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Congressional position-taking on punitive tariffs: president Trump’s 2018 auto tariff

Published online by Cambridge University Press:  30 January 2025

Michael S. Rocca*
Affiliation:
Department of Political Science, University of New Mexico, Albuquerque, NM, USA
Miao Wang
Affiliation:
Department of Political Science, University of New Mexico, Albuquerque, NM, USA
*
Corresponding author: Michael S. Rocca; Email: msrocca@unm.edu
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Abstract

On 1 March 2018, President Trump declared a 25% tariff on certain steel imports by invoking Section 232 of the 1962 Trade Expansion Act. The tariff pitted two of America’s most storied and interconnected industries, steel and auto producers, against one another and made allies out of longtime bitter political opponents on Capitol Hill. Later that same year, President Trump doubled down on the steel tariff when he initiated a Section 232 investigation on auto and auto parts imports. The auto industry blasted the proposal, while steel offered its strong support. This paper examines the congressional response to President Trump’s proposed auto tariff. Specifically, we explain why 159 MCs signed a letter opposing the tariff. After controlling for other factors, such as district interests and campaign contributions, we find that ideology matters more than party affiliation on whether legislators signed the auto letter. We also find the second dimension of the DW-NOMINATE score to matter, suggesting the strong presence of intra-party cleavages. Our findings highlight the complex nature of trade policy as a domain of bipartisan agreement amidst broader political polarization and at a time when traditional party platforms on the issue are rapidly changing.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Vinod K. Aggarwal

On 1 March 2018, President Trump declared a 25% tariff on certain steel imports by invoking Section 232 of the 1962 Trade Expansion Act. It was not the first shot of President Trump’s trade war, coming more than a month after his Section 201 tariff action over solar panels and large washing machines.Footnote 1 Nor was it the largest tariff action, easily dwarfed by later Section 301 tariff actions that ultimately covered 360 billion dollars imports from China by the end of 2019.Footnote 2 But it could have been his most extraordinary tariff action.

First, this tariff was the earliest Trump tariff action to provoke significant market reaction, causing a plunge of the DOW Index comparable to what the much more extensive waves of Section 301 China tariff would eventually trigger.Footnote 3 Second, the Trump Administration’s defense of the tariff was unprecedented. By invoking Section 232 of the 1962 Trade Expansion Act (which prescribes trade protection measures against national security threats) to cover imports from close US allies, the Trump Administration virtually claimed that products from these allies posed national security threats, a move with potentially profound foreign policy ramifications.Footnote 4 Furthermore, the statutory basis for the tariff action established substantial presidential unilateral authority over a policy area constitutionally assigned to Congress.

Finally, the protected economic sector itself—the steel industry—held a special place in American history and culture dating back to the Industrial Revolution. A longtime showcase of national strength and pride, the development of American steel industry in the latter half of the 19th Century contributed to the rise of the United States from the frontier of the Western world to a globally leading power.Footnote 5 On the eve of and during World War Two, American steelmaking experienced significant growth as a crucial part of the “Arsenal of Democracy” and occupied as much as one third of world total capacity prior to the war and 48.4% by 1950.Footnote 6 Steel literally provided the structure of the some of the most prominent symbols of American culture and progress of the 20th century, from the skyscrapers in its largest cities to the muscle cars that roamed its roads.

The reaction to President Trump’s Section 232 tariff action was mixed. Those who supported the tariff argued that it was necessary to protect the US steel industry from unfair trade practices such as “dumping,” or the flooding of the US market with product prices lower than the exporter’s domestic market. Not surprisingly, among the most vocal supporters was the steel industry itself. For example, Roger Newport, CEO of AK Steel, one of America’s largest domestic steel producers, wrote in an op-ed that he supported President Trump’s “bold action” to “defend our national security and combat the flood of imports that have been eroding America’s steel industry over several decades.”Footnote 7

Those who opposed the tariff railed against the national security rationale for the tariff as well its potentially negative effects for steel’s downstream users.Footnote 8 In a rare intra-party rebuke of the president, opponents included Republican leaders in Congress such as Speaker of the House Paul Ryan (R-WI) and Senate Majority Leader Mitch McConnell (R-KY).Footnote 9 Among the tariff’s most ardent opponents was one of the most important downstream users of steel, and another classic American industry birthed from the Industrial Revolution: the US automobile industry.Footnote 10 For instance, the CEO of Ford Corporation contended that the Trump tariffs on steel and aluminum would cost his company 1 billion dollars within one year.Footnote 11 General Motors claimed that the tariff would lead to “a smaller GM, a reduced presence at home and abroad for this iconic American company, and risk less—not more—US jobs.”Footnote 12

The steel and auto industries squared off again when President Trump initiated a Section 232 investigation on auto and parts imports on 23 May 2018.Footnote 13 As in the steel case, the Commerce Department decided on 17 May 2019 that such imports threaten US national security and recommended a 25% tariff on auto imports. The auto industry blasted the proposal, concerned that the tariff would increase prices in an industry operating in a highly globalized supply chain. The Alliance of Automobile Manufacturers, the main lobbyist for US auto industry, claimed that the tariff would amount to a $45 billion tax on consumers and wipe out any benefits from President Trump’s recently passed tax cuts for low- and middle-class-income Americans.Footnote 14 The steel industry, on the other hand, saw the auto tariffs as an opportunity to consolidate support for its own tariffs. For example, the United Steelworkers voiced their support for this tariff.Footnote 15 Economists refer to this as “cascading protections,” or a secondary round of tariffs (in this case, on auto imports) to protect products negatively impacted by the primary round of duties (in this case, on steel imports).

While President Trump’s auto tariff pitted longtime industry allies against one another, it also brought longtime political rivals together. Perhaps most interesting was the response in the highly polarized US Congress, where it provoked a rare example of bipartisanship. On 8 May 2019, a letter signed by a bipartisan pool of 159 members of the House of Representatives was sent to Director of the National Economic Council Lawrence (Larry) Kudlow urging him to advise President Trump against imposing new trade restrictions on autos and parts. Writing on behalf of the auto industry, the letter claims that “hard-working Americans in the auto sector” are “not a threat to national security” and that tariffs would increase vehicle prices and “threaten hundreds of thousands of jobs.”Footnote 16 Signees include legislators on opposite sides of the political spectrum, such as conservative firebrand and Trump ally Jim Jordan (R-OH) on the one hand and Democratic Whip James Clyburn (D-SC) on the other.

