "off the books" labor rate for illegal immigrant households headed by high school dropouts may be higher than the overall average of 45 percent.)
Indirect taxes such as sales, excise, and property taxes are determined by household consumption levels as estimated from the CEX and are unaffected by a family's legal status. Similarly, population-based services such as highways, sewers, and fire protection services are allocated on the basis of consumption or on a per capita basis and would be largely unaffected by a household's legal status. It is often reported that illegal immigrants consume less as a share of income and send more money back as remittances to their native countries. If this is true, illegal immigrants will pay less in consumption and property taxes relative to their incomes than will other social groups. However, since the analysis estimates the consumption and property taxes paid by low-skill immigrant households (both legal and illegal) on the basis of the self-reported consumption of low-skill Hispanic households in the CEX (immigrant and non-immigrant), the tendency for immigrant households to consume less and send part of their income abroad in remittances is already, to a considerable degree, built into the analysis. Similarly, population-based services such ashighways, sewers, and fire protection services are allocated on the basis of consumption or on a per capita basis and would be largely unaffected by a household's legal status.
Specific Calculations on Expenditures and taxes
The average cost of government benefits and services per low-skill household was calculated for 61 separate expenditure categories. The algorithms employed for each category are described below, and the specific calculations are shown in Appendix Table 4. Average payments per low-skill household were calculated for 33 specific tax and revenue categories. The algorithm used for each revenue category is described below, and the calculations for each category are presented in Appendix Table 5.
Calculations for Specific Direct Benefit Expenditures
Calculations for Public education
Calculations for Specific Means-Tested Benefit Expenditures
Means-Tested Expenditures in General. Aggregate figures on federal means-tested expenditures were taken from Office of Management and Budget totals in Historical Tables, Budget of the United States Government, Fiscal Year 2006. (See Appendix Table 1.) Federal expenditures on individual means-tested programs are presented in Appendix Table 4 and were taken from Congressional Research Service, Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY2002-FY2004.
Figures on specific state and local means-tested expenditures are presented in Appendix Tables 2A, 2B, 2C, and 3 and were taken from the CRS report. These figures exclude state means-tested expenditures financed by federal grants. An estimated $2.5 billion in state-run General Relief programs was included in the "public assistance" category in Appendix Table 4; these expenditures do not appear in the CRS report because they lack a federal component.
The total means-tested expenditure figure of $564.7 billion, presented in Appendix Table 4, excludes means-tested veterans benefits (which are counted as public good spending) and most means-tested educational spending.
Medicaid Expenditures in General. The Medicaid Statistical Information System (MSIS) reports Medicaid expenditures for four recipient groups: children, disabled non-elderly adults, able-bodied non-elderly adults, and elderly adults. The MSIS data further divide expenditures in each of the four recipient categories into expenditures for individuals in three residential/institutional statuses: recipients in the general population, recipients in nursing facilities, and recipients in intermediate care facilities for the mentally retarded (ICF-MR). The interaction of the four recipient categories and the three residential categories yields 12 overall sub-categories for Medicaid expenditures. Separate calculations were made for each of these 12 sub-categories. The estimation of aggregate Medicaid expenditures in each of the 12 sub-categories is described in Appendix C. The methods for estimating the low-skill immigrant share of Medicaid expenditures in each of the 12 sub-categories are described below.
Medicaid Expenditures on Elderly Persons in the General Population. After the amount of Medicaid spending that went to elderly persons in the general population was determined according to the procedures in Appendix C, the share of those Medicaid expenditures that went to elderly recipients in low-skill immigrant households was calculated directly from CPS data. The following example illustrates the overall equations for estimating Medicaid expenditures for elderly persons in low-skill immigrant households in the general population, incorporating the steps in Appendix B and C. Let:
Mel = Medicaid expenditures for elderly persons residing in low-skill immigrant households in the general population;
Mei = Medicaid expenditures on the elderly in long-term care institutions;
Met = Total Medicaid expenditures on the elderly according to MSIS data;
MSISt = Total Medicaid expenditure according to MSIS data;
CRSt = Total Medicaid expenditure according to Congressional Research Service data; and
CPSe = Share of Medicaid expenditures for elderly persons in the CPS going to elderly persons residing in low-skill immigrant households.
