Would NAFTA have been approved by the House of Representatives under President Bush?

Presidents, parties, and trade policy

Christopher S. P. Magee1

Abstract

This paper examines five trade policy votes in the United States House of Representatives, one

during each of the last five presidential terms. The paper investigates the determinants of representative

voting and shows that Congress members are more likely to support trade liberalization if the President is

a member of their own party. The estimation allows a prediction to be made of the likely House trade

votes under alternative presidential election outcomes. The model predicts that the probability of NAFTA

being approved would have been greatly reduced by a victory for President Bush (41) in the 1992

election. Neither the trade promotion authority granted to President Bush (43) in 2001 nor the CAFTA

signed in 2005 would likely have been approved under Democratic Presidents.

1 Department of Economics, Bucknell University, Lewisburg, PA 17837; cmagee@bucknell.edu; phone (570) 577-1752; fax (570) 577-3451. I would like to thank James DeVault, Gene Grossman, and participants at the August 2005 Columbia University Conference in honor of Jagdish Bhagwati for helpful comments on an early draft.

1

1. Introduction

The North American Free Trade Agreement (NAFTA) was negotiated under President George

H.W. Bush (41) and formally signed in December 1992. President Bush had lost the November 1992

election, however, so it was left to his successor, President William J. Clinton, to gain approval of the

agreement from a skeptical Congress. President Clinton launched a vigorous effort to gain support in

Congress for the agreement, and ultimately it was approved by 17 votes in the U.S. House of

Representatives and more easily in the Senate in November 1993.

Would the NAFTA have been approved by the United States House of Representatives if George

Bush (41) had won the 1992 election instead of Bill Clinton? The agreement faced a tough battle in the

House (a late September 1993 poll of House members found 190 representatives opposed and 161 in

favor) and President Clinton’s lobbying efforts were widely seen as an important part of securing passage

(the Congressional Quarterly Almanac (1994, pp. 171-178) describes his campaign to pass the bill).

Despite vocal opposition to NAFTA by two of the three ranking Democrats in the House and only

lukewarm support from the other, 40 percent of Democrats (102 representatives) eventually voted to

approve the trade deal. Would so many have supported it if the presidential lobbying efforts had come

from a Republican? If not, a Republican President would have needed to make up the votes by

convincing Republicans opposed to the NAFTA to support it in order to pass the agreement, but there

were only 44 such Republicans in the House. Thus, it seems likely that NAFTA would have had less

support in the House in 1993 under President Bush than it enjoyed under President Clinton.

A similar situation emerged in 2001. President George W. Bush (43), who had just narrowly won

election in 2000, asked Congress to grant him trade promotion authority (formerly called fast-track

negotiating authority) to negotiate new regional trade agreements. Despite Republican control of the

House of Representatives and overwhelming support among Republicans, the trade bill passed by the

narrowest of margins, 215 – 214. The prominent trade deal negotiated using the trade promotion

authority, the Central American Free Trade Agreement (CAFTA), then passed the House in 2005 by only

217 – 215. Would the Republican majority in the House of Representatives have pushed so hard to give

2

the negotiating authority to a Democratic President Gore or for CAFTA to be signed by a President

Kerry?

This paper investigates the determinants of Representatives’ voting on five trade bills, one in each

of the last five presidential terms. Three of the bills, in 1991, 1998, and 2001, gave the sitting President

the ability to negotiate new trade agreements under a fast-track procedure in which the Congress could

vote the trade deal up or down but could not make amendments to it. The two other votes were for

approval of the NAFTA in 1993 and the CAFTA in 2005. All the bills primarily concerned new regional

agreements with countries in Latin America. The 1991 fast-track vote became a referendum on NAFTA

and one of the important considerations at the time of the 1998 vote was whether to add Chile to the

NAFTA bloc. The 2001 trade promotion authority vote allowed negotiation of the Central American Free

Trade Agreement. The 1993 and 2005 votes to approve NAFTA and CAFTA differed from the other

votes in that the terms of the agreements were known at the time of the votes but legislator decisions were

made in largely the same way on each of the votes. In the fast-track bills, representatives voted based on

what they expected the agreements to be while in the bills approving each trade deal they voted based on

what they observed the agreements to be.

Perhaps the most robust result in the paper is that representatives are much more likely to support

bills approving trade deals or authorizing new trade negotiations if the President is a member of the same

party. Figure 1 illustrates the partisan difference graphically. Republican support for granting the

President fast-track negotiating authority was 87 percent under President Bush (41) in 1991 and 89

percent under his son in 2001. The 2005 CAFTA also received similar support under President Bush

(43). During the Clinton presidency, however, only 75 and 68 percent of Republicans, respectively, voted

in favor of the 1993 NAFTA bill and 1998 fast-track bill. Thus, support among Republicans for the trade

bills was 71 percent during the Democratic administration and 88 percent during the Republican

administrations, a difference that is statistically significant at the 1 percent level. The Democrats in the

House show a similar but less pronounced pattern. Democratic support for the trade measures rose by

five percentage points when President Clinton entered office in 1993 and then fell by five percentage

3

points when he left office and was replaced by President Bush (43) in 2001. This result mirrors the

conclusion of Epstein and O’Halloran (1999) that Congress members are more likely to vote to delegate

authority to the executive branch when the President is a member of the representative’s party. An

implication is that divided government makes trade liberalization less likely to be enacted.

As a result of the President’s greater ability to command trade votes from House members who

belong to the same party, Republican and Democratic Presidents will have different capacities to push

trade measures through the U.S. House of Representatives. This paper asks whether the outcome of the

trade bills shown in Figure 1 have been different had the other party won the presidency. The results

suggest that two of the five trade policy votes (the 2001 fast-track and the 2005 CAFTA) would probably

not have passed had the previous presidential election outcome been reversed. The 1993 NAFTA vote

would also have been placed in greater danger of defeat by a reversal of the 1992 presidential election.

The next section describes the literature examining congressional votes on trade policy. Section

three then discusses studies that investigate why Congress members are more likely to vote in favor of

bills supported by a President of their own party. The data and the empirical model used to test the

relationship between the President’s party and congressional trade votes are described in section four.

Section five then presents the results of the estimation while the final section concludes.

2. Literature on congressional votes and trade policy

In 1991, the House and Senate passed bills giving President Bush (41) fast-track negotiating

authority to submit any completed trade deals to Congress for an up-or-down vote without amendments.

