Explaining the Internationalist Orientation in American Foreign Economic Policy: Theories of Legislative Politics in Trade and Aid Policy

Helen V. Milner

B. C. Forbes Professor of Politics and International Affairs, Princeton University hmilner@princeton.edu

Dustin H. Tingley1 PhD Student, Politics Department, Princeton University

dtingley@princeton.edu Robertson Hall, Princeton University, Princeton NJ, 08544

Abstract Since 1945, American foreign economic policy has been oriented toward engagement with the international system. Given the changes in world politics and economics as well as American domestic politics over the past twenty years, scholars have wondered whether American foreign economic policy might change. What groups have supported this internationalist policy since the late 1970s, and have they changed over this period? We examine legislative voting in the US House of Representatives from the 96th to the 108th Congress (1979-2004) on trade and aid. Beyond description, we use theory to develop testable hypotheses about sources of support for and opposition to aid and trade. We show that a bipartisan group has persisted supporting trade and aid; Stolper-Samuelson models best explain this. But supporters in the two areas differ in important ways. Most interestingly, labor and liberal Democrats remain part of the group supporting aid, while they no longer do on trade.

1 Corresponding author. The authors would like to thank Raymond Hicks for assistance.

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I. Introduction

Great powers in world politics make different decisions about what strategies to pursue,

and these decisions have critical influences on how the international system operates. Since 1945,

the central element of American foreign economic policy has been its active engagement with the

international system. This internationalist orientation meant that American trade policy favored

lowering barriers to trade in goods and services, and that the US pursued a relatively generous

program of giving foreign assistance to other countries. Prior to 1945, US policy was much more

isolationist, relying upon protection of the domestic market and eschewing foreign aid. This post-

World War II internationalist policy, it is claimed, was built on two pillars: a bipartisan coalition

in Congress and presidential dominance of foreign policy (e.g., (Johnson, 2006)). Given the

changes in world politics and economics as well as in American domestic politics over the past

twenty-five years, scholars have wondered whether the direction of American foreign policy

might change dramatically (Ikenberry, 2005). Would this internationalist policy be replaced by a

more isolationist one?2 This question reflects concerns about the durability of the bipartisan

group that has supported this internationalist policy, as well as presidential dominance of it. This

study is one of the first to inquire systematically into the nature of the groups that have supported

and opposed foreign aid and trade liberalization in the US over the past twenty five years.

Further, we provide a theoretical explanation for these patterns and empirical tests of our

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propositions.

Our central questions are four. First, what groups have supported an internationalist

policy in aid and trade since the late 1970s? Is bipartisanship still evident? Second, are the groups

that support international engagement via trade the same as those that support foreign aid? W

it is often assumed that groups supporting internationalism are similar across issues, are the

supporters of aid and trade the same? Third, have the groups supporting aid and trade polic

changed over this quarter of a century? American foreign economic policy after 1945 was

designed for a world driven by the Cold War and by a serious North-South divide. Both of these

organizing features of world politics have disappeared, and new political and economic facto

such as globalization- have come to shape American politics and the world economy. What

consequences have these changes had for inte

cy agenda in trade and aid apparent?

To address these questions, we examine legislative voting in the US House of

Representatives from the 96th to the 108th Congress (1979-2004) on trade and aid issues. We show

that for each area a bipartisan group has been necessary for continuing engagement, but that the

groups in aid differs from those in trade in substantial ways. Further, the supporters in trade

2 A second dimension of US foreign policy concerns unilateralism versus multilateralism.

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aid than trade, while the president has more influence in trade than aid policy. Bringing

evolved over time, whereas those in aid have been more stable. Our theory claims that the

distinct support groups in aid and trade depend upon the characteristics of legislators

r ideologies, rather than their party affiliations or presidential preferences.

In general, the groups supporting aid and trade differ, but both policies require bipartisan

support. Democrats are more supportive of foreign aid than are Republicans, while Republicans

tend to be more supportive of trade liberalization. But fractures within the parties are large and

salient; party identification only explains a small part of legislators’ votes. Many discussion

American foreign policy focus on parties and presidents, but we think this misses a central

element of the politics surrounding foreign policy (Destler, 1995; Lancaster, 2007). A central

core of support for international engagement in trade and aid cuts across the parties and lies in the

regions that gains economically from trade and aid, i.e., those regions that are well endo

human and physical capital. Groups possessing such endowments are the winners from

internationalism and its biggest supporters. On the other hand, groups whose economic intere

seem to imply they should oppose internationalism are divided. Organized labor is a staunch

opponent of trade liberalization, as expected, but is supportive of foreign aid giving. Labor’s

division on the twin policies of internationalism is reflected in the division of the Democrat

Party. Cleavages across class lines thus dominate trade politics; capital and labor and their

respective supporters line up as opponents in this area. Political ideology also plays a role,

mainly in the aid area where legislators representing conservative voters oppose aid. The

cleavages around aid thus cut across class and party lines; supporters include economic wi

from aid plus its ideological proponents among liberal voters and labor. The power of the

presidency, in contrast, is apparent only in the trade arena. In particular, Democratic presidents

have used their influence to push Democratic legislators to support trade policies they endorse.

No party in the US today wholeheartedly supports international engagement; hence, presidents

must craft bipartisan legislative support, which limits their dominance of the agenda. Further, aid

and trade seem to represent substitutes in foreign policy terms, as majorities in the two parties se

hem, but not the other, as advancing US national interests (Palmer and Morgan, 2006).

Our project is one of the first to study these great power preferences and to compar

and aid policy. Beyond describing these groups, we theorize about the sources of different

groups’ preferences for aid and trade openness, showing that the economic characteristics of

domestic groups matter, that organized interest group pressures are salient, and that ideology is

sometimes important. We use standard theories from the political economy literature to compar

the power of alternative explanations for these groups. We find strong support for (Heckscher-

Ohlin based) Stolper-Samuelson theories of trade and aid. We find that ideology matters

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systematic theory and empirical tests to our understanding of American foreign economic policy

is an important step in advancing research in this area.

II. Theories of American Foreign Economic Policy

Most theories that address questions about the nature of foreign policy focus on one of

three sets of factors. Some tend to look at a country’s place in the international system and

predict policy given that relative global position (see for example (Elman, 1995; Haas, 2007)).

This approach is less helpful since it seems to suggest that unanimous support for policy should

be evident at home since all actors in the country share the country’s same global position. In

terms of American foreign economic policy, no such unanimity in the executive branch,

legislature or public has been apparent since 1945. Others focus most attention on the executive

branch and on the preferences and beliefs of the executive (whether prime minister or president

and cabinet)(Canes-Wrone et al., 2006; Howell and Pevehouse, 2007). For this group, presidents

have much more influence over foreign policy than they do domestic policy, and more influence

than the public or Congress. Others pay more attention to domestic economic and social factors;

for instance, there exists a large literature in trade policy that emphasizes the economic

characteristics of political actors’ constituencies (e.g., (Hiscox, 1999; Ladewig, 2006)). Our

approach uses the last two set of theories to explore the nature of the groups supporting and

opposing aid and trade policy in the US.

Unlike most other studies of foreign policy, we focus our attention on the legislature and

in particular the House. We think that legislators in the House closely reflect the interests, ideas,

and concerns of their constituents. They have the shortest (re)election periods, the smallest

constituencies, and higher turnover rates (Collier and Munger, 1994). Further, some claim that

the House after the mid 1970s took over the dominant position on most international policy issues

from the Senate (Johnson, 2006). Hence they may well provide the best mapping of the groups

that support and oppose trade and aid policy.

The President proposes most foreign policy initiatives, such as trade liberalization

agreements, and presents budgets to Congress for foreign aid giving. Majorities in Congress must

approve his proposals before they can be implemented. Why would legislators support an

internationalist policy of generous aid and trade liberalization? A first hypothesis that must be

entertained, our null hypothesis, is that legislators simply vote idiosyncratically on these issues.

Both issue areas may seem arcane and distant from the domestic concerns of their constituents;

they may also be seen as unimportant, having few, if any, consequences for their constituents. In

this view, no predictable group of legislators should appear in support of aid and trade. No set of

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factors should be able to systematically explain legislators’ votes on trade and aid policy, since

they (and their constituents) either do not have preferences or do not know them in these areas.

To the extent that trade and aid are marginal to the US economy, this perspective gains

plausibility. How important are trade and aid to the US? American trade dependence has grown

much since the 1970s. By 2000, roughly 25% of the US economy was exposed to trade; that is,

exports and imports accounted for a quarter of GDP. Imports since 2000 have been well over $1

trillion per year, and exports from the US close to $1 trillion, combined they are equivalent to the

size of the entire US government budget (WTO, 2006, table II:4). Economic aid has been a less

salient part of the US economy, but not insignificant.3 It has accounted for less than 1% of US

GDP since the Marshall Plan ended. Nevertheless, the US is the largest absolute donor in the

world since its GDP is so large. The amount of aid is also similar in many years to the amount of

direct government spending on agricultural supports, an area that has received considerable

scholarly attention (GPO, 2004; Hansen, 1991; OECD/DAC, 2007; Poole and Daniels, 1985).

The fact that much foreign aid is tied to domestic suppliers suggests that legislators and domestic

groups see aid as valuable; an estimated 72% of US aid in 2006 remains tied

(CenterForGlobalDevelopment, 2007). Since aid is a much smaller part of the economy, one

might expect that economic and social factors would explain it less well.

A milder version of the null hypothesis is that legislators simply follow the president’s

lead. Presidents propose foreign policy and legislators vote in favor of it if they come from the

president’s party and against it if they are from the opposition party (Howell and Pevehouse,

2007). In this version, legislators (and their constituents) take cues from the President and

following party loyalty vote in accord with the president. Legislators thus have no preferences

regarding trade and aid and/or no incentives to find them out. This argument suggests no

predictable group of legislators supporting aid and trade policy should exist; rather, support will

change as the president’s party and his interests change. We also test this presidential dominance

hypothesis.

In addition to the null hypothesis and the presidential dominance ones, we explore two

other sets of theories that claim to explain legislators’ votes. Below we examine the specific

hypotheses that are derived from such political economy models and ideological arguments.

III. Theory and Hypotheses about Economic Interests.

3 Note that non-military aid is no longer primarily directed toward Israel and Egypt. In 1998, a deal was struck to end all non-military aid to Israel and to halve all non-military aid to Egypt in ten years. In the FY08 budget proposed, Israel no longer gets any non-military aid and Egypt gets less than half of what it got in the 90s—less than $400 million.