Medicaid expenditures for elderly persons residing in low-skill immigrant households in the general population can then be calculated:
Mel = (Met - Mei) times CRSt/MSISt times CPSe
Expenditures for children, non-elderly disabled adults, and non-elderly able-bodied adults in low-skill immigrant households in the general population were calculated in a similar manner.
Specific Calculations for Population-Based Programs
Calculations for General Government
Support Services for Other Government Programs
Specific Calculations for Financial Obligations Relating to Past Government Activities
As explained in Appendix A, the entry of low-skill immigrants into the U.S. does not raise the costs of interest on public or other financial obligations relating to past government activity (at least in the intermediate term) for other taxpayers. As a consequence, expenditures relating to interest and other obligations are not included in the fiscal deficitscalculations for low-skill immigrants presented in this paper.
Specific Calculations for Public Goods Expenditure
This category includes spending on national defense, international affairs, science and scientific research, veterans programs, natural resources and the environment, and financial obligations relating to past public goods spending. As explained in Appendices A and D, the entry of low-skill immigrants into the U.S. does not raise the costs of public goods for other U.S. taxpayers; therefore, public goods expenditures are not included in the fiscal deficitscalculations presented in this paper.
Specific Calculations for taxes and Revenues
Specific Calculations for Federal taxes and Revenues
Specific Calculations for State and Local taxes and Revenues
Calculating Medicaid expenditures is challenging because about one-quarter of Medicaid spending goes for care for persons in nursing homes and other long-term care and intermediate-care institutions; these individuals are not included in the Current Population Survey. To obtain an accurate account of Medicaid spending, one must carefully separate institutional from non-institutional expenditures and estimate the share of institutional expenditures going to low-skill immigrants.
The Medicaid expenditure calculations in the paper were based on data from the Medical Statistical Information System (MSIS) for 2003, the most recent year available. MSIS separates Medicaid expenditures into four separate recipient categories: elderly, children, non-elderly able-bodied adults, and non-elderly disabled adults. MSIS also separates expenditures into three institutional/residential statuses: residence in the general population, residence in nursing facilities, and residence in Intermediate Care Facilities for the Mentally Handicapped (ICF-MR). Combining the four recipient categories with the three residential statuses yields a total of 12 expenditure sub-categories, each of which has been calculated separately in this paper. Expenditures in each of these 12 sub-categories were calculated by the following steps.
Step One: Allocation of Expenditures to Persons of Unknown Recipient Status. A portion of the Medicaid expenditures goes to individuals whose recipient category is unidentified in the MSIS. These anonymous expenditures were imputed into the four normal recipient categories pro rata according to the distribution of MSIS expenditures to clearly identified recipients.
Step Two: Allocation of Institutional Long-term Care Expenditures to Individuals of Unknown Recipient Status. Within both nursing facility and ICF-MR expenditure categories, a portion of Medicaid spending goes to individuals whose recipient category is unidentified. These expenditures were imputed into the four normal recipient categories pro rata according to the distribution of MSIS nursing facility and ICF-MR expenditures to clearly identified recipients.
Step Three: Inclusion of Ancillary Medical Costs in Institutional Care. MSIS expenditures for care in nursing facilities (NF) and Intermediate Care Facilities (ICF-MR) cover only the cost of residential care in those institutions and do not include Medicaid payments for ancillary medical services, such as drugs, physician, lab, and X-ray services, received by recipients in institutional care. Ancillary expenditures as a percent of institutional long-term care spending vary by recipient group. Ancillary expenditures on children have been estimated to be about 22 percent of this group's facility institutional long-term care costs, about 64 percent for non-elderly able-bodied adults, about 25 percent for non-elderly disabled adults, and about 12 percent for elderly adults. The MSIS figures for expenditures on individuals in institutions were adjusted to include ancillary medical services funded by Medicaid for those individuals; this yielded an adjusted institutional long-term care expenditure total (ALCET) for each of the four recipient categories in nursing facilities (NF) and each of the four recipient categories in ICF-MR.
Calculation of Medicaid Costs for the General Population. The
ALCET for elderly recipients in NF and ICF-MR was subtracted from
the overall MSIS expenditure total for elderly recipients (as
adjusted in step three). This yielded an estimate of residual
Medicaid expenditures on elderly recipients in the general
(non-institutional) population covered by the CPS. The same
procedure was applied to the other three recipient groups in the
general population: children, non-elderly able-bodied adults, and
non-elderly disabled adults.
