ECONOMICS & POLITICS
Volume 190954-1985
March 2007

No. 1

PUBLIC FINANCE AND INDIVIDUAL PREFERENCES OVER
GLOBALIZATION STRATEGIESGORDON H. HANSON, KENNETH SCHEVE, AND MATTHEW J. SLAUGHTER

Do preferences toward globalization strategies vary across publicﬁnance regimes? In this paper, we use data on individual preferences
toward immigration and trade policy to examine how pre-tax and posttax cleavages diﬀer across globalization strategies and state ﬁscal jurisdictions. High exposure to immigrant ﬁscal pressures reduces support
for freer immigration among U.S. natives, especially the more skilled.
The magnitude of this post-tax ﬁscal cleavage is comparable to the pretax labor-market eﬀects of skill itself. There is no public-ﬁnance variation in opinion over trade policy, consistent with U.S. trade policy
having negligible ﬁscal-policy impacts. Public ﬁnance thus appears toshape opinions toward globalization strategies.

1. INTRODUCTION

INTERNATIONAL ECONOMIC policies that regulate the ﬂow of goods, capital,and labor across borders vary substantially not only across countries andover time but also within these diﬀerent dimensions of integration with theworld economy. One of the major puzzles in political economy is why somany countries appear to adopt relatively liberal trade policies but relatively
illiberal immigration regulations. Trade and immigration liberalization bothhave the potential to improve a country’s economic welfare through eﬃciency gains. Because international ﬂows of goods and labor both work to
integrate national labor markets with the global economy, these policies
often have similar eﬀects on worker outcomes in the labor market, leading
many scholars to view the distributional consequences of liberalization to bequite similar as well.
Absent a simple eﬃciency or distributional explanation, most existing
scholarship turns to important non-economic diﬀerences between trade andimmigration policy. Most obviously, negative voter attitudes toward foreigncultures and minority groups may be more inﬂuential for immigration thantrade, leading to relatively more public support for liberal trade policies.
In this paper, we develop an alternative argument: government policies
that redistribute income alter the distributional politics over trade and immigration policy and often favor trade as opposed to immigration as a
strategy for international economic integration. In short, we argue that
Corresponding author: Kenneth Scheve, Department of Political Science, Yale University,
PO Box 208301, New Haven, CT 06520-8301, USA. E-mail: kenneth.scheve@yale.edu
r 2007 The Authors. Journal compilation r 2007 Blackwell Publishing Ltd.,
9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA
02148, USA.

1

2

HANSON ET AL.

public ﬁnance considerations can have a major impact on who supports
liberalization and what kind of liberalization is favored.
Freer trade and immigration can aﬀect government ﬁscal activity bycomparable amounts, through their similar impacts on labor demand andthus pre-tax labor income. But there may be important ﬁscal diﬀerences
between the two. Perhaps most crucially, immigrants may pay taxes, may
receive public services, and may vote over tax and spending choices. Imports, obviously, do none of these things. This suggests that quite diﬀerent
political coalitions may organize around trade and immigration because of
diﬀerent public-ﬁnance considerations, making globalization cleavages more
fractious than they might otherwise appear.
Consider the example of the United States. What are the labor-market
impacts of freer trade and immigration? The U.S. comparative advantage inmany skill-intensive products means that freer trade is likely to lower the
pre-tax earnings of less-skilled natives relative to more-skilled natives via the
Stolper–Samuelson process (Stolper and Samuelson, 1941). For some time
now, less-skilled individuals have comprised a large share of U.S. immigrants. In 2000, 31% of foreign-born adults in the United States had o12
years of education, compared with only 13% of native-born adults. Because
low-skilled and high-skilled labor tend to be complements, freer immigration
is likely to alter pre-tax earnings of natives like trade does. There is now
abundant evidence that freer trade and immigration have in fact generated
these pre-tax wage pressures.1
But do trade and immigration generate any post-tax impacts throughﬁscal channels? Freer trade might shift economic activity and thus tax revenue across diﬀerent states, with labor-market churning in the process. But
the magnitude of additional ﬁscal costs from this adjustment in countries
like the United States is likely to be modest, given the limited extent ofprograms for labor-market adjustment and that trade, unlike immigration,
does not change the potential pool of those receiving public assistance. For
example, the only U.S. outlay explicitly linked to trade liberalization, Trade
Adjustment Assistance (TAA), has recently cost o$300 million a year –about 0.01% of total federal spending in ﬁscal 2004. Revenue eﬀects fromtrade liberalization are also likely to be relatively small: the U.S. Constitution prohibits states from taxing trade, and at the federal level trade taxes
have recently constituted o1% of total federal revenue.2
But in many U.S. states, immigrants have access to public assistanceﬁnanced by taxes. Indeed, there is abundant evidence that immigrants makegreater use of means-tested welfare programs than do natives. Freer immigration may thus increase the net tax burden on U.S. natives and thus
1
For surveys on trade, see Feenstra (2000) and Feenstra and Hanson (2003). For important migration studies, see Borjas et al. (1997), Card (2001), and Borjas (2003).
2
Fiscal revenue data come from International Monetary Fund (2004). TAA information
comes from Kletzer and Litan (2001).

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

3

tend to lower their post-tax income. Progressive tax regimes are common in
the United States, which means that this ﬁscal burden may especially hit
higher income and more-skilled natives. All this suggests that freer immigration is likely to be evaluated by natives for not just its labor-market
impacts but its ﬁscal impacts as well.3
To make these ﬁscal concerns concrete, consider the recent experiences ofCalifornia and Texas. In the mid-1990s, both states had ﬁscally conservative
governors who were rising stars in the Republican party. Pete Wilson andGeorge Bush each faced diﬃcult ﬁscal environments, as their states had been
hit hard by the recession of 1990–1991. California and Texas were also
absorbing the brunt of the rising national surge of immigration. During the
1990s, as the foreign-born share of the U.S. population grew from 7.9% to11.1%, 37.3% of immigrants chose to reside in one of the two states (vs. just
17.4% of natives).
That many new immigrants were poor and relatively likely to receive
public assistance created the perception that native taxpayers in the twostates were bearing most of the ﬁscal costs associated with immigration. The
data clearly supported this perception. Smith and Edmonston (1997) calculated that in California over 1994–1995 immigrant households received anaverage ﬁscal transfer of $3,463, or 9.1% of average immigrant householdincome, which generated an average ﬁscal cost to native households of$1,178, or 2.3% of average native household income.
Bush and Wilson appeared to have similar politics. Among other issues,
they were both unabashed free traders who strongly supported the North
American Free Trade Agreement. Yet, they adopted very diﬀerent approaches toward immigration. In California, Wilson made restricting public
beneﬁts to immigrants the centerpiece of his strategy to control spending.
Memorably, he backed Proposition 187, a ballot measure to deny public
services to illegal immigrants. In Texas, Bush embraced the state’s immigrant population and courted the Latino vote, saying he would not support a measure like Proposition 187 in Texas.
This tale of two states suggests that ﬁscal policies shape voter attitudes
toward immigration.4 High-income voters are important Republican constituents in both states. In California, which funds generous public beneﬁts
with progressive income taxes, high-income voters may worry that immigration raises their tax burden. This was one source of pressure on Wilson
to reduce ﬁscal transfers to immigrants.5 Texas, in contrast, has a weaker3
On immigrant welfare take-up, see Borjas and Hilton (1996), Borjas (1999a, 1999b), Fix andPassel (1999), Zimmermann and Tumlin (1999), and Fix and Passel (2002).
4
As shown in Figure 4, there is substantial variation across states in their generosity towardeither immigrants or natives. This variation reﬂects the diﬀerences in the public beneﬁts provided by states, which became more pronounced after welfare reform in 1996 granted states
greater discretion in setting welfare policies. See Zimmermann and Tumlin (1999).
5
See Louis Freedberg, ‘‘Wilson Defends Stance on Illegals,’’ San Francisco Chronicle, June
23rd, 1994, p. A2.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

4

HANSON ET AL.

safety net and no state income tax. Its high-income voters may perceive
immigration as having a small impact on their tax obligations, which may
have given Bush greater latitude in how to address the issue.6
In this paper, we examine how ﬁscal policy may shape individual preferences toward diﬀerent globalization strategies. We ﬁrst develop a simple
framework of voter preferences, to see how pre- and post-tax cleavages may
diﬀer between trade and immigration and also across jurisdictions. Absent
distortionary tax and spending policies, standard trade theory predicts that,in any country, freer immigration and trade will be supported by relatively
abundant workers and opposed by relatively scarce workers. For many
countries, there is now abundant evidence of this.7 But ﬁscal policies that
redistribute income, which have largely been ignored by the literature, alter
the distributional politics.8 The ﬁscal impact of globalization policies may bepositive or negative across diﬀerent settings and for diﬀerent constituencies.
At the most general level, our argument is that ﬁscal considerations aﬀect the
distributive politics of globalization policy-making. Our theoretical framework clariﬁes the pre- and post-tax pressures on individual economic welfare
from various globalization policies with speciﬁc attention to the issues likely
to be quantitatively important for our empirical application.
We then apply this framework to the case of individual immigration andtrade preferences across U.S. states over the 1990s. For at least two important reasons, this is an especially rich empirical setting. One is the ample
evidence for the United States cited above to support both labor concernsthat immigration changes wages and ﬁscal concerns that it raises native tax
burdens. The other is that U.S. states vary greatly in the size of their immigration inﬂows, the generosity of their public beneﬁts, and the progressivity of their tax structures. This variation suggests that natives in somestates will be especially ‘‘exposed’’ to immigrant ﬁscal burdens.
Our empirical work combines data from multiple sources. What results is
an individual-level dataset with which we can apply our theoretical framework to examine how individual attitudes toward immigration and trade areshaped by important forces including individual labor-market skills andstate immigration and ﬁscal regimes. We exploit variation both across statesand over time in ﬁscal exposure to immigration, such as the fact that somehigh-immigrant states oﬀer generous public assistance while others do not.
Moreover, our data allow us to control for a wide array of individual6
In particular, Texas ﬁscal policies may have allowed Bush the political space to appear bothpro-immigrant, to appeal to the Latino vote, and ﬁscally conservative, to appeal to the party
base. See ‘‘Yo te quiero mucho,’’ Economist, September 28th, 2000.
7
See Scheve and Slaughter (2001a, 2001b), Kessler (2001), O’Rourke and Sinnott (2001), Hayset al. (2005), Beaulieu (2002), Baker (2005), Mayda and Rodrik (2005), and Mayda (2006). See
Citrin et al. (1997) and Hainmueller and Hiscox (2005, 2006) for alternative perspectives.
8
See Fetzer (2000) and Dustmann and Preston (2004b) for two exceptions that consider the
impact of ﬁscal issues on attitudes about immigration.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