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Two sets of factors may systematically explain legislators’ votes on aid and trade: their

economic interests and their ideological predispositions. Here we explore how the economic

interests of legislators’ constituents may affect their voting. Legislators desire most of all to

remain in office. This office seeking motivation leads them to pay attention to their constituents.

Voters may not know much about policy nor pay much attention to issues, but they tend to vote

legislative incumbents out of office when bad outcomes arise. Such punishment of incumbents

and the fear of it motivate legislators to develop preferences about all sorts of policies that could

affect outcomes in their districts.

Avoiding such bad outcomes (and sometimes being rewarded for good ones) means that

legislators may vote according to the distributional consequences that policies are expected to

have for their constituents. These distributional consequences in turn depend on the economic

characteristics of their districts. Trade and aid, according to various theories, have distributional

consequences, and different districts because of their different economic compositions will

experience the costs and benefits of aid and trade flows differently. The two most prominent

theories of such distributional consequences are Stolper-Samuelson and Ricardo-Viner models.

These lead us to anticipate that the district level economic consequences that legislators expect to

follow from aid and trade policies shape their preferences about trade and aid policy. We focus on

two basic elements that affect their political support for foreign economic policy: 1) the economic

composition of their districts and 2) the activities of interest groups like labor unions and business

associations.

These competing theoretical models, the Stolper-Samuelson (SS) and Ricardo-Viner

(RV) theorems, make different predictions about who the winners and losers will be from

international economic integration (Rogowski, 1989). Many have shown that these theorems

accurately predict congressional voting patterns on US trade policy, but controversy has arisen

over which of these two models best predicts trade policy (e.g., (Bailey, 2001; Baldwin and

McGee, 2000; Beaulieu, 2002a; Fleck, 2002; Ladewig, 2006). We extend these well-known

results to foreign aid because international foreign aid patterns are closely related to other

international economic flows ((Alesina and Dollar, 2000; Brakman and Marrewijk, 1998; Husain,

1993); for a longer discussion of why aid may be similar to trade see (Milner and Tingley, 2007)).

In this paper we concentrate on the Stolper-Samuelson model since it has received substantial

support in the literature. We also conducted an extensive series of tests of RV, and generally

found much less support for this theory. We discuss some of this research below, but concentrate

on SS in order to focus the paper.

The Stolper-Samuelson theorem (SS), which is based on the Heckscher-Ohlin model of

international trade, assumes that factors can easily move across industries; it predicts that the

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distributional consequences of international economic policies will vary by factors of production.

That is, those who own more capital and those who own relatively more labor will differ in their

preferences over these policies since they will differentially gain (and lose) from them. This

model sees the primary cleavage as one between capital and labor. In advanced industrial

countries, which are abundant in capital--especially human capital, the relatively scarce factor,

labor—especially unskilled labor—will lose from policies that open the economy to the world

and its poorer economies.

In addition, the Stolper-Samuelson framework predicts that encompassing interest groups

which represent capital or labor should be active players, lobbying and pressuring legislators to

adopt their favored position. These groups should be internally united on their preferences toward

trade; thus, it predicts that PAC support to legislators by capital and labor groups should be an

important component of legislators’ decisions (Hiscox, 2002). Labor groups should contribute to

legislators who vote against bills to liberalize trade, while capital groups should actively support

such bills. We are not arguing that PAC contributions are necessarily causal; instead we want to

see which groups support and oppose aid and trade. This model then generates a series of

predictions that are distinct from those of our null hypothesis.

In contrast, the Ricardo-Viner theorem (RV), or specific factors model, sees the major

groups in the economy as those organized around different industries, and not factors of

production. Since factors of production are not mobile but specific to an industry, groups like

capital and labor that work in the same industry face the same distributional consequences. If an

industry gains (loses) from foreign trade or aid, all factors of production (i.e., capital and labor) in

that industry should support (oppose) policies that promote trade or aid. The Ricardo-Viner model

focuses on the district level characteristics associated with trade flows: in particular, export

oriented versus import competing industries. In addition, the specific factors model predicts that

interest groups representing capital owners across the economy or labor generally should be

unable to form a unified position on trade; they will be divided in their policy preferences by their

sectoral characteristics (Hiscox, 2002, pgs. 38-40). The specific factors model then sets forth

predictions for these two sets of influences on legislators, ones which differ from the Stolper-

Samuelson model and our null hypothesis.

How do these models apply to foreign aid? Following models proposed by a variety of

economists, we point out the distributive consequences of aid for donor countries (e.g., (Bhagwati

et al., 1983, 1984; Brakman and Marrewijk, 1998; Jones, 1984; Kemp, 1995; Mayer and

Raimondos-Moller, 1999)). There are two effects associated with aid as an international transfer:

a direct income effect (the transfer of purchasing power usually financed by taxes) and a change

in the terms of trade. An individual’s preferences for foreign aid in the donor country depend on

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their factor ownership and on these terms of trade effects. Because aid affects the international

terms of trade, it in turn changes the distribution of income among factor owners in the donor

country. Their preferences then depend on how the terms of trade effect interacts with their

endowments.

As Mayer and Raimondos-Moeller (2003) note, a necessary condition for foreign aid to

increase the welfare of a person in the donor is that the transfer raises their income. An increase

in a person’s income will occur if the recipient country’s propensity to consume exceeds the

donor’s for the good which uses relatively intensively the factor that the person owns relatively

more of than the average person. For example, a transfer will increase a person’s income if the

recipient country has a higher propensity to consume the capital-intensive good than the donor

does and the person’s capital ownership ratio exceeds that of the average person in the donor.

Since poor recipient countries have a higher marginal propensity to consume certain goods, such

as food and capital intensive imports, than rich donor countries, a transfer would raise the world

prices of these goods. Then individuals in the donor country whose factors of production are

intensively used in the production of these goods have incentives to favor foreign aid, as the

Stolper-Samuelson theorem would anticipate. Since exports from rich countries to poor tend to be

capital intensive, this means that owners of capital in the donor benefit from aid through the terms

of trade effects.

Thus the main conclusion of the distributional models of aid, using the Stolper-

Samuelson framework, is that owners of capital in donor countries tend to gain from aid and thus

are more likely to support giving aid. On the other hand, owners of relatively unskilled labor in

the donor are likely to lose from aid and thus should oppose it. Likewise interest groups

representing capital should support aid, while those representing unskilled labor should oppose it.

The conclusions of the Ricardo-Viner model are that export-oriented districts should favor aid

and trade, while import-competing ones should oppose them both. As with trade, interest groups

representing capital and labor should be too divided in their preferences to make significant PAC

contributions to one side or the other.

These two theorems generate different predictions about the underlying bases of support

for and opposition to trade and aid policies. If the Stolper-Samuelson models are correct, we

should see class cleavages over aid and trade. A number of studies have asked which of these

two theorems provides the better explanation for trade (e.g., (Beaulieu, 2002a; Ladewig, 2006)).

Consistent with these scholars, we find much less support in trade voting for specific factors

models compared to Stolper-Samuelson ones in the time period we consider, and no support in

foreign aid voting. Thus in our empirical analysis, we focus on Stolper-Samuelson effects, and

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briefly discuss the relative performance of Ricardo-Viner models in the appendix and in a

separate paper (Tingley, 2008).

IV. Ideology and Its Influence.

A long debate has occurred over the relative role of ideology and interests in legislative

voting (e.g., (Kalt and Zupan, 1993)). We think that it is important to try to distinguish these two

factors, but that they both are likely to matter for legislators. Ideology is harder to define than

economic interests. Here we identify ideology with a set of beliefs about the proper role of

government in the economy and society, especially relating to government attempts to

redistribute income. As noted above, we look at the beliefs of legislators’ constituencies and

assume that legislators think that their constituents (or the majority of them) hold these beliefs

and thus act on their behalf.

In American politics, a liberal-conservative ideological spectrum is often used to describe

political beliefs (e.g., McCarty, Poole and Rosenthal, 2006). This traditional left to right

ideological scale may help explain views toward foreign aid and trade. The liberal-conservative

political spectrum often identifies liberals as holding strong beliefs in the importance of

government intervention in the economy, especially to deal with redistribution of wealth to the

poor (Bobbio, 1996; McCarty et al., 2006). The conservative position on this spectrum is

associated with beliefs about the importance of individual effort and the value of the market as

means of wealth generation and distribution; government intervention is often seen as inefficient

and ineffective, as well as morally undesirable. Given these beliefs, one would expect individuals

holding liberal values to favor aid and to be opposed to free trade; on the other hand, those

holding conservative values should favor free trade and oppose aid as a form of government

intervention to redistribute wealth globally. We would expect districts (or legislators) with more

liberal views to support aid and oppose free trade, while more conservative ones should support

trade and oppose aid. Ideology defined on this liberal-conservative scale would split

internationalist groups over the value of aid versus trade. A president valuing both might have to

construct an ideological coalition of opposites to garner support for both elements of

internationalism.

In sum, our hypotheses are:

1. Economic Interests: The greater the endowment of human (or physical) capital in a district, the

higher the probability that the legislator votes in favor of trade liberalization and foreign aid.

2. Economic Interests: The larger the contributions and activities of interest groups representing

capital (labor), the higher (lower) the probability that the legislator votes in favor of trade

liberalization and foreign aid.

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3. Ideology: The more conservative the members of a district are, the greater the probability that

the legislator votes in favor of trade liberalization but the less likely the legislator votes in favor

of foreign aid.

4. Presidential Dominance: The probability that a legislators votes in favor of an aid or trade bill

rises when the president both supports that policy and is from the same party as the legislator.

V. Empirical Evaluation of the Hypotheses

Research Design

Our analysis focuses on legislative voting in the US House of Representatives from the 96th-108th

Congress. In trade and aid the president needs the assent of Congress to implement his policies. In

trade, the Constitution gives the Congress explicit control over most trade policy, largely since it

is a matter of taxes. For the president to lower trade barriers or sign agreements with other

countries requires congressional assent. Presidents thus must bargain with Congress for trade

negotiating authority, which allows the President to lower US barriers by certain amounts in

exchange for foreign concessions; the President must then bring the international agreement back

to Congress for majority votes in both houses with no amendments. In addition, legislators can

introduce trade legislation of their own, usually out of (sub) committees, since they have

constitutional authority over national trade policy. We examine all three types of bills below:

presidential authorization to negotiate in trade, final passage of trade agreements, and individual

bills to regulate trade policy.