Step Five: Estimate of the Percent of Medicaid Spending Going to the 12 Sub-categories. The completion of steps three and four generated MSIS expenditures in each of the 12 recipient/residential sub-categories. These figures were converted into percentages of total MSIS Medicaid spending. The results are shown in Appendix Table C1.
Step Six: Adjustment of Aggregate Medicaid Spending to Equal FY 2004 CRS Levels. MSIS data show aggregate Medicaid expenditures of $233 billion in FY 2003. MSIS expenditures fall short of actual Medicaid expenditures because MSIS does not include disproportionate provider payments, some supplemental payments, and administrative costs. In addition, the MSIS expenditure calculations for the different recipient groups are based on FY 2003 data, which are the most recent available, and thus obviously fall short of the FY 2004 levels. The most comprehensive Medicaid expenditures come from the Congressional Research Service, which stated that aggregate federal and state Medicaid expenditures equaled $300.3 billion in FY 2004. The percent share expenditure total for each of the 12 recipient sub-categories in Appendix Table C1 were multiplied by the CRS expenditure total of $300.3 billion to produce the aggregate spending figures for each of the 12 sub-categories presented in Appendix table C2. This adjustment assumes that the difference between MSIS and CRS expenditures is distributed proportionally across the 12 sub-categories.
The Medicaid spending aggregates in Appendix Table C2 for the 12 sub-categories are used in Appendix Table 5 as the bases for calculating expenditures for low-skill immigrant households in each sub-category. The methods for estimating the low-skill immigrant share of expenditures in each of the 12 sub-categories are described in Appendix B.
Pure Public Goods, Private Consumption Goods, and Population-Based Services
Fiscal distribution analysis seeks to determine the government benefits received by a particular group compared to taxes paid. A necessary first step in this process is to distinguish government programs that provide "pure public goods" as opposed to "private goods." These two types of expenditures have very different fiscal implications.
Economist Paul Samuelson is credited with being the first to develop the theory of public goods. In his seminal 1954 paper "The Pure Theory of Public Expenditure," Samuelson defined a pure public good (or what he called in the paper a "collective consumption good") as a good "which all enjoy in common in the sense that each individual's consumption of such a good leads to no subtractions from any other individual's consumption of that good." By contrast, a "private consumption good" is a good that "can be parceled out among different individuals." Its use by one person precludes or diminishes its use by another.
A classic example of a pure public good would be a lighthouse: The fact that any particular ship perceives the warning beacon does not diminish the usefulness of the lighthouse to other ships. A typical example of a private consumption good is a hamburger: When one person eats it, it cannot be eaten by others.
Formally, all pure public goods will meet two criteria:
The second criterion is a direct corollary of the first. If consumption of a good is truly non-rivalrous, then adding extra new consumers will not reduce utility or add costs for the initial consumers.
The distinction between collective and private consumption goods can be illustrated by considering the difference between a recipe for pie and an actual piece of pie. A recipe for pie is a public consumption good in the sense that it can be shared with others without reducing its usefulness to the original possessor; moreover, the recipe can be disseminated to others with little or no added cost. By contrast, an actual slice of pie is a private consumption good: Its consumption by one person bars its consumption by another. Efforts to expand the number of individuals utilizing the pie slice will either reduce the satisfaction of each user (as each gets a smaller portion of the initial) or entail new costs (to produce more pie).
Examples of Governmental Pure Public Goods
Pure public goods are relatively rare. One prime example of a governmental public good is medical research. If research funded by the National Institutes of Health produces a cure for cancer, all Americans will benefit from this discovery. The benefit received by one person is not reduced by the benefit received by others; moreover, the value of the discovery to each individual would remain the same even if the U.S. population doubled.
Another notable example of a pure public good is defense expenditure. The utility of an Army division or and aircraft carrier lies in its effectiveness in combating foreign threats to America. In most respects, one person's benefit from defense strength is not reduced because others also benefit. The military effectiveness of an Army division or an aircraft carrier is not reduced just because the size of the civilian population being defended is increased.