5

characteristics and political attitudes that have been demonstrated to have astrong correlation with opinions about trade and especially immigration.
We have two main ﬁndings. First, high exposure to immigrant ﬁscal
pressures reduces support for freer immigration among natives, especiallythe more skilled. The magnitude of this post-tax ﬁscal cleavage is comparable to the pre-tax labor-market eﬀects of skill itself. Second, there is no
public-ﬁnance variation in opinion over trade policy, consistent with thedata that U.S. trade policy has negligible ﬁscal-policy impacts. The overall
message is that public-ﬁnance concerns appear to be crucial in shaping
opinions toward alternative globalization strategies.
Our paper has ﬁve additional sections. In section 2, we develop ourtheoretical framework. Section 3 presents our data and some motivating
summary statistics. In section 4, we discuss our econometric speciﬁcations,and in section 5 we report estimation results. Section 6 concludes.
2. THEORETICAL FRAMEWORK: THE WELFARE CONSEQUENCES OFIMMIGRATION AND TRADE

In this section, we develop a framework of voter preferences to examine how
pre-tax and post-tax cleavages may diﬀer for trade and immigration and also
across jurisdictions. For clarity, we focus on voter preferences based on justindividual economic welfare. As stated in the introduction, there are many
important non-economic determinants of attitudes toward globalization.
These will be an essential part of our empirical analysis.
Let V(p, Ii) be the indirect utility enjoyed by individual i, which depends
on the vector of prices for consumption goods and services, p, and also on
after-tax income available for consumption, Ii. In turn, after-tax income
depends on the pre-tax wage income, yi; the eﬀective income tax rate, ti; andgovernment transfers gi.
Ii ¼ yi ð1  ti Þ þ gi :ð1ÞTax rates and government transfers vary across individuals by both state ofresidence and level of income. Equation (1) assumes both that all income isfrom labor earnings, and that only labor earnings are taxed. Neither
assumption is essential, but they simplify the presentation.
Together, these assumptions imply that an individual’s economic wellbeing can be expressed as Vðp; yi þ gi  yi ti Þ. Thus, wellbeing can bethought of as depending on three separate terms: prices, p, pre-tax income,yi, and the post-tax net ﬁscal transfer, (gi  yiti). It is useful to consider the
impact of freer immigration or trade on each of these terms separately.
2.1

Impacts on Prices

If immigration lowers some of the prices in p at which goods and services areavailable in a state, its residents are better oﬀ. This may be particularly truer 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

6

HANSON ET AL.

for non-tradables that use intensively immigrant labor services. As is wellknown, freer trade can also alter relative prices, with higher prices forcomparative-advantage goods and services.
2.2

Impacts on Pre-Tax Labor Income

Next, consider the change in pre-tax labor income, yi, from freer immigration or trade. If immigration increases the relative supply of low-skilledlabor, then this income is likely to rise for high-skilled individuals and fall
for low-skilled individuals. We expect the opposite impacts if immigrants are
predominantly more skilled. These wage impacts could be national or local
in scope, depending on the extent of labor-market integration across states.
And they could even be zero if immigrants are absorbed via mechanisms
other than wage changes.9
Trade liberalization can also alter individual welfare through (nominal)
pre-tax labor income. Indeed, the net impact of this channel plus the commodity-price channel on real labor income is the focus of the Stolper–
Samuelson theorem, a well-known mechanism of standard Heckscher–
Ohlin trade theory. Here, the net impact on real pre-tax earnings varies
along factor lines, not industry lines, thanks to suﬃcient interindustry factor
mobility. Impacts on pre-tax income would be diﬀerent with relatively immobile factors of production.
2.3

Impacts on Post-Tax Net Fiscal Transfer

The third channel to consider is the change in the net ﬁscal transfer received
by individual i. In countries like the United States, this net ﬁscal transfer,(gi  yiti), contains state and federal components. We assume that the federal
component can be expressed as a reduced-form function of individual
characteristics (e.g. age, income, family size). The state component of net
ﬁscal transfers will depend on the interaction of individual characteristics, assummarized by yi, and state tax and spending policies, as summarized by ti
and gi.
Consider ﬁrst how immigration will change net ﬁscal transfers received bynatives. For the U.S. case, as stated in the introduction, there is now
abundant evidence that immigrants make greater use of means-tested welfare programs than do natives. Accordingly, we assume that the arrival of
immigrants to a state raises demand and, given eligibility rules, cost for its
welfare services. In principle, states can meet this higher immigrant-related
cost in one of three ways: borrow, reduce other transfers, or raise tax revenue.
In practice, for most U.S. states, borrowing is not an option: all but Vermont
self-impose constitutional or statutory balanced-budget requirements. We
9For evidence on national vs. local wage impacts of immigration, see Borjas et al. (1997), Card
(2001), Borjas (2003), and Hanson and Slaughter (2002).

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

7

therefore assume that states meet higher immigrant welfare costs by a
combination of reduced government transfers to and increased taxation ofnatives. So, with higher immigration, natives suﬀer a decline in (gi  yiti)
because of lower gi and/or higher ti.
The exact ﬁscal impact on each native in each state will depend on individual characteristics, predominantly income. It will also depend on statecharacteristics: the nature of state ﬁscal policy in terms of progressivity andwelfare generosity, and the magnitude of the state’s total immigrant inﬂow.
We expect natives to experience larger falls in net ﬁscal transfers when living
in states with larger immigrant inﬂows and/or generous welfare programs.
For states that use more progressive tax and spending systems, we also expect the declines in net ﬁscal transfers to fall disproportionately on moreskilled natives.
Now consider the ﬁscal impacts of freer trade. Like freer immigration,
freer trade can alter (gi  yiti) via pre-tax changes in yi. Unlike freer immigration, however, freer trade does not bring about a change in the population and thus changes in welfare take-up that must be accommodated bychanges in the net ﬁscal transfers to natives. It is true that trade might increase churning in the labor market as workers and ﬁrms adjust to changes
in relative prices. But the magnitude of additional ﬁscal costs from thisadjustment in countries like the United States is likely to be modest, given
the limited extent of state and federal programs for labor-market adjustment.10 We conclude that freer trade generally does not generate the sameﬁscal pressures as immigration, and certainly does not do so in countries
with minimal trade taxes and minimal labor-market policies.11
2.4

Summary of Theoretical Framework

Freer immigration and trade can aﬀect individual economic welfare and thus
policy preferences through product prices, pre-tax labor income, and posttax net ﬁscal transfers. Research to date has largely ignored this thirdchannel. Our framework clariﬁes that for immigration, this channel is likely
important, but that for trade its relevance depends on whether trade andﬁscal policies are explicitly linked, which is not the case in the United States.
Our framework generates a number of testable predictions. The pre-tax
labor-income pressures from both immigration and trade are likely to cleave
10

An alternative argument may be that a generous tax and transfer system that provides moreinsurance to workers reduces opposition to liberalization. For cross-country evidence consistent
with this idea, see Hays et al. (2005) and Scheve and Slaughter (2006). This eﬀect may be
relevant in settings in which borrowing is allowed or for which the incidence of taxes paying
for the insurance is not clear – settings unlike the U.S. states. Or this eﬀect may especially apply
to less-skilled individuals at greater risk from liberalization but less likely to pay the costs.
Our empirical work investigates the possibility of this alternative.
11
Today, in many countries, trade taxes constitute a small share of total government revenue.
This is not true for many non-OECD countries, and was not true for almost all of today’s
advanced countries in earlier centuries. See United States Trade Representative (2003).
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

8

HANSON ET AL.

across skill groups within all jurisdictions. But for immigration there should
also be after-tax ﬁscal pressures that vary with state ﬁscal regime and skill
type. Natives in states who are ﬁscally exposed to immigration, thanks to a
combination of high immigrant inﬂows and/or generous welfare programs,
should be less supportive of immigration than natives in less-exposed states.
To the extent that states rely on progressive tax-and-spending regimes, thisreduced support for freer immigration should be especially strong among
higher income and more-skilled natives.
3. DATA AND SUMMARY STATISTICS

The data for our analysis come from three sources. Individual attitudes on
immigration and trade come from the 1992 and 2000 American National
Election Studies (NES; Sapiro et al., 1998), which are extensive surveys ofcurrent political opinions based on an individual-level, stratiﬁed random
sample of the U.S. population. We select these two NES years to best matchour data from the 1990 and 2000 U.S. Censuses of Population and Housing,from which we obtain data on immigrant and native populations, labor
forces, and use of public assistance, and also to allow for signiﬁcant temporal variation in these characteristics.12 Finally, data on state ﬁscal policies
come from the U.S. Censuses of Governments.
3.1

Fiscal Impact of Immigrant Populations in U.S. States

We begin our data discussion by showing that the ﬁscal impact of immigration varies signiﬁcantly across U.S. states. States vary both in their
exposure to immigration and in their generosity of public assistance. Insummarizing immigration patterns across U.S. states, we take households(rather than individuals) as the unit of analysis. Households are the units on
which government agencies assess income taxes, property taxes, and otherlevies. For determining individual eligibility for means-tested beneﬁt programs, it is typically household characteristics that are evaluated (Zimmermann and Tumlin, 1999). An immigrant household is deﬁned as one whose
head is foreign born. Importantly, this deﬁnition of the immigrant population includes U.S.-born children of immigrants.
It is now well documented that within the United States the immigrant
population is geographically concentrated. For the nation as a whole, theshare of the population living in immigrant-headed households was 16.5%
in 2000, up from 11.5% in 1990. For 2000, the immigrant population share
was between 30% and 40% in two states (California, New York), and it wasabove the national share in just 11 other states.13
12
Although the NES conducted a study in 1990, the survey instrument does not include an
immigration policy question.
13
These 11 states are New Jersey, Hawaii, Florida, Nevada, Texas, Connecticut, Massachusetts, Arizona, Rhode Island, Illinois, and District of Columbia.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

9

GLOBALIZATION STRATEGIES
0.4

Immigrant Share 2000

0.3

0.2

0.1

0
0

0.1

0.2

0.3

0.4

Immigrant Share 1990

Figure 1.

