Executive Summary
Since 1975, Oneida county and the city of Utica, New York have welcomed
thousands of refugees from around the world. Through 1999, the Mohawk
Valley Resource Center for Refugees, had resettled 8,759 refugees in the
Utica area, arranging housing, education, employment, and social services
for incoming refugees. The refugees have come from 22 countries with about
40% coming from Bosnia, 21% from the former Soviet Union, and 14% from
Vietnam.
While the humanitarian benefits are clear, there is less consensus as
to whether the refugees are a net benefit or cost to the local economy.
Refugees add to the workforce and broaden the local tax base, providing
employers with quality low-wage workers. At the same time, refugees use
social and educational services, potentially adding to the burden shared
by local taxpayers. Yet neither the benefits or costs have been seriously
addressed in a comprehensive study of the impact of the refugees on the
local economy.
The present study accounts for the fiscal benefits and fiscal costs of
refugee resettlement in the Mohawk Valley. A fiscal analysis differs from
a benefit-cost analysis and the more common economic impact studies in
that a fiscal analysis tracks the flow of public resources used and created
from a particular policy. The study is addresses the question of whether
refugee resettlement costs area residents more in public costs than is
raised through additional tax revenue.
The main findings in the study are listed below.
- Refugees are a net cost in the early years and then yield benefits
for many years to come. In the long run, evidence suggests that efforts
to resettle refugees in Utica, quite apart from any non-fiscal benefits
or costs, is a net fiscal benefit to the community.
- Assuming a typical flow of about 750 refugees per year, simulations
show net annual benefits become positive after 13 years while the cumulative
benefit becomes positive in year 23. After 23 years of operation, the
total fiscal effect of continual waves of 233 refugee households per
year will be and will remain positive.
- The costs of refugee resettlement are front-loaded. After 13 years,
the cumulative net benefit of a single household becomes positive and
remains positive every year after. This does not imply that the costs
of such factors as Medicaid and TANF are reduced to zero. These costs
remain, although they do diminish somewhat over time. Rather, other
positive benefits due to increased participation in labor and real estate
markets now outweigh the negatives.
- The first year net cost of a single refugee household is about $4,413,
with education costs making up 40%, TANF 34 %, and Medicaid 26% of the
total taxpayers costs for refugee households. Over time, the TANF costs
drop quickly, children move out of the school systems. Although Medicaid
participation does diminish somewhat, it remains high. For refugees
households who have been in the area for at least 4 years, 6 percent
are reported to be on TANF while 36 percent receive Medicaid. About
18 percent receive Food Stamps, benefits which are fully paid by the
federal government.
- The primary fiscal benefits accruing from refugees stems from their
participation in labor markets (and therefore consumption of local goods)
and real estate markets. Direct benefits are derived from sales and
property taxes, while indirect benefits accrue through positive effects
on local real estate markets.
- The costs and benefits depend on the composition of the households
and on their willingness to stay in the Utica area. The average refugee
household in our study has lived in the area for about 5 years, has
3.22 people, including 1.27 kids and 1.95 adults. The average age of
the adults in the household is less than 30 years of age, while the
average age of the children in the household is 9.2 years of age. Only
3.7 percent of all refugees who arrive are greater than 65 years of
age.
- Most, but not all, refugees' first jobs are in traditionally low-wage
jobs requiring little formal training and relatively low levels of English
proficiency. The average starting wage rate is $7.18 per hour and less
than 2 percent of refugees start out in jobs paying $10/hour or more.
Small manufacturing assembly work is easily the most common work for
refugees, accounting for about 27 percent of all refugee jobs. Another
15 percent went into sewing jobs. The remaining 58 percent of jobs were
more evenly distributed with production workers and machine operators
being the next most common jobs.
- There is little evidence that refugees have hurt the employment opportunities
of native workers. Native workers now face the lowest unemployment rates
in the last 20 years. To the degree that crowding out is real, that
refugees have displaced native workers, it would have to be in the small
assembly and sewing jobs and to an even lesser degree in the production
and machine operator jobs, jobs which pay generally low wages. A similar
argument applies to the question of the impact of refugees on wages.
Such impacts, if any, are likely small, likely localized to a small
sector of Oneida County, and likely localized to a small sub-sector
labor market.
Outline
1. The Need
2. Purpose and Approach
2.1 A Fiscal Analysis
2.2 Scope of Study
2.3 The time frame for analysis
2.4 Unit of Analysis
3. Background Research and Previous Findings
3.1 Labor Market and Migration Effects
3.2 Fiscal Impacts 4. An Overview of the Utica/Rome Economy 4.1 Population
Changes and Components of Change Table 1: Demographics by Geographic
Definition 4.2 Changes in Industry and Occupational Structure Table
2: Employees by Industry, Oneida County Table 3: Number of Employees
by Occupation 4.3 Change in Wages and Unemployment, and Public Assistance
Caseloads Table 4: Labor Force and Employment 1977-1998, Oneida County
Table 5: Oneida County Public Assistance Spending and Average Monthly
Caseloads, 1987 - 1998 (1997 dollars) 5. The Impact of Refugees on Local
Labor Markets Table 6: Most common Job Titles (N= 2986) Table 7: Top
Ten Paying Job Titles Table 8: Job Openings, Seekers, and Refugee Workers
6. An Accounting of the Fiscal Benefits and Costs 6.1 Composite Household
Table 9: The Composite Refugee Household 6.2 Refugee Center Table 10:
Overview of the 1999 MVRCR Budget 6.3 Education 6.4 Public assistance
Table 11: Participation in Public Assistance Programs Table 12: Probit
Model of Program participation 6.5 Fiscal Benefits: 7. Simulation Results
Table 13: Simulated Annual and Cumulative Discounted Net Benefits 8.
Sensitivity Analysis 9. Concluding Remarks 1: The Need Since 1975, Utica,
through the efforts of the Mohawk Valley Resource Center for Refugees,
have been welcoming and resettling refugees from around the world. The
Refugee Center was established and is sponsored by the Lutheran Immigration
Refugee Service. Through 1999, the Refugee Center has resettled 8,759
refugees in the Utica area, arranging housing, education, employment,
and social services for incoming refugees. The refugees have come from
22 countries with about 40% coming from Bosnia, 21% from the former
Soviet Union, and 14% from Vietnam. While the humanitarian benefits
are clear, there is less consensus as to whether the refugees are a
net benefit or cost to the local economy. The refugees add to the workforce
and broaden the local tax base, one that has been declining for many
years, providing employers with quality low-wage workers. At the same
time, refugees use social services, potentially adding to the burden
shared by local taxpayers. Yet neither the benefits or costs have been
seriously addressed in a comprehensive study of the impact of the refugees
on the local economy. In 1999, associates of the Arthur Levitt Public
Policy Center at Hamilton College became interested in local refugee
resettlement and made this a topic for broader study. This report is
one product of a larger study funded by the Levitt Center. The findings,
judgements, and opinions expressed in the study are the author's and
do not represent the opinions of Hamilton College or the Arthur Levitt
Public Policy Center. 2. Purpose and Approach 2.1 A Fiscal Analysis
The present study is intended to be a first attempt to account for the
fiscal benefits and fiscal costs of refugee resettlement in the Mohawk
Valley. A fiscal analysis differs from a benefit-cost analysis and the
more common economic impact studies in that a fiscal analysis tracks
the flow of public resources used and created from a particular experiment
or policy. For this study, we define the policy as the future resettlement
of refugees in the Utica area. In contrast, a benefit-cost study attempts
to determine the impact of a policy on the overall well being of a community.
Economic impact studies tend to estimate the overall changes in spending
in an economy, but typically ignore the effect of an event on government
spending and revenues. A fiscal analysis may be considered a first step
in more comprehensive benefit-cost analysis which must also weigh and
account for the change in the well-being of the population due to the
policy. Consider the opening of a new restaurant. A fiscal analysis
should account for additional public costs of the restaurant such as
increased sanitation costs and increased tax revenues. On the other
hand, a benefit-cost study would not only account for these fiscal factors
but also weigh the value to the community of having a new restaurant,
perhaps of a type that adds to the variety of dining options available,
and therefore, one that increases the utility of the population apart
from its fiscal impact. Therefore, the present study is not intended
to determine whether refugee resettlement in the Mohawk Valley is a
worthwhile endeavor. Such a judgment goes far beyond the present study,
and requires an accounting of the total impact of the policy on total
well-being of the population of the Mohawk Valley. Rather, the study
is intended to address the question of whether refugee resettlement
costs area residents more in public costs than is raised through additional
tax revenue. In other words, do refugees and the economic activity they
bring, pay more in taxes than they cost in public services? 2.2 Scope
of Study Because there are several levels of governmental authority,
all which have the power to tax and all of which spend money on their
citizens, the results of a fiscal study may differ widely depending
how one defines the geographic region of analysis. For example, if the
policy in question involves the flow of resources from one region (say
the state of New York) to another (Utica), whether the flow results
in a benefit depends on one's point of view. If the unit of analysis
is the state of New York, a $1 million grant from the state of New York
to the City of Utica would be defined as a mere transfer of resources
from residents in one part of the state to other residents in the same
state. Some have more money while others have less, yet the net effect
is a zero. We call this a pure transfer. However, if the unit of analysis
is the Mohawk Valley, the $1 million dollar grant is a pure benefit
(at least the portion not raised from taxes paid by MV residents). So
the same policy leads to very different results, depending on the definition
of the geographic region of analysis. The present study chooses the
Utica/Rome Metropolitan Statistical Area, which includes Oneida and
Herkimer counties, as the region of analysis. While most of the refugees
relocated by the Refugee Center settle in Utica, a broader unit of analysis
is required for at three reasons. First, due to the ease of transportation
and the close proximity of the many towns and villages near Utica, the
local labor markets in which the refugees work are not consistent with
the City boundaries. Second, the unit of measurement for the cost of
social services is at the county level. Third, most federally collected
data use the Utica/Rome MSA as the smallest unit of disaggregation.
Therefore, much of the required data are available and most reliable
at the MSA level. This local perspective differentiates this study from
most others done on the fiscal effects of immigration, some of which
are reviewed below. This local unit of analysis requires care be taken
to distinguish the local taxes from state and federal taxes and local
expenditures from state and federal expenditures. Certainly, not all
benefits paid to refugees by the county come from county funding, just
as not all taxes paid by refugees benefit the county. An increase in
sales tax revenue due to the refugee influx is a clear benefit to the
county, while income taxes paid to the state and federal governments
do not directly benefit the county budget. Similarly, public assistance
programs have differing degrees of county contribution. Some, like food
stamps, are funded completely at the federal level. Although local taxpayers
pay for federally distributed public assistance benefits through federal
taxes, the tax payments would be the same no matter where in the U.S.
the refugees settled. Therefore, the local cost of federally funded
benefits is virtually zero. The flow of federal and state money into
the Utica-Rome area may provide additional tax revenue at the local
level. To the extent that external spending increases non-food and non-housing
consumption, local governments may benefit from federal and state government
public assistance transfers. The benefits, however, would be much less
than the dollar value of the government transfer. It may even be insignificant
in magnitude given the small share that leaks into county revenue. It
would be tempting to label federal benefits, say $100 in Supplemental
Security Income (SSI), as a benefit to the local MSA. Indeed, the typical
economic impact study would count the benefit and any additional spending
that happens as a result of the transfer. This is commonly referred
to as the multiplier effect. However, the benefit of the $100 in SSI
goes directly to the recipient, while the county benefits only to the
degree that there are leakages, through sales and property taxes, from
the all additional spending caused by the initial transfer. 2.3 The
time frame for analysis The fiscal benefits and costs of refugee relocation
are likely to accrue at different points in time. Many of the costs,
such as the use of medical services and cash transfers, are incurred
during the first several months after the refugees arrive. The benefits,
such as increased tax revenue, may accrue over the lifetime of the refugee.