Finally, individuals may receive psychic satisfaction from the preservation of wildlife or wilderness areas. This psychic satisfaction is not reduced because others receive the same benefit and is not directly effected by changes in the population. By contrast, enjoyment of a national park may be reduced if population increases lead to crowding. In consequence, general activities to preserve species may be considered a public good, while provision of parks is a private good.
Pure Public Goods Compared to Population-Based Goods
Many government services that are dubbed public goods are not true public goods. Economists Thomas MaCurdy and Thomas Nechyba state that "relatively few of the goods produced by [the] government sector are pure public goods, in the sense that the cost of providing the same level of the good is invariant to the size of the population." In other words, many government services referred to conventionally as "public goods" need to be increased at added expense to the taxpayer as the population increases, thereby violating the criterion of zero-cost extension to additional users.
For example, police protection is often incorrectly referred to as a "public good." True, police do provide a diffuse service that benefits nearly all members of a community, but the benefit that each individual receives from a policeman is reduced by the claims other citizens may make on the policeman's time. Someone living in a town of 500 protected by a single policeman gets far more protection from that policeman than would another individual protected by the same single policeman in a town of 10,000.
The National Academy of Sciences explains that government services that generally need to be increased as the population increases are not real public goods. It refers to these services as "congestible" goods: If such a program remains fixed in size as the number of users increases, it may become "congested," and the quality of service will consequently be reduced. An obvious example would be highways. Other examples of "congestible" goods are sewers, parks, fire departments, police, courts, and mail service. These types of programs are categorized as "population-based" services in the paper.
In contrast to population-based services, governmental pure public goods have odd fiscal properties. The fact that a low-income person who pays little or nothing in taxes receives benefit from government defense or medical research programs does not impose added cost or reduce the utility of those programs to other taxpayers. Therefore, it is inaccurate to say that the non-taxpayers' use of these programs imposes a burden on other taxpayers. On the other hand, non-taxpayers or individuals who pay little in taxes are "free riders" on public goods in the sense that they benefit from a good for which they have not paid.
The entry of low-skill immigrants into the U.S. does not increase the costs or reduce the utility of public goods for other taxpayers; therefore, public goods spending is not included in the net fiscal deficit calculations for low-skill immigrant households presented in this paper. By contrast, entry of low-skill immigrants does increase costs and reduce the utility of "congestible" or population-based services for other taxpayers; therefore, those expenditures have been included in the net fiscal deficit calculations for low-skill immigrant households presented in this paper.
 See Appendix Tables 1, 2A, 2B, and 2C.
 This figure includes persons in nursing homes. See Appendix A.
 In measuring the distribution of benefits and services, this paper will count the value of each benefit and service as equal to the cost borne by the taxpayer to deliver it. The cost of any benefit to the taxpayer does not necessarily equal the subjective value the beneficiary may place upon the benefit. For example, if the food stamp program provides a family $400 per month in food stamp benefits, the family itself may value the food stamps at more or less than $400. Similarly, if a child receives public education costing $10,000 per pupil per year, the child's family may subjectively value those education services as worth more or less than $10,000. While the question of recipient valuation of government benefits is an interesting one, this paper is concerned with the basic question of the distribution of benefits valued according their costs to taxpayers
 This figure includes property income earned by the government such as sale of assets or interest earned on assets.
 For example, the Census Bureau assigns Medicare costs in this manner in the Current Population Survey.
 Congressional Research Service, Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY2002-FY2004, March 27, 2006.
 This spending figure excludes means-tested veterans programs and most means-tested education programs.
 National Research Council, The New Americans: Economic, Demographic, and Fiscal Effects of Immigration (Washington, D.C.: National Academy Press, 1997), p.303.
 Of this total, an estimated $67 billion represents the costs of financial obligations resulting from past public goods expenditures. These costs are entered in the public goods category in Table 1.
 National Research Council, The New Americans, pp. 302, 303.
 Paul A. Samuelson, "The Pure Theory of Public Expenditure," Review of Economics and Statistics, Vol. 36, No. 4 (1954), pp. 387-389.
 National Research Council, The New Americans, pp. 302, 303.
 Passel, Unauthorized Migrants, p. 2.
 Ibid., p. 6.
 Passel, Unauthorized Migrants, p. 23
 Passel, Ibid., p. 4. The current report does not cover the estimated 1 million illegal immigrants who are not represented in the CPS.