Share of state population in immigrant-headed households.

As Figure 1 shows, California and New York have long been immigrant
havens. However, the immigrant population has been growing most rapidly
in states that traditionally have not been immigrant gateway locations. In
Figure 2, states with the most rapid immigrant population growth over the
1990s (North Carolina, Georgia, Arkansas, Nebraska, Colorado, Utah) had
relatively small immigrant populations in 1990. Other states with rapidly
growing immigrant populations (Nevada, Colorado, Utah, Oregon,
Arizona) had moderate immigrant populations in 1990. These two groupsof states had rapid job growth during the 1990s. And, with the exceptionof Oregon, these states are not known for the generosity of their welfare
programs.
The ﬁscal impact of immigrants is, however, only partially related to thesize of immigrant ﬂows. Depending on both immigrants’ characteristics andstate policies, immigrants may or may not access public assistance or consume other public services and may or may not pay taxes. The extent of ﬁscal
transfers from natives to immigrants depends on these factors as well.
Individuals use public services in many forms, including public safety (ﬁreand police protection), public spaces (parks and recreation facilities), public
education, public healthcare, and public assistance (welfare). For immigrants, it is access to public assistance that is perhaps the most controversial. The Census of Population and Housing collects information on
cash assistance in the form of supplemental security income, aid for families
with dependent children (which has become temporary assistance for needyr 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

10

HANSON ET AL.
1

Relative Immigrant Pop. Growth

0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0

0.1
0.2
Immigrant Population Share 1990

0.3

Figure 2. Immigrant population growth minus native population growth, 1990–2000.

families), and general assistance. This is only a partial list of means-tested
entitlement programs, and it excludes non-cash beneﬁts such as food stamps,
Medicaid, public housing, and energy subsidies. In contrast, the Census
of Governments data discussed below measure both cash and non-cash
beneﬁts.
Figures 3a and 3b plot the fraction of immigrant and native households
that received cash public assistance in 1990 and 2000. The likelihood that
immigrants receive welfare varies widely across states. The states in which
immigrants were most likely to receive beneﬁts are mostly high-income stateson the east and west coasts (California, New York, Massachusetts, Pennsylvania, Connecticut). In 1996, there was a major reform of federal U.S.
welfare law, which imposed a lifetime cap on the number of years an individual could receive certain cash beneﬁts and that excluded non-citizens
from eligibility for many types of beneﬁts. After 1996, many states at least
partially replaced beneﬁts at the state level that immigrants lost at thefederal level, adding to the cross-state variation of public beneﬁts available
to immigrants.14
As discussed in section 2, an important requirement of our analysis below
will be to measure accurately variation in natives’ potential ﬁscal exposure to
immigrants across both states and years. Our measure would ideally accountfor the relative size of the immigrant and native populations as well as the14

For evidence on this replacement, see Zimmermann and Tumlin (1999).

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

11

GLOBALIZATION STRATEGIES

Immigrant Households

0.16

0.12

0.08

0.04

0.04

0.08

(a)

0.12

0.16

0.12

0.16

Native Households

Immigrant Households

0.16

0.12

0.08

0.04

0.04

(b)

0.08
Native Households

Figure 3.

(a) Share of households receiving public assistance, 1990. (b) Share ofhouseholds receiving public assistance, 2000.

incidence and value of immigrant uptake of beneﬁts. Figure 3 shows immigrant uptake incidence, but only for cash beneﬁts and without any value
information. The Census of Governments measures the annual value of bothr 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

12

HANSON ET AL.

cash and non-cash beneﬁts by state, but not broken out between immigrants
and natives. However, Figure 3 shows a positive correlation between thefraction of native and immigrant households receiving public assistance(a statistically signiﬁcant 0.24 in 2000, when weighted by state population),
which suggests that welfare spending in total should be a reasonable proxyfor welfare spending on immigrants only.
Accordingly, our ﬁrst measure of potential ﬁscal exposure to immigrants,
Fiscal Exposure 1, is a dichotomous indicator variable equal to one for stateyears that meet two conditions: (1) that have relatively high welfare generosity, measured as above the national median welfare spending per native;and (2) that have relatively high immigrant populations deﬁned as thosestates with a ratio of immigrants to natives above the mean state immigrantnative population ratio for working-age adults in 1990.15 Our welfarespending measure from the Census of Governments includes a broad rangeof beneﬁts, including cash and medical assistance.
An alternative measure of native ﬁscal exposure might use the immigrant
uptake intensity in Figure 3 but scale it against all native households tomeasure the overall native tax base. The result is Figures 4a and 4b, whichplot the number of immigrant households receiving cash beneﬁts relative tothe total number of native households against the ratio of immigrant tonative households for 1990 and 2000, respectively.
Many states have both small immigrant populations and small numbers ofimmigrant households on welfare. Among high-immigration states, there isconsiderable variation in immigrant uptake of welfare. California and New
York stand out as states with high immigrant welfare use. Among states withimmigrant households equal to 10–20% of the number of native households
in 1990, the ratio of welfare-receiving immigrant households to native
households ranges from 0.005 in Nevada to over 0.02 in Massachusetts.
Although the relative size of the immigrant population is comparable inthese two states, in eﬀect each native household in Massachusetts must
support four times as many immigrant households on welfare as does eachnative household in Nevada.
This cross-state variation in the expected ﬁscal cost to natives of immigrant welfare use creates the potential for regional variation in public
opinion about immigration policy – even among states with similar-sized
immigrant populations. Accordingly, we construct our second measure,Fiscal Exposure 2, as a dichotomous indicator variable equal to one for15
Our results are robust to raising or lowering this cutoﬀ (equal to 0.12). In Figure 1, this
cutoﬀ identiﬁes states that are spread out from the mass of states with low immigrant populations in both years. What matters for the empirical results is separating high-immigration from
low-immigration states, which is achieved by a range of cutoﬀ values. By categorizing states as
being either high immigration or low immigration, we are implicitly assuming that the skill mix
of immigrants across states is similar. In reality, there are important diﬀerences across states,
which we have addressed in other work. See Hanson et al. (2005a).

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

13

GLOBALIZATION STRATEGIES
1990

Imm HHs on Welfare / Native HHs

0.05

0.04

0.03

0.02

0.01

0
0

0.1

0.2
Immigrant HHs / Native HHs

0.1

0.2
Immigrant HHs / Native HHs

(a)

0.3

0.4

2000

Imm HHs on Welfare / Native HHs

0.05

0.04

0.03

0.02

0.01

0
0

(b)

0.3

Figure 4. Immigrant households receiving public assistance relative tonative households.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

0.4

14

HANSON ET AL.

state-years in which the ratio of immigrant households receiving cash forms
of welfare relative to the total number of native households exceeds 0.012.16
This ratio that deﬁnes Fiscal Exposure 2 gauges the potential ﬁscal eﬀects
of immigrants on natives insofar as it incorporates both the incidence ofimmigrant cash welfare use and also the relative sizes of the immigrant andnative populations. Relative to Fiscal Exposure 1, Fiscal Exposure 2 has the
disadvantages of excluding non-cash beneﬁts and also containing no measure of the value of welfare use. We thus prefer our ﬁrst measure, but forrobustness use both.
An advantage of using dichotomous measures of ﬁscal exposure to immigration is that it allows for non-linearities in how immigration’s ﬁscal
costs aﬀect individual preferences about immigration policy. In principle, we
can allow for a high degree of non-linearity simply by including a suﬃcientnumber of categorical variables to describe the level of ﬁscal exposure. In
practice, we ﬁnd that the dichotomous measures we use appear to be suﬃcient to summarize the relationship between ﬁscal exposure and policy
opinions.
3.2 Public Opinion About Globalization and State Generosity Toward
Immigrants
The NES is an extensive survey of individual political opinions, including
opinions about trade and immigration, based on a stratiﬁed random sampleof the U.S. population. These surveys also report respondent characteristics
including age, gender, educational attainment, and location of residence. To
evaluate individual preferences toward immigration and trade, we use twoquestions from the NES. Regarding immigration, the NES asks
Do you think the number of immigrants from foreign countries who are permitted to come to the United States to live should be increased a little, increased a lot, decreased a little, decreased a lot, or left the same as it is now?