Because the benefits and costs do not accrue at the same, future benefits
and costs must be discounted to their present value, where the present
value may be defined as how much an asset or stream of payments received
in the future is worth to someone today. Choosing the discount factor
by which future benefits and costs are discounted back to their present
value is a crucial stage in any benefit cost study. Following other
studies, we use a 4 percent discount rate (Lee and Miller, 2000), but
given that the results may be sensitive to this choice, the final results
are calculated over a range of discount rates. Generally, economists
agree that social discount rates from 2.5 to 5.0 percent cover the range
of rates that should be used to discount public benefits and costs.
The time frame over which one counts benefits and costs may also impact
the outcome of a fiscal analysis. Because the benefits of refugee resettlement
accrue over the working life of incoming refugees, a short time span
may not appropriately account for future benefits. This study uses a
period of 60 years. As such, the study account for benefits throughout
the working lives of the current refugees and their children. While
some children may work beyond 60 years, benefits that far into the future
will be so heavily discounted as to be of insignificant magnitude. 2.4
Unit of Analysis The primary unit of analysis is the refugee household.
Previous studies find different results depending on whether the unit
of analysis is the individual immigrant (refugee in this case) or the
household, or the household plus children born to immigrants in the
United States. Studies of individuals tend to focus on individuals who
come during their working years (or older), thereby minimizing the costs
of education. We choose the household which includes all refugees born
prior to arriving in the area. A study incorporating the benefits and
costs of children of refugees born in the U.S. would require assumptions
about fertility patterns, something we know very little about with respect
to refugees who settle in the Utica/ Rome area. The analysis will be
done in two ways. The first method is to follow a single cohort of refugees
through the time period of analysis, 50 years. This analysis takes into
consideration the age, sex, and education composition of arriving refugees
using the average characteristics of refugees who arrived over the last
ten years. In addition to demographics, I estimate wage profiles and
public assistance use profiles. This portion of the analysis seeks to
answer the question, do refugees pay in more than they take out of the
economy? Refugee resettlement, however, is not a one-time event. New
refugees arrive every year. The second method of analysis estimates
the fiscal impact of a continuous flow of refugees. Obviously, the total
effect on the economy from refugee resettlement must take into account
the cumulative impact of new waves of refugees as they arrive. Therefore,
this second method analysis better identifies the time necessary for
the fiscal benefits to outweigh the costs of a continual stream of refugees.
3. Background Research and Previous Findings The economic impact of
immigration has been a topic of considerable interest for the last 30
years. While this study concerns refugees, whose impact may be distinct
from immigrants in general (Refugees make up about 15 percent of immigrants.),
the immigrant literature gives guidance, highlighting the important
issues and providing results which may serve as a benchmark. In addition
to summarizing some of this literature, this section also draws on the
smaller body of research focusing on economic effects of refugees on
local and national economies . 3.1 Labor Market and Migration Effects
Economists have put a large share of their research efforts into understanding
the effects of immigration on labor market, specifically the wages and
employment of immigrant and native workers. Despite the size of the
literature, the results are mixed. For example, studies using older
cohorts of immigrants commonly find that immigrants, although they typically
had lower starting wages, had on average greater lifetime earnings than
average native workers. Yet more recent studies find that immigrant
workers, mostly due to a decline in skills and education, can expect
to earn lower wages throughout their working years (Borjas, JEL 1994).
It has long been recognized that immigration may impact native workers,
although theoretically the direction of the impact is indeterminate.
Just as any entrant into a labor market may displace another worker
already in that market, immigrants have the potential to displace native
workers or drive down wages for those who keep their jobs. In this case
immigrants would be considered substitutes for native workers. It is
also possible that immigration has positive effects on native workers.
Those espousing this theory argue that immigrants are entrepreneurial
and accumulate productive capital at a higher rate than native workers
(Greenwood and Hunt, 1995). Alternatively, immigrants fill less desirable
jobs that natives avoid and thereby complement native workers. In this
case, immigrants would not tend to decrease either wages or the probability
of employment. The effects of such theories depend on the skill levels
of immigrant workers. To the degree that immigrants are relatively low-skilled
workers, they may have adverse or substitution effects on native low
skilled workers and positive or complementary effects for higher skilled
workers. Finally, since immigration leads to an increased demand for
goods, the demand for labor may increase leading to positive effects
for both native and immigrant workers. The actual impact of immigration
on wages and employment is therefore an empirical question, and one
which a number of studies have attempted to answer. The findings in
the empirical literature, of which Friedberg and Hunt (1995) and Borjas
(1994) provide comprehensive reviews, are far from unanimous. Across
studies using a wide variety of methodologies and data sources, the
most common finding is that immigrants do tend to substitute for native
workers, although the magnitudes of the effects on employment and wages
are typically quite small. Borjas (1994), for example, finds no studies
that increase joblessness or decrease wages among natives by more than
two percent. Wilson and Jaynes (1997), a cross industry study which
pays particular attention to the concentration of immigrants, report
small negative impacts on native employment but positive effects on
native wages in industries and geographic regions with higher concentrations
of immigrants, other things equal. Frey ( 1997) offers one possible
explanation for the small magnitude of the negative impacts. He argues
that immigration leads to an out-migration of low-skilled native workers.
If this is true, empirical studies may understate the full impact of
immigration on employment and wages, depending on the composition of
leavers. However, a recent study by Card and DiNardo (2000) finds that
areas that have had population growth through immigration also tend
to see an increase in the flow of low-skilled native workers into the
area, a finding in sharp contradiction to Frey's theory and findings.
One conclusion that appears rather robust across studies is that the
strongest negative labor market effects seem to fall on other foreign
born workers, and most strongly on recent immigrants. Greenwood and
Hunt ( 1995) find that the wage effect of immigration on foreign born
workers is roughly two and one-half times the effect on native workers.
Economists attribute this finding to the continual flow of new immigrants
into industries and regions with high concentrations of foreign born
workers. Unfortunately, a comparable literature does not exist on the
labor market impacts of refugees on U.S. labor markets. However, since
the effects of immigration are typically measurable only in areas with
high concentrations of immigrants, one may conclude that refugees, a
small subset of all immigrants, would have even smaller effects. This
does not mean there are no effects. If refugees, due to common skills
or lack of English proficiency, tend to concentrate in a particular
industry or small geographic area, local effects may be noticeable.
Recent years have witnessed a growing literature on the factors contributing
to the economic success of refugees. Refugees are by-and-large involuntary
immigrants and face greater obstacles than most immigrants. Potacky-Tripodi
(1999) reviews several large studies on the economics success of refugees
and extends previous studies. She concludes that refugees with more
education, greater facility with the English language, greater length
of stay in the U.S., and who live in families headed by a married couple
tend to have higher levels of employment, greater household income,
and a lower probability of public assistance utilization. The presence
of children and adults over 65 years of age tends to hamper economic
status. 3.2 Fiscal Impacts A second body of literature relevant for
this study addresses the broader fiscal impact of immigration. Again
this literature tends not to separate refugees from other immigrants,
but the findings are instructive. The key question in this literature
is how much do immigrants contribute through taxes of all kinds relative
to the costs they impose through the services and benefits they receive?
The literature in this area is both younger and smaller than the labor
market impact literature, probably due more to the lack of data, lack
of consensus on methods, and difficulties in several key definitions
than to lack of interest. Some of the difficulties in defining family
units and the relevant time frames for such analyses will show up later
in this report. Several studies, notably Borjas (1994), Fix and Passel
(1994), Smith and Edmonston (1997), and Moore (1998) attempt to determine
the net fiscal impact of immigration. Fix and Passel's results are representative
of the common finding that immigrants pay more in taxes that they receive
in government services. Moore (1998) concludes that the net present
value of benefits less costs is between $20,000 and $80,000 for each
immigrant. Borjas (1995) points out, however, that more recent immigrants,
due to a deterioration in skills among those admitted, are not likely
to present such a positive picture. In calculations he would qualify
as rough, he estimates that in 1990, immigrant households in the U.S.
cost taxpayers about $16 billion. Such single-year estimates may be
not be useful as benefits and costs are incurred at different points
in time and the number and composition of immigrants changes over time.
Because the funding for the public services, including cash assistance
and in-kind benefits, is not shared equally across federal, state, and
local governments, the fiscal impacts of immigrant and refugee resettlement
will differ. For example, Social Security is a federal program requiring
no local contributions. Medicaid and cash assistance through Temporary
Assistance for Needy Families (TANF) requires a state and local contribution.
Oneida County pays 25% of the benefit costs for these programs. Lee
and Miller (2000), using CPS and Census data, project the fiscal impacts
of immigration on federal, state and local governments. They find that
immigration is an overall net benefit for the country, but a net loser
for state and local governments, at least in the short run. One way
to compare the differential impacts is to compare the time it takes
to break even. Lee and Miller find that it would take 10 years for a
single immigrant to become a net contributor to the U.S. economy, 16
years if we consider the children of immigrants. However, for state
and local governments the breakeven time horizon is about 45 years.
It should be emphasized that such an exercise requires a number of assumptions
which make generalizing these results to a specific county unreasonable.
For example, suppose an immigrant settles in County A, has children,
and lives there for 20 years. After 20 years the children move to County
B. County B will reap the benefits of the education investment in the
children, while County A will not. 3.2.1 Costs The costs of immigration
tend to be easier to identify and measure than the benefits. The primary
costs of immigration are incurred through the costs and congestion of
the services they use (such as cash transfer programs, health care,
and education) and the indirect costs on native workers. While the U.S.
has a relatively clear immigration policy, it has few assistance programs
targeted at immigrants. Fix and Zimmerman (1995) review the programs
available to immigrants. Generally, immigrants use the same programs
available to natives. Refugees, however, do benefit from several programs
that provide health care, public assistance and job assistance as established
in the Refugee Act of 1980. The Act makes economic adaptation of refugees
a prime goal, where economic adaptation is unsatisfactorily defined
as being employed and not receiving means-tested cash assistance. Funding
of the Act has been seriously eroded by inflation since its passing,
from over $7,000 per immigrant in 1984 to about $2,000 per immigrant
in 1994 (Espenshade, Fix, Zimmerman, and Corbett, 1997). The federal
government also provides funding for language training through the elementary
and secondary school system and for adults. The Emergency Immigrant
Education Act offers some financial support for local governments that
can demonstrate significant economic strain due to immigration. The
policy is designed to offset costs. Unfortunately, the name of the Act
is somewhat deceiving as the education assistance available through
the act is minimal. Most of the emergency assistance is dedicated to
offset the costs of incarcerating criminal aliens. Borjas (1994) finds
the probability of welfare assistance among immigrants to have increased
since 1970, largely due to a decrease in the average skill and education
levels of more recent immigrants. In 1990, immigrants participated in
cash assistance programs at a rate 2.5 percentage points above the native
population, a finding which is exacerbated when other noncash public
assistance programs are also considered (Borjas and Hilton, 1996). Using
the March 1995 Current Population Survey, Bean et al (1997) find 10.6
percent of immigrant households receive some sort of cash assistance
compared to 8.1 percent for native households. In New York State, the
differential increases to 6 percentage points, from 17 percent for immigrants
compared to 11 percent for natives (Passell and Clark, 1998). Removing
refugees from the pool of immigrants decreases the proportion of immigrants
receiving cash assistance (Fix and Passell, 1994). Of course, this implies
that refugees receive benefits at a higher rate than other immigrants.