 This figure assumes that the missing illegal immigrant households are similar to those appearing in the CPS. If 41 percent of low-skill immigrant households are illegal, then the addition of 10 percent more illegal immigrant households would boost the overall number of low-skill immigrant households by roughly 4 percent. Presumably, the aggregate net tax burden would increase proportionately.
 A very small number of immigrants who reside in nursing facilities have also been added to the calculations; individuals who reside in nursing facilities do not appear in the CPS. See Appendices A and B.
 Estimate provided by Steven A. Camarota of the Center for Immigration Studies.
 Randy Capp, Everett Henderson, Jeffrey S. Passel, and Michael Fix, Civic Contributions Taxes Paid by Immigrants in the Washington, DC Metro Area, The Urban Institute, May 2006, p. 6, fn. 3, at www.urban.org/UploadedPDF/411338_civic_contributions.pdf; Jeffrey S. Passel, Rebecca L. Clark, Immigrants in New York: Their Legal Status, Income and Taxes, Urban Institute, 1998, at www.urban.org/publications/ 407432.html. Camarota, The High Cost of Low-skill Labor.
 Passel, Unauthorized Migrants, Camarota, The High Cost of Low-skill Labor.
 George J. Borjas, Heaven's Door: Immigration Policy and the American Economy (Princeton, N.J.:Princeton University Press, 1999), p. 27.
 Ibid., p. 8.
 This calculation assumes the low-skill immigrant remains in the U.S. for his full life.
 An alternative approach to calculating lifetime fiscal costs is to multiply the average fiscal cost per age category by the expected survival rate of householders from age 25 on; this allows the number of households to shrink slowly as the heads of household age. This approach also yields a net lifetime fiscal burden of around $1.2 million. Figures are available upon request.
 This figure excludes non-immigrant adults in these households.
 The Social Security retirement age will be raised to 67 in 2022.
 It would be possible for some low-skill immigrants to obtain eligibility for Social Security and Medicare and then return home; this would remain very costly for U.S. taxpayers, though perhaps slightly less costly than if the immigrant remained in the U.S.
 Walter A. Ewing and Benjamin Johnson, "Dollars without Sense: Underestimating the Value of Less-Educated Workers," Immigration Policy Center, May 2007, p. 1.
 National Research Council, The New Americans.
 Technically, the intergenerational fiscal impact of low-skill immigrants would equal the net present value of the fiscal losses and gains of the first and subsequent generations of immigrants. Using a net present value approach, the fiscal surplus in the second generation would need to be greater than $19,500 per household per year in order to generate an overall surplus by the end of the second generation.
 National Research Council, The New Americans, p. 334 (table 7.5) and p. 328 (figure 7.10).
 In 2004, 2 percent of profits, rental, and interest income equaled around $36 billion. Assuming a 40 percent aggregate tax rate on this income, total taxes would equal around $11.4 billion. Subtracting the worker's share of corporate profits tax, which is already included in the basic calculations in Appendix table 5, would yield around $11 billion in indirect tax revenue. These should be considered very preliminary and uncertain estimates.
 George J. Borjas, "The Labor Demand Curve Is Downward Sloping: Reexamining the Impact of Immigration on the Labor Market," Quarterly Journal of Economics, November 2003, pp. 1335-1374.
 Edwin Meese III and Matthew Spalding, "The Principles of Immigration," Heritage Foundation Backgrounder No. 1807, October 19, 2004. See also, Edwin Meese III and Matthew Spalding, "Where We Stand: Essential Requirements for Immigration Reform," Heritage Foundation Backgrounder No.2034, May 10, 2007. Robert Rector, "Amnesty and Continued Low-Skill Immigration Will Substantially Raise Welfare Costs and Reduce Poverty," Heritage Foundation Backgrounder No, 1936, May 16, 2006, p. 13.
 A temporary guest worker program must limited in scope and limited in duration; it must not be a pathway to legal permanent residence and citizenship; guest workers should not bring their families to the U.S., since the inclusion of families would greatly increase costs to U.S. taxpayers, and the policy of birthright citizenship should not apply to children born to guest workers temporarily in the U.S.; participants should not be entitled to U.S. welfare and should not become eligible for future Social Security and Medicare benefits; employers should be required to cover medical costs of workers while they are in the U.S. Edwin Meese III and Matthew Spalding Ph.D., "Permanent Principles and Temporary Workers," Heritage Foundation Backgrounder No.1911, March 1, 2006.