For the main analyses of immigration in the paper, we set the variable Immigration Opinion equal to 1 for those individuals favoring immigration to
be decreased slightly or considerably and 0 for those individuals favoring
immigration to be maintained or increased.17 This question requires respondents to reveal their general position on the proper direction for U.S.
immigration policy.18 In 2000, 44.8% of respondents favored decreasing
16
The threshold of 0.012 was selected based on Figure 4a. Along the y-axis of this graph, there
is a substantial gap between Texas and the states above it separated by 0.012.
17
Using the fully disaggregated coding of the responses to this question and changing our
econometric speciﬁcations accordingly generates qualitatively similar results. We dichotomize
this variable for ease of exposition and comparison with trade opinions.
18
The question does not ask what skill-mix immigrants would have relative to the survey
respondent or the native population as a whole. We assume that responses are informed by ther 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

15

immigration (15.0% slightly, 29.8% considerably), 44.5% favored leaving
immigration unchanged, and 9.8% favored increasing immigration (5.8% by
a little, 4.0% by a lot).
Regarding trade, the NES asks,
Some people have suggested placing new limits on foreign imports in order toprotect American jobs. Others say that such limits would raise consumer prices
and hurt American exports. Do you favor or oppose placing new limits onimports, or haven’t you thought much about this?19

We set the variable Trade Opinion equal to 1 for those individuals favoring
protection and 0 for those opposing it. This question requires respondents toreveal their general position on U.S. trade policy. Note that the question
does not ask what sector(s) would receive import restrictions. We assume
that responses to the question are informed by the idea that import limits
will be placed on comparative-disadvantage sectors. This seems more sensible than alternatives such as limits on comparative-advantage sectors. In
2000, 48.5% of respondents favored new restrictions on imports.
Our theoretical discussion in section 2 focused on two motivations for
opposition to immigration and trade. One is the concern that immigrationand trade put downward pressure on pre-tax wages for less-skilled workers.
Our focus is on the second concern: that immigrant use of public services
alters the net ﬁscal burden on native taxpayers. In states with high ﬁscal
exposure to immigration, we expect natives to be less supportive of freer
immigration than are natives elsewhere. To the extent that states rely on
progressive tax-and-spending regimes, this reduced support should be
especially strong among more skilled natives, for whom the negative ﬁscal
eﬀects of immigration on after-tax income work against the positive wageeﬀects of immigration on pre-tax labor income. Recall that because U.S.
trade policy does not have the same ﬁscal consequences as immigration, we
do not expect support for trade policy to vary across states either by expected welfare costs of immigrants or even by alternative measures of ﬁscal
exposure tailored to trade as opposed to immigration.
Our econometric estimation will examine both these motivations, as well asa host of other important non-economic factors that may aﬀect an individual’s

skills of actual U.S. immigrants in recent decades, which are relatively low and thus increase therelatively supply of less-skilled workers. The distribution of U.S. immigrants does include a
substantial number of relatively skilled individuals. Nonetheless, the average U.S. immigrant isless skilled; we assume that this central tendency informs respondents’ answers to the question.
19
In 2000, the NES asked some respondents this question and some respondents a similar but
not identical question that did not include the response option ‘‘Haven’t you thought muchabout this.’’ In the main trade results reported in Table 7, we include all respondents from the2000 survey who answered either form of the question. The results are qualitatively the same if
those respondents asked the experimental question are excluded from the analysis.
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

16

HANSON ET AL.
Table 1 Support for Decreased Immigration by Education and
Fiscal Exposure to Immigrants

Fiscal exposure
measureFiscalexposure

No highschoolHighschoolSomecollegeCollege
graduate

Fiscal Exposure 1

Low
High
Low
High

0.537
0.625
0.498
0.658

0.571
0.558
0.572
0.557

0.507
0.461
0.516
0.464

0.362
0.420
0.361
0.435

Fiscal Exposure 2

Notes: Table 1 reports the fraction of native-born individuals reporting that they would preferimmigration to be decreased (by a little or by a lot) in the NES surveys for 1992 and 2000. Stateswith high immigrant welfare costs have values of Fiscal Exposure 1 (or Fiscal Exposure 2) equal
to 1. No high school refers to those with o12 years of education, high school refers to those with
12 years of education, some college to those with 13–15 years of education, and college graduates to those with 16 or more years of education. Summary statistics are calculated using the
NES sampling weights.

stance on immigration, e.g. political beliefs and ethnicity. But before turning
to these estimates, it is instructive to see whether simple summary statistics
reveal patterns consistent with these two considerations.
The fraction of native-born individuals favoring new restrictions on immigration and trade in the 1992 and 2000 NES surveys varies strongly witheducational attainment. Pooling both years, 54.1% of those without a highschool diploma favor new immigration restrictions, vs. just 38.6% of college
graduates. Support for trade restrictions varies even more dramatically byskill type: 72.2% of individuals without a high-school diploma support
further restrictions, compared with just 39.4% of college graduates. The
most educated are the least opposed to immigration and trade, broadly
consistent with the expectation that less-skilled natives have more restrictionist policy opinions due to labor-market competition.
Table 1 breaks down the overall skills cleavage in immigration opinions(for four standard levels of education: less than high school, high school,some college, and college graduates) according to whether an individual lives
in a state for which the welfare costs of immigrants are expected to be high or
low as measured by Fiscal Exposures 1 and 2. The key ﬁscal quantity ofinterest is the diﬀerence in opinions of similarly skilled respondents acrossstates.
Table 1 shows that in states with high expected ﬁscal costs, 42–44% ofcollege graduates have restrictionist immigration opinions, compared with
only 36% in states with low expected costs. This diﬀerential is even larger for
high-school dropouts, somewhere between nine and 16 percentage points.
Both sets of diﬀerentials are statistically signiﬁcant. These cross-state cleavages are broadly consistent with the idea from our theoretical frameworkthat ﬁscal concerns reduce support for immigration among U.S. natives. No
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

17

statistically signiﬁcant diﬀerential exists for intermediate schooling groups(high-school graduates, some college). Based on theory, we would expect
the policy preferences of individuals in these groups to be less aﬀected byﬁscal concerns. The patterns we uncover for immigration policy, however,
do not generally hold for trade policy opinions whether ﬁscal exposure ismeasured in terms of the welfare costs of immigrants or more generally.
Again, because U.S. trade policy does not have the same ﬁscal consequences
as immigration, this is consistent with our framework.
4.

EMPIRICAL SPECIFICATIONS

Our theoretical discussion highlighted three distinct channels through which
immigration and trade are likely to aﬀect an individual’s economic wellbeing: prices, pre-tax income, and post-tax net ﬁscal transfers. We build on
this framework to specify reduced-form estimating equations for individual
preferences regarding immigration and trade policy.
  ðT  Þ be a latent variable indicating opposition to immigration
Let Iist
ist(trade) by a native individual i living in state s at time t. We model the de  ðT  Þ as follows:
terminants of Iistist
 ¼ a þ b 1ðEduc Þ þ g 1ðEduc Þ1ðImm Þ
Iist
0
istj
istk
st
j
k
þ lk 1ðEducistk Þ1ðFEst Þ þ yXist þ dZst þ mist ;ð2Þwhere j is an index from 1 to 3; k is an index from 1 to 4; 1(Educistj) and1(Educistk) are a series of dichotomous variables indicating individual
educational attainment; 1(Immst) is the dichotomous variable Immigration
indicating whether the state in which the respondent lives is a highimmigration state; 1(FEst) is a dichotomous variable, Fiscal Exposure 1 or 2,
indicating whether the state in which the respondent lives faces a high levelof ﬁscal exposure to immigration; X is a vector of individual-level control
variables, Z is a vector of state-level control variables; a, b, g, l, y, and d areparameters to be estimated; and mist is a mean-zero random error termthat reﬂects unobserved factors associated with individual preferences
over changes in immigration or trade policy, including the impact of immigration or trade on the unobserved determinants of wage income andﬁscal transfers.
The ﬁrst term in this expression, a0, is simply a constant. The second andthird terms evaluate the pre-tax income channel for how immigration andtrade aﬀect economic wellbeing. The second term is indexed by j because for
1(Educistj), we include three indicator variables, High School, Some College,
and College, with No High School as the omitted category. The third term
is indexed by k because we interact all four educational categories withthe variable Immigration, indicating whether the respondent lives in a highimmigration state.
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

18

HANSON ET AL.

This parameterization provides a pre-tax labor-market interpretation of
b1. . .3 and g1. . .4.20 In the presence of low-skilled immigration, we expect
opposition to immigration to be decreasing in respondent skill levels becauseof its eﬀect on earnings across skills. Thus, the coeﬃcient for College, b3,
should be less than zero, and perhaps the same will hold for Some College,b2. If immigrants alter wages locally rather than nationally, then correlations
between skills and opinion should be stronger in states with higher immigration levels. This implies that the coeﬃcient on the interaction between
No High School and Immigration, g1, should be greater than zero and/or thatthe coeﬃcient on the interaction between College and Immigration, g4,
should be less than zero (with analogous predictions for the other two
education–immigration interactions). With the exception of the last point oflocal wage impacts, these same predictions apply to trade, insofar as freer
trade expands the national eﬀective supply of low-skilled labor.21
The fourth term in equation (2), lk1(Educistk)1(FEst), evaluates the mainargument of this paper: that the consequences of immigration for post-tax
net ﬁscal transfers have an important eﬀect on individual economic wellbeing and thus policy opinions. We interact all four educational variables
with our measures indicating whether the respondent’s state faces high ﬁscal
exposure to immigration. Our theoretical discussion highlighted the impactsof immigration on net ﬁscal transfers across diﬀerent income groups. But forour benchmark speciﬁcations, we use education to diﬀerentiate ﬁscal exposure across individuals. This is because income is well known to be poorly
measured, non-randomly missing in surveys, and sensitive to transitory
shocks (e.g. illness or bonuses) that do not reﬂect permanent income andthus ﬁscal status.
The parameters l1. . .4 indicate whether respondents with No High School,
High School, Some College, and College in high ﬁscal-exposure states are
more or less likely to oppose immigration. Our theoretical discussion suggests that respondents across all income/educational categories should be
more opposed to immigration in states with high ﬁscal exposure to immigrants, and that this should be especially true for high-income/educatedindividuals due to the progressivity of state tax and transfer systems. We
therefore expect the parameters l1. . .4 to be positive and increasing inmagnitude. In principle, a similar eﬀect might be observed for trade. But inpractice, we do not expect opposition to trade to vary signiﬁcantly with state

20
Note that because Immigration is interacted with all four education categories, it is notnecessary to include Immigration by itself. This point also applies to Fiscal Exposures 1 and 2.
21
Consistent with much of the labor-economics literature on wage impacts from immigration,
this speciﬁcation assumes local labor markets are delineated by states. Our key results demonstrating the importance of public-ﬁnance considerations for public opinion about immigration
policy are robust to dropping the interactions between education and Immigration, which would
be consistent with immigration having national and not state-level wage impacts.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