Not only is President Trump’s tariff policy an important subject of study, but it also provides an opportunity to analyze factors critical to congressional behavior in a context where there is reason to expect a congressional member’s (MC) usual partisan incentives and alignments to be less prominent. Our question is, what explains congressional position-taking on the proposed 2019 auto tariff? In particular, we seek to understand the complex interplay between ideology and party regarding position-taking on the auto tariff proposal. After controlling for other factors such as district interests and campaign contributions, we find that ideology matters more than party affiliation on whether legislators signed the auto letter. Interestingly, we also find the second dimension of the DW-NOMINATE score to matter as well.

These findings highlight the complex nature of tariff policy as a domain of bipartisan agreement amidst broader political polarization. The research sheds light on the strategic considerations driving legislative support or opposition and contributes to our understanding of the broader implications of trade policy in a polarized era. This study clarifies the complex relationship between economic policy, political ideology, and the shifting sands of American partisanship through this lens.

Literature review

Following Fenno, we assume members of Congress have three goals: getting reelected, making good public policy, and attaining influence within Congress (e.g., institutional promotion).Footnote 17 Of those, getting reelected is the most “proximate” because it “must be achieved over and over if other ends are to be entertained.”Footnote 18 Congressional behavior, therefore, is thought to be primarily electorally oriented. One important electoral-oriented activity is position-taking, which Mayhew defines as “the public enunciation of a judgmental statement on anything likely to be of interest to political actors.”Footnote 19 Positions can be taken through roll call votingFootnote 20 or non-roll call activities such as bill sponsorship,Footnote 21 cosponsorship,Footnote 22 press releases,Footnote 23 and floor speeches.Footnote 24

Research is mixed on whether Mayhew’s simple electoral explanation can be applied to issues of tariff policy and, more generally, trade policy.Footnote 25 Some scholars find evidence that House member’s position-taking on the issue of trade liberalization is decided to a large extent by constituency and district factors,Footnote 26 such as employment gain/loss,Footnote 27 the presence of organized labor,Footnote 28 anti-trade presidential vote share,Footnote 29 district economic conditions,Footnote 30 labor skills,Footnote 31 minority population,Footnote 32 industry featuresFootnote 33 , class distinctions,Footnote 34 and the intensity of foreign competition.Footnote 35 Box-Steffensmeier, Arnold and Zorn further identify the constituency effects on the timing of House members’ position-taking on trade: MCs who receive clear signals from the constituency declare their positions earlier while those getting conflicting signals delay their announcement in pursuit of more information.Footnote 36

Other scholars, however, remain skeptical of such a link.Footnote 37 The challenge is that most voters neither know nor care all that much about specific trade policy issues because few directly impact their lives. For instance, Guisinger finds US trade policy is a low-salience issue regarding voters’ stated importance, knowledge of policy outcomes, and holding politicians accountable for their decisions.Footnote 38 Similarly, Rho and Tomz argue that because most voters do not understand the economic consequences of trade policies such as protectionism, there is little connection between economic self-interest and policy preferences.Footnote 39 More generally, these studies are consistent with landmark studies from Converse, who shows that voters lack ideological constraint, particularly on foreign policy, and Miller and Stokes, who show the connection between legislators’ and constituents’ attitudes is lowest on foreign policy compared to other issues.Footnote 40

One implication of voters’ inattentiveness to trade policy is that it may free MCs from the usual constraints of constituency opinion.Footnote 41 Of course, MCs are not completely untethered from the electoral connection; their positions must remain within acceptable behavior if they wish to get reelected. Indeed, attentive groups such as interest groups and other sub-constituencies will expect MCs to remain responsive to their specific trade preferences.Footnote 42 Furthermore, challengers anxiously await any minor misstep. However, compared to other issues, trade policy is not sufficiently salient for them to serve MCs’ electoral goals. Because of this, parties are likely to be less of a constraint as well. According to Arnold, the extent to which parties care about issues—and are, in turn, willing to expend valuable resources to influence legislative behavior—is directly tied to the issues’ relationship to electoral outcomes.Footnote 43 Just as Miler and Allee find with congressional activity before the International Trade Commission,Footnote 44 the lack of party influences seems very likely in the auto tariff story.Footnote 45 As we mentioned above, the auto tariff letter was signed by an almost equal number of Democrats and Republicans, suggesting the lack of party constraint.

It is worth noting that while party affiliation has historically influenced American politicians’ stances on free trade,Footnote 46 recent shifts and complexities challenge this notion. Bauer, Pool, and Dexter’s seminal work lays the foundation for understanding the nuanced evolution of US trade policy, emphasizing the intricate interplay between political strategies, economic theories, and commercial interests that shape party positions.Footnote 47 Historically, bipartisan consensus favored free trade from the Roosevelt to the Kennedy administrations. However, this consensus began to erode due to partisan realignment and international economic developments.Footnote 48 The Democratic Party, influenced by the decline of conservative Southern DemocratsFootnote 49 and the rise of manufacturing union-linked Northern Democrats in the 1970s,Footnote 50 veered toward protectionism. This shift necessitated Republican support to pass recent Trade Promotion Acts, even with Democratic presidents.Footnote 51 Karol’s analysis further clarifies this transition, focusing on the Democratic Party’s “coalition maintenance” strategy, where adapting to core constituency interests, especially the labor unions’ shift toward protectionism, became paramount. On the flip side, the Republican Party maintained a consistent pro-free trade stance until the 2016 election of President Trump marked a notable pivot toward protectionism within the GOP. This evolving landscape underscores a departure from predictable party stances on trade policy, revealing a complex arena of intra-party diversity and shifting priorities that defy simple categorization by party lines.

Theory

What factors influence congressional positions on trade policy in the absence of strong constituency and partisan constraints? Ideology is one possibility. Consistent with Fenno’s goal of seeking good public policy, Kucik and Moraguez argue that free trade encompasses a strong ideological element.Footnote 52 This notion pertains to individual and collective views on government involvement in the market, the dynamics of wealth distribution, and the principles of market autonomy. Generally, individuals with conservative ideologies lean toward a philosophy of minimal governmental interference in economic activities, rooted in the trust that markets can regulate themselves effectively. This philosophy often translates into a robust endorsement of free trade policies. Conversely, those with more progressive viewpoints argue for a proactive government role in the economy to address economivc disparities. Such individuals advocate for “fair” trade, prioritizing considerations like environmental and labor standards, which can lead to a more cautious stance toward free trade agreements.

But it is more complicated than a unidimensional ideological spectrum would suggest. The debate around free trade also intersects with nationalist or domestic priorities that don’t align neatly with the traditional left-right ideological divide. For instance, some right-wing legislators, despite generally agreeing with conservative economic principles, critique free trade for not serving the national interest or enhancing the United States’ global stature. A recent poll from Pew Research highlights these ideological complexities, finding a significant portion of Tea Party supporters (63%) view free trade as bad for the United States.Footnote 53 As a result, politicians on the extreme right encounter a dual set of ideological challenges when navigating trade discussions.