As Kahane (1996a) describes, while the fast-track bill was important for the GATT Uruguay Round

negotiations, the political debate over it largely focused on the merits of the proposed North American

Free Trade Agreement. Kahane runs a probit regression on the 1991 fast-track vote in the Senate and

finds that labor contributions, a strong union presence, and expected state job losses from NAFTA are

correlated with votes against the fast-track bill. Kaempfer and Marks (1993) also examine the

determinants of House voting on the bill, and they find that representatives were more likely to support

4

fast-track negotiating authority if they came from high wage districts with few workers in the textile and

apparel industries, and if they received relatively little in the way of labor union campaign contributions.

A number of papers have examined the 1993 NAFTA vote in the House. Steagall and Jennings

(1996) find that NAFTA voting depended on whether the representative came from a right-to-work state,

the percentage of his total contribution receipts that came from labor PACs, from business PACs, from

energy PACs, and from PACs overall. Kahane (1996b) employs a similar econometric model and finds

that labor contributions were correlated with votes against NAFTA in the House but not in the Senate. He

also finds that Northern (but not Southern) Democrats were more likely than Republicans to vote against

NAFTA, as were representatives from states that had high unemployment rates and that were expected to

lose jobs as a result of NAFTA. Both papers, however, treat contributions as exogenous to the

representative voting decision. Baldwin and Magee (2000a) use a simultaneous equation model to control

for the endogeneity of contributions and find that labor money is still strongly correlated with votes

against NAFTA while corporate contributions are correlated with votes in favor of NAFTA. The

politician’s ideology, the relative importance of exporting jobs in the district, union membership rates,

and the district education levels were also important influences on a representative’s votes.

The effect of President Clinton’s lobbying efforts in favor of NAFTA is examined in Uslaner

(1998). He finds that President Clinton was much more likely to meet with House Democrats than with

Republicans in an effort to persuade them to vote for NAFTA – he met with 27 percent of House

Democrats in 1993 between August 3 and the November 17 vote while meeting with only 10 percent of

Republicans. The meetings with Democrats were also more fruitful – Democrats who were contacted by

Clinton were 62 percent more likely to support NAFTA than those not contacted, while Republicans

contacted actually became less likely to support NAFTA.

Baldwin and Magee (2000b) examined the 1998 fast-track vote in the House and found that many

of the same factors influencing the NAFTA vote remained important five years later. Labor and business

contributions, ideology, unions, education levels, and exporting jobs in the district all continued to be

significant factors affecting voting decisions.

5

3. Theory on Presidents, party, and congressional votes

Since 1934, Congress has delegated much of its authority to the executive branch in setting trade

policy by restricting its own ability to offer amendments to trade negotiated by the executive. Epstein and

O’Halloran (1999) discuss how a “hold-up problem” plagues any delegation of authority. Congress is

willing to delegate authority to the President if it believes that he will use his authority to enact policies

favorable to Congress. In order to get authority, Presidents are willing to promise Congress that he will

act in their interests. Once he gets authority, however, the President has an incentive to choose policies

that promote his own political interest rather than those of Congress. The President cannot fully commit

ahead of time to choose policies favorable to Congress rather than himself, and thus representatives are

reluctant to cede authority.

Trade policy faces the hold-up problem on two levels. First, without delegating authority,

Congress cannot credibly commit not to change the terms of a trade agreement after it has been

negotiated. Foreign governments are unwilling to enter into negotiations without such a commitment.

Thus, in order to secure new trade deals, Congress binds its own hands by delegating fast-track

negotiating authority to the executive branch and establishing the rule that the final agreement must be

voted on without amendments. The cost of delegating authority for a representative is likely to be higher

the farther the President’s policy preferences are from the representative because the executive branch

makes the many small decisions and compromises that shape the trade agreement. Party membership is a

good indicator of policy preferences, and thus the cost of delegating authority is smaller for

representatives who are members of the President’s party. Epstein and O’Halloran (1999) find support

for this prediction: legislators who are members of the President’s party vote in favor of delegating

authority more often than members of the opposition party.

Persson and Tabellini (2000) also present a model in which the different branches of government

interact to determine policy outcomes. In their model, the power to propose legislation gives the agenda-

setter the ability to push policy outcomes in his or her preferred direction. In trade policy, the executive

6

branch is the agenda-setter once Congress has granted it trade promotion authority. The President then

wants to negotiate a trade agreement as close as possible to his or her own personal preferences while still

putting together a winning coalition in Congress. Since party and policy preferences are so closely

related, a Democratic President will negotiate a trade agreement that brings more Democratic

representatives into the minimum winning coalition than a Republican President will.

Another possible reason why the President’s party might matter in House votes on trade policy is

that the President may be more willing or able to trade concessions on non-trade matters for a favorable

trade policy vote if the representative is in the President’s party. According to Grayson (1995), there

were 47 representatives who received special benefits from President Clinton in exchange for voting for

NAFTA in 1993. These included 29 Democrats (11 percent of all Democrats in the House) and 18

Republicans (10 percent of all Republicans). Thus, the negotiations over the NAFTA vote do not provide

any strong evidence that horse-trading for trade policy votes takes place primarily within the President’s

party. Finally, voter perceptions of the President may influence their decisions about which candidate to

support for House and Senate races. If so, representatives have an incentive not to give political points to

a President of the opposition party or to inflict political damage to a President of their own party.

4. Data and model

Representatives’ votes on important bills depend on constituency pressures, interest group

lobbying, and the personal preferences of the Congress member. This paper includes several variables

measuring the trade preferences of constituencies. Since the bills involved expanding trade preferences

for Latin American countries, the percentage of citizens in each district who are Hispanic may influence

the district views on the trade bills. Trade liberalization will tend to reduce U.S. wages for low-skilled

workers in the long run according to the Stolper-Samuelson theorem, and thus the paper includes district

per-capita income and the percentage of citizens over 25 years of age without a high school degree.

Labor unions in the United States have been strongly opposed to regional trade liberalization for the past

several decades, so union membership among the constituency may also affect representatives’ voting

7

decisions. The labor union variable measures the state union membership percentage among all workers

and is described in Hirsch and Macpherson (2003).

The education, per-capita income, and Hispanic percentage variables are taken from the 1990 and

2000 Censuses for each congressional district. Census information from 2000 was used for the 2001 and

2005 votes, although the values in the data set changed because of redistricting between these years. For

the 1991, 1993, and 1998 votes, a weighted average of the two censuses, based on how close the vote was

to 1990 and to 2000, was used. For the 1993 vote, for example, the per-capita income variable is a

weighted average of the 1990 and 2000 district per-capita incomes, with the 1990 value receiving seven-

tenths of the weight and the 2000 value receiving three-tenths of the weight.