 Robert Rector, "Senate Immigration Bill Would Allow 100 Million New Legal Immigrants over the Next Twenty Years," Heritage Foundation WebMemo No. 1076, May 15, 2006.
 John C. Eastman, Ph.D., "From Feudalism to Consent: Rethinking Birthright Citizenship," Heritage Foundation Legal Memorandum No. 18, March 30, 2006. Robert Rector, "Amnesty and Continued Low-Skill Immigration Will Substantially Raise Welfare Costs and Reduce Poverty," Heritage Foundation Backgrounder No 1936, May 16, 2006.
 Passel, The Size and Characteristics of the Unauthorized Migrant Population in the U.S.
 Eligibility for Social Security is granted after 40 quarters (ten years) of lawful employment.
 Robert Rector, "Amnesty and Continued Low-Skill Immigration Will Substantially Raise Welfare Costs and Reduce Poverty," Heritage Foundation Backgrounder No 1936, May 16, 2006. Robert Rector "Importing Poverty: Immigration and Poverty in the United States," Heritage Foundation Special Report No. 9, October, 25, 2006, p. 29.
 Office of Management and the Budget, Historical Tables, Budget of the United States Government, Fiscal Year 2006.
 Office of Management and the Budget, Analytical Perspectives, Budget of the United States Government, Fiscal Year 2006, pp. 299-313.
 Congressional Research Service, Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY 2002-FY 2004, March 27, 2006.
 U.S. Department of Health and Human Services, Centers for Medicare and Medicaid Services, Medicare & Medicaid Statistical Supplement, Medicaid Tables 14.1-14.27, 2006. This survey covers 2003.
 U.S. Department of Labor, U.S. Bureau of Labor Statistics, Consumer Expenditure in 2004, Report 992, April 2006.
 U.S. Department of Health and Human Services, Centers for Medicare and Medicaid Services, Medicare & Medicaid Statistical Supplement, Medicaid Tables 14.1-14.27, 2006.
 Duke University and National Institutes of Health, National Institute on Aging, National Long Term Care Survey, 1999 Public Use Data Files National Long Term Care Study (NLTCS), 1999 public use dataset. Produced and distributed by the Duke University Center for Demographic Studies with funding from the National Institute on Aging under Grant No. U01-AG007198. The NLTCS is a nationally representative sample of individuals ages 65 years and older in long-term care facilities.
 U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, 2004 National Nursing Home Survey (NNHS), public use files, and U.S. Census Bureau, 2000 Census Summary File (SF 1), PCT16, PCT17-PCT17I.
 Jeffrey S. Passel, The Size and Characteristics of the Unauthorized Migrant Population in the U.S.: Estimates Based on the March 2005 Current Population Survey, Pew Hispanic Center, March 7, 2006. See also Jeffrey S. Passel, Unauthorized Migrants: Numbers and Characteristics, Pew Hispanic Center, June 14, 2005.
 These are estimates for the number of individuals in long-term care institutions at a given point in time during the year. The number of individuals who reside in such institutions at any time during the year would be higher.
 On any given day, some 1.49 million individuals reside in long-term care nursing facilities, according to the 2004 National Nursing Home Survey. In addition to individuals in nursing facilities, some 155,000 other individuals live in other types of long-term care facilities, according to the 2000 Census. The majority of these individuals reside in wards, hospitals, and other facilities for the handicapped.
 Unpublished estimates calculated by the authors using the 1999 National Long Term Care Study (NLTCS).
 The 120,000 low-skill immigrants in institutional care was added to the denominator for all calculations concerning benefits or taxes per low-skill immigrant household. The 120,000 low-skill immigrants and 1.65 million persons in general in institutional care were included in all calculations based on share of the population. Low-skill immigrants in institutional care are assumed to pay neither FICA nor income tax. Individuals in institutional care were not included in the calculations concerning population-based services or indirect taxes using Consumer Expenditure Survey data; this omission will have little or no effect on the figures in this report.