Parallels exist on the extreme left as well, who oppose free trade primarily due to concerns over economic inequality and labor rights, fearing that it exacerbates income disparities and undermines labor standards in a race to the bottom. They also critique free trade for potentially eroding environmental protections and enhancing corporate power, arguing that such policies favor multinational corporations at the expense of national sovereignty and democratic governance. Additionally, their opposition is rooted in principles of global justice and solidarity, emphasizing the need for trade agreements to promote equitable development and prevent exploitation of developing countries.

So, opposition to free trade from the extreme left reflects a broader skepticism toward globalization and a preference for trade policies prioritizing social welfare, environmental sustainability, and equitable economic development over the interests of multinational corporations and unfettered market access. While the extreme right might share the skepticism toward free trade, their opposition often centers around nationalism, the preservation of cultural identity, and concerns about losing sovereignty to global institutions, showcasing how different ideological perspectives can lead to similar policy stances for various reasons. Consistent with this idea, Xie finds that ideological extremists of both parties’ congressional caucuses tend to oppose free trade and attack more moderate colleagues for promoting liberalization policies.Footnote 54

We are left with an intriguing puzzle. On the one hand, it would be reasonable to expect that the greatest support for President Trump’s tariff should come from the most extreme members of each party (the “populist wings” of both parties). More specifically, progressive MCs will support the auto tariff—despite their antipathy to President Trump—because protecting a major US manufacturing industry prevents trade liberalization’s detrimental effects, such as worsening labor conditions, employment opportunities, and wealth distribution.Footnote 55 Furthermore, conservative MCs, allied with President Trump’s nationalist/populist movement, have largely inherited his trade protectionist views.Footnote 56 To the contrary, MCs who are ideological moderates/political insiders (the “establishment wing” of both parties) have advocated for trade liberalization since the New Deal era and are expected to oppose the unprecedented anti-trade move by the Trump Administration. Therefore,

Ideological Extremity Hypothesis: The likelihood that an MC opposes President Trump’s auto tariff increases as their ideological extremity decreases, holding all else constant.

On the other hand, it may be that support for President Trump’s auto tariff remains ideological along traditional economic grounds. Karol’s research indicates that even in recent Congresses, ideological positions on economic issues have often followed a liberal-conservative spectrum.Footnote 57 Though Karol’s findings highlight a notable shift in the 1970s where the association between liberal and conservative ideologies and views on trade reversed, he finds evidence of a strong correlation in recent Congresses between ideology and stances on trade. Today’s ideological conservatives in Congress generally favor tariffs as measures to protect domestic industries and jobs, aligning with a more protectionist economic stance. Liberals oppose tariffs based on free trade principles and are concerned about negative impacts on the global economy and higher consumer costs. This division reflects a traditional ideological disagreement on economic policy, where support or opposition to trade measures like tariffs can be anticipated based on a member’s placement on the economic liberal-conservative continuum. Therefore,

Economic Ideology Hypothesis: The likelihood that an MC opposes President Trump’s auto tariff increases as they become more liberal, holding all else constant.

Data and methods

Our goal is to explain congressional position-taking on President Trump’s 2018 steel tariff. The dependent variable is whether an MC signed a 8 May 2019 letterFootnote 58 addressed to Director Kudlow urging him to “advise the President against imposing trade restrictions that could harm the auto sector and the American economy.” The letter was signed by 159 lawmakers in the 116th Congress, almost evenly split between Democrats (78) and Republicans (81), on behalf of the auto industry’s interests (signatories are listed in the Appendix). This includes “American auto workers, parts suppliers and retailers, dealers, service providers, and millions of consumers” who “depend on a healthy and competitive US auto industry.” The dependent variable is dichotomous, coded 1 if an MC signed the letter and 0 if they did not. We, therefore, utilize logistic regression. The unit of analysis is the individual member of Congress in the 116th House of Representatives (2019–2020).

We include two main categories of variables in our analysis. Following studies from Conley and others that find trade liberalization is decided largely by constituency and district factors, the first set of measures are relevant characteristics of the MC’s district.Footnote 59 The independent variables in this category are whether the district is home to an auto plant (District Auto Plant) or a steel plant (District Steel Plant). Both are coded 1 if the district is home to one or more plants and 0 otherwise. We expect the presence of an auto plant to increase the likelihood that an MC signs the letter; we expect the opposite for steel plants. Additionally, we account for two key groups that the proposed auto tariff would have directly impacted: the per capita total number of employees in steel (Steelworkers) and auto manufacturing industries (Auto Manufacturing Employees) in a state.Footnote 60 Finally, we include a novel measure for the importance of steel to a district. Steel Exclusions measures the total number of requests for exception from the original Section 232 steel tariff per district. Individual companies filed these requests under a process created by the Commerce Department to help alleviate the domestic economic pressures created by the tariff. We expect the number of exclusion requests in an MC’s district to be negatively correlated to the likelihood of signing the auto letter.Footnote 61

We include three additional controls for an MC’s constituency. The first is district partisanship (Trump 2016), measured as President Trump’s two-party vote share in the 2016 election. We expect higher Trump percentages to increase the likelihood that an MC supports President Trump’s tariff proposal, thereby decreasing the odds that they sign the letter. We also include a control for the percentage of the foreign-born district population (% Foreign Born). We include this measure due to the possibility that the underpinnings of tariff and immigration policies are related. Nationalism and globalism, for example, are at the heart of both policy debates, with nationalists preferring closed markets and borders and globalists preferring them open. Therefore, we expect the likelihood of signing the auto letter to increase (e.g., increased globalism) as foreign born increases, holding all else constant. Congressional district data were collected from the US Census Bureau and Dave Leip’s Atlas of US Presidential Elections.

Finally, following Karol’s argument that stances on trade are a function of party-linked groups’ preferences, we include measures for the amount of campaign contributions an MC receives from the auto (Auto Contributions) and steel producing (Steel Contributions) industries, respectively.Footnote 62 Both variables are logged due to the skewed nature of the data. Because both industries were on the opposite side of this issue, we expect the signs to be opposite. Specifically, we expect auto contributions to be positively related to the likelihood that an MC signs the letter and steel contributions to be negatively related. We obtained data on campaign contributions from OpenSecrets.

The second set of independent variables is a key focus of our paper: the member-specific variables of party and ideology. Party affiliation is coded one if the MC is a Democrat and zero if she is a Republican. We do not expect a strong party effect on the likelihood of signing the letter. Consistent with Karol, we measure MCs’ ideology using Lewis et. al’s first and second-dimension DW-NOMINATE scores (Ideology 1 and Ideology 2, respectively).Footnote 63 We also include an MC’s Ideological Extremity along this dimension, coded as the absolute difference between an MC’s first dimension DW-NOMINATE score and the chamber median. Given the recent rise in protectionist attitudes of both ends of the ideological spectrum,Footnote 64 we expect the likelihood of signing the letter (i.e., objecting to the steel tariffs) to increase as ideological extremity decreases. Not surprisingly, party, ideology, and Trump’s 2016 vote share are highly correlated in the 116th Congress. Due to multicollinearity, we isolate their effects in separate models.