If job skills are sector-specific, then workers in exporting industries will tend to favor

liberalization while those in import-competing industries oppose it. Thus, trade votes are allowed to

depend on jobs in exporting industries relative to jobs in exporting and import-competing industries in the

district. To control for other characteristics of the workers in a district, the estimation also includes the

fraction of manufacturing employees in each of 19 different 2-digit SIC industries. These variables were

measured by mapping County Business Pattern employment data into districts based on the fraction of

each county’s population that resided in the congressional district. There was a change in industry

classification systems between 1993 (which used SIC codes) and 1998 (which used NAICS codes). For

1998, 2001, and 2005, then, the NAICS were mapped into SIC industries.2 Because of the change in how

these variables were measured, the yearly variation in the employment variables was removed before

including them in the regression.

The ideology and personal views of representatives are controlled for by including a party

variable and the interest group ratings of each Congress member from the American Conservative Union

(ACU), the Chamber of Commerce (COC), and the AFL-CIO. These ideological ratings show the

percentage of times in which the representative voted in the manner favored by the interest group on key

votes. Some groups include the trade votes in their ratings. To prevent the trade vote from affecting the

8

ideological variables in the model, each representative’s rating comes from the alternative year in the

congressional session, so that the ratings used in the 1991 vote were from 1992, and those used for the

1998 vote came from 1997. Since the 2006 ratings are not available at the time of this writing, the 2005

ideology measures are defined as the percentage of times the representative votes in the interest group’s

preferred manner on the non-trade votes in 2005. The educational attainment of the representative may

also influence his or her personal preferences on trade policy, so two dummy variables are included that

indicate whether the Congress member has a college degree and whether she has an advanced degree.

Unobserved variables specific to the time period and the trade bill in question may also affect

representatives’ votes. In 1998, for instance, representatives may have been reluctant to support President

Clinton while he was tarnished by the Monica Lewinsky scandal. Representatives may also have been

more reluctant to approve a final trade agreement than to give the President negotiating authority since in

the latter case, a second yes vote would be needed to change existing trade rules. Thus, the model

includes year dummy variables to control for any unobserved but time or vote-specific factors that affect

all representatives.

The argument made in this paper is that even after controlling for interest group pressure and for

all of the variables described above, which measure the factors traditionally examined in voting analyses,

the party of the President will influence how representatives vote. In order to measure this effect, the

model includes an extra variable that equals one if the President is of the same party as the representative

during the year the vote takes place. Thus, the variable equals one for Republican representatives in

1991, 2001, and 2005, and it equals one for Democratic representatives in the 1993 and 1998 votes.

Interest group lobbying is measured in this paper, as in most others, through campaign

contributions taken from the Federal Election Commission. In the long run, trade liberalization will help

capital-owners and hurt workers in the U.S, while in the short run, exporting industries will benefit while

import-competing ones are harmed. This paper includes contributions from corporate PACs (representing

capital-owners) and labor PACs. Beaulieu and Magee (2004) find strong evidence that corporate PACs

2 The NAICS-SIC concordance is available upon request from the author.

9

favor regional trade liberalization while labor PACs oppose it. They find much smaller differences,

however, between PACs from exporting industries and those representing import-competing industries.

One complication is that interest groups are likely to give campaign contributions to

representatives already predisposed to favor the position taken by the interest group. Labor groups, for

example, want to help candidates who are opposed to regional trade liberalization win election. As a

result, running a simple OLS regression of trade votes on campaign contributions provides biased

estimates of the impact of contributions on votes since the contribution variables are correlated with the

error term. This paper provides two different approaches to solving the problem of endogenous

contribution variables. The first is to estimate a voting equation that includes a fixed effect for each

representative. These fixed effects capture any unobserved characteristics (that are constant over time)

that make the representative more or less likely to vote for the trade bills. The estimated equation is

(1) itititititiit )con_Lcon_CPres_SameX'(Fvote εββββα +++++= 321 ,

where 1=itvote if representative i votes for the trade bill in time t, 1=itPres_Same if the President is a

member or representative i’s party in time t, itcon_C and itcon_L are corporate and labor

contributions, and itX is a vector of other variables that affect the trade votes. Including the fixed effects

for each representative ( iα above) means that equation (1) can only be estimated for those

representatives who change their trade vote at least once. There are 484 votes by representatives who

switched their position on the trade bills at least once during this time period.

A second way of getting consistent estimates of the determinants of trade votes while treating

contributions as endogenous is to set up a system of equations as in Chappell (1982).

(2) it,vititititit )con_Lcon_CPres_SameX'(Fvote ε+β+β+β+β= 321

(3) it,citit Z'con_C εα +=

(4) it,litit Z'con_L εδ +=

10

In order to identify the system, there need to be variables in the vector itZ in equations (3) and (4) that

are excluded from the explanatory variables in equation (2). The excluded variables are instruments that

identify the effect of contributions on voting decisions, and they should be strongly correlated with

contributions but not affect representatives’ votes on the trade bills. The instrumental variables used in

this paper are the number of terms in office, the age of the representative, and whether she was on the

Ways and Means Committee or Labor Committee, an incumbent in the last election, or the chair or

ranking member of one of the House committees. Party variables, interest group ideological ratings, and

year dummy variables are also included in both the contribution equations and the voting equation. An

observation is a representative in a particular year, and thus there are 2175 observations (435

representatives and five trade votes). After omitting representatives who did not vote on the trade bills or

are missing variables, there remain 2135 observations with full information.

The question that motivated this paper is what would have happened to the NAFTA and the other

trade policy votes if there had been different presidential election outcomes. The estimates of equations

(1) and (2) provide a way of answering that question. Both models give a predicted probability of voting

in favor of the trade bill for representative i:

(5) )con_Lˆcon_CˆPres_SameˆX'ˆ(Fv̂ ititititit 321 β+β+β+β= .

Summing this probability over all representatives in office at the time yields the total predicted votes in

favor of the measure. Thus, the predicted fraction supporting the bill (out of N total votes on the

measure) is

(6) ∑=i

itv̂N

portsupoffractiondictedPre 1 .

If the previous presidential election had gone the other way, the predicted probability that representative i

would support the trade bill would be

(7) )con_Lˆcon_Cˆ)_PresSame(ˆX'ˆ(Fv̂ itititit'it 321 1 β+β+−β+β= .