 Office of Management and Budget, Analytical Perspectives, Budget of the United States Government, Fiscal Year 2006, p. 301.
 U.S. Census Bureau, Federal State and Local Governments: 1992 Government Finance and Employment Classification Manual, sections 3.31 and 7.24.
 National Research Council, The New Americans: Economic, Demographic, and Fiscal Effects of Immigration (Washington, D.C.: National Academy Press, 1997), p.308.
[64 ]If CPS underreports benefits by 15 percent, the underreporting would be corrected by multiplying the CPS total by the inverse of 100 percent minus 15 percent (the inverse of 85 percent).
 U.S. Census Bureau, Governments Division, Public Education Finances, 2004, issued March 2006. Costs included both current expenditures and capital outlays.
 In the average month in 2004, about 1.49 million individuals resided in nursing homes; another estimated 155,000 individuals resided in long-term care institutions other than nursing homes.
 The 62 percent statistic comes from the 2004 National Nursing Home Survey (NNHS). This analysis assumes that the share of Medicaid recipients in other types of long-term care institutions is equal to the share of Medicaid recipients in nursing homes.
 Estimates based on FY 2003 MSIS expenditure data, as published in Medicare & Medicaid Statistical Supplement, 2006, and adjusted to equal actual FY 2004 expenditure levels as reported by the CRS. The spending figure includes a 12 percent increase for ancillary medical services. See Appendix B.
 Some 98 percent of Medicaid's institutional long-term care expenditures on the elderly went to elderly persons in nursing facilities. The National Long Term Care Study showed that 59 percent of elderly Medicaid recipients in nursing facilities lacked a high school degree.
 Approximately 27 percent of total federal expenditure is devoted to pure public good functions; thus, 27 percent of federal support service expenditure was assumed to assist public good functions.
 National Research Council, The New Americans, p. 304.
 Office of Management and Budget, Analytical Perspectives, Budget of the United States Government, Fiscal Year 2006, pp. 299-323.
 William C. Randolph, "International Burdens of the Corporate Income Tax," Congressional Budget Office Working Paper No. 2006-09, 2006.
 Robert Rector, Christine Kim, and Shanea Watkins, The Fiscal Cost of Low-Skill Households to the U.S. Taxpayer, Heritage Foundation Special Report No. SR-12, April 4, 2007.
 Passel, The Size and Characteristics of the Unauthorized Migrant Population in the U.S , p. 1.
 Ibid., p.7.
 Passel, Unauthorized Migrants, p. 23.
 Ibid., p. 4. The current report does not cover the estimated 1 million illegal immigrants who are not represented in the CPS.
 This figure assumes that the missing illegal immigrant households are similar to those appearing in the CPS. If 41 percent of low-skill immigrant households are illegal, the addition of 10 percent more illegal immigrant households would boost the overall number of low-skill immigrant households by roughly 4 percent. Presumably, the aggregate net tax burden would increase proportionately.
 Information provided by Steven A. Camarota of the Center for Immigration Studies.
 Randy Capp, Everett Henderson, Jeffry S. Passel, and Michael Fix, Civic Contributions Taxes Paid by Immigrants in the Washington, DC Metro Area, Urban Institute, May 2006, footnote 3 on page 6, at www.urban.org/UploadedPDF/411338_civic_contributions.pdf; Jeffrey S. Passel and Rebecca L. Clark, Immigrants in New York: Their Legal Status, Income and Taxes, Urban Institute, 1998, at http://www.urban.org/ publications/407432.html; Steve Camarota, The High Cost of Low Skill Labor, Center for Immigration Studies, August 2004.
 In the case of Medicare, the CPS actually slightly overreports the total cost of benefits; therefore, in this case, the adjustment procedure results in a small reduction in Medicare costs per household compared to the CPS data.
 Data from U.S. Census Bureau, Governments Division, Public Education Finances, 2004, issued March 2006.
 The means-tested spending total does include Head Start.
in this appendix are based on FY 2003 MSIS data, U.S. Department of
Health and Human Services, Centers for Medicare and Medicaid
Services, Medicare & Medicaid Statistical Supplement,
2006, Medicaid Tables 14.1-14.27, at www.cms.hhs.gov/MedicareMedicaidStatSupp/LT/itemdetail.asp?
sortOrder=ascending&itemID=CMS1190631&intNumPerPage=10 (February 20, 2007).
