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; [email protected]; phone (570) 5771752; 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
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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
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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.
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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 agendasetter 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 seventenths 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)
voteit = F ( α i + β ' X it + β1 Same _ Presit + β 2 C _ conit + β 3 L _ conit ) + ε it ,
where voteit = 1 if representative i votes for the trade bill in time t, Same _ Presit = 1 if the President is a
member or representative i’s party in time t, C _ conit and L _ conit are corporate and labor
contributions, and X it is a vector of other variables that affect the trade votes. Including the fixed effects
for each representative ( α i 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)
voteit = F ( β' X it + β1 Same _ Pres it + β 2 C _ conit + β 3 L _ conit ) + ε v ,it
(3)
C _ conit = α' Z it + ε c ,it
(4)
L _ conit = δ ' Z it + ε l ,it
10
In order to identify the system, there need to be variables in the vector Z it 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)
ˆ' X + β
ˆ Same _ Pres + β
ˆ C _ con + β
ˆ L _ con ) .
v̂it = F ( β
it
1
it
2
it
3
it
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)
Predicted fraction of support =
1
v̂it .
N i
∑
If the previous presidential election had gone the other way, the predicted probability that representative i
would support the trade bill would be
(7)
ˆ' X + β
ˆ ( 1 − Same_Pres ) + β
ˆ C _ con + β
ˆ L _ con ) .
v̂'it = F ( β
it
1
it
2
it
3
it
11
Again, summing over all representatives would generate the counterfactual predicted number of yes votes
under an alternative presidency.
(8)
Counterfactual predicted fraction of support =
1
v̂'it .
N i
∑
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.
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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 F < 10 ). Tests of the instruments in Table 4,
however, provide highly significant Wald statistics of F = 509 (corporate) and F = 66 (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 Republicancontrolled 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
1991 Trade vote
1993 Trade vote
1998 Trade vote
2001 Trade vote
2005 Trade vote
Corporate
contributions
Labor
contributions
Republican
Definition and source
1= vote for fast-track, house.gov
1=vote for NAFTA, house.gov
1= vote for fast-track, house.gov
1= vote for fast-track, house.gov
1= vote for CAFTA, house.gov
_______Mean_______
0.546
0.539
0.426
0.501
0.502
Vote=no
Vote=yes
Contributions from corporate PACs, in 1000s of
147.724
2000 $, fec.gov
Contributions from labor PACs, in 1000s of 2000
28.294
$, fec.gov
1= Representative is Republican, house.gov
0.759
1=President is same party as Representative,
President’s party
0.620
house.gov
1 = Representative is a member of the House
Majority party
0.686
majority party, house.gov
American Conservative Union Representative
71.706
ACU rating
rating, Sharp (2000) and acuratings.org
Chamber of Commerce Representative rating,
COC rating
80.926
Sharp (2000) and uschamber.com
AFL-CIO Representative rating, Sharp (2000)
AFL-CIO rating
29.845
and aflcio.org
Percent Hispanic Hispanic percent of district, census.gov
10.420
No High School percent of district without a high school degree,
20.053
Degree
census.gov
Per-capita
District per-capita income in 1000s of 2000 $,
21.242
income
census.gov
Union
State union membership percent, unionstats.com 13.290
Fraction export Export jobs in district as fraction of export and
61.417
jobs
import jobs, County Business Patterns
Representative 1= Representative has a college degree,
0.921
college degree bioguide.congress.gov
Rep. advanced 1= Representative has an advanced degree,
0.636
degree
bioguide.congress.gov
Age
Age of representative, bioguide.congress.gov
52.306
1= Representative is on the Ways and Means
Ways and means
0.113
Committee, house.gov
1= Rep. is on the Education and the Workforce
Labor committee
0.088
Committee, house.gov
Representative’s terms in office,
Terms
4.347
bioguide.congress.gov
Chair/ranking
1= Representative is a chair or ranking
0.122
member
committee member, house.gov
1= Representative was incumbent in last election,
Incumbent
0.848
house.gov
Fraction
Fraction of manufacturing jobs in SIC xx,
varies
emp_SIC xx
County Business Patterns
Std. dev.