11

Again, summing over all representatives would generate the counterfactual predicted number of yes votes

under an alternative presidency.

(8) ∑=i

'itv̂

NportsupoffractiondictedpretualCounterfac 1 .

In calculating the predicted votes and probabilities the bill will pass under an alternate President,

the assumption is made that only the President’s party is changed, while all else is held equal. This

assumption may be incorrect if the President pushes for passage of the bill at the smallest possible

political cost and thus tries to convince just barely enough representatives to support the measure. In that

case, the probability of the trade bills passing under a different President may be higher than the estimates

in this paper indicate because the President might be able to persuade a few more representatives to

support a trade act if a change in circumstances made their votes needed to secure its passage.

Table 1 presents the definitions, sources, and means of all the variables used in the model. The

first few rows reveal the average support for each of the trade bills. As the table shows, there was

considerable support for the 1991 fast-track negotiating authority and then for passage of the NAFTA

agreement in 1993, with both bills passing with about 54 percent of the vote in the House of

Representatives. The support for the regional trade agreements drops off after 1993, however, as the

1998 fast-track bill failed with only 42 percent of the vote and the 2001 bill passed by the narrowest of

margins (215 votes in favor and 214 votes opposed). The drop in support for the trade bills was most

prominent among Democrats, as Figure 1 shows. While 40 percent of Democrats voted for NAFTA in

1993, only 15 percent voted for the 1998 fast-track bill, 10 percent voted for the 2001 trade promotion

authority bill, and 7 percent for CAFTA in 2005. There was a small drop in support for the trade bills

among Republicans between 1993 and 1998, but by 2001 their support had surged back to 89 percent, and

it remained at 88 percent for CAFTA.

For each of the explanatory variables, Table 1 presents the mean values separately for the

representatives who voted for and against the trade bills. The symbol “≠” indicates that the means are

significantly different between the two groups of representatives. The table shows that there are large

12

differences between the representatives who voted for the trade bills and those who voted against. The

trade bill supporters tend to be Republicans who are rated highly by conservative and business groups but

not by labor unions. They also get large amounts of money from corporate PACs but relatively little from

labor PACs. The latter result could be either because the PACs give their money to representatives who

are already in favor of the PAC’s favored policy position or because the money helps the interest group to

convince the representative to vote a certain way. As Figure 1 showed, Congress members in the party of

the President are more likely to support the trade bills than are representatives in the opposition party.3

5. Results

Table 2 presents a simple comparison of trade policy votes and three party variables: one that

indicates whether or not the President is in the same party as the representative, a second that indicates the

representative’s party, and a third that indicates whether the representative’s party holds a majority of

seats in the House of Representatives. The estimates show that a representative is significantly more

likely to vote in favor of the trade bills if he is a Republican, is in the majority party in the House, and if

the President is in the same party. These variables are strongly correlated with trade votes. The

coefficients in the final column mean that Republicans are 59 percentage points more likely to support the

trade bills than are Democrats. Being in the majority or in the President’s party raises the probability of

voting for the trade bill by 16 percentage points. All coefficients are statistically significant.

Table 3 presents the results of estimating equation (1), which controls for unobserved

characteristics of the representatives affecting their trade policy stances by including politician fixed

effects. Because the voting equation is nonlinear, the column entitled “marginal effect” reveals the

impact that a unit change in the X variable has on the probability of a yes vote when all of the other

explanatory variables are at their mean values. One complication in the estimation is that the

observations may not be independent. Representatives who wish to see a trade act pass and thus would

3 Even if one considers only the first four trade votes (two under Democratic Presidents and two under Republicans), representatives in the President’s party are ten percentage points more likely to support the trade bill.

13

support it if their vote is going to be decisive may nonetheless want to vote against the act for political

reasons if their vote is not decisive.4 In such a situation, individual votes depend on the votes cast by

others. To correct for this correlation between observations, the standard errors are calculated using the

Huber/White/sandwich estimator.

There are several surprising coefficient estimates in Table 3. First, corporate contributions are

negatively associated with the trade vote, so an increase in money a politician receives from corporate

PACs actually reduces the likelihood she votes for the trade bills. Labor contributions do not

significantly affect trade votes, but greater state union strength is estimated to increase the probability that

a politician supports the trade bills. These results are not robust to changing the model specification.

Less surprising is the significant negative coefficient on the No High School Degree variable,

which means that representatives with a less-educated constituency are likely to oppose the trade bills. Of

the ideological variables, only the chamber of commerce rating significantly affects trade votes.

Representatives from districts with more jobs in exporting industries and fewer jobs in import-competing

industries are also more likely to support the trade bills.

The variable with the largest impact on trade votes in Table 3 is the indicator for whether or not

the President is a member of the representative’s party. The estimates indicate that representatives who

are in the President’s party are 56 percentage points more likely to vote for the trade bills than are

representatives of the opposition party, all else equal. An average Representative is predicted to vote for

the trade bills with a 74 percent probability if she is in the same party as the President, but an opposition

party member has only an 18 percent probability of supporting the trade bills. Thus, Table 3 strongly

supports the theoretical prediction that representatives in the President’s party are more likely to approve

of trade deals negotiated by the President or to delegate authority to negotiate new trade deals.

Table 4 presents the results of estimating equations (2) – (4) by full-information maximum

likelihood. The first columns shows the results of estimating the voting equation (2), while the columns

4 During the House voting on CAFTA, for instance, there were negotiations among a group of Republicans who each wanted to vote “no” but who had agreed that they would muster enough “yes” votes to pass the act.

14

labeled “Corporate contributions” and “Labor contributions” estimate equations (3) and (4) respectively.

Unlike the estimates in Table 3, the results in Table 4 indicate that corporate contributions are

significantly and positively correlated with votes in favor of the trade bills while labor money is

negatively correlated with the trade votes. One explanation for the different results is that the regressions

use different samples of legislators. The fixed-effects estimation can only include observations in which a

representative changes his or her vote on the trade bills at least once during the period. This restriction

reduces the sample size to 484 in Table 3 compared to the 2135 observations in Table 4. The smaller

sample shows no significant correlation between the trade votes and either contribution variable, even

when an OLS regression is estimated without fixed effects. When this same regression is estimated using

all 2135 observations, however, the coefficient on corporate contributions is significantly positive and the

coefficient on the labor contribution variables is statistically significant and negative, with magnitudes

similar to those in Table 4. Thus, a significant relationship between contributions and trade votes exists

only among those representatives who do not change their policy stance. This result supports the

argument that votes are not bought and sold on a quid pro quo basis, but rather that contributions, or a

long series of contributions as Snyder (1992) argues, give interest groups access to representatives and a

chance to convince the legislator that a certain policy stance is preferable. Once that persuasion has taken

place, there is no evidence in the data here that representatives will later switch policy positions in

exchange for a surge of campaign money.