Though consistent with Karol, including the second dimension DW-NOMINATE score (Ideology 2) marks a departure from most research on position taking in Congress. According to Poole, Rosenthal, and Hare, the meaning of the second dimension has “…largely shifted from representing regional differences (e.g., between northern and southern Democrats) within the parties to intra-party divisions that are more subtle and less clear.”Footnote 65 These divisions appear on votes such as raising the debt ceiling, domestic surveillance, and government funding bills. For the reasons covered above, we believe it is reasonable to include trade policy among those cleavages. For example, MCs who rank at the low end of this variable’s score list include not only progressives such as Representative Alexandria Ocasio-Cortez (D-NY) but also conservatives such as Representatives Justin Amash (I-MI), Chip Roy (R-TX), and Matt Gaetz (R-FL). Given the cross-cutting multidimensional nature of trade policy, we expect Ideology 2 to have a significant effect on whether an MC signed the letter.

Finally, we include measures for caucus and committee membership. Specifically, we control for whether the MC was a member of the Auto Caucus, Steel Caucus, and Ways and Means Committee which has jurisdiction over trade policy.

Results

We begin with two observations related to descriptive statistics. First, Figure 1 depicts the relationship between the two dimensions of the DW-NOMINATE ideology score by those who signed and did not sign the letter. What stands out is the ideological heterogeneity of both groups. There are no discernible ideological differences between those who signed and those who did not sign the letter. Indeed, there appears to be as much heterogeneity within the parties as across the parties. Each party—the Democrats grouped on the left side of the first dimension, Republicans to the right—contains an ideologically diverse set of MCs who signed (and did not) the auto letter. These preliminary findings support our expectation that positions on President Trump’s auto tariff differ from most issues in today’s partisan and highly polarized environment.

Figure 1. Ideology and signees scatterplot.

Industries have a lot to gain or lose from tariffs. Unsurprisingly, contributions from auto manufacturers reached all-time heights during the 2020 presidential election cycle, while contribution from steel producers equaled their all-time heights from the 2012 cycle. Figure 2 depicts these trends from 1990 to 2022. The total for the auto manufacturers is particularly compelling; in a striking illustration of the salience of tariff policy, their total contributions in 2020 more than double their totals from 2008, when bailing out the auto industry was a significant point of disagreement in Congress during the financial crisis. Furthermore, Figure 3 depicts the average contributions MCs received from the steel and auto-producing industries. Contributions are further broken into whether MCs signed the letter. On average, automakers contributed $7,057 to MCs who signed the auto letter versus $5,200 to those who did not. However, this is a statistically significant difference (p > .05). There is no difference between signees and non-signees in steel contributions. MCs received about $2,750 from steel producers regardless of their position on the auto tariff. So, on the one hand, MCs who signaled their opposition to the auto tariff averaged more contributions from the primary target of the tariff, auto manufacturers, than other MCs. On the other hand, there is no bivariate relationship between contributions from the secondary market—steel producers—and MCs’ positions.

Figure 2. Total Contributions from automobile and steel production industry, 1990–2022.

Source: Open Secrets (available at https://www.opensecrets.org/industries/indus.php?ind=m02&cycle=2020 and https://www.opensecrets.org/industries/indus.php?ind=n14&cycle=2020, accessed August 9, 2023).

Figure 3. Auto and steel contributions (vs. signatories).

Source: Open Secrets (available at https://www.opensecrets.org/industries/indus.php?ind=m02&cycle=2020 and https://www.opensecrets.org/industries/indus.php?ind=n14&cycle=2020, accessed August 9, 2023).

We now turn our attention to the main findings. First, Model 1 shows that Democrat is statistically insignificant, controlling for all else. As expected and consistent with Miler and Allee’s study, party had no effect on legislators’ positions on the auto tariff. However, Trump Vote Share (2016) is statistically significant at the .01 level.Footnote 66 In an indication of this issue’s complexity, the coefficient is positive, suggesting that the likelihood of an MC signing the letter opposing the tariff increases as Trump’s vote share in their district increases. Table 2 depicts changes in predicted probabilities, calculated from minimum to maximum values of each stastistically significant independent variable. Specifically, moving from the minimum value (4.9% in New York’s 15th district) to the maximum (80.4% in Alabama’s 4th district) increases the likelihood of signing the letter by about 56%.

Second, Model 2 shows that both dimensions of the DW-NOMINATE scores are statistically significant and positive. Moving from the minimum value of the first dimension (–.725, Representative Sylvia Garcia, TX-29) to the maximum (.883, Representative Andrew Biggs, AZ-5) increases the likelihood by 30%. The Economic Ideology Hypothesis is thus supported. The effect of the second dimension is large. Moving from the minimum value of the second dimension (–.924, Representative Alexandria Ocasio-Cortez, NY-14) to the maximum (.84, Representative Elizabeth Fletcher, TX-7) increases the likelihood by 61%.

Finally, Model 3 shows that Ideological Extremity is statistically significant and, as expected, negative. The Ideological Extremity Hypothesis is supported as well. Specifically, changing from the most moderate members of the House (Representative Max Rose of New York and Representative Elaine Luria of Virginia) to its most extreme member (Representative Andrew Biggs of Arizona) decreases the likelihood of signing the letter by 25%. As we stated above, this aligns with Xie’s finding and how today’s opponents of free trade appear to be among the most ideologically extreme in both parties. These findings suggest that ideological influences mattered to positions on President Trump’s auto tariff. They show that traditional economic ideologies intertwine with other concerns that are not explained solely by the first DW-NOMINATE dimension.Footnote 67 We will have more to say about this topic later.Footnote 68

There are several interesting results among the control variables as well. First, consistent with position-taking research generally, as well as Conley’s research on trade policy, district characteristics did matter to whether an MC signed the letter. The number of employees in a state’s auto manufacturing industry is particularly important. Auto Employees is statistically significant (p < .01) and positive in each model. Specifically, moving from the minimum (0, Alaska) to maximum (161.6, Michigan) employment increases the probability of signing the letter by about 55%. The relationship between employment and signatories is illustrated in Figure 4. The map shows the prominence of the auto industry in the nation’s Midwestern, Northern, and Southern regions. While not a perfect correlation, the percentage of those state’s congressional delegation that signed the letter was among the highest in the country.