In foreign aid, the president also needs congressional approval since this involves taxing

and spending. Congress must agree to his proposals to appropriate and then allocate funds for

foreign aid each year. Unlike in trade, aid spending authority is usually part of a much larger

foreign operations bill, which contains spending authority for all forms of international activity in

the US government. Committees amend the president’s proposals and we generally examine

these amendments, rather than the annual omnibus foreign operations bills. Hence, although the

exact processes differ, the president requires congressional majorities to implement his foreign

policies in both of these areas.

We seek to tap legislators’ general sentiments toward trade and foreign aid. Our

dependent variable is the probability that a legislators votes in favor of trade and foreign aid. To

identify the proper population of votes relating to aid and trade policy, we utilized the Voteworld

program, various publications by the Congressional Quarterly, and the Congressional Record.

With this population of votes (itself a subset of all House votes), we selected a sample of votes

that met certain a priori criteria to identify the votes that tapped legislator positions on aid and

trade.

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We include aid votes that satisfied the following criteria. First, we identified the universe

of amendments related to foreign aid that received roll call votes in the House between 1979-

2004 (96th-108th Congress). Second, we selected a subset that had the clear legislative

consequence of increasing or decreasing foreign aid funding, such that they could be

unambiguously coded. This requires that we exclude procedural, conference report, and final

passage votes; and it means that most of our votes involve amendments to final passage bills.

While interested in separately analyzing the universe of final passage votes, our reading of the

Congressional Record is that these votes concern a wide range of foreign operations issues, many

of which are orthogonal to foreign aid. A separate paper considers these final passage votes

(Milner and Tingley, 2007). Third, we do not consider amendments that involved specific

countries or programs that primarily support specific countries (like the Economic Support Fund).

Such votes usually tap geopolitical and country specific issues not related to general sentiments

toward aid. Fourth, we excluded amendments that dealt with ‘hot-button’ issues, like abortion and

AIDS, because these votes also address a very different set of political issues. Fifth, we exclude

votes on two specific, and important, types of foreign aid: food aid (PL480: Food for Peace

program) and export promotion (Import Bank or the Overseas Private Investment Corporation).

These programs represent an important means of international engagement. They also tap very

particular and narrow interests that more general aid votes might not. For example, in separate

analysis of food aid votes, we see that (as expected) district agricultural production has a strong

effect on support food aid. We do not see this relationship with the more general votes we include

in our sample. Thus combining a range of different types of votes could bias inferences. For

export promotion programs we expect that if economic interests influence voting in our current

sample, then they would be especially salient for votes on these programs. We look forward to

giving all of these types of aid legislation a more detailed treatment than space allows here. The

resulting set of foreign aid votes taps salient, yet still general, preferences for and against aid.

We pursue a similar strategy with regard to trade votes. We include trade votes that 1)

had clear consequences for US trade policy (e.g., were not procedural votes or ‘sense of

Congress’ votes), 2) did not deal with individual products unless those products dealt with major

US industries (e.g., steel, automobiles, textiles, sugar), and 3) had been used by previous scholars

in roll call vote analysis and that further review indicated that the votes were sufficiently trade

oriented.4 Most of our trade votes are final passage votes, as preceding floor votes on a particular

trade bill—if they happened—tended to be procedural. A thorough description of each bill is

provided in our on-line appendix.

4 Some votes used by other scholars involve issues that, upon detailed inspection of the Congressional Record, were rather tangential to actual trade policy and thus we do not include them.

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We chose our sample of votes from the 96th-108th Congress primarily because this period

covers a broad span of American political history that has witnessed many changes domestically

and internationally. This sample gives us variation on the party of the President, divided

government, and the state of the US economy. Our votes should indicate general preferences

about foreign aid or trade. Our votes are similar enough to get at this general preference, but not

so similar that they merely inflate our number of observations without adding new information.

Our dependent variables then are two: a legislator’s vote on aid bills and his/her vote on trade

bills. Votes were recoded so that a 1 equaled support for aid and trade liberalization, while a 0

indicated opposition. We estimate the probability that a legislator votes in favor of aid or trade

given a series of characteristics about his or her district.

Empirical Analysis

We begin our discussion of the empirical results with a series of graphs that illustrate

interesting differences between voting on aid and trade. This gives us a general understanding of

trade and aid voting in the US during the years in our sample prior to moving into a more detailed

multivariate analysis. Table 1 charts the average DW-Nominate scores of Republicans and

Democrats by their position on aid and trade. DW-Nominate scores are a commonly used

measure of legislator ideology, usually thought of as arrayed along the liberal-conservative

(Left/Right) dimension with a higher number being more conservative. The scores are derived

from extracting a common dimension from voting over all bills within a Congressional session.5

For each vote, we took the average DW-Nominate score of legislators in each party by whether

they supported or opposed foreign aid or trade liberalization. The horizontal axis arrays the votes

along Congressional sessions, while the vertical axis shows the calculated average DW-Nominate

score for each group, with 95% confidence intervals surrounding each calculated average.

Two interesting patterns emerge. First, aid supporters when arrayed along the ideological

dimension are an ideologically ‘non-connected’ group. Support for foreign aid comes from liberal

Republicans and liberal Democrats; opponents are conservative Republicans and conservative

Democrats. This pattern is quite stable throughout our sample of aid votes (1979-2004). Support

for trade policy, on the other hand, has shifted around in this ideological space over time. Prior to

the 1990’s support for free trade came from conservative Democrats and conservative

Republicans. While conservative Democrats tended to maintain their support for free trade, more

conservative Republicans started to oppose free trade—a change which could be titled the “Ross

Perot effect.” Increasingly from 1992 onward, the ideologically connected group of liberal

Republicans and conservative Democrats formed the core of support for freer trade. Thus,

5 Unfamiliar readers may wish to consult http://voteview.com/dwnomin.htm, or (Poole and Rosenthal, 2006)

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preliminary evidence suggests that while the groups supporting foreign aid (liberal Democrats

and liberal Republicans) have persisted, the groups supporting free trade have been less stable.

The second observation is that differences within parties tend to be much greater for aid

than they are for trade. Ideological differences also seem to split Democrats much more than

Republicans for aid votes, while this is less true for trade votes. Table 1 suggests that ideology

will be a better predictor of legislative voting on aid than on trade.

<Insert Table 1 here>

Table 1 also suggests an important question in thinking about internationalist policy: does

it require bipartisan support? Do Democrats need Republicans to support aid and do Republicans

need Democrats to support free trade? Table 2 investigates this by graphing, for each vote, half of

all votes cast and the number of pro-aid or pro-trade votes coming from the Democratic or

Republican parties (respectively). This clearly shows that in both aid and trade, support is needed

from members of the opposite party. Internationalism is a bipartisan policy.

<Insert Table 2 here>

Another way to compare how legislators within parties vote on trade and aid is to match

up all trade and aid votes within a congressional session, and calculate simple cross-tabulations.

E.g., one might cross-tabulate the NAFTA final passage vote and the amendment to cut aid funds

to the World Bank in the 103rd Congress. Unlike many other studies we include many votes in our

analysis, and thus presenting the results from all such vote pairs in cross-tabulated form would be

unwieldy. Instead we graph a measure of ordinal association, the gamma score (which is

equivalent to the Yule’s-Q that Broz reports (2005) in his work on similar issue areas), between

trade and aid votes for each party for all combinations of votes in our sample that are in the same

session. The left hand axis for the top two graphs in table 3 is the gamma score, and the right

hand side is the z-score obtained by dividing the gamma score by its asymptotic standard error.

The organization of our cross-tabulations that produce these scores is such that the top row is an

anti-aid vote, the bottom row is a pro-aid vote, the left column is anti-trade and right column pro-

trade. Given this organization, a positive gamma implies that the population tends to lie along the

diagonal from top left to bottom right. A negative gamma implies the population tends to lie on

the bottom left to top right diagonal (Liebetrau, 1983, pg. 75). I.e., legislators tend to be in the

anti-trade/anti-aid and pro-trade/pro-aid cells when the gamma score is positive and in the off

14

diagonal cells when the gamma is negative. When the associated z-score is larger in magnitude,

then the relationship (either on or off diagonal) is stronger.

<Insert Table 3 here>

The top left graph of table 3 shows Democrats in the early 1980’s were significantly

more likely to lie on the off diagonal: either pro-aid/anti-trade or anti-aid/pro-trade.6 Inspection of

the actual cross-tabulations suggests that during this period if a Democrat was pro-aid, they were

much more likely to be anti-trade. This block of legislators drives the negative gamma score we

see for this period. This association fades away for Democrats in the 1990’s and later, after which

a slight increase in the average number of pro-trade Democrats occurs on several trade votes. For

Democrats in the 1990’s and up, the gamma score was insignificant for most vote cross-

tabulations. The off diagonal relationship in the early period gets lessened as more Democrats

support trade in the later period. Republicans, on the other hand, did not have a significant

measure of association between the two policy areas in the 1980’s. But in the 1990’s and later

Republicans who were pro-aid tended to also be pro-trade. Of course, most Republicans were

anti-aid and pro-trade. But as more Republicans became pro-aid/pro-trade during this period the

gamma score turns positive and is significant in this later period. This observation couples nicely

with table 1, as in the later periods more liberal Republicans began to favor both aid and trade

liberalization, whereas more conservative Republicans have increasingly opposed

internationalism in both issue areas. Taken together, this means that the saliency of party in

staking out pro or anti-internationalist positions has changed over time. Democrats in the earlier

period were better able to keep a pro-aid anti-trade position, but some Democrats began to take

more pro-trade positions in the 1990’s. This possibly suggests that changes in executive branch

leadership, from the Reagan/Bush I era to the Clinton era may be driving these changes. Clinton’s

pressure on Democrats to vote for NAFTA may be part of this. More curious is the relatively high

percentage of Democrats voting in favor of the trade liberalization under George W. Bush.

Republicans on the other hand had a less structured set of policy positions in the early period, but

have become increasingly divided along pro and anti internationalism lines.

Multivariate Analysis

The above analyses provide an overview of the groups supporting internationalism, but

treat party and legislator ideology as the only things we need to know. The next section tests

6 Non-ordinal measures of association, such as similar chi-square tests, reveal a similar story but do not give the directional inferences that the gamma measure does. Tau-b tests results are basically identical to the gamma measures.

15

predictions deduced from the political economy and ideology models using multivariate

regression analysis. This allows us to estimate how district level variables affect the voting of

legislators, and then to make comparisons across issue areas. In this section we turn to a panel

data setting that analyzes voting over our entire sample.