Most results in Table 4 are similar to those in Baldwin and Magee (2000a). Large Hispanic

populations are correlated with votes in favor of the trade bills, while representatives with less educated

and more unionized constituencies are less likely to support the trade measures. Representatives who are

rated highly by the Chamber of Commerce and poorly by labor unions and conservative groups (all else

equal) are more likely to support the trade bills.

15

One interesting new result is that Congress members with advanced educational degrees are more

likely to vote for the trade bills, all else equal.5 This result suggests that politicians are not purely

captives of their interest groups and constituencies. Instead, their personal preferences appear to have

some influence on their policy decisions. The declining support for regional trade liberalization in the

House of Representatives is evident in the coefficients on the year dummy variables. Holding the other

determinants of voting constant, an average representative was 34 percentage points less likely to vote for

NAFTA in 1993 than she was to vote for the 1991 fast-track bill authorizing the negotiation of NAFTA,

and she was between 45 and 49 percentage points less likely to vote for the later trade bills. The 1998

year dummy variable has the largest negative coefficient in both Tables 3 and 4, which might be evidence

of a “Monica effect” that reduced support for the President’s policies among all representatives.

As in Table 3, being in the President’s party significantly increases the chance a representative

will vote for a trade bill. A typical representative was 23 percentage points more likely to support the

trade measures during years when his party controlled the executive branch than he was during other

years. That difference is much larger than the difference between a typical Democrat and Republican.

Changing the partisan control of the presidency is equivalent to a change of $129,000 in labor

contributions or $205,000 in corporate money to a typical representative. Thus, both Tables 3 and 4

suggest that the presidential party variable has a very strong and robust effect on representative voting.

The role of the President cannot explain much of the large decline in Democratic support for the

trade bills during 1991 – 2005, however, since the biggest drop occurred between 1993 and 1998 while

President Clinton was in office. The decline among Democrats during these years is more plausibly

explained by the fact that the party lost control of Congress and became much more reliant on labor

unions for campaign contributions. Whereas labor and corporate contributions were roughly equal for

Democrats in 1993, labor money was 60% greater than corporate money in 1998. The shift to Republican

administrations in 2001 and 2005 provides a more compelling explanation for the continued drop in

5 The representative education variables could not be included in the fixed effect estimation because the fixed effect captures the influence on trade votes of any representative characteristics that are constant over time.

16

Democratic support for the trade bills in those years, however, because labor contributions became

relatively less important for Democrats between 1998 and 2005. Thus, both increased influence by

organized labor over the party’s trade policy and the control of the Presidency help explain the trend

among Democrats against regional agreements between 1991 and 2005.

The estimates from the contribution equations provide sensible results. Representatives on the

Ways and Means committee ($48,000 extra), who are the chairs or ranking members of committees

($59,000), and who are members of the majority party ($27,000) get more money from corporations than

does the typical House member. Incumbents, those with many terms of seniority, and representatives

rated highly by the Chamber of Commerce and the American Conservative Union also are favored by

corporate PACs. Surprisingly, corporate PACs gave more money to a Democrat than to an equivalent

Republican. Labor unions gave more money to members of the labor committee, to Democrats, to the

chairs and ranking members of committees, and to representatives who had few terms in office. Young

representatives get more money from both corporate and labor groups. This result is consistent with

Snyder (1992), who argues that PACs want to concentrate their money on young representatives who will

be in office a long time. While there is a clear trend upward in real contributions, being in the same party

as the President does not significantly influence a representative’s receipts of either corporate or labor

money. The independent variables explain about 30 percent of the variation in corporate contributions

and about 53 percent of the variation in labor money. Having good instruments in the model is important

because Staiger and Stock (1997) show that coefficient estimates may be biased if the instruments have

poor predictive power (a commonly used benchmark is 10<F ). Tests of the instruments in Table 4,

however, provide highly significant Wald statistics of 509=F (corporate) and 66F = (labor).

Table 5 presents the results from equations (6) and (8), which allow a comparison of predicted

vote support under alternate Presidents. The top half of Table 5 uses the voting equation coefficient

estimates in Table 4 while the bottom half of Table 5 is based on the fixed-effect estimates in Table 3.

The first column presents the fraction of representatives who actually supported the bill, and the second

column shows the predicted fraction based on equation (6). With a large sample of representatives, the

17

mean expected support for the bills will have approximately a normal distribution according to the

Central Limit Theorem. Thus, the predicted fraction of support in column 2 and a standard error of this

prediction6 can be used to estimate the probability that more than 50 percent of the voters support the bill.

These probabilities that the bills will pass are presented in column 3. The last two columns of the table

show the predicted levels of support and probabilities that the bills would pass under a President of the

other party.

For the 1991 fast-track bill, 55.9 percent of the representatives were predicted to support the

measure, which meant that it had nearly a 99 percent chance of passing the House. Had there been a

Democrat as President in 1991, all else been equal, the model predicts that 63 percent of representatives

would have supported the bill, and it would have passed with near certainty. Since there was a sizable

Democratic majority in the House, a Democratic President Dukakis would have gained more votes among

Democrats than he would have lost among the relatively fewer Republicans.

The 1993 NAFTA vote is more interesting. The model predicts that the NAFTA would receive

54 percent of the vote and have a 95 percent chance of passing. If President Clinton had lost to President

Bush (41) in 1992, however, the model predicts that support for the agreement would have dropped to

only 50.7 percent. With this predicted vote share, the NAFTA is given less than a 60 percent chance of

being approved during a second Bush term in the early 1990’s.

The 1998 fast-track bill failed to pass the House by a large margin, as less than 43 percent of

representatives supported it. The model predicts that a Dole presidency (combined with the Republican-

controlled House) would have increased its chances of being approved only slightly, to 7 percent.

The 2001 fast-track measure passed by only one vote, but the model over-predicts its chances

slightly, giving it a predicted 50.6 percent of the vote and a 58 percent chance of being approved under

President Bush (43). In a counterfactual Al Gore presidency, the predicted support in the House drops to

less than 49 percent of the representatives and the model estimates that it would have had a 38 percent

6 The standard errors were estimated using a bootstrapping technique in which the data set was re-sampled 1000 times, and the model was then re-estimated and used to generate predicted fractions of support for each bill.