Immigrant participation rates also vary widely depending on country
of origin. For example, Asian and Mexican/Central American immigrants
receive cash benefits at rates much higher than natives, while European
immigrants (not necessarily refugees or even recent immigrants) receive
benefits at lower rates than natives (Bean et al., 1997). Education
is a major cost of immigration just as it is for natives. Most immigrants
arrive as working age adults, having already completed school in their
home country. Immigrants who arrive as adults require relatively little
education spending. However, providing education for the children of
immigrants is a burden that falls heavily on state and local governments.
Refugees and their children are more likely to have had their formal
schooling interrupted due to political turmoil in their home country,
and may have lower levels of language proficiency upon arrival. Spending
on education, whether on children or adults, is costly, but it is also
an investment. Educating immigrants pays off if they stay in the country
(or county) and are productive taxpayers throughout their working years.
While educating immigrant children is more expensive than educating
immigrant adults, the children typically have a longer working life.
In fact, revenue from the children of immigrants in their working years
is the largest fiscal benefit of immigration (Lee and Miller, 2000).
3.2.2 Benefits The fiscal benefits to immigration have been widely discussed
but tend to be harder to quantify than the costs which are typically
government expenditures. As stated earlier, immigration increases the
national income by more than what it costs to employ them (Borjas, 1995).
Immigrants are consumers so they expand market size and provide valuable
inputs to production. Expanded markets means some resources that would
be unemployed or underemployed are more likely to be put into use. To
the degree that these increased activities increase tax payments, they
generate fiscal benefits. Also, because new immigrants are typically
of working age, some have even discussed using immigration policy as
means to finance Social Security for the aging U.S. population. A larger
population of working age households broadens the pool of tax payers.
Certainly the most tangible benefits of immigration are the taxes paid
by immigrants and their children. Income taxes are levied by the federal
government, most state governments, and sometimes by local governments.
Even though local governments typically don't levy income taxes, they
may still benefit from increased allocations from state budgets. Local
governments benefit more directly from taxes placed on consumer goods
and on personal and business properties. The benefits of immigration
are strongly affected by the age profile of arriving immigrants. To
the degree that the arriving immigrants are of working age, they will
be able to move more quickly into the workforce, meaning more immediate
benefits. This is not to suggest that moving immigrants quickly into
the work force is an optimal strategy. Another key factor in determining
the benefits of immigration is the skill level of immigrants. Because
higher wages leads to increased tax revenues, there is an incentive
to admit higher skilled immigrants and to train those who arrive to
use the skills they bring. 3.2.3 Implications for Refugees At a minimum,
the preceding literature review suggests that the issues involved in
determining the fiscal benefits and costs of refugee resettlement are
complex. If refugee resettlement affects the economic activity of others,
then simply adding up the taxes paid by refugees and subtracting the
local cost of the public services they use will not suffice. Refugees
may affect the income (and therefore consumption and tax paying) prospects
of native workers. Past studies suggest that influx of refugees can
have both positive and negative effects on local labor markets. To determine
the impacts, some assessment must be made as to the effect of refugees
on the wages and migration effects on native workers. Are refugees a
substitute for local workers, driving down wages and forcing out native
workers? Or does the refugee workforce lead to reduced production costs,
perhaps attracting specific types of industry? A careful look at the
trends in the Utica/Rome labor markets will give some clues to answer
these questions. As for the net fiscal impact, the literature suggests
that immigration is beneficial at a national level but costly for states
and local governments. If the local economy could be called typical,
then we might expect the results of the fiscal analysis to be negative.
However, none of the studies cited address the impact of refugees or
the impact of immigration on a specific local region. They are, therefore,
average results. As we will see below, the economic and demographic
circumstances Mohawk Valley are far from typical, and the question as
to the net fiscal impacts of refugee resettlement are wide open. 4.
An Overview of the Utica/Rome Economy Before discussing the impact of
the flow of refugees, it is necessary to describe, at least in brief,
the economy into which they are coming. Once described as a thriving,
the economy of Utica and its surrounding communities has struggled in
the 1980's and 1990's. The exodus of major employers such as General
Electric (later Martin Marietta) and the closing of the Griffiss air
base were among the shocks which have had painful and lasting impacts
on the local community. While recently there have been improvements
which give reason for optimism, the economy into which refugees arrive
is vastly different from late 1980s when unemployment rates were falling
and the workforce was growing. This section describes those changes
deemed most relevant for this study. 4.1 Population Changes and Components
of Change Labor is a crucial resource for any economy. While the population
in most U.S. cities, counties, and Metropolitan Statistical Areas (MSAs)
has been growing over the last two decades, the Utica-Rome MSA has seen
its population decrease. In 1970, the Utica-Rome MSA boasted 340,477
people. The population decreased by nearly twenty thousand people in
the 1970s to 320,700 in 1980. The rate of decrease lessened in the 1980s
but had reached 316,886 in 1990. By 1998 the MSA population had fallen
to 294,677, a drop of more than 13 percent over nearly two decades.
A significant share of the drop in the 90s occurred after the announcement
and ultimate closing of the Griffiss Airbase in 1994. Similar population
patterns hold for Oneida County and are even more extreme for the city
of Utica. For example, the Oneida county population dropped from 253,465
in 1980 to 236,437 in 1998. Population decreased by 5.7 percent from
1990 to 1998. The City of Utica lost 9.2 percent of its population in
the 1980s and continued to lose another 10.5 percent from 1990 to 1998.
In 1998 the Utica population was estimated to be 61,368, down from 75,632
in 1980. Because the Utica population decreased at a faster rate than
Oneida County, Utica's share of the county's population also fell in
the 1980's and 1990's. Whereas Utica made up nearly 30 percent of the
Oneida county population in 1980, the share had fallen to roughly 21
percent in 1998. Without international immigration, not all of which
is attributable to refugees, the out-migration numbers would be far
more extreme. Estimates from the Bureau of Census show net domestic
immigration for the Utica-Rome MSA from 1991 to 1998 of -32,874, 82
percent of which was from Oneida county. However, over the same period
international immigration added (on net) 4,282 to the MSA population.
In other words, to some extent, the migration out of the MSA is mitigated
by international migration into the area. On average, about 4,100 natives
were leaving the area while an average of 535 international immigrants
arrived in the MSA. Table 1: Demographics by Geographic Definition Utica-Rome
MSA Oneida County City of Utica Population 1980 320,180 253,836 75,632
Population 1990 316,866 251,030 68,637 Population, 1998 294,677 230,628
61,368(1996) Average Household size, 1998 2.48 2.50 2.36 Net native
immigration, 1991-1998 -32,874 -27,225 NA Net International immigration
1991-1998 4,282 3,531 NA Percent White, not Hispanic, 1998 90.6 89.4
80.4 Percent Black, not Hispanic, 1998 5.1 5.8 12.6 Percent Hispanic
(1995 3.0 3.3 5.0 Percent without H.S. Diploma, 1995 21.8 22.2 Percent
H.S. graduates, 1995 31.8 29.3 People all ages in Poverty, 1995 14.1
People under age 18 in Poverty,1995 22.4 Median Age,1980 31.7 31.6 34.0
Median Age, 1990 34.0 33.8 34.4 Median Age, 1998 36.1 35.7 35.4 Median
Household Income, 1998 $31,426 $32,424 $23,434 Median Family Income,1998
$40,748 $41,400 $33,026 Sources: U.S. Bureau of Census; Marketview Comparison
Report (Clarities, Inc.); Technical Assistance Center, SUNY at Plattsburgh.
One of the key questions regarding the migration out of the area is
who is moving away. The demographics tell part of the story. As we see
in Table 1, since 1980 the Utica and Oneida populations have become
older, increasing in all three geographic definitions to approximately
34 years of age with the share of population over 65 increasing significantly.
Over the same time period the average household size decreased, suggesting
that movers out of the area tend to be larger working age households.