Our dependent variable is dichotomous, with a one indicating a vote in favor of

internationalism. Our data are collected in a panel format with the legislator-vote as the unit of

analysis. We estimate a series of probit models using our set of votes for each issue area. Our

model specification includes vote fixed effects to control for any unmodeled heterogeneity across

votes and differences in the yeas-nays margin across votes. Here we present results from a

marginal effects specification (‘population averaged’) (Liang and Zeger, 1993; Neuhaus et al.,

1991), which uses a GEE estimator with a probit link and an exchangeable within group

correlation structure. Thus, slope coefficients indicate the influence on a population of legislators,

not individual legislators per se; put differently, they tell us the average impact of a variable on an

average legislator’s probability of voting in favor of aid or trade. Heterogeneity across legislators

is accounted for by calculating robust standard errors. Our results do not change if we use a

random effects specification, which relaxes the assumption that the intercept for particular

legislators is identical across votes. Because of the relatively small number of observations per

legislator, we do not use legislator fixed effects. The panel specification means that we are

combining votes within and across Congressional sessions, which allows us to compactly analyze

our data. In our robustness checks below we show that running separate probit regressions for

each vote yields identical conclusion.

Independent Variables

Before presenting our results, we briefly describe our independent variables; a more

thorough discussion is in appendix 1. We test predictions made by Stolper-Samuelson models by

measuring capital endowments at the district level; Stolper-Samuelson models propose that the

greater the amount of capital (human capital or physical) used in the district (relative to unskilled

labor), the more likely is a vote in favor of aid and trade. Following other scholars (Beaulieu,

2002a, b; Broz, 2005; Broz and Hawes, 2006), we measure this by the percentage of people

working in high skill jobs (% HighSkill).7 We expect this measure of human capital to be

positively related to support for aid and freer trade.

7 Others have used similar measures, such as the percentage college educated (Bailey, 2001). We operationalized RV type dynamics by measuring the percentage of people in a district identified as being in net export oriented industries relative to those in import competing at the SIC four digit level (Baldwin and McGee, 2000). We constructed this measure for every Congressional session in our sample. We also constructed several measures used by other authors for all the years in our sample (Broz, 2005; Ladewig, 2006). We then conducted a series of model fit exercises using both Bayesian Information Criterion (BIC)

16

We also constructed measures of relative physical capital endowments by aggregating the

amounts of fixed capital and labor in manufacturing industries following the procedure used by

Ladewig (2006). The lnCapitalEstab variable measures the (log) of capital stock in all

manufacturing sectors, and the lnLaborManuf variable measures the (log) of manufacturing

employment, at the district level for all Congressional sessions in our sample.8 We expect the

capital measure to be positively related to support for internationalism, and the labor measure to

be negatively related. Stolper-Samuelson models also suggest that districts abundant in

agriculture should favor both aid and trade. We measure this by calculating a district’s total value

for livestock and crop production (MktValAgProd).

PAC contributions from corporate sources (CorpPAC%), labor groups (LabPAC % PAC),

and money-center banks (BankPAC %) are operationalized as a percentage of total PAC

contributions. All of these campaign contributions are implemented as the percentage of total

PAC contributions (per the advice in (Roscoe and Jenkins, 2005, pg. 60)) and taken from the

electoral cycle preceding the Congress where we observe an actual vote.9 Stolper-Samuelson

models predict that corporate PAC’s, including money-center banks, will support aid and free

trade, while labor groups will be in opposition. We also added a variable for unionization

(%union) in order to see if districts that had higher union density were less favorable to aid and

trade, as Stolper-Samuelson models would predict.

Ideologically based theories suggest that legislators from more conservative districts will

support free-trade but oppose foreign aid, while legislators from more liberal will have opposite

preferences. Following scholars in American politics, we measure district ideology as the

percentage of the two party vote for the President that goes to the Republican candidate,

PrezVoteRepub% variable. In the US two party system, we argue that an individual’s political

ideology is well indicated by his/her vote for one of the two major parties. The district average of

Republican votes should indicate how conservative the district is likely to be.

If the Presidential dominance hypothesis is right, then what should matter are Presidential

party dynamics. Thus we created a Presidential support variable using data from David Rohde, and Bayes’ factors. Our results generally extend Ladewig’s findings beyond the 102nd Congress where his analysis left off: SS fits Congressional voting significantly better than RV. However, RV fit the data better on several votes in this post 102nd Congress period, including the important NAFTA and GATT votes in the 103rd Congress. In order to focus this paper on comparisons between aid and trade we briefly discuss these results in an online appendix and a more thorough discussion in a separate research note (Tingley, 2008). 8 We used GIS software to translate county level data to district level data whereas Ladewig manually made estimates from district maps. Nevertheless, our variables correlate at a very high level for the Congressional sessions where our analyses overlap (r>.9). 9 Readers should not that we are not using PAC contributions to argue that PAC money buys votes. Instead, we use PAC contributions as a way to measure the affinity of different groups in society to different types of policies. Ultimately we would love to use an appropriate instrument that would help us get around the various problems that plague the analysis of PAC contributions, and we invite readers to make concrete suggestions to this end.

17

coded as a 1 if the President was of the legislator’s same party and the President supported aid or

trade liberalization, and 0 otherwise (Rohde, 2004). If the Presidential dominance hypothesis is

right, this variable PrezSupport should be positive for both aid and trade. We also explored more

nuanced versions of this variable, but our substantive results did not change and thus we retain

our single dummy variable measurement.10 The nature of the data prevents us from investigating

a variety of other theoretical conceptions about the interactions between the President and

Congress. For example, we are unable to incorporate various forms of strategic interaction

between the President and Congress. This could arise if the President were only to issue positions

if a vote was expected to be close. Thus, while we think it is important to measure the potential

influence of the President (something that previous roll call voting analyses have not done),we

note that future work will be needed to better establish the relationship between the two branches

on these and other international economic policy areas. We think that if the president is powerful,

he should at least be able to pull his own party members to support his favored policies.

In addition to testing our hypotheses, we include a variety of common control variables

so that our results do not suffer from omitted variable bias. We include regional control variables

because other foreign policy studies have concluded that regional variations are important.

Trubowitz, for instance, argues that “Once the champion of Cold War internationalism, the

Northeast had become the defender of neo-isolationism by the 1980s”, while the South and West

had turned into the supporters of international engagement (1998, pg 232). His argument stresses

that regions within the US have distinctive economic stakes in American foreign policy;

isolationist versus internationalist policies affect the regions quite differently and hence make

their representatives differentially supportive of such policies. Many previous analyses of roll

call voting on foreign policy issues do not include these measures. By estimating models with

these controls, we are more confident that our inferences are not biased by regional differences

that we do not otherwise measure.

Finally, we also included a number of demographic variables at the district and state level

(when district level variables were not available). A more complete discussion of these variables

is in appendix 1.

10 Instead of the dichotomous PrezSupport variable we considered the full range of dichotomous variables produced by 1) the President’s position (support aid/trade, oppose aid/trade, no position) and 2) whether legislator was of the same party as the President. Unfortunately, including these variables and vote fixed-effects generate problems in the statistical analysis because particular dummy variables started to make vote fixed effects drop. For example, take a vote where the President did not take a position. Then the dummy variable representing the President taking a pro position and the legislator being a member of the President’s party would be collinear with the dummy variable for that vote, because all legislators would have a “0” for that vote. Hence, the vote fixed effect drops, and the interpretation of the other dummy variables becomes quite problematic because the omitted categories become combinations of vote fixed effects and the omitted Presidential category.

18

Table 4: Predicted Relationships (Aid/Trade)

Null President SS Ideological

% High Skill Workers (0/0) (0/0) (+/+) (0/0)

Bank PAC % PAC (0/0) (0/0) (+/+) (0/0)

Corp PAC % PAC (0/0) (0/0) (+/+) (0/0)

Lab PAC % PAC (0/0) (0/0) (-/-) (0/0)

% unionized (0/0) (0/0) (-/-) (0/0)

PrezSuppSamePty (0/0) (+/+) (0/0) (0/0)

District Ideology

(higher=more conservative) (0/0) (0/0) (0/0) (-/+)

Agricultural Production (0/0) (0/0) (+/+) (0/0)

Results

We present six different multivariate models in table 5 for aid and trade votes. We wish

to avoid both criticisms of omitted variables and ‘garbage can’ regressions (Achen, 2002), and

thus we move from relatively simple regressions to more complicated ones. Our first regression

contains our core political economy variable (%HighSkill) and PAC variables. The second two

sets of regressions add party, demographic control variables, and regional control variables. Next

we drop party and add our district level ideology variable. The final set of regressions includes

uses alternative district level measures of Stolper-Samuelson.11 We first discuss the direction and

significance of our variables for each issue area, and then move to comparing models and

estimating the substantive impact of our variables. We estimate models separately explaining

support for aid and trade in order to isolate the effect of our variables on each issue area. While

we believe that there could be a relationship between legislator’s preferences about the two issue

areas, this relationship is neither uniform nor constant, as shown in table 3, and thus we do not

believe that our estimation strategy is biased in any systematic way by not including relationships

across the two issue areas.

Our results strongly suggest that the null hypothesis of idiosyncratic votes by legislators

can be rejected. Further, the presidential dominance hypothesis receives no support in the aid

case and only limited support in the trade one. Our economic interest and ideological variables

11 We estimated a number of other models to check the robustness of our results. We discuss some of these robustness checks below, but note that our results are consistent across models.

19

predict votes well and suggest that a core group of legislators supporting an internationalist policy

exists.

The Stolper-Samuelson model does quite well in both aid and trade votes. Our measure

of capital endowments (%HighSkill) is highly significant and positive for both aid and trade

votes, indicating that legislators from districts with high levels of human capital are more likely to

vote in favor of foreign aid and free-trade. The results for trade are consistent with those found in

the literature. The strong positive relationship for aid is as predicted by the Stolper-Samuelson

model, but is perhaps more surprising. The same variable used by others to study trade

preferences and support for financial bailouts has the same effect for aid voting. This result

indicates that a core group of supporters exists for an internationalist policy that is composed of

similar groups on trade and aid. Thus our results provide an important extension of previous

findings in trade policy to that of foreign aid voting.

One criticism of the %HighSkill variable is that it might capture other effects beyond

economic factors, and thus the measure might be problematic despite the fact that a range of

published studies use this measure. For example, those districts with higher skill levels might also

be more cosmopolitan and hence open to international engagement. Unfortunately, criticisms of

this type often stop without suggesting ways to control for these other influences. One suggestion

is to include the percentage of adults that have a college degree; however, this correlates with the

skill variable at a high level, ranging from .65 in the 1980’s to .97 in the 2000’s. This multi-

collinearity is a statistical nuisance (akin to having a small n or low variance in IV’s), but over-

determination between Stopler-Samuelson models and cosmopolitanism is a theoretical problem.