19

ﬁscal exposure because of the small magnitudes of any likely ﬁscal eﬀects oftrade in the context of U.S. states.
Finally, the ﬁfth and sixth terms in equation (2), yXist and dZst, estimate
the eﬀect of various individual-level and state-level control variables including Age, Age Squared, dichotomous indicator variables Female andHispanic, State Unemployment, a year indicator variable for 2000, and in
most speciﬁcations a full set of state ﬁxed eﬀects to account for time-invariant
features of states that may inﬂuence individual attitudes toward immigrationand trade. Some of these control variables account for the price channel,
which depends on consumption patterns not measured in our data.22 Importantly, the controls may capture some non-economic inﬂuences on policy
opinions. We will report results with many additional control variables thatmeasure tolerance, isolationist sentiment, ideology, and partisanship, all ofwhich more directly attempt to account for non-economic determinants ofpolicy opinions.
 ðT  Þ is unobserved. Let I ,In equation (2), the latent variable Iist
ist
ist
Immigration Opinion, (Iist, Trade Opinion) be an indicator variable equal to
one if an individual favors decreasing immigration (restricting trade) and > 0Þ ¼ PrðI ¼ 1Þ or PrðT  > 0Þ ¼
zero otherwise, in which case PrðIist
ist
istPrðTist ¼ 1Þ. Assuming that the idiosyncratic component of individual preferences, mist, is normally distributed, then for immigration (analogously for
trade), the following applies:PrðIist ¼ 1Þ ¼ Fða0 þ bj 1ðEducistj Þ þ gk 1ðEducistk Þ1ðImmst Þþ lk 1ðEducistk Þ1ðFEst Þ þ yXist þ dZst Þ;

ð3Þ

where F(  ) is the standard normal cdf. We will estimate equation (3) as a
probit, ﬁrst on immigration and then on trade preferences, and report robust
standard errors clustered on states. All estimations use NES data for nativeborn individuals pooled across 1992 and 2000. We focus on the subsample ofnatives to highlight the public-ﬁnance aspect of preference formation.
5. ESTIMATION RESULTS

5.1

Immigration-Policy Preferences

Table 2 reports our benchmark coeﬃcient estimates of equation (3) for
immigration preferences. Each speciﬁcation includes the set of benchmark
controls discussed in section 4, and we estimate speciﬁcations both without
and with state ﬁxed eﬀects. We prefer including state eﬀects because there
are likely to be unobserved, unmeasured but time-constant features of states
22
The interactions between educational attainment and whether the respondent lives in a highimmigration state may also control for the price channel because consumption patterns mayvary by income and education and with the size of the local immigrant population.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

20

HANSON ET AL.
Table 2

Immigration-Policy Preferences, Benchmark Specifications
Fiscal Exposure 1
Model I1

Model I2

Fiscal Exposure 2
Model I3

Model I4

0.182 (0.101) 0.168 (0.107) 0.211 (0.095) 0.206 (0.103)
0.071
0.118
0.027
0.046
Some College
0.047 (0.097) 0.027 (0.098) 0.102 (0.100) 0.092 (0.104)
0.626
0.783
0.309
0.379
College0.347 (0.119) 0.356 (0.130) 0.298 (0.116) 0.295 (0.127)
0.004
0.006
0.011
0.020
No High School  Immigration 0.445 (0.141) 0.474 (0.173) 0.365 (0.257) 0.667 (0.270)
0.002
0.006
0.155
0.014
High School  Immigration
0.016 (0.117) 0.034 (0.136) 0.012 (0.122) 0.248 (0.140)
0.889
0.802
0.920
0.077
Some College  Immigration
0.098 (0.094) 0.033 (0.097) 0.143 (0.088) 0.116 (0.151)
0.297
0.734
0.105
0.439
College  Immigration
0.078 (0.111) 0.016 (0.128) 0.183 (0.115) 0.043 (0.165)
0.480
0.900
0.112
0.796
No High School  Fiscal
0.090 (0.200) 0.246 (0.169) 0.102 (0.264) 0.189 (0.259)
Exposure (1 or 2)
0.652
0.147
0.698
0.465
High School  Fiscal
0.008 (0.141) 0.303 (0.130) 0.011 (0.137) 0.144 (0.136)
Exposure (1 or 2)
0.954
0.020
0.936
0.288
Some College  Fiscal
0.036 (0.089) 0.237 (0.109) 0.003 (0.082) 0.138 (0.110)
Exposure (1 or 2)
0.686
0.030
0.974
0.211
College  Fiscal
0.219 (0.118) 0.490 (0.145) 0.347 (0.127) 0.526 (0.117)
Exposure (1 or 2)
0.063
0.001
0.006
0.000
High School

State ﬁxed eﬀects
Baseline control variables
Observations
Log-likelihood

No
Yes
2,978
2,021.13

Yes
Yes
2,978
1,995.44

No
Yes
3,117
2,115.0

Yes
Yes
3,117
2,088.7

Notes: This table reports coeﬃcient estimates for probit regressions on native individuals fromthe 1992 and 2000 NES surveys. The dependent variable is Immigration Opinion, equal to 1 forrespondents who support further restricting immigration and 0 otherwise. The baseline control
variables are Age, Age Squared, Female, Hispanic, State Unemployment, a year indicator variable for 2000, and a constant. Each cell reports a coeﬃcient estimate, a state-clustered robust
standard error in parentheses, and a p-value. Observations are weighted using sampling weightsfrom the NES data.

that both may inﬂuence support for immigrants and may also be correlatedwith our ﬁscal-exposure measures.
We ﬁrst note that the results across all four speciﬁcations in Table 2 replicate the ﬁnding in the literature that more-skilled natives are less likely tosupport immigration restrictions. The coeﬃcients on education alone indicate the relationship between education and immigration opinions forrespondents in states for which immigration is low in both magnitude andexpected ﬁscal eﬀects. Here, opposition to immigration is the weakest amongcollege graduates. The coeﬃcient on College in Model I2 implies that college
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

21

graduates were approximately 14 percentage points less likely to prefer fewer
immigrants than high-school dropouts.23
The results for respondents in high-immigration but low-ﬁscal-impact
states show more evidence of this skills cleavage. For both ﬁxed-eﬀects
speciﬁcations, the coeﬃcient on the interaction between No High School and
Immigration is positive, large in magnitude, and statistically signiﬁcant (noneof the other skill interactions with Immigration is signiﬁcant). Low-skilled
respondents have substantially stronger support for further immigration
restrictions in those states for which immigration is high but ﬁscal exposure
is low. More precisely, as this result is the clearest in speciﬁcations with stateeﬀects, it is in those states with increasing levels of immigrants that lowskilled natives most support restrictions. This is consistent with stronger
labor-market consequences of immigration in those states, so that diﬀerences in policy opinions across skill groups are likely to be larger.24 The
results for Model I2 imply that the diﬀerence in probability of supportingtighter immigration policies between College and No High School natives
doubles in states with high immigration, to a diﬀerence of over 30 percentage
points.
Our main substantive question of interest, however, is whether potentiallyhigh ﬁscal costs from immigration shape policy preferences. Our theoreticalframework suggested that this eﬀect may hold across all natives, but is likely
to be the strongest for those with the highest skills and income. Across all
four speciﬁcations in Table 2, the coeﬃcients on interactions between College and Fiscal Exposure 1 (or 2) are positive and statistically signiﬁcant.
College-educated natives have more-restrictionist policy views in states forwhich the net ﬁscal burden of immigration is likely to be high. Table 2 also
oﬀers evidence of a ﬁscal eﬀect for the other skill categories. Our preferred
speciﬁcation in Table 2 is Model I2, which uses Fiscal Exposure 1 (rather
than 2) and includes (rather than excludes) state eﬀects. In Model I2,
the interaction of Fiscal Exposure 1 with each of the four skill measures ispositive and statistically signiﬁcant (although only marginally so for the
No High School interaction).
These results for the ﬁscal-exposure regressors are consistent with thecentral argument of this paper: the post-tax ﬁscal burdens associated withmore immigrants tend to increase support for immigration restrictions, and23
The size of this eﬀect is very similar across all four speciﬁcations. We note that for respondents in these states, we do not observe the hypothesized diﬀerences between the No HighSchool, High School, and Some College groups. There is some evidence (Models I3 and I4) that
individuals with (i.e. not without) a high-school degree have the most restrictionist opinions.
24
Scheve and Slaughter (2001b) found little support for the prediction that policy opinion
diﬀerences between more- and less-skilled workers are the strongest in gateway communities.
The analysis in this paper takes advantage of a longer time period between surveys in order toestimate speciﬁcations with state ﬁxed eﬀects that account for unobserved state characteristics
and identify changes in immigration population.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

22

HANSON ET AL.