4.2 Changes in Industry and Occupational Structure Utica's refugees
enter into a local economy that has undergone considerable structural
change over the last twenty years. Since 1980, the industrial mix in
the Mohawk Valley has evolved, and the most significant trend, one not
unique to the Mohawk Valley, has been a movement away from manufacturing
and toward a greater reliance on the service sector. Using data from
the State of New York on those workers covered by unemployment insurance,
data on most but not all workers, we can track the change in industry
structure over time. These trends are plotted in Figure 2. In 1980,
30.6 thousand workers, or about 26.7 percent of all workers, in the
area worked in the manufacturing sector of the economy. The numbers
were slightly lower than in 1979 when the manufacturing sector was at
its largest. Of course, not all the workers in the manufacturing sector
were involved in the manufacturing process itself. Some were accountants
or were in sales or management. Yet their livelihood was dependent on
the production of a physical product. At the same time, at 20.6 thousand
workers the service industries employed roughly two-thirds as many workers
as the manufacturing sector. As it has across the country, employment
in the manufacturing sector has diminished in size while the service
industries in the Mohawk Valley have grown appreciably since 1980, both
in terms of employment and as a share of the entire local economy. From
1980 to 1998, employment in the manufacturing sector decreased by 33
percent and by nearly 15 percent in the1990s alone (Table 3). From 1980
to 1998, the share of workers in manufacturing decreased from nearly
26.7 percent to 15.6 percent. The decrease in manufacturing employment
was matched with even larger increases in the service sector. In the
1990s, the service sector saw employment increase by 38 percent, from
18 percent of workers to over 30 percent. In fact, the service and insurance
and real estate industries are the only sectors that experienced growth
in the 1990s. 1980 1990 1998 Change 1990-1998 Industry Number of Employees
Percent of Employees Number of Employees Percent of Employees Number
of Employees Share of Employees Number of Employees Percent Change in
Employees Percentage Change in Share Total, Non-agricultural 114.6 100.0
128.5 100.0 129.7 100.0 1.2 0.9 -- Manufacturing 30.6 26.7 23.7 18.4
20.2 15.6 -3.5 -14.8 -2.9 Transpor-tation and Utilities 3.9 3.4 4.4
3.4 3.9 3.0 -0.5 -11.4 -0.4 Trade 22.1 19.3 28.0 21.8 26.3 20.3 -1.7
-6.1 -1.5 Insurance, Real Estate 5.5 4.8 7.5 5.8 8.2 6.3 0.7 9.3 0.5
Services 20.6 18.0 28.8 22.4 39.8 30.7 11.0 38.2 8.3 Total Govern-ment
29.0 25.3 31.8 24.7 27.9 21.5 -3.9 -12.3 -3.2 Estimated Population 320.2
-- 316.6 -- 294.7 -- -6.9 -- Source: U.S. Bureau of Census. County Business
Patterns. Table 2: Employees by Industry, Oneida County Occupations
Because people tend to look for certain types of jobs and train for
occupations, not industries, the change in industry structure tells
only part of the story. It says little about what the workers are actually
doing on the job. Within the manufacturing industry, some are managers
or professionals (say an accountant) while others are classified as
service providers (such as the janitorial staff). Table 3 reports that
of the roughly 134 thousand workers employed in the Utica/Rome MSA in
1994, 15.8 percent work in service occupations. Another 28 percent work
as managers, administrators or in professional and technical occupations,
a category that would include such occupations as office managers, engineers,
architects, teachers, lawyers, and health technologists. More than another
quarter of employees, work in wholesale and retail sales positions or
in administrative support. Other than administrative support, all of
these occupations are projected by Department of Labor economists to
be growing occupations for upstate New York. Of the growing occupations,
the professional, technical and sales occupations are projected to experience
the greatest growth. Unfortunately labor demand is not projected to
grow for all occupations. Employment in the precision production and
craft occupations, which include mechanics, repairers and the Table
3: Number of Employees by Occupation Utica/ Rome North Country Region*
Occupation Employ-ment 1994 Percent of Total Employ-ment Employ-ment
1995 ProjectedEmploy-ment 1998 Net Openings 1998 Proj Employ. Change1994-2004
Proj. % Change1994-2004 Total, All Occupations 134,019 100.0 210,770
213,800 5,830 2,450 1.2 Managers and Administrators 13,158 9.8 11,700
11,900 290 400 3.7 Professional and Technical 24,392 18.2 50,150 51,610
1,390 3,070 6.2 Marketing and Sales 14,389 10.7 25,260 26,230 1,180
1,520 6.5 Administrative Support 23,035 17.2 37,630 37,140 720 -2,910
-7.9 Service 21,138 15.8 38,600 40,110 1,590 1,940 5.0 Agricultural,
Forestry, Fishing 3,410 2.5 1,690 1,760 50 30 1.8 Precision Production,
Craft 15,363 11.5 18,930 18,990 400 -280 -1.5 Operators, Fabricators,
and Laborers 19,134 14.3 26,620 25,900 610 -1,300 -4.8 * The North Country
is defined to include Oneida, Madison, Herkimer, Fulton, Montgomery,
and Schoharie counties.Source: U.S. Bureau of Census. County Business
Patterns; Technical Assistance Center, SUNY at Plattsburgh. Technical
Assistance Center, SUNY at Plattsburgh. construction trades is expected
to decrease by 1.5 percent from 1994-2004, what may be called a modest
decrease. However, the bottom row of Table 3 reports a greater projected
employment decrease of nearly 5 percent for the operator, fabricator
and laborer occupations. This category includes machine operators and
assemblers, transportation workers and material moving occupations,
handlers, equipment cleaners, and general laborers. 4.3 Change in Wages
and Unemployment, and Public Assistance Caseloads The labor force in
Oneida County peaked in 1990. After being relatively stable from 1977
to 1988, the labor force grew rapidly in the late 1980s. Employment
also boomed in the late 1980s with unemployment dropping from 9.1 percent
in 1983 to 4.7 percent in 1990. Similar to the national trend, the recession
of 1991-1992, along with corporate downsizing, led to a rapid increase
in unemployment in the Oneida County unemployment with the number of
unemployed increasing by 50 percent from 1990 to 1991 from 6.8 thousand
to 10.3 thousand people. The result was an increase in the unemployment
from 4.7 to 7.1 percent in 1991 and to 7.4 percent in 1992. Perhaps
more important, this episode also spurred another decrease in the local
labor force. Table 4: Labor Force and Employment 1977-1998, Oneida County
year Labor force Employed Unemployed Unemployment Rate Estimated Population
(000's) 1977 134.2 121.3 12.9 9.6 326.9 1978 134.5 125.1 9.4 7.0 325.6
1979 137.4 129.0 8.3 6.1 323.7 1980 136.2 126.2 10.0 7.4 320.2 1981
135.2 124.9 10.3 7.6 319.8 1982 133.2 121.2 12.0 9.0 319.8 1983 133.6
121.5 12.1 9.1 320.4 1984 134.3 124.7 9.6 7.1 320.1 1985 133.7 123.8
9.9 7.4 319.4 1986 134.6 125.1 9.5 7.0 317.0 1987 133.6 126.4 7.2 5.4
316.2 1988 135.7 129.2 6.5 4.8 315.3 1989 138.9 131.4 7.5 5.4 316.1
1990 145.6 138.8 6.8 4.7 316.6 1991 144.3 134.0 10.3 7.1 318.6 1992
143.2 132.6 10.6 7.4 319.0 1993 143.6 134.4 9.2 6.4 317.7 1994 144.0
136.0 8.1 5.6 315.4 1995 143.4 135.4 8.0 5.6 308.3 1996 141.2 133.7
7.5 5.3 302.4 1997 142.8 135.3 7.5 5.2 297.9 1998 142.4 136 6.5 4.5
294.7 1999 4.3 Source: New York State Department of Labor. Since 1992,
the economic picture for Oneida County has shown signs of improvement.
Although the population continues to fall, the level of employment has
actually increased. A good share of the population exodus can be linked
to the closing of the Griffiss Airbase. Since military employees are
not counted in the labor force statistics, the labor force and employment
statistics show little response to the closing of the base, while population
decreased by 13 thousand people from 1994 to 1996. In part, the exodus
of spouses and family of military personnel may have opened employment
possibilities and drawn previously discouraged workers into the labor
force. In 1999, the rate of unemployment in Oneida County stood at 4.3
percent, the lowest rate in at least 22 years. Participation in public
assistance programs tends to follow the unemployment rate, but in Oneida
County, public assistance participation tells a more mixed story. A
combination of falling unemployment rates in the 1990s and the Personal
Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996
resulted in shrinking caseloads for Temporary Assistance for Need Families
(TANF), New York State Safety Net (SN)/Home Relief (HR), and the Food
Stamp Program (FS). The Food Stamp Program and Aid to Families with
Dependent Children (AFDC), which was replaced by TANF, reached their
peak participation in the 1990s in 1994 while SN/HR peaked in 1991.
As shown in Table 6, TANF caseloads (measured in households) dropped
by 30 percent from 1994 to 1998. Using recently updated data, 1999 average
monthly caseloads were 33 percent lower than in 1994 . Oneida county
residents, who fund 25 percent of TANF and Medicaid benefits, saw their
tax burden from TANF drop by 36%. Food stamp usage also declined after
1994, though at a more modest rate. In 1998, food stamp participation
was 13 percent lower than in 1994 . Home Relief, New York's version
of General Assistance, fell throughout the 1990s. From 1990 to 1998,
HR participation fell by 56 percent. Table 5: Oneida County Public Assistance
Spending and Caseloads, 1987 - 1998 (1997 dollars) Year Medicaid* TANF/ADFC*
Safety Net/Home Relief** Food Stamps* Public Assistance Share of O.C.
Spending 1987 $14,415,914(9500) $5,246,773(3524) 1707 0 (9440) 0 1988
$14,537,348(9878) $5,170,779(3273) 1551 0 (8821) 0 1989 $14,288,841(10056)
$4,863,931(3170) 1754 0 (8421) 0 1990 $16,660,713(11093) $5,844,563(3212)
1803 0 (8544) 0 1991 $19,048,813(12119) $6,851,377(3594) 1905 0 (9299)
0 1992 $20,336,699(13535) $6,514,413(3416) 1638 0 (10165) 0 1993 $22,542,062(14666)
$6,287,828(3563) 1812 0(11035) 0 1994 $23,896,860(15173) $6,193,503(3604)
1658 0(11316) 0 1995 $24,189,745(15290) $5,999,611(3425) 995 0(11113)
0 1996 $22,505,857(15290) $4,900,031(3037) 837 0(11117) 07741 1997 $23,616,757(15830)
$2,686,829(2637) 831 0(10481) 0(7423) 1998 $25,474,854(15804) $3,959,402(2529)
795 0(9794) 0 * Participation numbers are correspond to the monthly
average number of participants.** The Home Relief participation numbers
are for the month of December in each year.Source: Oneida County Department
of Social Services. While participation and spending on TANF, HR, and
FS all declined after 1994, Medicaid caseloads continued to increase
as they have throughout the 1990s. Adjusting for inflation, Oneida County's
share of Medicaid benefits was 53% more in 1998 than in 1990. The 15,804
average participants per month in 1998 was up by 4,711 over 1990, an
increase of 42%. On the one hand, one should not be surprised at these
numbers. The PRWORA of 1996 decoupled TANF and Medicaid making it easier
for households not participating in TANF to qualify for Medicaid coverage.
The large increase in participation from 1996 to 1997 supports this
hypothesis. On the other hand, the other components Oneida County's
public assistance appear to be improving at the same time more families
are needing and using Medicaid. Total employment is up, unemployment
is low, and reliance on TANF and food stamps is falling. In combination,
these observations lead to several possible explanations, and there
may be some truth to all of them. First, health insurance is becoming
harder and harder for the average or low wage worker to afford, leading
to higher rates of Medicaid usage. Second, while employment is high,
wages for new jobs are not sufficient to pay for health insurance. Finally,
while health insurance used to be automatic, employers may be cutting
back on fringe benefits, forcing workers to make the choice between
buying health insurance or not. In any case, the Medicaid numbers indicate
a significant and growing share of Oneida County residents without private
health insurance. 5. The Impact of Refugees on Local Labor Markets The
impact of refugees on the local economy depends largely on how refugees
fit into the local labor markets. While data are insufficient to provided
precise answers, this section addresses the questions: What types of
jobs and wages are refugees getting? Are refugees crowding natives out
of the labor market? Does the increase in labor supply appear to be
driving wages for native workers down? 5.1 Types of Jobs Refugees come
with a wide range of skills, education, training, and work experience.
Yet, moving directly into those occupations is difficult for most refugees,
especially in the short term. Insufficient language skills, occupational
licensing, and regulations form significant barriers to smooth transition
into local labor markets. For example, someone trained as a lawyer in
Bosnia cannot simply begin to practice law in Utica, NY. At a minimum
it requires taking the state bar exam and probably requires additional
schooling because of differences both in the educational requirements
and the content of law between U.S. law and law in their country of
origin. Such difficulties exist for a wide array of occupations from
nursing to plumbing. When refugees arrive in Utica, they sign contracts
agreeing to accept work whenever they are able and whenever jobs are
available. While all refugees receive intensive English training, the
duration of such education depends, in part, on the availability of
employment. When jobs are easy to find, ESL training may be as short
as two months, a time period far too short for most refugees to become
proficient in the English language. This limited English training has
a tremendous impact on the types of jobs that refugees tend to take.
The MVRCR keeps data on every refugee who comes to Utica, including
information on the jobs into which they are placed. While preserving
worker confidentiality, they were kind enough to provide data on the
types of jobs and wages for every refugee in their database, which begins
in 1989. Because some refugees were placed in jobs more than once, I
use only the most recent job for each individual, resulting in a database
of 2986 jobs. Table 6 presents the numbers of jobs, percent of jobs,
and hourly wages for the ten most common job titles. The table is sorted
from the most common job to the least (among the top ten). All told
the top ten job types account for 73 percent of all jobs. The remaining
27 percent are spread among a large number of job titles and employers.