The extent of this theoretical over-determination is not clear. Those who think that the college

education variable taps cosmopolitanism assume a tight relationship between education and

cosmopolitanism, though we are unaware of why this necessarily must be the case. Similarly it is

not clear why more education always leads to greater acceptance of free market ideas, as higher

level education need not be in neo-liberal or classical economics.

As noted above, we collected other measures of capital and labor endowments, following

the procedure laid out by Ladewig (2006). We obtain largely the same results for these variables

as we do for our high skill variable. The lnCapitalEstab variable is positive for aid and trade,

whereas the lnCapitalEstab is negative for both aid and trade. These variables are significant

in our simpler models, but lose their significance once we condition on many other variables.

Taken together with our results for our skill measure, we find relatively strong support for our

models of economic interests in both aid and trade. Thus, the same empirical relationship

identified in trade seems to apply to aid.

20

Our next set of results focuses on the contributions of interest groups representing capital

and labor. We argue that the Stolper-Samuelson model can help explain the direction of these

contributions. This model suggests that capital and labor groups will be united in their

preferences that their contributions will correlate with legislative voting records. We expected

similarities across trade and aid voting in the role of capital and labor PACs. But the data do not

show this. The role of organized labor in particular follows a different pattern than expected:

labor PAC contributions (LabPAC%) tend to go to legislators that supported foreign aid and

opposed free trade, even when we control for party. While labor’s opposition to trade is

understandable in terms of our model, the positive relationship to aid is more puzzling. This

positive relationship between labor and foreign aid has been documented elsewhere using

archival material from the AFL-CIO (Milner and Tingley, 2007). These results pose an

interesting contrast across the issue areas. While organized labor was pro-trade before the 1970s,

changing economic conditions eroded its support for free trade. By the time our sample starts in

the late 1970’s, organized labor has become increasingly hostile towards trade liberalization.

Conversely, organized labor, which supported and benefited greatly from early aid programs like

the Marshall Plan, continued to support foreign aid programs.

Another interesting difference between aid and trade policy is that while money-center

bank PAC contributions (BankPAC%) tend to make up a higher percentage of total PAC

contributions for legislators voting in favor of foreign aid, this relationship is not significant for

trade votes. This extends the results of several studies (Broz, 2005; Broz and Hawes, 2006) to

foreign aid, and illustrates how large banks appear to have preferences for international

engagement beyond their support for the financial bailouts and IMF programs that Broz and

Hawes have considered.12 Instead these banks also support legislators that support foreign aid

programs more generally. In a separate paper we consider the historical bases of this support for

aid more directly. Their impact is negligible, however, for trade. Money center banks do not

appear to have salient and unified interests with respect to trade policy, or at least these interests

are not discernible from the data we consider. Thus a key difference between aid and trade policy

appears to be that large, internationally exposed banks help maintain support for aid but have less

influence or salient preferences over trade policy.

12 We do not consider here the difference-in-differences approach that Broz also uses. This procedure took the set of legislators that changed their vote from one financial bail out vote to a later vote. This change was regressed on changes in bank PAC contributions. We also conducted these analyses for our PAC variables. Depending on the model specification our results were in the expected direction and significant or insignificant. This was further complicated by not having a large sample of “switchers”, making us less confident in the statistical technique. Finally, this procedure explicitly samples on the dependent variable, and hence we have good reason to doubt the inferences that come out of it.

21

Contributions from corporate PAC’s (CorpPAC%) had a surprising negative relationship

in several models for trade votes. While negative significant in some of the trade models, this

variable was insignificant for the set of aid votes. Our Corporate PAC result is somewhat

surprising for trade.13 Labor’s opposition to trade and bank PACs support for aid confirm our

hypotheses about PAC’s, but labor’s support for aid and corporate PACs sometimes significant

opposition to trade do not. Taken together, the organized interest groups provide mixed support

for the economic interest hypotheses.14

District agricultural production (MktValAgProd) is not significantly related to the set of

foreign aid votes in our sample,15 but highly agricultural districts tend to be more free trade

oriented. As we control for region, we do not believe this is picking up regional effects. This

result is consistent with Stolper-Samuelson predictions on trade, which view the US’s relative

abundance in land favoring trade liberalization.

One important criticism of models 1 and 2 in table 5 might be that our economic

measures do not pick up on the ideological orientation of congressional districts, and thus suffer

omitted variable bias. It is possible, if not likely, that many of our economic and demographic

variables correlate with aggregate district ideological orientation. Thus including district level

measures of ideology may decrease the impact of our economic variables. Nevertheless, we re-

estimate our models to include district ideological variables. Our liberal-conservative measure,

the percentage of the district’s two party vote that is for the Republican Presidential candidate

(PrezVoteRepub%), is negative and significant for aid, while positive and significant for trade. As

predicted by theories of political ideology, more conservative districts favor trade and oppose aid,

largely because of their beliefs about the role of the government in the economy.

It is also common for scholars to include a legislator-specific ideological variable in

regression analysis of voting, though the appropriateness of this is debated. While we are more

interested in evaluating the influence of district level economic variables, our results largely do

not change if we include legislator’s DW-Nominate scores.16 Interested readers may consult these

13 This measure of capital PAC correlates negatively with free-trade support in the early 1980’s, but then trends positively. We note that both our capital and labor PAC measures aggregate across organizations, possibly obscuring more fine-grained dynamics. We obtain similar results if we restrict our attention to contributions by the AFL-CIO. 14 We also constructed a variable that measured the percentage of PAC contributions from the top 50 exporters, recreating and extending a measure first used by Nollen and Quinn (1994) This variable was positive but insignificant for both our trade and aid panels, though the variable was much closer to attaining conventional significance levels for the trade panel. 15 Not surprisingly, when we look at the set of votes on food aid legislation (PL 480: Food for Peace), legislators from districts with high agricultural production significantly favor foreign aid. We discuss these results in a separate paper. 16 The only change is that our LaborPAC% variable remains positive, but loses its statistical significance. Our union measure remains positive and significant. Labor’s tight support of foreign aid is documented elsewhere, and thus our substantive conclusions remain unchanged (Milner and Tingley, 2007).

22

statistical models in our on-line appendix. However, we take a moment to comment on the results

from using legislator-specific ideological variables instead of district level measures of liberal-

conservatism. As we saw in table 1, more conservative legislators are more likely to oppose

foreign aid and support free trade, while more liberal legislators do the reverse. As the critical

reader may have observed, DW-Nominate scores do a better job sorting out within party voting

behavior over foreign aid than for foreign trade. Not surprisingly, when we estimate the marginal

effect of a legislator’s DW-Nominate scores, the magnitude of the effect is almost four times as

large for aid as for trade. 17 We observe a similar difference between aid and trade using the

district level measure of ideology (PrezVoteRepub%) (see below). Controlling for a range of

other factors, ideology appears to matter much more for foreign aid than it does for trade.

Political party (Party) is highly significant for both our aid and trade votes. Yet while

Republicans are more likely to vote in favor of free trade, they are less likely to vote in favor of

foreign aid. While Democrats are more likely to vote against free trade, they generally favor

foreign aid. Thus party, not surprisingly, follows a patter similar to what we saw with the liberal-

conservative ideology measure. Clearly including both party and ideology would be inappropriate

as they are highly correlated. Nevertheless, table 1 shows that ideology can have a significant

impact within parties, especially for aid. We return to these within party differences below.

Models 3 and 4 include regional variables. Compared to legislators from the Northeast,

southern legislators were less likely to support foreign aid. Legislators from the West (West) and

Midwest (Midwest) are more likely to vote in favor of free trade compared to Northeastern

legislators. This supports only part of Trubowitz’s claims; the West has become a solid bulwark

of support for trade policy. These regional controls do not, however, change the results for our

other variables, and thus regional differences do not seem to powerfully predict aid and trade

votes.

We also consider several district-level demographic variables that may be related to

support for aid and free trade. Legislators from districts with large foreign-born populations

(%ForBorn) are likely to vote in favor of foreign aid in several of our models. A district’s foreign

born population had a less salient effect on trade votes. While positive, this variable was not

consistently significant. Consistent with evidence that the African-American lobby supports

foreign aid, legislators from districts with large African-American populations (%Black) are more

likely to favor foreign aid. No consistent relationship holds for trade votes. Our measure of

unemployment level (Unemploy%) and change in (state level) unemployment were almost always

negative but never significant. While the economic stress unemployment causes was a frequently

17 Marginal effects results calculated using the mfx2 command in STATA show that the larger aid marginal effect does not have a confidence interval that overlaps with the small trade marginal effect. See on-line appendix and discussion below.

23

cited source of opposition to both trade and aid, this does not materialize in our data. There is no

consistent relationship between (the log of) median income (LogMdnIncm) and either trade or aid

voting. Some have used income as a measure of altruism, suggesting that richer districts should

provide more support for aid (and perhaps trade) (Krueger, 1996); we do not find this result.18

The preceding discussion focused on district and legislator preferences as predicted by

political economy models and those emphasizing ideology. As discussed in our literature review,

an alternative (though complimentary) way to explain legislative behavior is to more formally

consider the relationship between the Executive and Legislative branch. The President clearly

plays a key role in shaping both aid and trade policy, and thus the President may be able to also

influence legislative voting by taking particular positions on the bills.

Our multivariate results show that the effect of having a President of the same party issue

a statement in support of aid or free trade, versus not taking a position, is positive and significant

for trade, but negative and insignificant for aid (PrezSupport).19 There is also some evidence that

the impact of the President taking a position is less than that of some of our other economic

variables.20 This contrasts with Kesselman’s (1961) findings that emphasized the role of the

President in influencing aid role call voting, and supports the skepticism about this result

articulated by Asher and Weisberg (1978). To see why there is a difference between aid and

trade, we can look at this relationship using simple cross-tabulations. In our sample of 10 high

saliency aid votes, the President took a pro-aid position on 6 votes, and no position on the 4

others. In our sample of 20 high saliency trade votes, the President took a pro-trade position on 16

votes, and no position on 4 others. Consistent with previous work, the President—regardless of

his party—tends to have a strong preference for both foreign aid and free trade. The question that

interests us, however, is whether the President’s position taking has an influence on legislative

voting.