Table 3 Estimated Effect of Increasing Fiscal Exposure to Immigration on the
Probability of Supporting Immigration Restrictions
Fiscal exposure
measureFiscal Exposure 1

Fiscal Exposure 2

Education level

Change in probability of supporting
immigration restrictions

No High School
High SchoolSome College
College
No High School
High SchoolSome College
College

0.097 (0.066)
0.119 (0.050)
0.094 (0.043)
0.189 (0.053)
0.075 (0.102)
0.057 (0.054)
0.055 (0.044)
0.202 (0.042)

Notes: Based on the estimates from Models I2 and I4, this table reports the consequences for the
probability of supporting immigration restrictions of changing from a state in which ﬁscal exposure to immigration is low (Fiscal Exposure 1 or 2 equals 0) to a state in which it is high (Fiscal
Exposure 1 or 2 equals 1) for individuals at diﬀerent skill levels. The standard error of thisestimate is reported in parentheses.

do so even among those more skilled individuals likely to beneﬁt in the labormarket from immigration. These results are the paper’s main ﬁnding.
The substantive magnitude of the ﬁscal-exposure eﬀect is large. For the
preferred ﬁxed-eﬀects speciﬁcations, Tables 2 and 3 report the estimatedeﬀect across diﬀerent skill groups of increasing ﬁscal exposure to immigration on the probability of supporting immigration restrictions. For Fiscal
Exposure 1, moving a college graduate from a state with low to high ﬁscal
exposure to immigration raises the probability of favoring fewer immigrants
by 18.9 percentage points (standard error of 5.3 percentage points). The sizeof the comparable eﬀect for natives in the other three educational categories
is about 10 percentage points, signiﬁcantly diﬀerent from zero for highschool and some college. The magnitude of this post-tax ﬁscal cleavage iscomparable with the magnitude of the pre-tax labor-market cleavage acrossskills mentioned above. For Fiscal Exposure 2, the results are almost identical in magnitude for college graduates (20.2 percentage points, standard
error of 4.2) but are smaller and less precisely estimated for the other skill
categories. We conclude from our benchmark results in Tables 2 and 3 thatliving in states with high ﬁscal costs from immigration signiﬁcantly increases
the likelihood of restrictionist opinions, and that the magnitude of this ﬁscal
cleavage is large and in fact comparable in size to the labor-market cleavage
across skills.
To evaluate the robustness of our benchmark results and also probe ourinterpretation of them, we estimated many alternative speciﬁcations. Someof these are reported in Tables 4–6. The two speciﬁcations in Table 4 add
to our benchmark ﬁxed-eﬀects models a broader set of demographic andr 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

23

GLOBALIZATION STRATEGIES
Table 4

Immigration-Policy Preferences, Additional ControlVariables

High SchoolSome College
College
No High School  Immigration
High School  Immigration
Some College  Immigration
College  Immigration
No High School  Fiscal Exposure (1 or 2)
High School  Fiscal Exposure (1 or 2)
Some College  Fiscal Exposure (1 or 2)
College  Fiscal Exposure (1 or 2)
Unemployed
Union Member
Government Employee
Partisanship
Ideology
Tolerance
Isolationism
State ﬁxed eﬀects
Baseline control variables
Observations
Log-likelihood

Fiscal Exposure 1

Fiscal Exposure 2

Model I5

Model I6

0.142 (0.159)
0.022 (0.150)
0.304 (0.169)
0.507 (0.234)
0.038 (0.171)
0.019 (0.106)
0.133 (0.112)
0.273 (0.264)
0.331 (0.144)
0.222 (0.134)
0.529 (0.144)
0.281 (0.145)
0.165 (0.108)
0.015 (0.065)
0.030 (0.017)
0.046 (0.024)
0.044 (0.022)
0.461 (0.066)

0.146 (0.152)
0.006 (0.142)
0.289 (0.160)
0.662 (0.374)
0.238 (0.172)
0.167 (0.157)
0.024 (0.155)
0.287 (0.355)
0.276 (0.136)
0.182 (0.094)
0.603 (0.131)
0.271 (0.143)
0.164 (0.107)
0.006 (0.062)
0.032 (0.017)
0.050 (0.024)
0.052 (0.023)
0.463 (0.065)

Yes
Yes
2,201
1,419.25

Yes
Yes
2,277
1,463.65

Notes: This table reports coeﬃcient estimates for probit regressions on native individuals fromthe 1992 and 2000 NES surveys. The dependent variable is Immigration Opinion, equal to 1 forrespondents who support further restricting immigration and 0 otherwise. The baseline control
variables are Age, Age Squared, Female, Hispanic, State Unemployment, a year indicator variable for 2000, and a constant. Each cell reports a coeﬃcient estimate and a state-clustered robust
standard error in parentheses. Observations are weighted using sampling weights from the NES
data.

political control variables.25 The estimates for these additional control
variables are mostly consistent with previous ﬁndings in the literature. For
example, respondents who scored higher on our measure of Tolerance were25
The variables Unemployed, Union Member, and Government Employee are dichotomousindicator variables. The variable Partisanship is a seven-point score ranging from 1 if a respondent self-identiﬁes as a ‘‘strong Democrat’’ to 7 if a respondent self-identiﬁes as a ‘‘strong
Republican.’’ The variable Ideology is a seven-point score ranging from 1 if a respondent
identiﬁes themselves as ‘‘extremely liberal’’ to 7 if a respondent identiﬁes themselves as ‘‘extremely conservative.’’ The variable Isolationism is a dichotomous variable coded 1 if the respondent indicates agreement with the statement ‘‘This country would be better oﬀ if we juststayed home and did not concern ourselves with problems in other parts of the world’’ and 0
otherwise. The variable Tolerance is a ﬁve-point scale indicating the extent of agreement with thestatement ‘‘We should be more tolerant of people who choose to live according to their own
moral standards, even if they are very diﬀerent from our own,’’ with a 1 indicating ‘‘strongly
disagree’’ and 5 indicating ‘‘strongly agree.’’r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

24

HANSON ET AL.
Table 5

Immigration-Policy Preferences, Income Specifications

Income Quartile 2
Income Quartile 3
Income Quartile 4
Income Quartile 1  Immigration
Income Quartile 2  Immigration
Income Quartile 3  Immigration
Income Quartile 4  Immigration
Income Quartile 1  Fiscal Exposure (1 or 2)
Income Quartile 2  Fiscal Exposure (1 or 2)
Income Quartile 3  Fiscal Exposure (1 or 2)
Income Quartile 4  Fiscal Exposure (1 or 2)
State ﬁxed eﬀects
Baseline control variables
Observations
Log-likelihood

Fiscal Exposure 1

Fiscal Exposure 2

Model I7

Model I8

0.137 (0.096)
0.156
0.184 (0.124)
0.137
0.140 (0.098)
0.152
0.037 (0.151)
0.806
0.055 (0.115)
0.633
0.171 (0.130)
0.188
0.097 (0.107)
0.366
0.220 (0.162)
0.175
0.284 (0.169)
0.092
0.262 (0.120)
0.029
0.421 (0.134)
0.002

0.163 (0.092)
0.078
0.173 (0.113)
0.128
0.106 (0.098)
0.276
0.083 (0.176)
0.639
0.278 (0.163)
0.088
0.305 (0.167)
0.068
0.076 (0.151)
0.616
0.235 (0.163)
0.150
0.003 (0.147)
0.986
0.152 (0.157)
0.334
0.413 (0.150)
0.006

Yes
Yes
2,734
1,846.18

Yes
Yes
2,867
1,936.72

Notes: This table reports coeﬃcient estimates for probit regressions on native individuals fromthe 1992 and 2000 NES surveys. The dependent variable is Immigration Opinion, equal to 1 forrespondents who support further restricting immigration and 0 otherwise. The baseline control
variables are Age, Age Squared, Female, Hispanic, State Unemployment, a year indicator variable for 2000, and a constant. Each cell reports a coeﬃcient estimate, a state-clustered robust
standard error in parentheses, and a p-value. Observations are weighted using sampling weightsfrom the NES data.

less likely to have restrictionist opinions about immigration policy. Individuals with isolationist views about the role of the United States in theworld, as measured by Isolationism, were much more likely to support further immigration restrictions. These ﬁndings highlight the common claimin the literature that policy attitudes about immigration are shaped in partby non-economic considerations (e.g. Citrin et al., 1997; Dustmann and
Preston, 2004a; Hainmueller and Hiscox, 2005; Scheve and Slaughter,
2001b).26 We would add that these non-economic considerations potentially26This interpretation needs, however, to be made cautiously. It is, of course, possible thatfactors such as levels of tolerance, ideology, and isolationist sentiments are a consequence ofr 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

25

GLOBALIZATION STRATEGIES

Table 6 Immigration-Policy Preferences, Benchmark Specifications in States withRelatively Progressive Tax Systems
Progressive Tax
System Measure 1

Progressive Tax
System Measure 2

Model I2

Model I2

0.285 (0.235)
0.224
0.382 (0.150)
0.011
0.315 (0.056)
0.000
0.803 (0.064)
0.000

0.229 (0.299)
0.444
0.290 (0.219)
0.185
0.477 (0.144)
0.001
0.905 (0.104)
0.000

Yes
Yes
Yes
Yes
1,293
857.36

Yes
Yes
Yes
Yes
1,752
1,161.03

Fiscal exposure measure
No High School  Fiscal Exposure 1
High School  Fiscal Exposure 1
Some College  Fiscal Exposure 1
College  Fiscal Exposure 1
Education variables
Education  Immigration variables
State ﬁxed eﬀects
Baseline control variables
Observations
Log-likelihood

Notes: This table reports coeﬃcient estimates for probit regressions on native individuals instates with relatively progressive tax systems from the 1992 and 2000 NES surveys. Progressive
Tax System Measure 1 is all states with above-median values of the ratio of the top income tax
rate to the bottom rate. Progressive Tax System Measure 2 is all states with above-median valuesof the ratio of income tax revenue to total revenue. The dependent variable is Immigration
Opinion, equal to 1 for respondents who support further restricting immigration and 0 otherwise. The baseline control variables are Age, Age Squared, Female, Hispanic, State Unemployment, a year indicator variable for 2000, and a constant. Each cell reports a coeﬃcient estimate,a state-clustered robust standard error in parentheses, and a p-value. Observations are weighted
using sampling weights from the NES data.

provide a complementary answer to our emphasis on ﬁscal considerations inaddressing why individuals might have diﬀerent opinions about alternative
globalization strategies. Certainly, one reason is that prejudice and otherpolitical attitudes may play a larger role in policies like immigration incomparison with policies like trade.
Rather than exploring the results for these control variables in greater
detail, we focus on the robustness of our key ﬁscal ﬁndings for these speciﬁcations. For both Models I5 and I6, the key ﬁscal-exposure estimatesremain statistically and substantively signiﬁcant. If anything, results comethrough more clearly with the additional controls: now the interaction terms

economic competition rather than exogenous determinants, although a completely economic
reductionist account seems implausible. Moreover, a number of the additional control variables
may be endogenous to immigration policy opinions. For these reasons, we retain our benchmark
speciﬁcations in most of the remaining results discussed in the paper.
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