It is important to keep in mind that these jobs are the initial jobs
for Utica's refugees. The MVRCR keeps no formal records after the first
year, so it is difficult to estimate the share of workers who remain
at their initial jobs, the average duration of the initial job, or the
types of jobs into which these workers transition. Work by Coughlan
and Owens-Manley, which focuses on refugees who have become citizens
or who have purchased houses, suggests considerable labor mobility among
these subgroups. However, their research also suggests that there remains
a serious mismatching of refugee skills and jobs four and five years
after arriving in the area. The most common initial jobs for refugees
are jobs that require little training and relatively low levels of English
proficiency. Small manufacturing assembly work is easily the most common
work for refugees. Of the nearly 3000 jobs, 26.7 percent of all refugees
went into assembly jobs. Another 15 percent went into sewing jobs. The
remaining 60 percent of jobs were more evenly distributed with production
workers and machine operators being the next most common jobs. The sixth
through tenth most common job titles each accounted for roughly three
percent of initial jobs. Table 6: Ten Most Common Refugee Job Titles
Job Title Number of Refugee Workers Placed Percent of all Refugee Jobs
Average 1999 Wages for Refugee Workers Assembler 798 26.7% $6.50 Sewer
445 14.9% $6.25 Production worker 206 6.9% $7.25 Machine Operator 166
5.5% $7.50 Presser 114 3.8% $6.82 Nurse Aide 100 3.3% $7.25 Greenhouse
Worker 98 3.3% $5.54 Folder 96 3.2% $6.00 Meat Cutter 91 3.0% $6.50
* 1998 data Laborer 87 2.9% $6.80 * 1998 data Total 2201 73.7% 2986
jobs recorded.Source: Mohawk Valley Resource Center for Refugees. It
should come as little surprise that the wage rates for these initial
jobs is relatively low, ranging from $5.54 for greenhouse workers to
$7.50 for jobs as machine operators. These jobs require little if any
experience and the training investment is minimal. It should be emphasized
again that these jobs are initial jobs. To the degree that refugee workers
are mobile, a topic about which little is known, the table should not
be used to imply the total number working in these occupations. Most,
but not all, refugees' first jobs are in traditionally low-wage jobs
requiring little formal training. Some refugees do find higher paying
jobs, although less than 2 percent of refugees start out in jobs paying
$10/hour or more. Among those jobs that do pay well, there is no job
title paying more than $10/hour in which more than 3 refugees are employed.
The top 10 paying job titles for refugees' initial jobs are listed below
in Table 7. Table 7: Top Ten Paying Job Titles Job Title Hourly Wage
in 1999 Mason $23.00 Draftsman $16.00 Construction Worker $14.45 Laborer
$13.60 Supervisor $11.80 Teacher, English as a Second Language $11.45
Insurance Sales $11.25 Laboratory Technician $11.0 Loader $10.65 Maintenance
Workers $10.60 Source: Mohawk Valley Resource Center for Refugees. The
higher paying jobs generally require previous training and experience
and do not tend to be jobs typically classified as professional jobs.
In some cases, such as the teachers and supervisors listed above, it
is the refugee's relative mastery of the English language that qualifies
them for jobs that are high-paying relative to most refugee jobs. While
the MVRCR is contractually obligated to assist refugees for a period
of one year after their arrival, the center has recently launched an
effort to improve the job matches for refugees. The job placement contracts
may not allow refugees to go straight into the work they are trained
to do, but the center hopes to assist the refugees in developing strategies
for moving into meaningful and fulfilling jobs. The MVRCR has hired
an additional staff member whose chief responsibility is to determine
each refugee's past experience and education or training and then to
assist refugees in reentering jobs similar to those held in their previous
country. Beyond one year, relatively little is known (or at least formally
recorded) as to the Utica refugees job mobility and economic success.
Coughlan and Owens-Manley interviewed two groups of Bosnian refugees:
those who have attained U.S. citizenship and those who have purchased
houses in the area . Of the refugees they interview, most are not working
for their initial employer or in their initial job. Current jobs include:
city planner's assistant ($28,000 per year); teacher ($40,000 per year);
Human Resource Clerk ($11,000 per year); computer programmer ($28,000
per year), machine operator ($18,500); molding mechanic ($20,000); receiving
clerk ($24,000); truck driver ($30,000); grinder ($19,200). While the
Coughlan and Owens-Manley research is difficult to quantify, it does
suggest that at some refugees are able to move from their initial jobs
into better paying jobs. In addition, most of the families they interview
have more than one worker. Local newspaper articles and letters to the
editor have expressed the obvious concern that refugees may crowd natives
out of the local labor market. Others theorize that the availability
of refugee labor will attract employers to the area. Such new businesses
would not only employ refugees, but also employ natives and may potentially
bring new taxpayers into the area. A direct and thorough answer to the
question of crowding out would require a level of data not currently
available. For example, time series data on population show the area
population decreasing over the last 20 years. Some of the population
decreases can be traced to major corporate shutdowns and to the closing
of the Griffiss Airbase. We know little, however, about the demographics
and socioeconomic characteristics of those who leave. Unfortunately,
households who leave the area are not questioned as to their reasons
for leaving. And those businesses that have moved into the area are
reluctant to list the availability of refugee labor as a reason for
coming to the Mohawk Valley . To address the question indirectly, I
use data from the New York State Department of Labor on job openings
in June 1999 and a separate database on registered jobs seekers in the
same month. The data represent only a share of the total number of opening
and job seekers as not all employers contact the NYS job placement offices
and not all job seekers register for employment services with the DOL
job placement services. However, the DOL is the largest database available
for this purpose and all people receiving unemployment benefits are
registered for with the job placement service automatically . Moreover,
not all job seekers are unemployed; some are simply looking for better
work. Nonetheless the Department of Labor data are instructive. In Table
8 I present the June 1999 job openings and job seekers data by occupation
and combine this with the initial jobs data on refugees' first jobs
over the last ten years. The table attempts to show where the refugees
tend to find jobs relative to the rest of the job-seeking pool and to
the number of openings in the various occupational classes. Whereas
a large proportion of job seekers are looking for managerial, professional,
or technical or sales positions, refugees rarely enter into these positions.
Table 8 shows that 46 percent (top three rows) of job seekers are seeking
jobs in these three occupational categories. Only 5 percent of refugees
find managerial, professional, or technical or sales positions. In fact
only 11 refugees have ever been placed directly into managerial or professional
jobs. About 40 percent of the job openings are in the service sector.
This was the only sector where the number of opening was Table 8: Job
Openings, Seekers, and Refugee Workers Occupation Current Openings in
June 1999 Current Seekers in June 1999 Seekers/openings, June 1999 Initial
Refugee Jobs since 1989 Initial Refugee jobs/Current Openings Managerial
107 304 2.84 2 0.02 Professional 120 365 3.04 9 0.08 Technical, Sales,
Admin Supp 723 1539 2.13 148 0.20 Service 1141 820 0.72 315 0.28 Farming
3 46 15.33 114 38.00 Precision Production 251 501 2.00 490 1.95 Operatives
529 1182 2.23 1901 3.59 2874 4757 1.66 2979 1.04 Sources: New York State
Department of Labor and Mohawk Valley Resource Center for Refugees.
greater than the number of seekers. The final column shows that the
total number of refugees who have taken service jobs is less than 30
percent of the number of jobs advertised in a single month. In contrast,
refugees appear to take a larger share of the job openings in the agricultural
occupations. Most of these agricultural jobs are at local greenhouses,
jobs that pay among the lowest of all refugee jobs. A vast majority
of refugees gain jobs in the precision production or operative and laborers
categories. In fact 80 percent of refugees have been placed in jobs
in one of these two categories. Again, the language requirements for
these jobs explains a large share of the reason refugees are taking
these jobs. About 35 percent of job seekers, who also include refugees
registered through the state employment service, are looking for these
production, machine operator, and laborer jobs. While it is impossible
to determine if refugees have increased unemployment among natives,
if such substitution has taken place, you expect it to be in the precision
production or operative and laborer occupations. There is little evidence
that refugees have hurt the employment opportunities of native workers.
As shown in Table 4, employment has been relatively stable in the late
1990s while the population has decreased. The result has been declining
unemployment rates. Native workers now face the lowest unemployment
rates in the last 20 years. Some may counter that the refugees effect
is being under counted since many of those pushed out of jobs have left
the area. It cannot be said with any certainty, that native population
outflows would have been lower had the refugees not been coming. Yet
the native outflows have so far outnumbered the inflow of refugees.
To the degree that crowding out is real, that refugees have displaced
native workers, it would have to be in the small assembly and sewing
jobs and to an even lesser degree in the production and machine operator
jobs, jobs which pay generally low wages. A similar argument applies
to the question of the impact of refugees on wages. Such impacts are
likely small, likely localized to a small sector of Oneida County, and
likely localized to a small sub-sector labor market. One final piece
of information is helpful in sorting out the crowding out puzzle. The
MVRCR works hard to place refugees only in jobs that provide health
insurance benefits. Given that many smaller employers cannot provide
health insurance benefits and that jobs that pay relatively low wages
are much less likely to offer health insurance benefits, refugees take
a very selective share of the low wage jobs available. This may be viewed
in two ways. First, one may conclude that the refugee impact, to the
degree that there is one, is on an even smaller sector of the labor
market. Or, one may conclude that in that smaller area, the impact must
be even stronger. Disentangling this puzzle would require far more data
than is currently available. 6. An Accounting of the Fiscal Benefits
and Costs 6.1 Composite Household To predict the costs of future waves
of refugees, I use the average characteristics of all refugees households
arriving between 1990 and 1999 to define the typical or composite household.
Naturally, as refugees come their families or households differ in many
ways. Some may have one adult while others have three or 4 adults and
several children. Finding the exact cost for each family type would
be cumbersome. Because the purpose is to predict future costs, and because
Table 9: Means and Descriptive Statistics for Composite Refugee Household
Variable Mean Std.Dev. Min Max Tenure in U.S. (In Years) 4.80 3.07 0.68
11.52 Household Size 3.23 2.22 0 19 Number of Children 1.27 1.67 0 15
Number of Adults 1.95 1.07 0 8 Age of Householder 29.72 14.22 0.09 89.84
Householder > 60 years of Age 0.05 0.21 0 1 HouseholderMarried 0.53
0.50 0 1 From Bosnian 0.47 0.50 0 1 From USSR 0.26 0.44 0 1 From Vietnam
0.22 0.41 0 1 From Eastern Europe 0.02 0.13 0 1 From Africa 0.02 0.13
0 1 From Cuba 0.01 0.09 0 1 N= 1415 householdsSource: Calculations based
on data from the Mohawk Valley Resource Center for Refugees. we have
no information on the characteristics of future refugees, our best guess
is that future households will be, on average, similar to the refugees
who arrived from 1990 to 1999. The data on refugees come from the Mohawk
Valley Resource Center for Refugees. The data set includes limited information
on most refugees who arrived in Utica between 1989 and 1999, and who
did not move out of the area. Altogether there are 1415 households in
the sample and 4567 individuals. A household is defined as all people
living together at a particular address or dwelling. The average tenure
in the U.S. of those in the data is about 4.8 years. Table 9 displays
the mean characteristics of the households in the data. The composite
household has 3.22 people, including 1.27 kids and 1.95 adults. The
average age of the adults in the household is less than 30 years of
age, while the average age of the children in the household is 9.2 years
of age. Only 4 percent of the households are headed by an elderly person
and only 3.7 percent of all refugees who arrive are greater than 65
years of age. About one-half of the adult householders are married.