0.498
0.499
0.495
0.501
0.501
≠
91.866
107.254
≠
106.013
75.551
≠
0.176
0.499
≠
0.376
0.500
≠
0.425
0.497
≠
27.507
38.273
≠
49.140
26.221
≠
77.559
37.172
11.663
15.259
≠
23.276
8.287
≠
20.170
6.294
≠
15.731
6.728
63.733
28.983
0.928
0.266
0.650
0.479
53.041
9.972
0.065
0.284
0.107
0.299
4.838
4.126
0.112
0.322
0.860
0.354
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
President’s party
Republican
Majority party
Year 1993
Year 1998
Year 2001
Year 2005
Constant
percent predicted correctly
Pseudo-R2
Observations
Coefficient
0.620 ***
Coefficient
0.450 ***
1.584 ***
Coefficient
0.384 ***
1.542 ***
0.453 ***
-0.301 ***
-0.940 ***
-1.150 ***
0.622
0.043
2136
0.791
0.281
2136
0.791
0.297
2136
Coefficient
0.407 ***
1.652 ***
0.397 ***
-0.203 **
-0.708 ***
-0.425 ***
-0.512 ***
-0.830 ***
0.791
0.318
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
Corp. contributions
Labor contributions
President’s party
Majority party
ACU rating
COC rating
AFL-CIO rating
Percent Hispanic
No HS degree
Per-capita income
Union
Year 1993
Year 1998
Year 2001
Year 2005
Fraction export jobs
Fraction emp SIC 20
Fraction emp SIC 21
Fraction emp SIC 22
Fraction emp SIC 23
Fraction emp SIC 24
Fraction emp SIC 25
Fraction emp SIC 26
Fraction emp SIC 27
Fraction emp SIC 28
Fraction emp SIC 29
Fraction emp SIC 30
Fraction emp SIC 31
Fraction emp SIC 32
Fraction emp SIC 33
Fraction emp SIC 34
Fraction emp SIC 35
Fraction emp SIC 36
Fraction emp SIC 37
Fraction emp SIC 38
Psuedo - R 2
Percent predicted correctly
Observations
Coefficient
-0.0051 ***
0.0017
1.5596 ***
1.0890 ***
-0.0114
0.0208 **
-0.0006
0.0369
-0.1364 **
-0.0176
0.2945 ***
-0.6284 **
-1.6305 ***
-1.0534 *
-0.5737
0.0502 ***
-0.0117
0.3855
-0.0369
-0.0029
-0.0967 **
0.1802 **
-0.0023
0.0604
-0.0948 **
-0.1599
0.1048 **
-0.5961 **
0.0217
0.0435
0.0191
-0.0983 ***
0.0220
-0.0071
-0.1104 **
Marginal
effect
-0.0020
0.0007
0.5609
0.4077
-0.0045
0.0083
-0.0002
0.0147
-0.0542
-0.0070
0.1171
-0.2390
-0.5183
-0.3734
-0.2178
0.0200
-0.0047
0.1532
-0.0147
-0.0012
-0.0385
0.0716
-0.0009
0.0240
-0.0377
-0.0635
0.0417
-0.2369
0.0086
0.0173
0.0076
-0.0391
0.0087
-0.0028
-0.0439
0.4485
0.8347
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.
∂y
for continuous variables and it shows the change in the
The marginal effects column reports
∂x
probability that y=1 for a change from 0 to 1 for binary explanatory variables.
24
Table 4: Simultaneous equation model estimates
Voting equation
Variables
Constant
Corp. contributions
Labor contributions
Republican
President’s party
Majority party
ACU rating
COC rating
AFL-CIO rating
Percent Hispanic
No HS degree
Per-capita income
Union
Rep. college degree
Rep. advanced degree
Year 1993
Year 1998
Year 2001
Year 2005
Fraction export jobs
Fraction emp SIC 20
Fraction emp SIC 21
Fraction emp SIC 22
Fraction emp SIC 23
Fraction emp SIC 24
Fraction emp SIC 25
Fraction emp SIC 26
Fraction emp SIC 27
Fraction emp SIC 28
Fraction emp SIC 29
Fraction emp SIC 30
Fraction emp SIC 31
Fraction emp SIC 32
Fraction emp SIC 33
Fraction emp SIC 34
Fraction emp SIC 35
Fraction emp SIC 36
Fraction emp SIC 37
Fraction emp SIC 38
R2
Observations
Coefficient
1.8563 ***
0.0029 ***
-0.0046 ***
0.3414 ***
0.5906 ***
0.0064
-0.0187 ***
0.0228 ***
-0.0200 ***
0.0169 ***
-0.0345 ***
0.0033
-0.0300 ***
-0.0433
0.1977 ***
-0.9095 ***
-1.4382 ***
-1.3101 ***
-1.3607 ***
0.0012
0.0171 ***
0.0190
-0.0385 ***
0.0183 ***
0.0058
0.0437 ***
0.0080
0.0095
-0.0110
-0.0119
0.0264 ***
0.0076
-0.0087
-0.0013
0.0323 ***
-0.0213 ***
0.0328 ***
0.0072 *
0.0032
Marginal
effect
Corporate
contributions
Variables
Constant
0.0012
-0.0018
0.1355
0.2322
0.0025
-0.0075
0.0091
-0.0080
0.0068
-0.0137
0.0013
-0.0120
-0.0173
0.0787
-0.3388
-0.4883
-0.4562
-0.4692
0.0005
0.0068
0.0076
-0.0153
0.0073
0.0023
0.0174
0.0032
0.0038
-0.0044
-0.0048
0.0105
0.0030
-0.0035
-0.0005
0.0129
-0.0085
0.0131
0.0029
0.0013
Labor
contributions
Republican
President’s party
Majority party
ACU rating
COC rating
AFL-CIO rating
Age
Ways and means
Labor committee
Terms
Incumbent
Committee chair
Year 1993
Year 1998
Year 2001
Year 2005
4.8401
-21.0679 *
3.4057
27.4299 ***
0.3592 **
1.1097 ***
0.0226
-1.3083 ***
48.4204 ***
-30.5783 ***
4.2370 ***
45.4339 ***
59.4146 ***
-5.0653
15.2717 *
34.2981 ***
50.5798 ***
75.1348 ***
-38.8881 ***
-1.3856
-6.4625
-0.3780 ***
0.0828
0.6491 ***
-0.3685 **
-10.3875 **
7.4121 *
-1.8887 ***
6.6593 *
24.7957 ***
0.1699
13.9055 *
25.5284 ***
23.4746 ***
0.5421
0.3024
0.5332
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
Fraction
supporting
bill
__Under actual President__ __Under alternative President__
Predicted
Fraction
Predicted
Fraction
probability bill
predicted to probability bill predicted to
will pass
support bill
will pass
support bill
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*
Fraction
supporting
bill
__Under actual President__ __Under alternative President__
Fraction
Predicted
Fraction
Predicted
predicted to probability bill predicted to
probability bill
support bill
will pass
support 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
100%
90%
89%
87%
80%
88%
75%
68%
70%
60%
50%
40%
35%
40%
30%
20%
15%
10%
10%
7%
0%
1991
1993
1998
Year
Republicans
Democrats
2001
2005
27
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