18

chance of passing. The 2005 CAFTA vote is also predicted to have been defeated had President Bush

(43) not won reelection in 2004. The probability of its being approved drops from over 61 percent under

President Bush to 39 percent under a Democratic President Kerry.

The conclusion that different presidential election outcomes in 1992, 2000, or 2004 would have

significantly reduced the chances of passage for NAFTA in 1993, trade promotion authority in 2001, and

the CAFTA in 2005 is quite robust to changes in model specification. The bottom half of Table 5

presents estimated probabilities these bills will pass based on the fixed-effect model in Table 3. Since the

fixed-effects model includes only those representatives who changed trade votes, the predictions are

based on a smaller subset of politicians. They confirm the results described above, however, showing

significant declines in the likelihood that the NAFTA, 2001 trade promotion authority, and CAFTA trade

bills would pass the House had the previous presidential election outcomes been reversed. Thus, of the

four bills that were approved either enacting new trade deals or allowing them to be negotiated under the

fast-track procedure, three of them (the NAFTA and CAFTA approvals and the 2001 trade promotion

authority vote) would have had significantly reduced chances of being approved had the previous

presidential elections gone the other way.

Looking at all five votes, it is clear that the chances of trade deals passing are higher under

unified government. In each vote simulation, the number of expected votes rose when the presidency

moved to the party that was in the majority for the simple reason that there were more legislators the

President could influence in favor of his trade liberalization agenda. Thus, as Epstein and O’Halloran

(1999) argue, divided government may hinder trade liberalization since Congress members are

considerably less likely to support the President’s trade policies if he is in the opposition party. Since

divided government has been the norm in the postwar period, the supporters of the recent regional trade

agreements were perhaps fortunate (and opponents unfortunate) to have one party control both the

executive and the House of Representatives in 1993, 2001, and 2005.

6. Conclusion

19

This paper has shown that Congress members are much more likely to support trade liberalization

measures or grant the President the power to negotiate new trade deals if the representative and the

President are members of the same party. While this result is not unexpected, the magnitude of the

presidential party effect on congressional voting is surprisingly large and robust. The effect of having a

President in the same party is much larger than the effect of the representative’s own party once ideology,

contributions received, and other voting determinants are controlled for. The size of this effect suggests

that divided government makes the passage of new trade bills much more difficult and that presidential

elections can greatly influence trade policy outcomes even when both presidential candidates have

identical trade policy platforms.

The estimates in this paper indicate that the North American Free Trade Agreement, which

passed by a comfortable 17-vote margin under President Clinton in 1993 would have had a much close

vote in the House of Representatives under a re-elected President Bush (41). The model predicts that

NAFTA would have had a 60 percent chance of passing and an expected margin of victory of about 3

votes under a Republican President. The 2001 bill giving President Bush (43) trade promotion authority

and 2005 CAFTA bill would likely have been rejected by the House under Democratic Presidents. Each

of these bills had about a 60 percent chance of being approved under President Bush but less than a 40

percent chance under a Democratic President.

Most of the existing theoretical literature on the political economy of trade policy, such as the

Grossman and Helpman (1994) “Protection for Sale” model, treats the government as a single entity. The

results in this paper indicate that such models miss the interactions between individuals and branches

within governments that can have important effects on the final trade policy decisions. Grossman and

Helpman (2005) and McLaren and Karabay (2004) are recent attempts to model the government more

realistically as a group of individuals with competing preferences and agendas. The strong effect of

presidential party on representatives’ trade votes shown in this paper suggests that extending the

theoretical literature toward greater diversity within the government can be a fruitful direction for

research.

20

The NAFTA case provides an interesting historical parallel. In 1841, Robert Peel was elected

Prime Minister of Britain in large part because agricultural interests turned to his Conservative Party to

preserve the protectionist Corn Laws. As Bhagwati (1989) describes, however, Peel pushed through a

repeal of the Corn Laws five years later even though a majority of his party voted against the move

toward free trade. In 1992, labor unions strongly supported and helped elect President Clinton. About

one year later, Clinton successfully shepherded NAFTA through to congressional approval even though

labor unions strongly opposed the agreement and a majority of Democrats in the House of

Representatives voted against it. Thus, both the repeal of the Corn Laws and the NAFTA were passed in

large part because groups with protectionist sentiments were able to elect the leader of their choice, who

was then able to push through trade legislation against the wishes of his own party.

21

Table 1: Variable definitions, sources, and mean values

Variable Definition and source _______Mean_______ Std. dev.1991 Trade vote 1= vote for fast-track, house.gov 0.546 0.498 1993 Trade vote 1=vote for NAFTA, house.gov 0.539 0.499 1998 Trade vote 1= vote for fast-track, house.gov 0.426 0.495 2001 Trade vote 1= vote for fast-track, house.gov 0.501 0.501 2005 Trade vote 1= vote for CAFTA, house.gov 0.502 0.501 Vote=yes Vote=no Corporate contributions

Contributions from corporate PACs, in 1000s of 2000 $, fec.gov 147.724 ≠ 91.866 107.254

Labor contributions

Contributions from labor PACs, in 1000s of 2000 $, fec.gov 28.294 ≠ 106.013 75.551

Republican 1= Representative is Republican, house.gov 0.759 ≠ 0.176 0.499

President’s party 1=President is same party as Representative, house.gov 0.620 ≠ 0.376 0.500

Majority party 1 = Representative is a member of the House majority party, house.gov 0.686 ≠ 0.425 0.497

ACU rating American Conservative Union Representative rating, Sharp (2000) and acuratings.org 71.706 ≠ 27.507 38.273

COC rating Chamber of Commerce Representative rating, Sharp (2000) and uschamber.com 80.926 ≠ 49.140 26.221

AFL-CIO rating AFL-CIO Representative rating, Sharp (2000) and aflcio.org 29.845 ≠ 77.559 37.172

Percent Hispanic Hispanic percent of district, census.gov 10.420 11.663 15.259 No High School Degree

percent of district without a high school degree, census.gov 20.053 ≠ 23.276 8.287

Per-capita income

District per-capita income in 1000s of 2000 $, census.gov 21.242 ≠ 20.170 6.294

Union State union membership percent, unionstats.com 13.290 ≠ 15.731 6.728 Fraction export jobs

Export jobs in district as fraction of export and import jobs, County Business Patterns 61.417 63.733 28.983