Finally, the composite household is 48 percent Bosnian, 26 percent Russian
(former Soviet Union), and 21 percent Vietnamese. 6.2 The Refugee Center
The Mohawk Valley Resource Center for Refugees is an affiliate of the
Lutheran Immigration and Refugee Service (LIRS). Given its nearly $1.7
million budget (1999), one may ask whether the operation of the refugee
center itself is a cost to the community. Certainly newspaper articles
in the Observer Dispatch have suggested that County tax dollars help
support the refugee center's operations. In fact, the operation of the
refugee center, apart from the flow of refugee who come because of it,
is more likely to be a benefit than a cost to the community. The MVRCR
operates largely on private donations from outside the Mohawk Valley
and from public and private grants. The primary funding comes from two
sources, the LIRS and State Grants which transfer competitive state
and federal funds to the refugee center. The LIRS administers funding
from the Office of Refugee Resettlement (ORR) for all the local resettlement
costs of refugees, $270,000 in 1999, and an additional $370,000 for
operations. Resettlement costs include the first month's rent on an
apartment, furniture, food, hygiene kits, and a small amount of cash
intended to get the families through the first couple of weeks in Utica.
Money from the LIRS funds 38 percent of the MVRCR expenses. A majority
of the New York State grants, which finance over one-half the expenses
of the refugee center, are federal dollars. More than 50% of the state
funding comes from the U.S. state department budget. Another $250,000
or 30 percent of the NY funding, comes from federal block grants for
targeted assistance. This funding is distributed based on the percentage
of refugees in the county population. These federal monies are allocated
to the 30 counties in the U.S. with the greatest percent of new refugee
arrivals in the last three years. The money is available strictly for
employment services. revenues come originally from state and federal
revenues. Roughly 2 percent of the MVRCR budget comes from the Oneida
County Health Department to fund translators for the county's tuberculosis
clinic. However, this money comes from the State of New York Health
Department from monies which they receive from the federal government's
Center for Disease Control. Another 2 percent of the center's budget
comes from the Utica City School District for the rent and janitorial
expenses of the classroom space used by the school district for ESL
training. Again, this particular funding come from New York State Employment
Preparation Education grants to the Utica School District. In both cases,
what appear to be costs to local taxpayers turn out to be dollars flowing
into Oneida County from the outside. Table 10: Overview of the 1999
MVRCR Budget RECEIPTS Dollars Share of MVRCR Budget Receipts from NYS
Grants $854,000 51.11 LIRS $642,951 38.48 U.S. DHSS $54,000 3.23 Oneida
County T.B. Clinic (Steve Smith mentioned this is State $) $34,000 2.03
Utica City School* $35,000 2.09 Other Private and Miscellaneous $51,000
3.05 Total Receipts $1,670,951 100.00 EXPENSES Payroll $936,000 56.02
Employee FICA, Insurances, Retirement $230,486 13.79 Operations and
Supplies $92,245 5.52 Vocational Training and Conference $22,400 1.34
Capital Expenses, Rent, Building Maintenance Insurance $83,600 5.00
Other Miscellaneous $16,200 0.97 REAP Citizenship Spending $20,000 1.20
Local Resettlement $270,000 16.16 Total Expenses $1,670,951 100.00 *
This item is for rent of school space for ESL classes and is part of
the Utica School Budget.Source: Mohawk Valley Resource Center for Refugees,
Annual Budget, 1999. While some money in the MVRCR appears to come from
local tax revenues, even these 6.3 Education The literature on immigration
suggests that the costs of education, little of which is funded by the
federal government, play a major role in making immigration a net cost
for state and local governments. While the average age of refugees is
nearly 30 years of age, many families come with children, and these
children typically enter the public school system. Therefore there are
two types of education costs that must be factored into the fiscal analysis,
the cost of English training for all refugees and the cost of general
education for refugee children. Whether education should be included
at all in such a question is a debatable question. One could argue that
education is a right, like the right to vote, and should not be included
in any type of economic analysis. In fact, education is an investment
the community makes for everyone who enters the area, not just for refugees.
Education costs must be included in a fiscal analysis because they are
real costs, funded in part through local taxation. The future benefits
of the education expenditures, namely the taxes from future economic
activity of adults and refugee children, are also accounted for in this
study. I assume that all refugees needing education reside in the Utica
school district. However, the Utica/Rome community does not bear the
full cost of educating refugees and their children. State and federal
dollars also fund local education. Because the goal of this study is
to determine the local fiscal impact, it is crucial to isolate those
costs that are borne by local population. For example, according to
data from the U.S. Department of Education, in 1999, 36.3 percent of
the Utica City school district expenditures on education were paid through
locally raised revenue, well below the national average for local contribution
of 45.5 percent. Typically, studies use the average per-pupil cost of
education to estimate the cost of adding additional students. With this
method, doubling the number of students would double total education
costs, a concept that economists call constant returns to scale. I,
however, find strong support for the argument that adding additional
refugees to the school district increases costs by less than the per
student average. Finding the marginal or additional cost of each student
added is also a difficult task because it would vary depending on whether
the additional student required the hiring of an additional teacher
or the building of an additional classroom. I use a modified average
per-pupil cost that acknowledges that there are some costs which are
unlikely to change when an additional student is added. It is unlikely,
for example that adding additional students will lead to the hiring
of an additional superintendent, additional principals or additional
custodial or building maintenance staff. Furthermore, given the decreasing
Utica population, the refugee influx has not added significant strain
on the number of classrooms or buildings. Therefore, building and maintenance
costs would be approximately the same whether the refugees came or not.
A close review of the Utica School District 1999-2000 annual budget
reveals that only 69.5 percent of the expenditures were likely to be
affected by the refugee population. These expenditures included teachers'
salaries, transportation, special programs and about 86 percent of employee
benefits. The adjusted per-pupil average cost is calculated by multiplying
the 69.5 percent adjustment factor by the local share of total expenditures
and dividing this number by the number of students enrolled. Using 1999
number, the total local share of school expenditures was $21.87 million
including local taxes receivable, payments in lieu of taxes, and taxes
on consumer utility bills. Using the October 1999 enrollment of 8,319
students, the adjusted per-pupil local cost is $1827. In addition to
the per-pupil cost above, the special needs of refugees may require
additional expenditures, possibly from local funds. Most if not all
refugees require extra language training due to low levels of proficiency
with the English language, typically for a three year period . The Utica
school district currently provides English as a Second Language (ESL)
assistance to approximately 1000 students throughout the district, 90
percent of which are refugees. Such training requires additional teaching
staff, space, and materials which would not be purchased if not for
the influx of refugees. In the 1998-1999 school year, the Utica School
District spent an additional $1,467,648 on instruction for students
needing language training. Of this, only a small share is funded from
the local tax dollars. After deducting Federal funds given through the
Emergency Immigration Education Program and Title 1 and the New York
State funding from Part 154, local taxpayers paid an additional $158,239
to provide ESL instruction for 882 students. The per pupil costs come
to $179 per student per year above the general education costs described
above. Using our profile of the typical refugee family with 1.27 children
and the age distribution of the arriving children, the average cost
of one year of education for the composite refugee family is $2,548.
Again this is the amount paid out of local taxes for the typical refugee
household. The simulation result presented later in this report uses
the actual age distribution for refugee children upon arrival in Utica
to determine the number of years of schooling required for refugee children.
As we will see, education is the single greatest current expense of
the influx of refugee into the Mohawk Valley. 6.4 Public Assistance
Newly arriving refugees come with few belongings and no means of support.
Therefore, for a while they must depend on public assistance to meet
their financial needs. The Refugee Center works with DSS to sign refugees
up for TANF, Food stamps, medicaid, and any other aid for which they
may qualify. To the degree that local taxes pay for these programs,
local taxpayers are picking up the bill for refugee resettlement. (Of
course significant numbers of refugees are also working and paying the
taxes supporting public assistance also. This will be accounted for
in the discussion of benefits.) In New York, counties contribute about
25 percent of the benefit costs for TANF and Medicaid. Food stamp benefits
and benefits through Supplemental Security Insurance, a program for
the elderly and disabled, are paid for by the federal government. To
the degree that local residents pay for food stamps and SSI, such costs
would be the same for local residents no matter where in the U.S. the
refugees were located . In addition to benefits, such programs carry
significant administrative costs; again, these costs are shared. Because
the public assistance programs would be in place without refugees, the
addition to administrative costs are likely to be negligible. This section
explains the computation of public assistance costs. To calculated public
assistance costs, I estimated program participation equations using
administrative data from the Oneida County Department of Social Services.
Three separate probit equations are estimated to predict the probability
of participation in TANF, Medicaid, and Food Stamps. I estimate program
participation as a function of tenure (time since arrival), Table 11:
Participation in Public Assistance Programs Sample Size Percent Participating
TANF Medicaid FS OVERALL 1415 9.5 35.9 14.4 Bosnia 663 10.4 32.9 8.9
Former Soviet Union 368 12.5 52.4 26.3 Vietnam 311 5.8 27 13.8 Other
73 2.7 19.2 6.8 Less Than 4 Years 736 12.8 35.9 10.7 Bosnia 560 10.7
33.6 9.1 Former Soviet Union 95 30.5 63.1 20 Vietnam 63 7.9 23.8 12.7
Other 18 0 5.5 5.5 More than 4 years 679 6 36.1 18.4 Bosnia 103 8.7
29.1 7.8 Former Soviet Union 273 6.2 48.7 28.6 Vietnam 248 5.2 27.8
14.1 Other 55 3.6 23.6 7.3 Household size 1 to 2 people 619 6.3 27.9
14.7 2 to 4 people 490 9.6 39 14.1 5 to 6 people 190 12.1 44.7 14.7
More than 6 people 74 24.3 50 13.5 Source: Oneida County Department
of Social Services. household size, and age of the householder. The
estimated equation is then used to predict the probability of participation
for our composite household. The key variable in the equation is tenure.
As expected, the probability of participation in TANF and Medicaid decreases
with time. Tenure does not have a statistically significant relationship
to food stamp participation. The total cost of TANF and Medicaid for
the composite refugee household is assumed to be the product of the
probability of participation in a year, the average number of months
on TANF or Medicaid for those who participate, and average monthly benefit
for those who participate. Average monthly benefits were calculated
from a small random and anonymous sample provide by the Oneida DSS.
Alternative approaches may have been to use the maximum grants available
for a particular family size or the average grant size for all participants.
However, to the degree that refugees are employed and earning income,
benefits may be significantly less than the maximum grant and may be
different from the typical program participant. Medicaid is clearly
the most heavily used of the part-county financed programs. However,
for those households receiving Medicaid benefits, one cannot assume
that the entire household receives the benefit. Nearly all refugees
are placed in jobs providing health insurance for the employee. In most
cases, the refugee has the option to pay for family coverage although
at a significant cost. Therefore, many of the households receiving Medicaid
receive benefits for those not covered by the employer's policy. Table
12: Probit Estimates of Refugee Program Participation TANF Medicaid
Food Stamps Log of months in U.S. -.3624(-5.278) -.0895(-1.809) -.0361(-0.685)
Household size .11195.707 .0920(5.863) .0623(3.867) Age of Householder
in Years -.0049-1.400 .0138(5.815) .0137(5.545) Constant -.2219(-0.777)
-.7384(-3.470) -1.199(-5.287) Observations 1415 1415 1415 Log Likelihood
Ratio, Chi2(3) 63.98 75.99 47.52 Log likelihood -413.550 -886.363 -755.324
Pseudo R2 0.0718 0.0411 0.0305 As with education, program benefits are
projected over time for the typical household and then multiplied by
the typical cohort size to determine the local share of the total public
assistance costs. These costs are then discounted back to the present.