Table 6 suggests that the influence of the President on aid voting is very different from

his influence in trade policy. Whereas the President’s decision to take a position on trade

18 This measure does have a positive and significant coefficient when we use Ladewig’s measures of capital and labor concentration, but only for trade voting. 19 As discussed previously we also measured the influence of the President in several other ways, but generally came to the same set of conclusions. One exception was if we simply took the President’s position (either pro-internationalism (1) or no position (0) in our sample). This variable was negative and significant for both aid and trade. This suggests that the influence of the President in trade policy may operate chiefly through members of the President’s party. We note that we do not model potential sources of strategic interaction between the President and the legislature, and hence we treat the set of cases where the President issues a position as no different from cases where the President does not issue a position. This is clearly inappropriate. However, given our interest is between comparing aid and trade, we see little reason why the strategic dynamics would be different across the issue areas. And hence the difference in impact that we identify remains interesting. 20 The marginal effect of our Presidential variable is several orders of magnitude smaller than the marginal impact of several of our economic variables. For dichotomous variables like Presidential support, the marginal effect is calculated as a discrete change in predicted probability.

24

legislation results in more legislators voting in favor of trade, this is not the case for aid votes. In

fact, legislators who are of the same party as the President are less likely to vote in favor of the

President’s position. We suspect that the influence of the President on trade policy is driven by

the shift of some Democrats towards a pro-trade position in the 1990’s when Clinton was

president, as shown in table 3.

<Insert Table 6 here>

To summarize, there are interesting similarities and differences between legislative

voting on foreign aid and trade policy. The similarities suggest that there are underlying forces

that keep together—or prevent the breakdown of—a broad internationalist policy orientation.

Predictions from the Stolper-Samuelson model help explain the similarities in these groups. Our

measure of district skill levels, which indicates human capital endowments relative to unskilled

labor, correlates positively with both foreign aid and free trade support. The population of

legislators coming from districts with relatively high levels of capital endowments is more likely

to support both foreign aid and free trade. This can readily be seen by looking at “defectors”

within each party: i.e., Democrats voting against aid or for trade, and Republicans voting in favor

of aid or against trade. Table 7 gives the mean levels of our skill variable, with 95% confidence

intervals, for defectors and party line voters over all votes in our regression analyses. Republicans

supporting aid tend to come from districts with much higher human capital, as do Democrats

supporting trade, relative to members of their parties voting the standard party position.

<Insert Table 7 here>

Differences in support for the two issue areas suggest ways that support for

internationalism is weaker—or could become weaker—in one area as opposed to the other.

Organized labor’s opposition to free trade, and support for foreign aid, is perhaps the most

interesting difference. Elsewhere we have documented labor’s relationship to foreign aid more

closely by using records from the AFL-CIO memorial archives. While it is clear that umbrella

organizations like the AFL-CIO, which have a high profile overseas, are generally supportive of

foreign aid, it is less clear what other non-affiliated union organizations prefer (if they have

salient preferences at all). Labor’s opposition to free trade has been extensively documented

elsewhere. Money-center banks appear to be strong supporters of foreign aid, most likely because

of the complementary role of aid for private finance. They do not appear to play a role in keeping

together support for, or against, free trade.

25

There are several potential explanations for these similarities and differences. Our results

suggest that distributional consequences matter for both aid and trade (as reflected by our human

capital measure), but that the effect of ideology for trade votes is smaller. The substantive

effect—the change in probability of supporting aid or trade—of increasing the skill variable by a

single standard deviation while holding other variables at their mean values is very similar across

the two issue areas: 9.4% for aid and 8.5% for trade (using model 4 from table 5). The

substantive effect of increasing the district ideology variable by a single standard deviation (using

model 4 from table 5) is dissimilar across the two issue areas: -8% for aid and 4% for trade. Table

8 lists these substantive effects for several of our variables. Thus the substantive impact of

ideology is approximately twice as large for aid as for trade. Interestingly, the substantive impact

of our skill measure is also larger than for our ideology measure for both issue areas, though

making more thorough comparisons would require more statistical detail than space permits here.

<Insert table 8 here>

The fact that ideology has a larger substantive effect in aid than in trade also holds using

marginal effects calculations. One explanation of this is that aid policy is an explicitly re-

distributional program, and hence taps ideological motivations more centrally. The effect of our

measure of relative capital (to unskilled labor) endowments is similar across the issue areas,

though slightly higher in aid than in trade. The substantive effects of the skill variable are similar

in magnitude to those seen in studies in other issue areas (e.g., (Broz, 2005)). The substantive

effects of using Ladewig’s measures of capital and labor endowments show a slightly larger

effect in trade than in aid. Thus the effect of these district economic variables is similar across the

two issue areas. Economic interests generate a clear set of preferences regarding aid and trade;

class cleavages strongly mark the trade area but are more diluted in the aid area where they are

cross cut by ideological factors.

VI. Robustness

Our models correctly predict a very high percentage of actual votes by legislators:

between 71%-74% for trade and 74%- 76% for aid. The proportional error reduction for both

issue areas is between 29-34%.21 The accuracy of our model does not appear to be driven by our

estimation strategy or other potential misspecifications. As mentioned, our results do not change

if we use a random effects specification.

21 To do this we used the PRE post-estimation routine in STATA.

26

We find similar results if we look at our votes individually. Analyzing votes separately

and displaying results in an economical way is difficult when there are many votes under

consideration. We adopt two approaches that 1) allow us to compare the effects of our variables

across aid and trade and 2) compactly display meaningful results from the analysis of many votes.

Our first procedure calculates a probit model for each vote separately, and then takes the

marginal effect for each of the variables at its mean. The marginal effect is the slope of the line

tangent to the probability link function, here calculated at the mean of the variable. We then

calculate the 95% confidence intervals of the marginal effects. Tables 9 and 10 display these

results for two of our key variables: %HighSkill and PrezVoteRepub%. On the left hand side of

these graphs are the results for aid votes and on the right hand side are results for trade votes.

There is a relatively consistent relationship between voting and these variables, with a significant

or near significant, marginal effect in a majority of votes. For trade the effect of our district

ideology level was more mixed than with aid. In aid there was a consistent and strong negative

relationship. Here again we see how the effect of district ideology is much more salient for aid

than for trade. These tables also demonstrate how our pooling strategy does not drive our results.

<table 9 here>

<table 10 here>

These tables do not however calculate substantive effects that many political scientists

find useful. Our on-line appendix explains and presents substantive effects from looking at each

vote separately using a Bayesian strategy with non-informative priors. By using Bayesian probit

models, we generated the posterior distribution of a variable’s slope coefficient for every vote in

our sample. We then use a procedure to calculate substantive effects of variables and see if there

are changes over time.22 We use this procedure for sheer convenience in reporting the substantive

effects of a variable for many votes within one graph and in a way that also picks up our

estimation uncertainty. Analogous results would obtain using a straight MLE approach. We find

similar substantive effects to those calculated using the pooled model in table 5. We find little

change over time; that is, the significance and impact of our key variables does not systematically

22 Specifically, we used the MCMCprobit package in the MCMCpack library to obtain posterior distributions on our slope coefficients for every vote. Then we fixed all variables at their session mean and (and party at Republican if party variable included), drew the ‘jth’ observation from each of these posterior distributions of coefficients, and calculated the predicted probability of voting in favor of aid or trade. Then, we increased each of the variables by their session standard deviation one at a time and calculated the change in probability, again for all j observations from each of the coefficient posterior distributions. Finally, we subtract the jth observation when all variables are held at the mean from the jth observation when a variable was increased by a standard deviation. This leaves us with a distribution of substantive effects that incorporates our uncertainty in the estimated coefficients without having to rely on delta method approximations.

27

change over time if we estimate the results one vote at a time. Our use of a panel estimator does

not drive our results, and again our inferences would be substantively similar were we to look at

individual votes.

Another possibility is that our results might be biased by including legislators with

heterogeneous electoral incentives. Legislators with particularly secure electoral prospects might

respond to district level factors differently compared to legislators elected by very close margins.

To address this, we reran our model 6 from table 5 and excluded legislators winning by more than

a certain percentage. Our results, presented in table 11, change little and, if anything, become

stronger for several of our key variables.

<Insert Table 11 here>

We also estimated models separately by party. The skill variable is positive and

significant for both issue areas and both parties. The Ladewig measures of economic interests are

correctly signed and significant for both issue areas for Democrats, but lose significance in the

model with many district level control variables. The effect of our district level ideology variable

for aid is more significant among Republicans, whereas for trade this variable was more

significant for Democrats. The effect of the percent of foreign born variable was more significant

for Democrats than Republicans in both aid and trade, with a positive coefficient in both issue

areas. The effect of our labor and bank PAC variables remained strong and significant for both

parties and issue areas. Overall, then our results are robust when separating our sample by party,

and we provide these results in our appendix.

Religiously based ideological preferences may also relate to support for international

policy (Busby, 2007). We collected religious membership data through the Association of

Religious Data Archives at the county level, and then transformed to the district level using

geographic concordance software. Regression models including the percentage of Jewish,

Evangelical, Protestant, and Catholic adherents by district had the same results as our main

models. The Evangelical measure was negative and significant for aid and the Jewish measure

was positive and significant for trade. Including these additional controls did not change our

results. Finally, we estimated our models including votes that we classified as being ‘low

saliency’. These votes satisfied most of our selection criteria, but were not as salient in tapping

preferences for aid or trade policy. Our results barely change by including these additional votes

and we report these results in our appendix. Overall, our results are quite robust.

VII. Conclusion and future research

Trade and foreign aid are two key dimensions of American foreign economic policy, and

as such play important roles in engaging the US with the rest of the world. In this paper we have

28

taken a first step toward theoretically identifying the political groups that support American

internationalism. We show that in both areas legislators do not vote idiosyncratically or simply on

the basis of the president’s position. Nor is partisanship the best predictor of these preferences.

Legislators appear to understand the economic effects of trade and aid policies on their districts

and on their political support within them, and vote accordingly. The distributional consequences

of aid and trade as reflected in the economic characteristics of their districts seem to affect their

preferences. Their votes are also shaped by the ideological preferences that their constituents

hold. Our theories do a better job of explaining support for aid and trade than do either random

voting, party affiliation, or presidential domination models. In particular, Stolper-Samuelson

models of trade and aid preferences receive important corroboration here. The strong support for

international engagement through aid and trade policy by districts with large percentages of high

skill workers is the most striking common source of support for the two policies; given that skill

levels have been rising across the US since the beginning of our sample this seems evidence for

future support for internationalism. This economic model then helps explain commonalities in

support for internationalism that would not be revealed by other models.