26

HANSON ET AL.

of Fiscal Exposure 2 with High School and Some College are also signiﬁcantly diﬀerent from zero.27
In Table 5, we experiment with alternative measures of individual skills
and relative ﬁscal position. Consistent with much work in labor economics,
our benchmark speciﬁcations measure individual skills and relative ﬁscal
position with educational attainment. This latter choice assumes that longrun or ‘‘permanent’’ income is determined primarily by human capital. As acheck on this assumption, in Table 5, we replace educational attainment with
reported income ranked by quartiles, retaining other aspects of the benchmark speciﬁcation. Our key ﬁscal results are qualitatively the same as thosein Table 2. For both measures of ﬁscal exposure to immigration, the interaction terms with all income quartiles are positive. For both ﬁscal measuresthe estimate is the largest and statistically signiﬁcant for the highest income
quartile. And for Fiscal Exposure 1, the estimate is signiﬁcant for the third
quartile and marginally so for the second. These results are consistent withthe argument that respondents more exposed to the tax and transfer consequences of immigration have more restrictionist immigration opinions.28
Another set of immigration results are presented in Table 6, where we
explore our interpretation of the key ﬁscal-exposure results. Our theoreticalframework emphasized that the ﬁscal impact of immigration may aﬀect
natives of all skill and income groups. But as most state tax and transfer
systems are at least somewhat progressive, the impact of immigration on
net ﬁscal transfers is likely to hit the most skilled, highest-income natives
the hardest. Evidence consistent with this argument has been presented interms of the magnitude of the eﬀect of ﬁscal exposure across diﬀerent skill
categories.
This interpretation can be bolstered by re-estimating our benchmark
speciﬁcations on the subsample of natives living in states with the mostprogressive tax systems. We identify these states with two measures. The ﬁrst
indicates all states with above-median values of the ratio of the top incometax rate to the bottom rate. The second indicates all states with abovemedian values of the ratio of income tax revenue to total revenue. Based on
our theoretical framework, we expect that the pattern of estimates for theconsequences of increasing ﬁscal exposure on restrictionist immigration will
be most clear in those states that match our theoretical discussion of relatively progressive tax and transfer systems.
The results reported in Table 6 conﬁrm this expectation, where we use ourpreferred Fiscal Exposure 1. The most striking diﬀerence between these27
To further test the robustness of the correlation between ﬁscal exposure and policy opinions
to the inclusion of additional control variables, we estimated a number of alternative speciﬁcations that added further measures of attitudes toward minority groups. In all speciﬁcations,the results were qualitatively similar to those reported in Table 4.
28
These results using income quartiles are also robust to including the additional control
variables discussed in Table 4.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

27

results and those in Table 2 for the full sample is that the magnitude of
the impact of living in a state with high ﬁscal exposure to immigration is
now much larger for these subsamples of states with relatively progressive
tax systems. For example, for the model using our ﬁrst measure of progressive states, moving a high-school graduate from a state with low tohigh ﬁscal exposure to immigration raises the probability of favoring fewer
immigrants by 15 percentage points – vs. just six to 12 percentage points inthe full-sample estimates of Table 2. For this same model, for college
graduates, the impact of living in a state with high rather than low ﬁscal
exposure is over 30 percentage points – vs. about 20 percentage points in thefull sample.
We also note that our interpretation of the key ﬁscal-exposure results is
supported not just by the larger substantive magnitudes for the subsample ofprogressive states. It is also supported by the evidence in Table 6 that thediﬀerences across education categories are now larger than before. The estimates in the ﬁnal column of Table 6 are not just larger but even suggest a
linear progression in the magnitude of the eﬀect of ﬁscal exposure, moving
up the four education groups from an estimated increase of 0 percentage
points to 11, 19, and 33, respectively.
Beyond Tables 4–6, we veriﬁed the robustness of our central results to
many other checks (unreported for brevity). For example, we experimented
with alternative measures of state ﬁscal exposure to immigration, such as
expanding our reported measures to account for other researchers’ interpretation of state responses to the 1996 federal welfare reform.29 We
dropped individual states from our sample, in particular outlier immigration
states shown in our ﬁgures such as California and New York. We added
additional non-economic individual characteristics that might help shapeopinions, e.g. additional tolerance measures. We estimated our main speciﬁcations using multiple imputation to address potential bias from item nonresponse in the surveys.
For all these checks, our main result from Tables 2–6 again persisted:ﬁscal exposure to immigration reduces support for freer immigration, andthis eﬀect is the strongest among the high-skilled/high-income natives who
pay a proportionately higher share of the ﬁscal costs. The magnitude of thisﬁscal cleavage is comparable to that for skill itself, from which we conclude
that public-ﬁnance considerations are crucial in shaping opinions toward
immigration policies.

29
Zimmermann and Tumlin (1999) categorize states that did not reverse federal welfare restrictions on immigrants set in the 1996 reforms, and thus post-1996 had regimes that were lessgenerous to immigrants than to natives. We recreated Fiscal Exposure 1 by removing from thegroup of high welfare generosity in 2000 states that Zimmerman and Tumlin categorized as nonreversers. For results on these and many other robustness checks discussed in this subsection, seeHanson et al. (2005b).

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

28
5.2

HANSON ET AL.

Trade Policy Preferences

Table 7 reports our estimates of equation (3) for trade-policy preferences.
Recall that based on our theoretical framework, we expect trade opinions
to depend on pre-tax labor-market concerns but not on post-tax ﬁscal
concerns. This is both because, in theory, trade does not have the necessary
ﬁscal consequences that immigration does by virtue of population changes,
and in practice because U.S. taxation and spending linked to trade policy isnegligible.
The ﬁrst two speciﬁcations in Table 7 are identical to Models I2 and I4 in
Table 2 for immigration, except that now the new dependent variablemeasures trade-policy opinions. Because these speciﬁcations measure stateﬁscal exposure to immigration, we do not expect to ﬁnd any correlation here
between ﬁscal concerns and trade opinions. The ﬁnal two speciﬁcations use
diﬀerent ﬁscal measures that may be more relevant to possible ﬁscal impacts

Table 7 Trade-Policy Preferences
Fiscal exposure measure
1

2

3

4

Model T1

Model T2

Model T3

Model T4

No High School  Fiscal
Exposure (1–4)
High School  Fiscal
Exposure (1–4)
Some College  Fiscal
Exposure (1–4)
College  Fiscal
Exposure (1–4)

0.111 (0.121)
0.360
0.390 (0.133)
0.003
0.971 (0.132)
0.000
0.367 (0.264)
0.165
0.228 (0.132)
0.084
0.221 (0.148)
0.135
0.046 (0.161)
0.773

0.020 (0.123)
0.869
0.267 (0.146)
0.067
0.849 (0.128)
0.000
0.232 (0.360)
0.519
0.132 (0.196)
0.500
0.111 (0.188)
0.553
0.223 (0.193)
0.249

0.074 (0.151)
0.623
0.268 (0.138)
0.053
0.908 (0.163)
0.000
0.004 (0.306)
0.989
0.021 (0.238)
0.928
0.173 (0.236)
0.462
0.045 (0.259)
0.863

0.033 (0.161)
0.837
0.263 (0.143)
0.066
0.946 (0.143)
0.000
0.245 (0.275)
0.373
0.160 (0.189)
0.398
0.064 (0.179)
0.719
0.376 (0.164)
0.022

State ﬁxed eﬀects
Baseline control variables
Observations
Log-likelihood

Yes
Yes
2,297
1,379.76

Yes
Yes
2,401
1,447.92

Yes
Yes
2,297
1,380.17

Yes
Yes
2,297
1,377.77

High SchoolSome College
College

Notes: This table reports coeﬃcient estimates for probit regressions on native individuals fromthe 1992 and 2000 NES surveys. The dependent variable is Trade Opinion. The baseline control
variables are Age, Age Squared, Female, Hispanic, State Unemployment, a year indicator variable for 2000, and a constant. Each cell reports a coeﬃcient estimate, a state-clustered robust
standard error in parentheses, and a p-value. Observations are weighted using sampling weightsfrom the NES data.
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

29

of trade. Fiscal Exposure 3 is deﬁned using just the ﬁrst criterion of Fiscal
Exposure 1; that is, it identiﬁes states with relatively high welfare generosity
measured as above the national median welfare spending per native. Fiscal
Exposure 4 is the same as Fiscal Exposure 3 but scores states on welfare
spending divided by gross state product rather than number of natives.
If state welfare programs provide some insurance to the pre-tax incomepressures generated by freer trade, then individuals who feel they carry theburden of this welfare spending may be less inclined to support freer trade.
As with immigration, given the progressivity of state ﬁscal regimes, thisdisinclination may be the strongest among the more-skilled, higher-income
individuals.
The results across all four speciﬁcations in Table 7 replicate the ﬁndings in
the literature that more-skilled individuals are less likely to support further
trade restrictions. For an individual in a state with low ﬁscal impact, thecoeﬃcients for Model T1 imply that the diﬀerence between a college graduate and high-school dropout in the probability of favoring further trade
restrictions is 0.37 (with a standard error of 0.05). This diﬀerence is identical
for residents in high ﬁscal impact states, and is robust across all alternative
speciﬁcations. This skills cleavage is consistent with the potential impact oftrade on pre-tax labor income being important in opinion formation.
More important for this paper’s focus on ﬁscal concerns, Table 7 shows
no consistent variation in opinions over trade policy across states based on
their ﬁscal regimes. The coeﬃcients in Table 7 for interactions between the
education variables and the ﬁscal-exposure measures are generally small andimprecisely estimated. We expected this for Fiscal Exposure 1 and 2, but also
ﬁnd this for Fiscal Exposure 3 and 4. The only exception is a statisticallysigniﬁcant coeﬃcient estimate on the interaction between College and Fiscal
Exposure 4 but in unreported results this particular ﬁnding was not very
robust.
This lack of a clear correlation between trade opinions and ﬁscal considerations, along with the opposite evidence for immigration, is consistent
with our overall argument that public-ﬁnance considerations appear to be
crucial in shaping opinions toward alternative globalization strategies.
Where public-ﬁnance matters can bite directly – in our data, for immigration
but not trade – we see important impacts on individual opinions.
6. CONCLUSIONSThis paper has examined the inﬂuence of public ﬁnance on individual
preferences toward alternative globalization strategies. In the absence ofdistortionary tax and spending policies, freer immigration and trade fora country would often be supported by similar groups thanks to similar
impacts on labor demand and thus labor income. But government policies
that redistribute income may alter the distributional politics. Immigrants
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