One obvious problem with this approach is that family composition changes
over time. In ten years, many of the refugee children will form their
own households (which also have some probability of participating in
public assistance programs) making the existing households smaller.
At the same time, refugee households may have additional children, increasing
household size. To avoid having to make assumptions about fertility,
family formation patterns and welfare use among yet to be formed households,
I assume that the current composite household stays together for the
next 50 years. I am sure that some will think of other costs, some of
which will be real costs to local taxpayers, some of which will not.
For example public housing and public health costs such as the TB clinic
through the Oneida County Health Department are services which benefit
refugees and for which they do not pay. Yet neither involves city or
county taxes. The maintenance and subsidies for public housing are federal
dollars which come through the Municipal Housing Authority. The TB clinic
mentioned above receives money from the state health department which
again distributes federal monies. For these and any other perceived
costs, it must be shown to use actual local tax revenues to be of significant
cost to local taxpayers. 6.5 Fiscal Benefits To qualify as a fiscal
benefit, any perceived benefit must pass the same test as the costs;
it must result in an increase in local tax revenues over that which
would exist in the absence of the refugees. For example, increased sales
(and therefore tax revenues) at one store, say one owned by a refugee,
is not a benefit if sales are reduced at another store in the tax jurisdiction.
Similarly, employing an individual (who would then pay taxes on local
consumption) cannot be counted as a benefit if that individual would
be employed somewhere else. In both cases, however, if the spending
in the area increases, then they would qualify as true benefits. Unfortunately,
benefits are harder to quantify than costs. We know that children go
to school and the rate of participation in public assistance programs.
Nonetheless, there are some clear and some potential benefits to resettling
the refugee population in Utica. For example, to the degree that the
refugees increase total taxable consumption in the area, sales taxes
revenues increase, lessening the burden on native taxpayers. Refugees
also buy houses and pay property taxes. This section describes the fiscal
benefits to the community and lays out the assumptions and rationales
for these benefits. Earnings Of course, one of the key determinants
of the economic contribution of refugees to the local fiscal picture
is the degree to which refugees participate in the labor markets. Refugee
earnings are not a direct benefit to the community, but assumptions
on earnings are necessary to determine the degree to which the refugees
benefit the local economy. Ideally, such data would be available from
a large cross-section of refugees who have been in Utica for varying
periods of time or a panel data which follows the same refugee households
over time. With such data we could observe employment rates and average
wages as a function of tenure in the U.S. Unfortunately, little direct
information is available regarding the employment and wage picture of
the refugees. We know most about the employment situation of refugees
when they first begin working. After several months of English as a
Second Language training, all working age adults must enter the labor
market and must accept any job that comes their way. The employment
office at the MVRCR works hard to place the refugees with employers
offering health benefits (not necessarily paid by the employer) and
in jobs with possibilities of advancement, a tough standard considering
the language barriers the refugees must still overcome. Unfortunately,
many of the jobs offer little possibility of advancement. Using data
provided by the refugee center, I can identify the first employment
situation, including their hourly wage and job title. Typically, refugees
retain the first job, at least through the first year during which the
refugee center remains in relatively close contact. After the first
year, very little is known about the labor supply of refugees. We must,
therefore, develop wage profiles based on indirect information such
as job titles and public assistance participation. For example, knowing
that roughly 35 percent of households participate in Medicaid tells
us that the median household income is above the poverty line, the cutoff
for Medicaid. Other recent research about a small subset of local refugees
also gives clues. Coughlan and Owens-Manley conducted interviews with
two groups of successful refugees, those who have gained citizenship
and those who have purchased housing. Although this research samples
those who have been most successful, the research demonstrates that
some refugees are finding higher paying jobs. For example, they interview
refugees who work as a paralegal, a city planner, an accountant, a part-time
teacher at SUNY/IT, an educational coordinator, a realtor, and a computer
programmer. These positions pay between $21,000 - $40,000 per year.
The Coughlan and Owens-Manley research does not demonstrate the typical
earnings path, but it does demonstrate that many refugees do relatively
well in local labor markets. Instead, the simulations below use the
typical wages from the jobs data provided by the MVRCR. It should be
emphasized that the jobs database contains information only on the first
job that each refugee takes, or in some instances a second job if people
switch jobs during the first year. In 1999, the average starting pays
was $6.40, while in 2000 (January through April) starting wages averaged
$7.18. Therefore, we assume that the starting wage of our composite
individual is $7.18 in year 1 which translates to an annual income of
$14,360. Following the previous literature on immigrants, I assume that
wages will increase by three percent per year (in real terms). Household
income depends not only on the wage rate but on the number of workers
and the number of hours worked. The number of potential workers for
this study is1.95, the number of adults in our composite refugee household.
Coughlan and Owens-Manley find that a high percentage of families with
two adults have both adults working, typically full time. Initially,
nearly all adult refugees work full time, and many work more than one
job. Long term, less is known. Given little is known, I make assumptions
as to the employment rate and hours worked for the first adult and the
remaining .95 adults in the composite household. The simulation assumes
an employment rate of 95 percent for the first adult in the household.
We know that about nine percent of the refugee households receive TANF
and data on a sample of those on TANF suggests that roughly one-half
of those on TANF are also employed. The remaining five percent are unemployed.
I assume an employment rate of .80 for the remaining adult (actually
.95 of an adult). All workers are assumed to work 40 hours per week.
At this rate, our composite households are predicted to earn an average
of $26,000 per year. Sales Taxes The most direct fiscal benefit of refugee
resettlement is the tax revenue the county and city collects on taxable
consumption. In Oneida county, food, and medications are exempt from
local sales taxes. Therefore, refugees pay sales taxes on the portion
of their incomes spent on items other than housing, food and health
care. Nationally, low-income households spent approximately 20% of their
budget on food. In addition, of the 65 percent of households not on
medicaid, the typical health insurance contributions are an estimated
$1500 per year. In addition, housing expenditures for the typical household
of 3.22 people is estimated to be the cost of a two-bedroom apartment
in Utica, $335 per month or $4020 annually. Given the local share of
sales taxes is 2 percent, sales taxes from a single refugee household
are calculated using the following formula: Sales Tax = [ 80 percent
of Earnings - $1500 - $4020] x 2 percent. Property Taxes Over the last
five years, hundreds of refugees have purchased houses, mostly within
Utica. Many of theses houses were off the tax rolls or in danger of
falling off. The refugees also improve the houses they buy, raising
not only their own property values but also the value of the entire
housing stock. Predicting future benefits depends not only on the number
of houses already purchased, but on the future demand. The most accurate
data available concerns homes purchased by Bosnian refugees in Utica.
As of October 1999, 217 Bosnian refugee households had purchased houses
in Utica, roughly one-third of all Bosnian households. Since October,
Bosnian families have continued to buy houses at a rapid rate, boosting
unofficial estimates to roughly 300 home purchases. If no other refugees
had purchased houses, this would mean that 20 percent of the 1415 refugee
families in our database had purchased houses. There is plenty of anecdotal
evidence that other refugees are buying houses, although the Bosnian
refugees may be buying at a higher rate. The net fiscal benefit simulations
for refugee households, including future households from unknown countries
of origin, use relatively modest estimates of home ownership. I assume
that the probability that a composite refugee buys a house in Utica
is zero for the first three years. In year four the probability of owning
a house jumps to .20 and increases by .02 annually until it reaches
a maximum of .60 in year 24. The probability remains at 0.60 for the
rest of the household's lifetime. The children of refugees may also
purchase houses. The stream of children's home purchases is more complex
due to the age distribution, years of education, probability of renting
and the probability that they leave the area. After all these assumption
are made, the simulations assume that it takes 20 years for home ownership
among children to reach 40 percent. Given rates of exodus, home ownership
among children is maxed at 50 percent rather than the 60 percent for
the adults. I assume a typical annual property tax of $2000 per house
owned. Given these assumptions, the composite refugee household pays
an annual property tax of $650 in year five. Those not living in owner-occupied
housing either live in private apartments or in public housing. It is
reasonable to assume that those in privately owned apartments share
a portion of the rent paid by the landlords. Certainly, if 1,000 refugee
households who rent were to leave Utica tomorrow, tax collections on
these properties would be affected, particularly because the native
population is also leaving the area. The simulations attribute a 20
percent share of the property taxes on rental units to the refugee renters.
The total property tax paid by the composite household is the sum of
the owner-occupied and renter's share of property tax. Total property
tax revenues from the original family unit start at $340 per household
in year one and reach $1000 per household in year 14. The children's
property tax in year 14 adds another $156 to the original household's
annual property tax contributions. Increased Property Values Whereas
adding one refugee household to the pool of home buyers may not affect
housing prices in Utica, adding a large number of households each year
will. Refugees represent the fastest (and perhaps, only) growing segment
of the local population of home buying age. Not only do refugees buy
houses, they affect the property values of other home owners. Utica's
housing market has suffered many years of population decline, migration
to the suburbs, and increasing inner city poverty rates. Combined, these
factors have had adverse effects on property values in the city. Anecdotes
abound as to the positive effect that refugees home purchases are having
on the community. Dilapidated homes are being renovated, and once failing
neighborhoods are being beautified. Yet, placing a value on the impact
of such changes on property values is an imprecise exercise. Using the
Utica City School Board budget, I estimate the total value of taxable
property to be $1.13 billion. The estimate is based on collections of
$19.1 million with a school tax rate of 16.37 per thousand. I speculate
that property values are 1 percent higher in Utica due to the flow of
refugees into the area. In some neighborhoods the impact may be much
higher while in others the refugee effect may be negligible. The willingness
of refugees to buy inner city homes may increase demand for houses outside
of the Utica City School District. The simulations assume there is no
effect on housing values outside of Utica. Tax Leakages on Public Assistance
Refugees bring with them an array of outside monies from sources such
as food stamps, SSI, and On-the-Job Training grants. While spending
on these programs cannot be counted as benefits to the community (they
are consumed by the refugees), there may be local tax leakages from
the additional spending. The simulation adds up the estimated benefits
from the primary transfer programs and assumes that 80 percent is spent
on taxable consumption which is taxed at a 2 percent rate. The result
is a small annual benefit in the range of $10-15 per household. The
Refugee Center The refugee center itself contributes to the fiscal health
of the community. It employs approximately 40 people, adding to total
employment in the area. The simulation counts tax leakages from MVRCR
payroll spending as benefit to the community. How Many Would Have Left?
The million dollar question, perhaps literally, is what would have happened
if the refugees had not come to Utica. Would more or fewer people have
left? Would wages be higher or lower? Would there be fewer business?