We show that bipartisan support for aid and trade remain essential. Presidents must build

cross party support; they cannot expect majorities in either party to favor aid or trade. But unlike

studies which assume that the groups supporting (or opposing) internationalism are similar across

issue areas, we demonstrate that their nature differs between aid and trade. In aid this group

includes liberal Republicans and liberal Democrats who come from districts that have relatively

high levels of capital endowments (especially human capital); in addition, organized labor

supports this as does the international banking community. The surprise here, compared to trade

policy, is organized labor’s continuing support for aid, and with it liberal Democrats’. Labor and

liberal Democrats support for aid is unexpected given the Stolper-Samuelson model. Opposition

to aid is centered in districts with conservative Republicans and conservative Democrats

especially from areas with high levels of unskilled labor. Again, the economic interests model we

use does not predict Republicans’ distaste for aid. Districts that have greater support for

conservative ideology also tend to oppose aid.

In trade, economic interests play a stronger role and they pit capital against labor more,

but still this splits the parties. For trade openness, the supporting groups are conservative

Democrats and liberal Republicans who come from districts with high concentrations of human

capital, high levels of agricultural production, and locations in the Midwest and West. Opponents

of trade include liberal Democrats, primarily those from regions with low skilled populations,

labor organizations and their PACs, and, increasingly, conservative Republicans from low skill

labor districts. Support from presidents of a legislator’s party also helps to turn legislators away

29

from opposing freer trade. While party affiliation or presidential power are important elements

for explaining a legislator’s preferences vis-à-vis trade or aid, our economic and ideological

theories provide a more complete understanding of these groups’ preferences.

The groups supporting trade have also changed over time, while those supporting aid

have been quite stable. Conservative Republicans have started to oppose trade, and in their

opposition to trade and aid have become a major anti-internationalist bloc. Moderate

Republicans, while a shrinking proportion of Congress overall, remain the bulwark of support for

internationalism, as they have since World War II. Besides these changes, the groups supporting

and opposing trade seem to have been fairly stable over this twenty-five year period (1979-2004).

Examining our data by individual votes yields a very similar story to our pooled analyses,

showing little systematic change. This stability is remarkable given the momentous changes in

world and American politics during this period. The end of the Cold War, globalization, the war

on terror (although just starting as we end), the polarization of American politics, and the

increasing Republican control of Congress all mark this period and could have dramatically

changed these patterns. Our data suggest that they did not.

The groups supporting foreign aid and free trade have important, and interesting,

similarities and differences. While economic interests appear to weigh on legislators in both issue

areas (something that is consistent with what legislators, Treasury Secretaries, etc. say in the

historical records we consulted (e.g., debates, testimony)), ideology appears to play a stronger

role for foreign aid than for trade. Given the weaker distributional consequences of aid, this result

might not be surprising. Those who believe the government’s role should be minimalist do not

support foreign aid, while those with a more expansive view of the government’s role in the

economy are more supportive.

One potential implication of our analysis is that support for foreign aid would be

significantly compromised if labor began to oppose aid, just as it did with trade beginning in the

early 1970’s. While supporters can change, labor continues to play an important role in support

for foreign aid. But this support is not guaranteed. For example, in the early 1990’s several labor

groups expressed frustration with aid money going to fund export-processing zones in developing

countries. This suggests that while scholars have become increasingly interested in the influence

of Evangelical Christian groups on foreign aid (Busby, 2007), scholars—and pro-aid

politicians—should not overlook underlying support from powerful labor groups like the AFL-

CIO.

Another implication of our comparison of voting on aid and trade is that the interaction

between the executive and legislative branches can differ depending on the issue area. Thus,

scholars who make broad claims about the role of the President versus Congress in foreign policy

30

(Canes-Wrone et al., 2006; Howell and Pevehouse, 2007) may miss important heterogeneity

across issue areas. Foreign policy comprises a number of interconnected policy areas. The politics

of international engagement are not monolithic across these areas. While the President

undoubtedly plays a crucial role in the conduct of foreign policy, the Congress matters in

important ways for matters beyond military issues. Presidential dominance of the policy agenda is

not the norm in aid, though there does appear to be some influence in trade policy.

Further work remains to be done to understand support for internationalism in the US.

We have taken the most systematic steps so far towards analyzing the domestic politics around

two important areas of international engagement. Theories of political economy and ideology can

help us to explain support for internationalism in the US. They add considerably beyond party

affiliation or presidential domination to our understanding of the political dynamics of foreign

policy making in the US. These models enable us to better understand the domestic sources of

preferences for internationalism in the world’s biggest great power.

______________________________________________

Appendix 1: Variable Descriptions

Votes

All roll call votes were obtained using the Voteworld program

(http://ucdata.berkeley.edu:7101/new_web/VoteWorld/voteworld/) or (www.voteview.com) . A

vote in favor of foreign aid or free-trade was coded as a 1, a vote in opposition coded as a 0.

Money-center Bank PAC Percent

The percentage of Political Action Committee campaign contributions made to a candidate by a

money- center bank in the previous election cycle. Money center banks are classified by the

FFIEC (Federal Financial Institutions Examinations Council) report 'Country Exposure Lending

Survey' on a yearly basis. Data obtained from the FEC (ftp://ftp.fec.gov/FEC) using the

‘Contributions from Committees to Candidates’ files (‘pas’). For the 96th Congress we used data

obtained directly through the FEC or manually inputted from paper bound FEC publications.

Previous scholars have not used the FEC’s 96th Congress campaign contribution data. Some

legislator had problems in the FEC data, such as having negative amounts, have ratio’s to total

PAC’s greater than one. We exclude these few legislators, though our results do not change if we

fix these ration values at 0 or 1.

Labor PAC Percent

The percentage of Political Action Committee campaign contributions made by FEC classified

‘Labor’ organizations. Data obtained from Federal Election Commission through

ftp://ftp.fec.gov/FEC using the candidate summary files (‘cansum’).

31

Corporate PAC Percent

The percentage of Political Action Committee campaign contributions made by FEC classified

‘Labor’ organizations. Data obtained from Federal Election Commission through

ftp://ftp.fec.gov/FEC using the candidate summary files (‘cansum’).

Skill

% of district of working age (16+) in executive, managerial, administrative, and professional

occupations. Data obtained from US Census and Broz. Working age persons defined by the US

Census as the civilian workforce plus military population.

Union

% of workers unionized in the representative’s state. For 96th-105th Congresses data is from

(Adler). Data for the 106th-108th Congresses is drawn from the Bureau of Labor Statistics

(Bureau_of_Labor_Statistics, 2005).

Agricultural Production

Market value of agricultural products (livestock and crops) taken from county level data collected

by the 1978, 1982, 1987, 1992, 1997 and 2002 Census of Agriculture. Converted into 2000

constant dollars and divided by 10000. For counties that straddle Congressional Districts we use

the geographic concordance procedure described above.

Party

Political party; 0=Democrat 1=Republican; Legislators with an independent affiliation are coded

as missing.

Percentage of Two Party Presidential Vote Republican

We take the total vote for the Republican Presidential candidate and divide it by the total vote for

either the Republican or Democratic parties. Data for the 95th-106th Congresses obtained from

Joshua Clinton. Data for the 107th and 108th Congresses from www.polidata.org.

Foreign Born Percent

% of total population born in a foreign country. Data obtained from (Adler) and 108th

Congressional District Summary Files, Census of Population and Housing DVD-ROM.

Unemployed Percent

% of working age person identifying as unemployed; Data obtained from (Adler) and 108th

Congressional District Summary Files, Census of Population and Housing DVD-ROM.

Unemployment Change

Data from BLS Local Area Unemployment Statistics (http://www.bls.gov/lau/). For

each year we calculated the state’s unemployment changes from years previous. Then,

within a session, we took the average of this change.

District Median Income

32

Median household income obtained from (Adler) and 108th Congressional District Summary

Files, Census of Population and Housing DVD-ROM. Specifications in the reported models use

the natural logarithm (ln) of this variable.

Religious Data

Churches and Church Membership in the United States, 1980 and 1990. Glenmary Research

Center, Religious Congregations and Membership Study, 2000. Accessed at

http://www.thearda.com/Archive/ChCounty.asp. All data is in county format and translated to

Congressional District using the procedure used for sectoral employment data.

President Support & Same Party

Coded as a 1 if the President took a pro-aid or pro-trade position and the legislator was of the

President’s party. In our sample, the President never opposed aid or trade liberalization. Thus a 0

corresponds to the President not taking a position and/or the legislator being of the opposite party.

Table 1

-.70

.7D

W-N

OM

Mea

n

96 96 96 97 98 102

103

104

104

108

Congressional Session

Dem Supp Dem OppRep Supp Rep Opp

Mean DW-Nominate by party; Confidence intervals in dashesAid Support and Ideology

-.70

.7D

W-N

OM

Mea

n

97 98 98 99 99 100

100

100

102

102

103

103

105

105

105

105

106

106

106

107

108

108

108

108

Congressional Session

Dem Supp Dem OppRep Supp Rep Opp

Mean DW-Nominate by party; Confidence intervals in dashesFree Trade Support and Ideology

Table 2

100

150

200

Vot

es

96 96 96 97 98 102

103

104

104

108

Congressional Session

Half All Votes Dem Pro-Aid

Aid VotesDo Dems Need Republicans for Aid Support?

5010

015

020

025

0V

otes

97 98 98 99 99 100

100

100

102

102

103

103

105

105

105

105

106

106

106

107

108

108

108

108

Congressional Session

Half All Votes Rep Pro-Trade

Trade VotesDo Repubs Need Dems for Trade Support?