Representative college degree

1= Representative has a college degree, bioguide.congress.gov 0.921 0.928 0.266

Rep. advanced degree

1= Representative has an advanced degree, bioguide.congress.gov 0.636 0.650 0.479

Age Age of representative, bioguide.congress.gov 52.306 53.041 9.972

Ways and means 1= Representative is on the Ways and Means Committee, house.gov 0.113 ≠ 0.065 0.284

Labor committee 1= Rep. is on the Education and the Workforce Committee, house.gov 0.088 0.107 0.299

Terms Representative’s terms in office, bioguide.congress.gov 4.347 ≠ 4.838 4.126

Chair/ranking member

1= Representative is a chair or ranking committee member, house.gov 0.122 0.112 0.322

Incumbent 1= Representative was incumbent in last election, house.gov 0.848 0.860 0.354

Fraction emp_SIC xx

Fraction of manufacturing jobs in SIC xx, County Business Patterns varies varies varies

≠ Indicates that the means are significantly different at the 1 percent level in two-tailed t-test.

22

Table 2: Relationship between party variables and trade votes

Variable Coefficient Coefficient Coefficient Coefficient President’s party 0.620 *** 0.450 *** 0.384 *** 0.407 ***Republican 1.584 *** 1.542 *** 1.652 ***Majority party 0.453 *** 0.397 ***Year 1993 -0.203 ** Year 1998 -0.708 ***Year 2001 -0.425 ***Year 2005 -0.512 ***Constant -0.301 *** -0.940 *** -1.150 *** -0.830 *** percent predicted correctly 0.622 0.791 0.791 0.791 Pseudo-R2 0.043 0.281 0.297 0.318 Observations 2136 2136 2136 2136

*, **, *** Indicate that the coefficient is significant at the 10, 5, and 1 percent levels respectively. Significance levels are calculated using Huber/White/sandwich estimator of standard errors.

23

Table 3: Fixed effect estimation of voting equation

Variable Coefficient Marginal effect

Corp. contributions -0.0051 *** -0.0020 Labor contributions 0.0017 0.0007 President’s party 1.5596 *** 0.5609 Majority party 1.0890 *** 0.4077 ACU rating -0.0114 -0.0045 COC rating 0.0208 ** 0.0083 AFL-CIO rating -0.0006 -0.0002 Percent Hispanic 0.0369 0.0147 No HS degree -0.1364 ** -0.0542 Per-capita income -0.0176 -0.0070 Union 0.2945 *** 0.1171 Year 1993 -0.6284 ** -0.2390 Year 1998 -1.6305 *** -0.5183 Year 2001 -1.0534 * -0.3734 Year 2005 -0.5737 -0.2178 Fraction export jobs 0.0502 *** 0.0200 Fraction emp SIC 20 -0.0117 -0.0047 Fraction emp SIC 21 0.3855 0.1532 Fraction emp SIC 22 -0.0369 -0.0147 Fraction emp SIC 23 -0.0029 -0.0012 Fraction emp SIC 24 -0.0967 ** -0.0385 Fraction emp SIC 25 0.1802 ** 0.0716 Fraction emp SIC 26 -0.0023 -0.0009 Fraction emp SIC 27 0.0604 0.0240 Fraction emp SIC 28 -0.0948 ** -0.0377 Fraction emp SIC 29 -0.1599 -0.0635 Fraction emp SIC 30 0.1048 ** 0.0417 Fraction emp SIC 31 -0.5961 ** -0.2369 Fraction emp SIC 32 0.0217 0.0086 Fraction emp SIC 33 0.0435 0.0173 Fraction emp SIC 34 0.0191 0.0076 Fraction emp SIC 35 -0.0983 *** -0.0391 Fraction emp SIC 36 0.0220 0.0087 Fraction emp SIC 37 -0.0071 -0.0028 Fraction emp SIC 38 -0.1104 ** -0.0439 Psuedo - 2R 0.4485 Percent predicted correctly 0.8347 Observations 484

*, **, *** Indicate that the coefficient is significant at the 10, 5, and 1 percent levels respectively. Significance levels are calculated using Huber/White/sandwich estimator of standard errors. Fixed effects are included for each representative.

The marginal effects column reports xy∂∂ for continuous variables and it shows the change in the

probability that y=1 for a change from 0 to 1 for binary explanatory variables.

24

Table 4: Simultaneous equation model estimates

Voting equation Corporate contributions

Labor contributions

Variables Coefficient Marginaleffect

Variables

Constant 1.8563 *** Constant 4.8401 75.1348 ***Corp. contributions 0.0029 *** 0.0012 Labor contributions -0.0046 *** -0.0018 Republican 0.3414 *** 0.1355 Republican -21.0679 * -38.8881 ***President’s party 0.5906 *** 0.2322 President’s party 3.4057 -1.3856 Majority party 0.0064 0.0025 Majority party 27.4299 *** -6.4625 ACU rating -0.0187 *** -0.0075 ACU rating 0.3592 ** -0.3780 ***COC rating 0.0228 *** 0.0091 COC rating 1.1097 *** 0.0828 AFL-CIO rating -0.0200 *** -0.0080 AFL-CIO rating 0.0226 0.6491 ***Percent Hispanic 0.0169 *** 0.0068 Age -1.3083 *** -0.3685 ** No HS degree -0.0345 *** -0.0137 Ways and means 48.4204 *** -10.3875 ** Per-capita income 0.0033 0.0013 Labor committee -30.5783 *** 7.4121 * Union -0.0300 *** -0.0120 Terms 4.2370 *** -1.8887 ***Rep. college degree -0.0433 -0.0173 Incumbent 45.4339 *** 6.6593 * Rep. advanced degree 0.1977 *** 0.0787 Committee chair 59.4146 *** 24.7957 ***Year 1993 -0.9095 *** -0.3388 Year 1993 -5.0653 0.1699 Year 1998 -1.4382 *** -0.4883 Year 1998 15.2717 * 13.9055 * Year 2001 -1.3101 *** -0.4562 Year 2001 34.2981 *** 25.5284 ***Year 2005 -1.3607 *** -0.4692 Year 2005 50.5798 *** 23.4746 ***Fraction export jobs 0.0012 0.0005 Fraction emp SIC 20 0.0171 *** 0.0068 Fraction emp SIC 21 0.0190 0.0076 Fraction emp SIC 22 -0.0385 *** -0.0153 Fraction emp SIC 23 0.0183 *** 0.0073 Fraction emp SIC 24 0.0058 0.0023 Fraction emp SIC 25 0.0437 *** 0.0174 Fraction emp SIC 26 0.0080 0.0032 Fraction emp SIC 27 0.0095 0.0038 Fraction emp SIC 28 -0.0110 -0.0044 Fraction emp SIC 29 -0.0119 -0.0048 Fraction emp SIC 30 0.0264 *** 0.0105 Fraction emp SIC 31 0.0076 0.0030 Fraction emp SIC 32 -0.0087 -0.0035 Fraction emp SIC 33 -0.0013 -0.0005 Fraction emp SIC 34 0.0323 *** 0.0129 Fraction emp SIC 35 -0.0213 *** -0.0085 Fraction emp SIC 36 0.0328 *** 0.0131 Fraction emp SIC 37 0.0072 * 0.0029 Fraction emp SIC 38 0.0032 0.0013