These are central, not peripheral questions. Yet answering any of these
questions precisely would be impossible. I simply point out that the
simulations presented below are intended to add information to the decision-maker's
pool of knowledge. It is always the reader's prerogative to add information
where crucial items have been omitted. For example, perhaps the flow
of refugees has encouraged one employer of 100 people to remain in the
area. Holding on to that one employer saves local taxpayers money that
would have gone to TANF, Home Relief, or making up for lost property
taxes. A firm of 100 people paying an average of $25,000 per year would
add nearly $1.6 million in spending on taxable items resulting in sales
taxes of $31,168. In addition, property taxes on the business and perhaps
lost property taxes on other real estate would add to the loss. Adding
in this type of savings, say $65,000 per year for this one business
establishment, would result in greater benefits than the simulations
show. 7. Simulation Results he ultimate question concerns whether refugees
are a net fiscal benefit or net fiscal cost to the natives of the Mohawk
Valley. This study finds the resettlement of refugees in Utica to be
similar to any major investment; refugees are a net cost in the early
years and then yield benefits for many years to come. In the long run,
the MVRCR's efforts to resettle refugees in Utica, quite apart from
any non-fiscal benefits, is a net fiscal benefit to the community. To
reach this conclusion, I simulate the benefits and costs over time for
the composite household. Because the refugees come in large numbers
each year, I also simulate what I would call a typical year, a year
in which 750 refugees arrive. Using our composite household of 3.22
people, this equates to 233 households. Finally, because such cohorts
arrive each year, I simulate overlapping waves of 233 households per
year. The results are presented below in Table 13. Table 13 presents
results for each of the three simulations. For each, I present a stream
of 50 years of predicted net benefit. Benefits are adjusted for inflation
and expressed in discounted or present value terms. The discounting
reflects the reality that any money invested in refugee resettlement
could have been invested otherwise. For example, given the choice and
assuming zero inflation, most people would rather have $10,000 today
than $10,000 ten years from now. If given $10,000 today, it could be
invested and be worth far more than $10,000 in ten years. Therefore,
I discount all future benefits and costs to present value terms. The
single household results simulate the net benefits for the composite
household. The household is assumed to stay in Oneida County and results
are projected out 50 years. In the early years, the household is a net
cost to the community, although the net cost diminishes each year. The
cost diminishes over time for a number of reasons. First, public assistance
participation declines slightly over time. Second, the number of refugee
children in school declines as the older children graduate. This becomes
stronger over time as initially younger refugees enter school as the
older children leave school. Rising wages and increased probability
of home ownership also lead to smaller net costs over time. Annual net
benefits become positive for the individual household in the thirteenth
year. The cumulative discounted benefits remain negative for the first
30 years. Table 13: Simulated Annual and Cumulative Discounted Net Benefits
Single Household 233 Households Overlapping Waves Year Annual Cumulative
Annual Cumulative Annual Cumulative 1 -4413 -4413 -590207 -590207 -590207
-590207 2 -3403 -7816 -364129 -954336 -954336 -1544543 3 -2984 -10800
-180328 -1134664 -1231236 -2775779 4 -2330 -13129 -63263 -1197927 -1369185
-4144964 5 -2111 -15240 -31831 -1229758 -1468045 -5613009 6 -1926 -17167
-7048 -1236806 -1535657 -7148666 7 -1524 -18691 58469 -1178337 -1524656
-8673322 8 -1224 -19915 103988 -1074349 -1458429 -10131751 9 -937 -20852
146652 -927696 -1340386 -11472137 10 -659 -21511 186901 -740796 -1173422
-12645559 11 -399 -21910 223409 -517387 -961974 -13607533 12 -147 -22057
258122 -259265 -708208 -14315741 13 99 -21958 291182 31916.68 -414121
-14729861 14 338 -21620 322698 354614.9 -81580.7 -14811442 15 571 -21048
352757 707372 287647.3 -14523795 16 799 -20250 381429 1088801 691883.4
-13831911 17 971 -19279 400232 1489033 1119568 -12712343 18 1135 -18144
417390 1906423 1568726 -11143617 19 1290 -16854 433032 2339455 2037533
-9106084 20 1368 -15486 435687 2775142 2510806 -6595278 21 1444 -14042
437942 3213083 2988025 -3607253 22 1458 -12584 430238 3643321 3457537
-149716 23 1471 -11113 422662 4065983 3919444 3769729 24 1483 -9630
415225 4481208 4373860 8143588 25 1479 -8151 405437 4886645 4817999
12961588 26 1475 -6676 395991 5282637 5252220 18213807 27 1471 -5204
386882 5669519 5676871 23890678 28 1468 -3736 378102 6047621 6092295
29982973 29 1465 -2271 369644 6417265 6498830 36481803 30 1463 -809
361498 6778763 6896801 43378604 31 1461 652 353658 7132420 7286530 50665134
32 1459 2111 346114 7478534 7668327 58333462 33 1458 3569 338858 7817392
8042496 66375958 34 1457 5026 331883 8149275 8409330 74785288 35 1457
6482 325179 8474453 8769117 83554405 36 1457 7939 318739 8793192 9122133
92676538 37 1457 9396 312554 9105746 10058855 102735393 38 1458 10854
306616 9412362 10763259 113498652 39 1460 12314 300919 9713281 11374448
124873100 40 1462 13776 295453 10008734 11840946 136714046 41 1464 15240
290213 10298947 12262850 148976896 42 1467 16708 285189 10584136 12648233
161625128 43 1471 18178 280376 10864512 12949953 174575081 44 1475 19653
275767 11140279 13191612 187766693 45 1479 21132 271354 11411632 13376829
201143522 46 1484 22616 267131 11678764 13508701 214652223 47 1489 24105
263093 11941856 13591859 228244081 48 1495 25601 259232 12201089 13628659
241872740 49 1502 27102 255544 12456632 13621281 255494021 50 1509 28611
252021 12708653 13571769 269065790 Source: Author's calculations. The
single household simulations do not take into account the fiscal benefit
of the MVRCR or the effect of the refugee influx on property tax collections.
These two effects require large numbers to come into play. If I convert
property tax revenue increases and increased sales taxes due to the
refugee center into per household terms, then an individual household
becomes an annual net contributor to the fiscal picture in year 7 and
becomes a cumulative contributor in the twelfth year in the Utica area.
The second set of simulations accounts for the fact that in a typical
year we can expect upwards of 750 refugees to arrive. Using 750 people,
there are 233 composite households in the typical year. These full cohort
simulations now incorporate the property value effects and factor in
the benefits of the refugee center itself. Furthermore, the assumption
that the household stays in Utica is now relaxed by allowing 15 percent
of refugees to leave the area after the first two years. As with the
single household simulations, 80 percent of the children are expected
to stay in the area. The annual net benefit for a full cohort is negative
for the first six years and positive every year afterwards. Again, the
education and public assistance costs overwhelm benefits in the early
years. After six years, the annual benefits become stronger than the
annual costs. This does not imply that the costs of such factors as
Medicaid and TANF are reduced to zero. These costs remain, although
they do diminish somewhat over time. Rather, other positive benefits
due to increased participation in labor and real estate markets now
become stronger than the negatives. After 13 years, the cumulative net
benefit becomes positive and continues to increase for every year after.
The final two columns of Table 13 report simulation results for overlapping
waves of refugees, such that 233 households arrive every year. These
simulations probably best depict Utica's reality. In this case, the
period of negative net annual benefits is longer than for the single
cohort because the largest costs come in the early years. In this simulation
the cumulative benefit is negative for 22 years and becomes positive
in year 23. This suggests that after 23 of operation, the total effect
of a continual flow of 233 refugee households per year will be and will
remain positive. 8. Sensitivity Analysis The results in any analysis
are based on a combination of observed data and a set assumptions made
by the researcher. Some assumptions must be made to capture the best
guess as to present and future conditions and simplify analysis. For
example, I assume that future cohorts of refugees will be similar to
the composite household, the average of all past waves of refugees.
Of course, not a single cohort will look exactly like the composite,
but it is my best guess as to the typical characteristics of future
refugees. Given that the simulations make use of a long list of assumptions,
the results are likely to be affected by the reasonableness of such
assumptions. If it is more reasonable to assume that future waves of
refugees will look more like the refugees of the past 5 years rather
than those arriving more than five years ago, then the assumption is
open to criticism. One way of determining the degree to which assumptions
affect the final results is to run the analysis under various assumptions.
If the final results don't change when we change an assumption, say
by using the characteristics of recent arrivals, then we have determine
that the results not sensitive to that particular assumption. The major
assumptions for this study are listed in Appendix 1, and some may be
more contentious than others. Some of the major assumptions concern
the rate of wage increases, the degree of labor market participation,
the stability of patterns of public assistance usage, the propensity
to move outside the area, the impact on local real estate prices, and
the appropriate rate of discounting of future benefits and costs. I
conduct sensitivity analyses on three types of assumptions: the social
discount rate, the rate of future wage increases, and the impact of
refugees on local real estate markets. The discount rate is a key parameter
in any analysis. Determining the discount rate is akin to asking how
much society values receiving a sum of money, say $100, at some time
in the future. If the current value is less than the $100, then some
mechanism must be put in place to discount future benefits and costs.
I run the simulations at three alternative values (three, four, and
five percent) that roughly define the range considered reasonable in
the benefit-cost literature. The results are relatively robust to a
change in the discount rate. Lowering discount rate to three percent
shifts the first year of positive net benefits to year 15 rather than
year 13. Increasing the discount rate to five percent has no effect
on the break-even year, but reduces the estimated long-term benefits.
Results are quite sensitive to the effect on local housing prices. I
assume a 1 percent increase in housing prices after the 3rd year of
residence. This is a cumulative effect and is assumed to be fixed over
time. Removing the price effect reduces the most significant benefit
of the refugee influx. As opposed to a single cohort breaking even in
7 years, with no real estate effect it takes 13 years to break even.
When I apply this to a model overlapping cohort it takes 35 years to
reach the first positive net-benefit year. Cumulatively it would take
much longer to break even. In a market with higher housing prices or
a smaller share of low-priced housing we would be unlikely to see the
positive effects of refugee immigration. Finally, I reran the model
with a variety of assumptions on wage growth and labor force participation.
Given the "best guess" model assumes real (above inflation) wage growth
rates of 4 percent for the main earner and 3 percent for the second
(partial) earner. To determine the sensitivity of the results to the
wage growth assumptions, I also try wage growth rates of zero and six
percent. As expected, slowing the wage growth rate to zero increases
the break-even year, extending it from 13 to 15 years. Increasing the
wage growth rate steepens the net-benefit profile, but does not change
the break-even year. The relatively small effect of these changes suggest
that small changes in the wage growth rate will have little effect on
the overall results presented in the report. 9. Concluding Remarks For
25 years, the Mohawk Valley Resource Center for Refugees has been welcoming
refugees to Utica. The refugees come with few possessions and with little,
if any, preparation for the life that awaits them in central New York.
Yet this humanitarian effort also involves the entire community as these
refugees become users of publicly funded services and contributors to
the payment of those services. This report attempts to do what no previous
research has done, determine whether refugees ultimately contribute
more than they take out of local tax payments. While the returns are
slow and modest in magnitude, this research finds refugees to be net
contributors. The initial costs which local taxpayers fund are significant
and include costs for education and public assistance. In the first
year in Utica, education costs make up 40%, Medicaid 26%, and TANF 34
% of the total taxpayers costs for refugee households. Over time, the
TANF costs drop quickly, children move out of the school systems, and
Medicaid usage drops although not as quickly as some might hope. At
the same time, their participation in labor markets (and therefore consumption
of local goods) and real estate markets leads to growing benefits for
the community. Simulations which add together all the identified and
quantifiable fiscal costs and benefits finds that refugees ultimately
give more to the community than they take away. If the simulations are
accurate, the fact that the refugee center has been operating for 25
years suggests that we have recently reached the point where cumulative
fiscal benefit of the influx of refugees positive. While new waves of
refugees bring new costs, the net annual and cumulative benefits will
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