Figure 4. State-level per capita auto manufacturing employees (10,000s). Note: Values depict the percent of a state’s total congressional delegation that signed the auto letter.

While employment in the auto industries increases pressure for MCs to sign the letter, the presence of steel plants does not. Steel Employees is statistically insignificant, suggesting that MCs are more responsive to car production than steel production regarding auto tariffs. However, the number of steel exclusion requests is statistically significant at the .05 level and negative in every model. On average, a one-unit increase in the logged number of requests decreases the likelihood of signing the auto letter by 18%. This suggests that as the importance of steel to an MC’s district increases, opposition to the auto tariff decreases. Finally, the percentage Foreign Born is statistically significant at the .01 level in every model. In each model, moving from the minimum value of foreign-born (1%, WV-3) to the maximum (57%, FL-25) increases the likelihood of signing the letter by about 52%. Table 3 depicts the districts with the top ten highest foreign-born populations. Six of the ten representatives on the list signed the letter. The only Republican on the list, Representative Mario Diaz-Balart (FL-25), did not sign the letter despite representing the highest foreign-born population in the nation.

Furthermore, according to Table 1, campaign contributions from the automotive industry (Auto Contributions) is statistically significant (p < .01) and, as expected, positive. Specifically, moving from the minimum to maximum values of the log of Auto Contributions increases the probability of signing the letter by about 18%. Steel Contributions, on the other hand, is significant in only Model 2. But, importantly, Model 2 shows a negative effect for steel contributions. This is consistent with our expectation that despite being longtime political and economic allies, auto and steel producers were on opposing sides of President Trump’s proposed auto tariff. The effects of contributions are consistent with Karol’s findings about a strong group-centered foundation of positions on trade policy. Of course, the relationship between an anti-auto tariff position and campaign contributions is likely endogenous. In other words, how can we be sure that contributions determined the position rather than vice versa? Scholars of non-roll call position-taking have long wrestled with this issue. Following Rocca and Gordon (Reference Rocca and Gordon2010, Reference Rocca and Gordon2013), we tested for the possibility of endogeneity by utilizing a system of two equations.Footnote 69 Our results suggested that endogeneity is not a serious concern in this case; like Karol’s findings, signing the letter was likely more a function of support from attentive groups rather than the other way around. Furthermore, the overall robustness of the auto contributions effect bolsters our confidence. Indeed, it is among the robust findings in the model.

Table 1. Main results

Note: The dependent variable is coded 1 if an MC signed the letter to Director Kudlow objecting to President Trump’s proposed auto tariff. Standard errors are in parentheses.

*p < .1; **p < 0.05, ***p < 0.01.

Table 2. Predicted probabilities

Note: Changes in predicted probabilities were calculated from minimum to maximum values of the relevant independent variable, holding all else constant at their means.

Table 3. Top ten foreign-born populations vs. signatories

All other control variables are consistently insignificant across all models. Belonging to the steel or auto caucuses did not matter to signing the letter or whether they belonged to Ways and Means. Finally, at least one auto or steel plant in an MC’s district did not affect their position on the auto tariff. In the case of auto plants, the presence of statewide auto employment likely diminishes the explanatory value of District Auto Plant. Though multicollinearity is not a concern here, the broader economic impact of statewide auto employment likely absorbs the variance otherwise attributed to local auto plant presence.

Discussion and conclusion

President Trump’s unprecedented steel and aluminum Section 232 tariffs received strong reactions from political and economic groups. On the one hand, those who supported the tariffs—US steel makers, especially—argued that the tariffs were necessary to protect the US steel industry from unfair trade practices, particularly from China. On the other hand, opponents—particularly steel’s downstream users such as US automakers—railed against the potential for untenable price hikes and lost jobs. The US steel and auto industries were again pitted against one another in 2018 when President Trump proposed a cascading tariff on imported auto parts. This potential new round of tariffs pushed a bipartisan pool of 159 members of the 116th House to write a letter opposing the trade redistricts to Director of the National Economic Council Larry Kudlow. Our study finds the following factors predict whether an MC chose to sign the letter: (1) some district factors, such as the presence of auto plants, the percentage of the district that is foreign-born, and Trump’s 2016 vote share; (2) campaign contributions from the auto industry; and, importantly, (3) ideology of the MC. Party affiliation of the MC only had a trivial effect.

In many respects, these findings echo those of classic studies of position-taking in Congress and a combination of recent examinations of trade policy specifically. First and foremost, the electoral connection matters to trade policy. Consistent with Karol’s research, MCs’ decision to sign the letter opposing the auto tariff was driven by attentive groups in their home district or state, evidenced by the robust effect of contributions from the auto industry. The number of autoworkers was also important, which aligns with Miler and Allee’s findings about the importance of pragmatic considerations.Footnote 70 Foreign-born population and Trump’s 2016 vote share also mattered, consistent with Conley’s research on how important district demographics can be to trade policy decisions.Footnote 71 In all, despite the public’s lack of knowledge of trade policy, positions on Trump’s auto tariff did not depart significantly from other instances of position-taking where electoral goals reign supreme.Footnote 72

That said, our analysis revealed two aspects of the auto-tariff signing that differ from most congressional position-taking. First, the effect of the party is nonexistent, which is unusual in today’s polarized Congress. This is consistent with Miler and Allee’s findings that legislators often transcend traditional party lines to advocate for trade measures that benefit their constituents directly. This behavior reflects a strategic departure from normal partisan dynamics, suggesting that the complexities of trade policy elicit a more nuanced form of representation. Legislators, whether Republican or Democrat, appear equally likely to oppose protectionist actions when these contradict the interests of their district or state. This underscores a pragmatism that belies the rigid partisan divisions observed in other policy areas.

However, unlike Miler and Allee, we find that ideology mattered greatly to MCs’ stances on the auto tariff. First, consistent with Karol, after controlling for other factors, we find a robust effect of ideology along traditional liberal-conservative economic grounds. Like most position-taking, the first dimension of the DW-NOMINATE score remained a strong predictor of whether an MC signed the tariff letter. Our analysis also highlighted the nuanced role of ideological extremity. MCs on both ideological extremes were more likely to oppose the auto tariff, supporting the Ideological Extremity Hypothesis. This opposition illustrates broader ideological critiques: the extreme left focusing on labor, equality, and environmental concerns, and the extreme right on national sovereignty and cultural identity. This highlights the complexity of ideological influences on trade policy, revealing a convergence of concerns across the ideological spectrum about the implications of globalization. It challenges the notion that economic self-interest alone guides legislative behavior on trade policies.