2R 0.5421 0.3024 0.5332 Observations 2135 2135 2135

*, **, *** Indicate that the coefficient is significant at the 10, 5, and 1 percent levels respectively. The system of equations was estimated by full-information maximum likelihood.

25

Table 5: Predictions of trade vote support under a different President

Based on Table 4 estimates for all representatives voting on the trade bills __Under actual President__ __Under alternative President__ Fraction

supporting bill

Fraction predicted to support bill

Predicted probability bill

will pass

Fraction predicted to support bill

Predicted probability bill

will pass 1991 Fast-track vote 0.546 0.559 0.986 0.627 0.999

1993 NAFTA vote 0.539 0.543 0.945 0.506 0.592

1998 Fast-track vote 0.426 0.419 0.001 0.463 0.070

2001 Fast-track vote 0.501 0.506 0.583 0.489 0.382

2005 CAFTA vote 0.502 0.508 0.615 0.492 0.392

Based on Table 3 estimates for representatives who switched votes at least once* __Under actual President__ __Under alternative President__ Fraction

supporting bill

Fraction predicted to support bill

Predicted probability bill

will pass

Fraction predicted to support bill

Predicted probability bill

will pass 1991 Fast-track vote 0.541 0.541 0.775 0.681 0.998

1993 NAFTA vote 0.589 0.585 0.971 0.457 0.239

1998 Fast-track vote 0.269 0.270 0.000 0.358 0.002

2001 Fast-track vote 0.500 0.501 0.504 0.424 0.115

2005 CAFTA vote 0.518 0.525 0.672 0.418 0.093

* Since the regression includes fixed effects for each Representative, only those who voted for at least one trade bill and against at least one can be included in the Table 3 regression and the bottom half of Table 5

26

Figure 1: House support for trade deals

87%

75%

68%

89% 88%

7%

35%40%

15%10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1991 1993 1998 2001 2005Year

Republicans Democrats

27

References

Baldwin, R. and C. Magee, 2000a, “Is Trade Policy for Sale? Congressional Voting on Recent Trade Bills,”

Public Choice 105: 79 – 101.

Baldwin, R. and C. Magee, 2000b, Congressional Trade Votes: From NAFTA Approval to Fast-Track

Defeat (Institute for International Economics: Washington D.C.).

Beaulieu, E. and C. Magee, 2004, “Four Simple Tests of Campaign Contributions and Trade Policy

Preferences,” Economics and Politics 16 (2): 163 – 187.

Bhagwati, Jagdish, 1989, Protectionism (MIT Press: Cambridge, MA).

Chappell, H. (1982). Campaign Contributions and Congressional Voting: A Simultaneous Probit-Tobit

Model. Review of Economics and Statistics 64 (1): 77-83.

Congressional Districts in the 1980’s (Congressional Quarterly Inc.: Washington D.C.) 1983.

Congressional Districts in the 1990’s: A Portrait of America (Congressional Quarterly Inc.: Washington

D.C.) 1993.

Epstein, David and O’Halloran, Sharyn, 1999, Delegating Powers: A Transaction Cost Politics Approach

to Policy Making under Separate Powers (Cambridge University Press: Cambridge).

Grayson, George, 1995, The North American Free Trade Agreement: Regional Community and the New

World Order (University Press of America: Lanham, MD).

Grossman, Gene, and Elhanan Helpman, 1994, “Protection for Sale,” American Economic Review 84 (4),

833-50.

Grossman, Gene, and Elhanan Helpman, 2005, “Party Discipline and Pork-Barrel Politics” Harvard

Institute of Economic Research Discussion Paper 2075.

Hirsch, Barry and David A. Macpherson, "Union Membership and Coverage Database from the Current

Population Survey: Note," Industrial and Labor Relations Review, Vol. 56, No. 2, January 2003,

pp. 349-54.

28

Kaempfer, William, and Stephen Marks, 1993, “The Expected Effects of Trade Liberalisation: Evidence

from US Congressional Action on Fast-Track Authority,” The World Economy 16 (6), 725 – 740.

Kahane, L., 1996a, “Senate Voting Patterns on the 1991 extension of the fast-track trade procedures:

Prelude to NAFTA,” Public Choice 87, pp. 35 – 53.

Kahane, Leo, 1996b, Congressional Voting Patterns on NAFTA: An Empirical Analysis. American

Journal of Economics and Sociology 55: 395-409.

McLaren, John and Bilgehan Karabay, 2004, “Trade Policy Making by an Assembly,” in Devashish Mitra

and Arvind Panagariya, eds., The Political Economy of Trade, Aid, and Foreign Investment

(Elsevier: Amsterdam) 11 – 29.

Persson, Torsten, and Guido Tabellini, 2000, Political Economics: Explaining Economic Policy (MIT

Press: Cambridge, MA).

Sharp, J.M, ed., 2000, Directory of Congressional Voting Scores and Interest Group Ratings, 3rd ed.,

volume 1, CQ Press, Washington D.C.

Snyder, J. (1992). Long-Term Investing in Politicians; Or, Give Early, Give Often. Journal of Law and

Economics 35 (April): 15 – 43.

Staiger, Douglas, and James Stock, 1997, “Instrumental Variables Regression with Weak Instruments,”

Econometrica 65 (3), 557 – 586.

Steagall, J. and K. Jennings (1996). Unions, PAC Contributions, and the NAFTA Vote. Journal of Labor

Research 17: 515-521.

Uslaner, Eric, 1998, “Let the Chits Fall Where They May? Executive and Constituency Influences on

Congressional Voting on NAFTA,” Legislative Studies Quarterly 23 (3), 347 – 371.