 The categories labeled "residential" in this analysis are termed medical assistance service categories in the MSIS.
 According to the 2004 National Nursing Home Survey, some 1.49 million individuals resided in nursing facilities on any given day in the year. About 88.3 percent of the nursing facility population, or 1.32 million individuals, were elderly persons. Among the elderly in nursing facilities, an estimated 60 percent report Medicaid as a source of payment for their nursing facility expenses. From these figures, this paper estimated that, on an average day, some 790,323 elderly Medicaid recipients lived in nursing homes. The average 12-month cost of Medicaid benefits for these individuals, including ancillary medical services, would be around $57,000. This figure is consistent with MSIS figures after adjusting for ancillary medical services and the general underreporting of expenditures in the MSIS.
 National Long Term Care Study (NLTCS), 1999 public use dataset. Produced and distributed by the Duke University Center for Demographic Studies with funding from the National Institute on Aging under Grant No. U01-AG007198. The NLTCS is a nationally representative sample of individuals ages 65 years and older in long-term care facilities.
 The state and local expenditures on public assistance presented in Appendix Table 4 include data and state TANF spending taken from the Congressional Research Service and an estimated $2.5 billion in state and local spending on General Relief.
 Randolph, "International Burdens of the Corporate Income Tax."
 The estimate that half of this tax was paid by business was provided by the Tax Foundation.
 Based on information provided by the Tax Foundation.
 Charles T. Clotfelter, Philip J. Cook, Julie A. Edell, and Marian Moore, "State Lotteries at the Turn of the Century: Report to the National Gambling Impact Study Commission," Duke University, April 23, 1999.
in this appendix are based on FY 2003 MSIS data, U.S. Department of
Health and Human Services, Centers for Medicare and Medicaid
Services, Medicare & Medicaid Statistical Supplement,
2006, Medicaid Tables 14.1-14.27, at www.cms.hhs.gov/MedicareMedicaidStatSupp/LT/itemdetail.asp?
sortOrder=ascending&itemID=CMS1190631&intNumPerPage=10 (February 20, 2007).
 Anna Sommers et al., "Medicaid's Long-Term Care Beneficiaries: An Analysis of Spending Patterns," Kaiser Commission on Medicaid and the Uninsured, 2006, Table 2. The Kaiser study used MSIS 2002 data; see Tables 4, 9, 10a and 10b.
 Congressional Research Service, Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY 2002-FY 2004, March 27, 2006, p. 234. The Congressional Research Service provides the same spending totals as CMS Form-64 of the Department of Health and Human Services. CMS-14 Medicaid expenditure data are substantially higher than those reported in MSIS. CMS Form-64 includes a number of medical services expenditures, such as disproportionate payments to service providers and supplemental payments, that MSIS does not report. In FY 2003, Medicaid medical services expenditures as reported in CMS Form-64 exceeded expenditures reported in MSIS by some $29.37 billion. CMS Form-64 also reported an additional $13.58 billion in state and local administration costs, which MSIS did not include. When these two items area added to the $233.20 billion medical services expenditures as reported by MSIS, the aggregate Medicaid expenditures in FY 2003 totaled $276.16 billion. This figure is consistent with the aggregate Medicaid expenditure figure reported by CRS.
 Paul A. Samuelson, "The Pure Theory of Public Expenditure," Review of Economics and Statistics, Vol. 36, No. 4 (1954), pp. 387-389.
 A third criterion is nonexclusion from benefit; it is difficult to deny members of a community an automatic benefit from the good. This aspect of public goods is not critical to the fiscal allocation issues addressed in this paper.
 James M. Buchanan, The Demand and Supply of Public Goods, Liberty Fund, Library of Economics and Liberty, p. 5.4.3, at www.econlib.org/library/Buchanan/buchCv5Contents.html (March 6, 2007).
 Thomas MaCurdy, Thomas Nechyba, and Jay Bhattacharya, "An Economic Framework for Assessing the Fiscal Impacts of Immigration," in James P. Smith and Barry Edmonston, The Immigration Debate: Studies on the Economic, Demographic and Fiscal Effects of Immigration (Washington, D.C.: National Academy Press, 1998), p. 16.
 National Research Council, The New Americans, p. 303.