This point is further emphasized by the robust effect of the DW-NOMINATE score’s second dimension. It is safe to say that scholars of position-taking have largely ignored the second dimension. Few studies control for it, and even fewer treat it as core to their theory. This is likely because scholars of the US Congress are genuinely confused by the measure. While Poole and Rosenthal originally explained that the dimension captures race-related issues,Footnote 73 it has since been reframed as picking up differences within the major parties over salient issues of the day.Footnote 74 For the middle of the twentieth century, for instance, this was civil rights. Harry Enten from FiveThirtyEight argues that the dimension may also capture an establishment versus anti-establishment dimension.Footnote 75

As Clinton, Katznelson, and Lapinski have noted, one might question why scholars estimate a two-dimensional model only to largely ignore the second dimension when tackling substantive topics.Footnote 76 Indeed, the second dimension’s significant role in explaining congressional positions on the auto tariff adds to our understanding of trade policy debates. Traditional models of congressional behavior do not fully capture the nature of legislators’ positions on trade. Indeed, the significance of the second dimension suggests a distinctive set of influences guiding legislators’ decisions. This aspect is particularly intriguing in trade policy, a field already fraught with complexities due to its intersection with global economics, national interests, and local constituency concerns. The second dimension, historically tied to race-related issues but now reflecting intra-party divergences on pressing contemporary matters, suggests a nuanced and somewhat unpredictable component to legislators’ stances on trade. Recognizing this additional component challenges scholars to continue to examine position-taking on trade in Congress, particularly as President Trump reshapes the Republican Party. It invites a deeper exploration into how evolving political landscapes, personal convictions, and emerging issues of the day shape trade policy debates, marking a departure from the predictability of partisan and ideological divides. We suspect the second dimension might matter in position-taking on other issues, particularly those that pit party allies against one another. Debates surrounding marijuana legalization, the debt ceiling, and regulating Big Tech come to mind.

As we note above, it is tempting to equate conservatism in the 116th House with President Trump’s MAGA stances. However, one of the most important findings of our analysis is that this is not the case. While the MAGA movement has undoubtedly influenced conservative ideology, there remains substantial heterogeneity within the Republican Party. Specifically, our analysis reveals that some conservative members of Congress continue to adhere to traditional free trade principles, demonstrating that alignment with MAGA is not uniform. This insight is particularly significant given the centrality of trade and tariff policy in President Trump’s administration, where protectionist policies were a defining feature of his economic agenda. Despite this, our findings show that many Republican members of Congress maintained support for free trade, highlighting ideological diversity within the GOP on a salient policy issue.

This heterogeneity is further reflected in President Trump’s struggles with congressional support during his tenure, even with Republican majorities. Despite high levels of vocal support from Republican lawmakers, Trump faced significant challenges in enacting key parts of his agenda, including healthcare and immigration reform.Footnote 77 His confrontational style and inconsistent policy positions often hindered his ability to build the coalitions needed for major legislative victories.Footnote 78 While Trump’s success rates in congressional votes were consistent with expectations given the political context,Footnote 79 his presidency was marked by limited policy achievements, government shutdowns, and increasing partisan.Footnote 80 As Lee notes, these struggles illustrate the limits of Trump’s influence and point to deeper ideological divisions within the GOP, particularly on issues such as trade, where traditional free-market conservatism and MAGA-style protectionism are often in conflict.Footnote 81

One limitation of our study is that it focuses on a single instance of position-taking—signing a letter in opposition to President Trump’s proposed auto tariffs. While we are confident in the robustness of our results, we recognize that studying a broader range of position-taking behaviors could provide a more comprehensive understanding of the shifting landscape of trade policy in the US Congress. Future research could examine other forms of position-taking, such as speech-making, bill sponsorship, cosponsorship, or even social media activity like tweets. Such work would provide additional insights into how members of Congress navigate trade policy in response to evolving political, ideological, and economic pressures.

President Trump’s Section 232 tariffs—first on steel and aluminum and later on downstream products—touched a nerve. They turned two of America’s most storied and interconnected industries, steel producers and automakers, into adversaries. It also made allies out of bitter political enemies, with Representatives James Clyburn and Jim Jordan signing onto the same position. Even Trump’s Democratic successor, President Joe Biden, cemented the tariffs in 2022, but only after making concessions to crucial allies such as the European Union.Footnote 82 Such is the chaotic nature of trade and tariff policy in today’s political and economic environment, particularly in the Republican Party. Time will tell whether President Trump’s staunch opposition to free trade defines the current stance of the GOP or President Ronald Reagan’s perspective that open trade is “one of the key factors behind [the U.S.’] great prosperity” will prevail.Footnote 83

Competing interests

The authors declare none.