30

HANSON ET AL.

may pay taxes and receive public services. Imports, obviously, do neither ofthese. This suggests that quite diﬀerent political coalitions may organize
around trade and immigration. In this paper, we developed a framework
for examining how pre-tax and post-tax cleavages may diﬀer across globalization strategies and also across ﬁscal jurisdictions and applied this framework to the case of individual immigration and trade preferences across
U.S. states.
Our results suggest that high exposure to immigrant ﬁscal pressures reduces support for freer immigration among natives, especially the moreskilled. The magnitude of this post-tax ﬁscal cleavage is comparable to thepre-tax labor-market eﬀects of skill itself. Further, we ﬁnd that there is no
public-ﬁnance variation in opinion over trade policy, consistent with thedata that U.S. trade policy has negligible ﬁscal-policy impacts. In considering the ﬁscal impacts of trade policy, we exploit variation in ﬁscal policy
at the state level, aggregating over communities within states that may havediverse industry mixes. There may be important ﬁscal impacts at the local
level – for instance, plant closures in a community may diminish local property tax revenues – that could aﬀect policy preferences, which our data do
not capture.
Our ﬁndings indicate that public-ﬁnance considerations are crucial in
shaping opinions toward alternative globalization strategies. It is not justdistributive politics in the labor market that feature prominently for these
opinions, as much recent work has investigated. It is also distributive politics
in the ﬁscal arena as well.
We think that this insight may shed light on a number of importantquestions in international political economy. For example, even within thesame policy domain, the ﬁscal issues at stake can vary greatly and accountfor diﬀerences in the politics observed in diﬀerent contexts. U.S. immigration policy was much more liberal a century ago than today. One source of
this diﬀerence may be that, unlike today, a century ago the United States
had virtually no social safety net. Fiscal considerations may also push in the
opposite direction. In current immigration debates in Europe, concern oversocial spending on immigrants is balanced against the need to recruit
workers whose tax payments could support state pension systems that face
dangerous shortfalls from signiﬁcantly aging populations.
But the most interesting application of our framework may be to help
explain why countries choose diﬀerent policy approaches toward diﬀerent
dimensions of international economic integration. It has long been recognized that many countries choose liberal trade but restrictionist immigration policies. Perhaps even more striking is how liberal policies regulating
foreign investment are compared with both trade and immigration. We thinkthat future research examining the ﬁscal consequences of policy alternatives
may help account for voter preferences and their role in explaining thesepolicy combinations.
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES31ACKNOWLEDGMENTS

For helpful comments, we thank Rafaela Dancygier, Jens Hainmueller, Shigeo Hirano, David Stasavage, Michael Tomz, and seminar participants at
Georgetown University, the Institute for International Economics, the London School of Economics, Stanford University, the University of Chicago, theUniversity of Illinois, the University of Michigan, the Université de Montréal,
the University of Notre Dame, and the University of Oregon. For ﬁnancial
support, we gratefully acknowledge the National Science Foundation.

GORDON H. HANSONKENNETH SCHEVE,

University of California
San Diego and NBER

Yale University

MATTHEW J. SLAUGHTER

Tuck School of Business at
Dartmouth and NBERREFERENCES

Baker, A., 2005, Who wants to globalize? Consumer tastes and labor markets ina theory of trade policy preferences. American Journal of Political Science 49,
924–938.
Beaulieu, E., 2002, Factor or industry cleavages in trade policy? An empirical test of
the Stolper–Samuelson theorem. Economics and Politics 14, 99–131.
Borjas, G. J., 1999a, Heaven’s Door: Immigration Policy and the American Economy(Princeton University Press, Princeton, NJ).
———, 1999b, The economic analysis of immigration, in: O. C. Ashenfelter and
D. Card, eds., Handbook of Labor Economics (North-Holland, Amsterdam)
1697–1760.
———, 2003, Welfare reform, labor supply, and health insurance in the immigrant
population. National Bureau of Economic Research Working Paper No. 9781.
——— and L. Hilton, 1996, Immigration and the welfare state: immigrant participation in means-tested entitlement programs. Quarterly Journal of Economics 111,
575–604.
———, R. B. Freeman, and L. F. Katz, 1997, How much do immigration and tradeaﬀect labor market outcomes? Brookings Papers on Economic Activity 1, 1–90.
Card, D., 2001, Immigrant inﬂows, native outﬂows, and the local labor market
impacts of higher immigration. Journal of Labor Economics 19, 22–64.
Citrin, J., D. Green, C. Muste, and C. Wong, 1997, Public opinion toward
immigration reform: the role of economic motivation. Journal of Politics 59,
858–881.
Dustmann, C. and I. Preston, 2004a, Racial and economic factors in attitudes
towards immigration. CReAM Discussion Paper No. 1.
——— and ———, 2004b, Is immigration good or bad for the economy? Analysis of
attitudinal responses. CReAM Discussion Paper No. 6.
Feenstra, R. C., 2000, The Impact of International Trade on Wages (University of
Chicago Press, Chicago).
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

32

HANSON ET AL.

——— and G. H. Hanson, 2003, Global production and inequality: a survey of trade
and wages, in: E. Choi and J. Harrigan, eds., Handbook of International Trade(Blackwell, Oxford, UK) 146–185.
Fetzer, J. S., 2000, Public Attitudes Toward Immigration in the United States, France,
and Germany (Cambridge University Press, Cambridge, UK).
Fix, M. and J. Passel, 1999, Trends in Citizens’ and Noncitizens’ Use of Public Beneﬁts
Following Welfare Reform, 1994–1997 (Urban Institute, Washington, DC).
——— and ———, 2002, The Scope and Impact of Welfare Reform’s Immigrant
Provisions (Urban Institute, Washington, DC).
Hainmueller, J. and M. J. Hiscox, 2005, Educated preferences: explaining attitudes
toward immigration in Europe. Harvard University Working Paper.
——— and ———, 2006, Learning to love globalization: the eﬀects of education on
attitudes toward international trade. International Organization 60, 469–498.
Hanson, G. H. and M. J. Slaughter, 2002, Labor-market adjustment in open
economies: evidence from U.S. states. Journal of International Economics 57, 3–29.
———, K. Scheve, and M. J. Slaughter, 2005a, Individual preferences over highskilled immigration in the United States. Mimeo, UCSD, Yale University, andDartmouth College.
———, ———, and ———, 2005b. Public ﬁnance and individual preferences overglobalization strategies. National Bureau of Economic Research Working Paper
No. 11028.
Hays, J., S. Ehrlich, and C. Peinhardt, 2005, Government spending and public
support for trade in the OECD: an empirical test of the embedded liberalism
thesis. International Organization 59, 473–494.
International Monetary Fund, 2004, Government Finance Statistics (International
Monetary Fund, Washington, DC).
Kessler, A., 2001, Immigration, economic insecurity, and the ‘‘ambivalent’’ American public. Working Paper No. 41, Center for Comparative Immigration Studies,
UCSD.
Kletzer, L. and R. Litan, 2001, A Prescription to Relieve Worker Anxiety, Policy Brief
No. 01-2 (Institute for International Economics, Washington, DC).
Mayda, A. M., 2006, Who is against immigration? A cross-country investigation ofindividual attitudes toward immigrants. Review of Economics and Statistics 88,
510–530.
——— and D. Rodrik, 2005, Why are some people (and countries) more protectionist
than others? European Economic Review 49, 1393–1430.
O’Rourke, K. and R. Sinnott, 2001, The determinants of individual trade policy
preferences: international survey evidence, in: S. M. Collins and D. Rodrik, eds.,
Brookings Trade Forum: 2001 (Brookings Institution Press, Washington, DC)
157–206.
Sapiro, V., S. J. Rosenstone, and W. E. Miller, The National Election Studies. 1998,
American national election studies, 1948–1997 [CD-ROM]. ICPSR ed. Ann
Arbor, MI: Inter-University Consortium for Political and Social Research[producer and distributor].
Scheve, K. F. and M. J. Slaughter, 2001a, What determines individual trade-policy
preferences? Journal of International Economics 54, 267–292.
——— and ———, 2001b, Labor-market competition and individual preferences overimmigration policy. Review of Economics and Statistics 83, 133–145.
——— and ———, 2006, Public opinion, international economic integration, and thewelfare state, in: P. Bardhan, S. Bowles, and M. Wallerstein, eds., Globalizationand Egalitarian Redistribution (Princeton University Press, Princeton, NJ)
217–260.
r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.

GLOBALIZATION STRATEGIES

33

Smith, J. P. and B. Edmonston, 1997, The New Americans: Economic Demographic,
and Fiscal Eﬀects of Immigration (National Academy Press, Washington, DC).
Stolper, W. and P. Samuelson, 1941, Protection and real wages. Review of Economic
Studies 9, 58–73.
United States Trade Representative, 2003, Revenue implications of trade liberalization: communication from the United States. Communication to World Trade
Organization, April 10th.
Zimmermann, W. and K. Tumlin, 1999, Patchwork Policies: State Assistance for
Immigrants under Welfare Reform. The Urban Institute Occasional Paper
No. 24.

r 2007 The Authors
Journal compilation r 2007 Blackwell Publishing Ltd.