33

Table 3

-6-4

-20

2G

amm

aZ-S

core

-.6-.4

-.20

.2.4

Gam

ma

97 98 102 103 108 108Session

Gamma Score

Gamma/AsympStanError

Gamma Measure of AssociationLegislator Votes on Individual Trade and Aid Bills: Dems

-20

24

6G

amm

aZ-S

core

-.20

.2.4

.6.8

Gam

ma

97 98 102 103 108 108Session

Gamma Score

Gamma/AsympStanError

Gamma Measure of AssociationLegislator Votes on Individual Trade and Aid Bills: Repubs

0.2

.4.6

.81

% P

ro-A

id

96 96 96 97 98 102

103

104

104

108

Congressional Session

Republicans

Democrats

% Pro-Aid, Within Party

0.2

.4.6

.81

% P

ro-T

rade

97 98 98 99 99 100

100

100

102

102

103

103

105

105

105

105

106

106

106

107

108

108

108

108

Congressional Session

Republicans

Democrats

% Pro-Trade, Within Party

<Table 5 Below> [For Formatting Purposes]

Table 6: Presidential Support Aid No Pres Position Pres Supports

% voting anti-aid

% voting pro-aid

% voting anti-aid

% voting pro-aid

Democrats with Dem President 81 19 64 36Democrats with Rep President 83 17 55 45Republicans with Rep President 51 49 19 81Republicans with Dem President 24 76 32 68

Trade No Pres Position Pres Supports

% voting anti-trade

% voting pro-trade

% voting anti-trade

% voting pro-trade

Democrats with Dem President 19 81 56 44Democrats with Rep President 9 91 28 72Republicans with Rep President 62 38 79 21Republicans with Dem President 65 35 63 37

34

Table 7

Mean High Skill % (95% conf. Intervals) Democrat Aid Supporter .223 (.220, .226) Democrat Aid Opponent .192 (.190, .195) Republican Aid Supporter .265 (.260, .271) Republican Aid Opponent .228 (.225, .231) Democrat Trade Supporter .261 (.257, .265) Democrat Trade Opponent .228 (.226, .231) Republican Trade Supporter .276 (.273, .278) Republican Trade Opponent .240 (.237, .244)

Table 8

Variable Aid Trade Movement From Baseline Model Skill Increase by 1 SD 9.4% 8.5% BankPAC Increase by 1 SD 4.1% 0.8% LaborPAC Increase by 1 SD 21.8% -19.0% DistrictIdeology Increase by 1 SD -8.7% 4.1%

Move from Pro-trade position to no position PrezSupport 1.0% -26.2%

Estimation uses model 4 from table 5 with region set at Northeast

Table 9

-2 0 2 4 6MargEffect

aid

-2 0 2 4 6MargEffect

trade

Variables in model: HighSkill PrezVoteRepub ForBorn UnemplChangelnMdnIncm Union% Unemploy% %BlackCongressional Sessions run lower (earlier) to higher (later)

HighSkill

35

Table 10

-2 0 2 4 6MargEffect

aid

-2 0 2 4 6MargEffect

trade

Variables in model: HighSkill PrezVoteRepub ForBorn UnemplChangelnMdnIncm Union% Unemploy% %BlackCongressional Sessions run lower (earlier) to higher (later)

PrezVoteRepub

36

37

Table 11: Models by Reelection Vote Percent

Aid and Trade Votes: Panel Probit with Population Average Effects and Vote Fixed Effects (omitted), by Reelection % ---------------------------------------------------------------------------------------- aidAll aid70 aid60 tradeAll trade70 trade60 ---------------------------------------------------------------------------------------- %HighSkill 3.737** 4.116** 5.321** 3.197** 4.499** 4.632** [0.886] [0.983] [1.203] [0.625] [0.730] [0.986] BankPAC% 5.802** 5.569* 9.030** 1.262 0.876 4.189+ [1.676] [2.383] [2.526] [2.072] [2.608] [2.224] CorpPAC% 0.256 0.308 0.241 -0.323 0.0644 0.164 [0.252] [0.334] [0.467] [0.208] [0.253] [0.362] LabPAC% 2.196** 2.409** 2.534** -2.065** -1.869** -1.898** [0.212] [0.261] [0.319] [0.182] [0.202] [0.259] PrezVoteRepubl% -2.078** -1.907** -1.930** 0.679* 0.569 0.215 [0.411] [0.534] [0.718] [0.320] [0.418] [0.542] PrezSupport -0.0275 -0.147+ -0.186 0.667** 0.700** 0.729** [0.0610] [0.0838] [0.120] [0.0383] [0.0479] [0.0712] Union% 0.0109* 0.00909 0.00579 -0.00376 0.000570 -0.00553 [0.00511] [0.00607] [0.00799] [0.00467] [0.00548] [0.00683] Unemploy% -1.173 -0.872 -4.303 -0.667 -0.926 -1.527 [2.263] [2.692] [3.305] [1.409] [1.801] [2.296] UnempChg_2yr 0.0310 0.0231 -0.0562 -0.0261 0.00423 0.00183 [0.0289] [0.0351] [0.0420] [0.0240] [0.0298] [0.0442] LogMdnIncm -0.360 -0.419 -0.737* 0.0314 -0.221 -0.00674 [0.237] [0.277] [0.368] [0.203] [0.267] [0.337] %ForBorn 2.038** 1.811** 2.595** 0.868* 1.152** 1.311* [0.547] [0.626] [0.960] [0.353] [0.423] [0.585] %Black 1.065** 1.376* 2.000** 0.245 -0.308 0.0280 [0.364] [0.546] [0.588] [0.231] [0.329] [0.445] MktValAgProd -0.974 -1.080 6.199 16.95** 15.31** 27.06** [4.862] [6.423] [8.540] [4.686] [5.151] [6.996] West -0.107 -0.172 -0.189 0.502** 0.476** 0.419** [0.107] [0.118] [0.161] [0.0839] [0.0935] [0.120] Midwest -0.0588 -0.100 -0.250 0.252** 0.310** 0.300** [0.106] [0.118] [0.163] [0.0772] [0.0852] [0.110] South -0.227* -0.224 -0.386* 0.0274 0.153 0.0544 [0.114] [0.138] [0.189] [0.0931] [0.109] [0.140] Constant 2.437 2.749 6.045+ -1.262 0.469 -1.526 [2.360] [2.746] [3.670] [2.023] [2.684] [3.400] ---------------------------------------------------------------------------------------- Observations 3945 2509 1314 9765 6175 2924 ---------------------------------------------------------------------------------------- Standard errors in brackets + p<0.10, * p<0.05, ** p<0.01

Table 5: Aid and Trade Votes: Panel Probit with Population Average Effects and Vote Fixed Effects (omitted) ---------------------------------------------------------------------------------------------------------------------------------------------------------------- aid1 trade1 aid2 trade2 aid3 trade3 aid4 trade4 aid5 trade5 aid6 trade6 ---------------------------------------------------------------------------------------------------------------------------------------------------------------- %HighSkill 2.050** 3.333** 4.060** 2.576** 4.021** 3.142** 3.737** 3.197** [0.519] [0.432] [0.822] [0.633] [0.860] [0.641] [0.886] [0.625] lnCapitalEstab 0.383** 0.510** 0.292* 0.320* [0.108] [0.132] [0.124] [0.163] lnLaborManuf -0.253** -0.334** -0.187* -0.283* [0.0693] [0.126] [0.0756] [0.143] BankPAC% 5.580** 0.260 5.409** 0.940 5.819** 1.495 5.802** 1.262 5.710** 0.506 5.343** 0.414 [1.658] [1.205] [1.580] [1.904] [1.618] [2.271] [1.676] [2.072] [1.730] [1.388] [1.713] [1.432] CorpPAC% 0.0352 -0.420* 0.205 -0.469* 0.294 -0.330 0.256 -0.323 0.0891 -0.382* 0.231 -0.432* [0.240] [0.196] [0.250] [0.207] [0.251] [0.211] [0.252] [0.208] [0.237] [0.194] [0.248] [0.195] LabPAC% 2.472** -2.387** 1.342** -1.659** 1.313** -1.572** 2.196** -2.065** 2.447** -2.434** 2.150** -2.240** [0.197] [0.161] [0.226] [0.200] [0.228] [0.204] [0.212] [0.182] [0.196] [0.162] [0.207] [0.172] party -0.828** 0.432** -0.854** 0.431** [0.0879] [0.0743] [0.0876] [0.0727] PrezVoteRepubl% -2.078** 0.679* -1.998** 1.316** [0.411] [0.320] [0.403] [0.299] PrezSupport -0.0729 0.640** -0.0806 0.646** -0.0275 0.667** [0.0679] [0.0389] [0.0682] [0.0399] [0.0610] [0.0383] Union% 0.0256** -0.00503 0.0147** -0.00533 0.0109* -0.00376 0.0139** 0.00114 [0.00447] [0.00396] [0.00526] [0.00483] [0.00511] [0.00467] [0.00438] [0.00376] Unemploy% 0.0915 -0.667 -0.256 -1.085 -1.173 -0.667 -2.542 -0.442 [2.008] [1.353] [2.061] [1.434] [2.263] [1.409] [2.172] [1.396] UnempChg_2yr 0.0200 -0.0171 0.0312 -0.0284 0.0310 -0.0261 0.0247 -0.0239 [0.0291] [0.0237] [0.0292] [0.0247] [0.0289] [0.0240] [0.0287] [0.0231] LogMdnIncm -0.214 -0.0991 -0.338 -0.00931 -0.360 0.0314 0.223 0.444** [0.218] [0.184] [0.233] [0.200] [0.237] [0.203] [0.183] [0.158] %ForBorn 2.403** 0.688* 2.363** 0.760* 2.038** 0.868* 1.798** 0.561 [0.504] [0.327] [0.516] [0.345] [0.547] [0.353] [0.573] [0.375] %Black 1.316** -0.398* 1.424** 0.119 1.065** 0.245 1.221** 0.0363 [0.269] [0.186] [0.303] [0.200] [0.364] [0.231] [0.346] [0.225] MktValAgProd -3.665 17.83** -0.974 16.95** [5.110] [4.734] [4.862] [4.686] West -0.213* 0.557** -0.107 0.502** [0.108] [0.0863] [0.107] [0.0839] Midwest -0.132 0.286** -0.0588 0.252** [0.107] [0.0784] [0.106] [0.0772] South -0.434** 0.126 -0.227* 0.0274 [0.117] [0.0921] [0.114] [0.0931] Constant -1.641** -0.655** 0.749 0.690 2.882 -0.724 2.437 -1.262 -1.377 -0.598 -2.711 -5.229** [0.171] [0.151] [2.174] [1.822] [2.362] [2.036] [2.360] [2.023] [0.930] [0.706] [1.998] [1.600] ---------------------------------------------------------------------------------------------------------------------------------------------------------------- Observations 3948 9774 3944 9751 3941 9751 3945 9765 3948 9774 3948 9765 ---------------------------------------------------------------------------------------------------------------------------------------------------------------- Standard errors in brackets + p<0.10, * p<0.05, ** p<0.01 Models estimated using the xtprobit command with the pa (population average) and robust extensions. This is equivalent to running xtgee with a Bernoulli family and probit link with robust standard errors and exchangeable correlation matrix.

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