Appendix

Aguilar, Pete (CA-31), D

Allred, Colin (TX-32), D

Armstrong, Kelly (ND-1), R

Arrington, Jodey (TX-19), R

Bacon, Don (NE-2), R

Baird, James (IN-4), R

Barr, Andy (KY-6), R

Barragan, Nanette (CA-44), D

Bera, Ami (CA-7), D

Bergman, Jack (MI-1), R

Beyer, Don (VA-8), D

Biggs, Andy (AZ-5), R

Bilirakis, Gus (FL-12), R

Bishop, Sanford (GA-2), D

Bonamici, Suzanne (OR-1), D

Brooks, Susan (IN-5), R

Brownley, Julia (CA-26), D

Bucshon, Larry (IN-8), R

Budd, Ted (NC-13), R

Bustos, Cheri (IL-17), D

Butterfield, G.K. (NC-1), D

Byrne, Bradley (AL-1), R

Calvert, Ken (CA-42), R

Carbajal, Salud (CA-24), D

Carter, Buddy (GA-1), R

Castro, Joaquin (TX-20), D

Chabot, Steve (OH-1), R

Clay, William Lacy, Jr. (MO-1), D

Cline, Ben (VA-6), R

Clyburn, James (SC-6), D

Cohen, Steve (TN-9), D

Cole, Tom (OK-4), R

Comer, James (KY-1), R

Connolly, Gerald (VA-11), D

Cooper, Jim (TN-5), D

Correa, Lou (CA-46), D

Costa, Jim (CA-16), D

Courtney, Joe (CT-2), D

Cox, TJ (CA-21), D

Crawford, Eric (AR-1), R

Crist, Charlie (FL-13), D

Cuellar, Henry (TX-28), D

Cunningham, Joe (SC-1), D

Cardenas, Tony (CA-29), D

Davidson, Warren (OH-8), R

Davis, Danny (IL-7), D

Davis, Susan (CA-53), D

Deutch, Theodore E. (FL-22), D

Dingell, Debbie (MI-12), D

Duncan, Jeff (SC-3), R

Dunn, Neal (FL-2), R

Delbene, Suzan (WA-1), D

Emmer, Tom (MN-6), R

Espaillat, Adriano (NY-13), D

Estes, Ron (KS-4), R

Ferguson, Drew (GA-3), R

Fleischmann, Charles (TN-3), R

Fletcher, Lizzie (TX-7), D

Foster, Bill (IL-11), D

Gomez, Jimmy (CA-34), D

Gonzalez, Vicente (TX-15), D

Gottheimer, Josh (NJ-5), D

Griffith, H. Morgan (VA-9), R

Hartzler, Vicky (MO-4), R

Himes, James (CT-4), D

Hollingsworth, Trey (IN-9), R

Horn, Kendra (OK-5), D

Huizenga, Bill (MI-2), R

Hurd, Will (TX-23), R

Jeffries, Hakeem (NY-8), D

Johnson, Bill (OH-6), R

Johnson, Dusty (SD-1), R

Johnson, Eddie Bernice (TX-30), D

Johnson, Hank Jr. (GA-4), D

Johnson, Mike (LA-4), R

Jordan, Jim (OH-4), R

Kelly, Trent (MS-1), R

Khanna, Ro (CA-17), D

Kilmer, Derek (WA-6), D

Kind, Ron (WI-3), D

Kinzinger, Adam (IL-16), R

Kustoff, David (TN-8), R

Larsen, Rick (WA-2), D

Lawrence, Brenda (MI-14), D

Lawson, Al (FL-5), D

Loebsack, David (IA-2), D

Long, Billy (MO-7), R

Loudermilk, Barry (GA-11), R

Lowenthal, Alan (CA-47), D

Luria, Elaine (VA-2), D

LaHood, Darin (IL-18), R

Marchant, Kenny (TX-24), R

Marshall, Roger (KS-1), R

Massie, Thomas (KY-4), R

Meeks, Gregory (NY-5), D

Meng, Grace (NY-6), D

Miller, Carol (WV-3), R

Mitchell, Paul (MI-10), R

Moolenaar, John (MI-4), R

Murphy, Stephanie (FL-7), D

McAdams, Ben (UT-4), D

McBath, Lucy (GA-6), D

McClintock, Tom (CA-4), R

McMorris Rodgers, Cathy (WA-5), R

Newhouse, Dan (WA-4), R

Norman, Ralph (SC-5), R

O’Halleran, Tom (AZ-1), D

Olson, Pete (TX-22), R

Palazzo, Steven (MS-4), R

Palmer, Gary (AL-6), R

Panetta, Jimmy (CA-20), D

Perlmutter, Ed (CO-7), D

Peters, Scott (CA-52), D

Porter, Katie (CA-45), D

Ratcliffe, John (TX-4), R

Rice, Kathleen (NY-4), D

Roby, Martha (AL-2), R

Roe, Phil (TN-1), R

Rogers, Harold (KY-5), R

Rouda, Harley (CA-48), D

Ruiz, Raul (CA-36), D

Rutherford, John (FL-4), R

Schneider, Bradley (IL-10), D

Schrader, Kurt (OR-5), D

Schweikert, David (AZ-6), R

Scott, Austin (GA-8), R

Scott, David (GA-13), D

Sewell, Terri (AL-7), D

Shalala, Donna (FL-27), D

Shimkus, John (IL-15), R

Simpson, Michael (ID-2), R

Sires, Albio (NJ-8), D

Smith, Adrian (NE-3), R

Stevens, Haley (MI-11), D

Stivers, Steve (OH-15), R

Suozzi, Tom (NY-3), D

Takano, Mark (CA-41), D

Taylor, Van (TX-3), R

Thompson, Bennie (MS-2), D

Thornberry, Mac (TX-13), R

Timmons, William (SC-4), R

Tipton, Scott (CO-3), R

Torres Small, Xochitl (NM-2), D

Torres, Norma (CA-35), D

Upton, Fred (MI-6), R

Van Drew, Jeff (NJ-2), R

Vela, Filemon (TX-34), D

Wagner, Ann (MO-2), R

Walberg, Tim (MI-7), R

Walden, Greg (OR-2), R

Walker, Mark (NC-6), R

Walorski, Jackie (IN-2), R

Watkins, Steve (KS-2), R

Wenstrup, Brad (OH-2), R

Wexton, Jennifer (VA-10), D

Williams, Roger (TX-25), R

Womack, Steve (AR-3), R

Woodall, Rob (GA-7), R

Wright, Ronald (TX-6), R

Footnotes

1 CNN, 7 March 2018; Congressional Research Service (2020).

2 New York Times, 15 January 2020; See also: https://ustr.gov/issue-areas/enforcement/section-301-investigations/tariff-actions (accessed 21 August 2023).

3 CNN, 7 March 2018; The Guardian, 2 April 2018; NBC News, 4 December 2018; CNBC, 4 August 2019.

4 Congressional Research Service (2021).

5 Kennedy (1989).

6 Federal Trade Commission (1977); Tarr (Reference Tarr and Robert1988).

7 Dayton Daily News, 9 March 2018. “AK Steel CEO: Saving American Steel Vital for National Security.”

8 In one particularly blistering editorial, the Wall Street Journal called the tariff a “ruse,” arguing that it was not only unnecessary given increases in steel domestic production capacity but driven mostly by the President’s desire for the “power to act unilaterally” (Wall Street Journal, 12 March 2018).

9 NBC News, 8 March 2018.

10 E.g., Wall Street Journal, 9 November 2018; Reuter, 17 January 2019.

11 Reuter, 26 September 2018.

12 The Street, 30 June 2018.

13 U.S. Department of Commerce (2018).

14 Forbes, 27 June 2018.

15 Politico, 19 July 2018.

16 The full letter can be found here: https://sewell.house.gov/sites/sewell.house.gov/files/232%20Letter%20to%20Trump%20Admin.pdf (accessed 21 August 2023).

18 Mayhew (Reference Mayhew1974), 16.

20 E.g., Canes-Wrone, Brady, and Cogan (Reference Canes-Wrone, Brady and Cogan2002); Jones (Reference Jones2003); Bovitz and Carson (Reference Bovitz and Carson2006).

21 E.g., Rocca and Sanchez (2008); Rocca and Gordon (2010).

22 E.g., Koger (2003); Harward and Moffett (Reference Harward and Moffett2010); Morin, Torres, and Collingwood (Reference Morín, Torres and Collingwood2021).

23 E.g., Grimmer (Reference Grimmer2013).

24 E.g., Rocca (Reference Rocca2007); Pearson and Dancey (2011); Lauderdale and Herzog (2016).

26 E.g., Miler and Allee (2018).

27 Marks (1993).

28 Conley (Reference Conley1999); Baldwin and Magee (Reference Baldwin and Magee2000).

29 Holian, Krebs and Walsh (Reference Holian, Krebs and Walsh1997).

30 Kahane (1996); Baldwin and Magee (Reference Baldwin and Magee2000).

32 Kang and Greene (Reference Kang and Kenneth1999).

35 Margalit (Reference Margalit2011).

36 Box-Steffensmeier, Arnold, and Zorn (Reference Box-Steffensmeier, Arnold and Christopher1997).

38 Guisinger (Reference Guisinger2009).

39 Rho and Tomz (Reference Rho and Tomz2017).

40 Converse (Reference Converse1964); Miller and Stokes (Reference Miller and Stokes1963); Lindsay (1994)

41 Uscinski, Rocca, Sanchez, Brenden (2009).

42 See, for example, Karol (Reference Karol2009).

44 Miler and Allee (2018).

45 But see Weller (Reference Weller2009), who finds that party affects roll call voting on trade policy after holding constituency factors constant.

46 E.g., Kahane (1996); Irwin and Kroszner (Reference Irwin and Kroszner1999); Milner and Judkins (2004).

48 Irwin and Kroszner (Reference Irwin and Kroszner1999); Irwin (2017); Karol (2000, Reference Karol2009)

49 Uslaner (Reference Uslaner2000); Irwin (Reference Irwin2017), 658–660.

51 Two TPAs has been passed in Congress since early 1990s, in the year 2002 and 2015, respectively. The TPA bills were passed when GOP controlled both chambers of Congress, a majority of GOP lawmakers voted for it, and the majority of Democratic lawmakers voted against it. For the 2015 TPA, please see: https://clerk.house.gov/Votes/2015374, and https://www.senate.gov/legislative/LIS/roll_call_votes/vote1141/vote_114_1_00219.htm. The final version of the 2015 TPA was attached to an unrelated House bill, H.R. 2146. For the 2002 TPA, please see: https://clerk.house.gov/Votes/2001481 and https://www.senate.gov/legislative/LIS/roll_call_votes/vote1072/vote_107_2_00207.htm.

52 Kucik and Moraguez (2017).

55 Raess, Dür, and Sari (2018); Osgood (2022); Osgood and Ro (Reference Osgood and Ro2022).

56 Stokes (2016); AP News, 7 June 2019; Younis (Reference Younis2021).

58 The full letter can be found here: https://sewell.house.gov/sites/sewell.house.gov/files/232%20Letter%20to%20Trump%20Admin.pdf (accessed 21 August 2023).

60 We were unable to locate steel and auto manufacturing totals at the congressional district level through the US Census, so we used statewide employees as a proxy. Auto manufacturing includes both motor vehicle and parts manufacturing.

61 Data for exception requests are available from the Commerce Department here: https://232app.azurewebsites.net/ Index. We log the number of total requests due to the skewed nature of the data.

62 Karol (2009).

63 Lewis, Poole, Rosenthal, Boche, Rudkin, and Sonnet (Reference Lewis, Poole, Rosenthal, Boche, Rudkin and Sonnet2024).

64 Stokes (2016); Goldstein, Judith and Gulotty (Reference Goldstein and Gulotty2019); CNBC, 20 September 2019; AP News, 7 June 2019; Baccini and Weymouth (Reference Baccini and Weymouth2021); Younis (Reference Younis2021); Osgood (2022); Osgood and Ro (2022).

65 Poole, Rosenthal, and Hare (Reference Poole, Rosenthal and Hare2015).

66 Though not shown in Table 1, Trump 2016 is also highly significant when Democrat is excluded from the model. Democrat remains insignificant when Trump 2016 is excluded.

67 It may be tempting to equate conservatism in the 116th Congress with President Trump’s Make America Great Again (MAGA) platform and, therefore, a departure from traditional conservative ideology. However, statistical analyses show that the ideological distribution and mean of Republicans’ DW-NOMINATE scores in the 116th Congress were no different from previous Congresses, including those during President Obama’s administration. For instance, t-tests indicate that the mean DW-NOMINATE score for House Republicans in the 116th Congress was statistically indistinguishable from those in the 113th, 114th, and 115th Congresses. Furthermore, the kernel density plots are nearly identical. A two-sample Kolmogorov–Smirnov (K-S) test shows no significant difference in the distribution of DW-NOMINATE scores for Republicans across the 113th to 116th Congresses. This suggests that while MAGA rhetoric has influenced some members of the GOP, the overall ideological positioning within the Republican Party did not undergo significant change across these Congresses. (Results for t-tests, kernel density plots, and K-S are available upon request.)

68 To test the robustness of our results, we also used Duck-Mayr and Montgomery’s ideology scores as alternatives to Lewis et al.’s measure. The results remain unchanged, indicating that our conclusions are robust across different measures of ideology.

69 The first equation, used to predict campaign contribution from the auto industry, sets up an instrumental measure to be included in the second equation, which predicts whether an MC signed the auto letter. The first equation is nearly identical to the second, with two exceptions. First, we exclude contributions from the steel industry for theoretical reasons; we do not expect steel contributions to determine auto contributions. Second, we include an MC’s benchmarked legislative effectiveness score (Volden and Wiseman 2014), measured as the ratio of their actual legislative effectiveness score (LES) to their predicted LES score (available at https://thelawmakers.org). Following Box-Steffensmeier and Grant (Reference Box-Steffensmeier and Tobin Grant.1999), we expect effectiveness to increase campaign contributions. The results in the first equation support this expectation; the benchmarked LES is significant and positive. The instrument in the second model, however, is statistically insignificant. All other findings are almost identical to those shown in Table 1. The two-stage equation results are available upon request.

70 Miler and Allee (2018).

73 Poole and Rosenthal (1991).

74 See https://voteview.com/about (accessed 14 July 2023).

77 Edwards (Reference Edwards2021); Smith (2021).

78 Pearson (2017).

80 Edwards (Reference Edwards2021); Smith (2021).

81 Lee (2018).

82 Bloomberg, 10 December 2022.

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Figure 0

Figure 1. Ideology and signees scatterplot.

Figure 1

Figure 2. Total Contributions from automobile and steel production industry, 1990–2022.Source: Open Secrets (available at https://www.opensecrets.org/industries/indus.php?ind=m02&cycle=2020 and https://www.opensecrets.org/industries/indus.php?ind=n14&cycle=2020, accessed August 9, 2023).

Figure 2

Figure 3. Auto and steel contributions (vs. signatories).Source: Open Secrets (available at https://www.opensecrets.org/industries/indus.php?ind=m02&cycle=2020 and https://www.opensecrets.org/industries/indus.php?ind=n14&cycle=2020, accessed August 9, 2023).

Figure 3

Figure 4. State-level per capita auto manufacturing employees (10,000s). Note: Values depict the percent of a state’s total congressional delegation that signed the auto letter.

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Table 1. Main results

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Table 2. Predicted probabilities

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Table 3. Top ten foreign-born populations vs. signatories