1. Introduction
The past decade has witnessed a notable reorientation of European Union (EU) trade policy (Meunier and Nicolaidis, Reference Meunier and Nicolaidis2019). Historically anchored in neoliberal principles and a bastion of openness and liberalization, economic and political developments in the past decade have led the EU to embrace a large array of initiatives and strategies that reflect a transition from a market-driven liberal approach to a more assertive, unilateral, and arguably less naïve stance on trade policymaking (Bauerle Danzman and Meunier, Reference Bauerle Danzman and Meunier2023). The so-called assertive trade policy of the European Commission, bolstered by the recently ratified Anti-Coercion Instrument and the Investment Screening Mechanism, is an example of this trend, along with a number of additional defensive initiatives designed to allow unilateral moves on the part of the EU (Freudlsperger and Meunier, Reference Freudlsperger and Meunier2024; Schmitz and Seidl, Reference Schmitz and Seidl2023). However, the question remains to what extent, and under what conditions, do individuals reflect anti-trade attitudes, or embrace international trade, across the EU.
Indeed, a substantial and growing body of work has been examining the individual-level drivers of mass attitudes towards international trade (for a comprehensive review, see Kuo and Naoi, Reference Kuo, Naoi and Martin2015). While earlier works, with mixed empirical results, tested the implications of economic trade theories that have distributional consequences at the individual level (e.g. Baker, Reference Baker2005; Mayda and Rodrik, Reference Mayda and Rodrik2005; Scheve and Slaughter, Reference Scheve and Slaughter2001), more contemporary studies have pointed to the interaction of both economic and non-economic factors that shape individual preferences (e.g. Johnston, Reference Johnston2013; Mansfield and Solodoch, Reference Mansfield and Solodoch2022). Scholars have pointed towards individuals’ economic welfare, such as their skill premium (O’Rourke and Sinnott, Reference O’Rourke and Sinnott2001), status of employment (Mansfield et al., Reference Mansfield, Mutz and Brackbill2019), and level of education (Hainmueller and Hiscox, Reference Hainmueller and Hiscox2006), as well as social and cultural factors. such as a cosmopolitan self-identity (Mansfield and Mutz, Reference Mansfield and Mutz2009; Mutz and Kim, Reference Mutz and Kim2017).
This research paper contributes to this literature by specifically adding to our knowledge of how residency in border regions influences public attitudes towards international trade, answering the question: Under what conditions are individuals more likely to support international trade? While previous works point to the significance of various economic and non-economic factors in shaping attitudes, the potential impact of geographic location has so far been under-theorized and under-researched. Studies have only considered location in terms of an import shock experienced by a region as a factor that might increase hostility towards open trade policies or globalization more broadly (Davenport et al., Reference Davenport, Dorn and Levell2021; Steiner and Harms, Reference Steiner and Harms2023).
However, border regions are likely to exert a unique and complex influence on attitudes towards international trade. For instance, internal border regions are typically more exposed to cross-border commercial activities, serving as hubs for the exchange of goods, services, commuting, and cross-border shopping. Therefore, the economic effects of international trade are likely to be more immediate and pronounced in these areas. External borders of a polity, however, can serve as a cultural and political divide between different communities, potentially sparking out-group anxiety.
The impact of geography on individual attitudes is thus complex and multifaceted. I shed light on this relationship by focusing on individuals across the European Union and by taking into account particular types of border residency on the one hand and using preferences towards different trade-related attitudes on the other. Instead of viewing borders as a uniform geographical location, I differentiate between EU borders (areas adjacent to other EU member states), non-EU borders (areas bordering non-EU countries), and maritime borders (regions near coastlines and key commercial ports). Additionally, I assess individuals’ support not just for a broad concept of international trade as the majority of studies have previously done, but for specific trade-related policies – i.e. opposition to import duties and support for EU trade agreements. I do so by proposing and testing five hypotheses using individual-level data from Eurobarometer 91.4 survey that reports on public support for trade policies (European Commission, 2019b) and providing details on Europeans’ attitudes on trade and EU trade policy – the only comprehensive EU survey specifically focused on trade policy (Eurobarometer has recently generated a follow up survey but the underlying data are not available). The survey was conducted on behalf of the European Commission by Kantar Public between the 9 May and 25 May 2019 with nationally representative samples of adults aged 15 years and older across EU members. Most importantly, it includes a dedicated module on attitudes on trade and EU trade policy, from which I draw several questions to construct dependent variables capturing individuals’ pro-trade sentiment, opposition to import duties, and support for EU trade agreements, as noted below.
This research paper subsequently makes several contributions. From a theoretical standpoint, it adds to the large and growing literature on individual-level trade attitudes (e.g.; Ehrlich and Maestas, Reference Ehrlich and Maestas2010; Mayda and Rodrik, Reference Mayda and Rodrik2005; Scheve and Slaughter, Reference Scheve and Slaughter2001; Spilker et al., Reference Spilker, Bernauer and Umana2018; Stiller et al., Reference Stiller, Dür and Huber2022) by examining the impact of geographic location on the public’s preferences. The paper specifically sheds light on if, and how, residing in a particular geographic area – here, borders – helps shape individuals’ attitudes. Secondly, the article contributes to border studies (e.g., Freudlsperger et al., Reference Freudlsperger, Lipps, Nasr, Schilpp, Schimmelfennig and Yildirim2024; Kuhn, Reference Kuhn2012; Schimmelfennig, Reference Schimmelfennig2021) by going beyond the consideration of borders as geographical demarcations, instead considering them as key entities that shape individuals’ attitudes.
From an empirical standpoint, I use the most granular individual-level data available in the EU, encompassing 7,033 respondents across eight EU countries. These micro-level data enable the inclusion of a range of demographic, regional, and national variables, allowing a more detailed analysis of attitudes. In addition, I consider individuals’ preferences towards specific trade policies, rather than merely considering international trade as a single, unified policy area. This distinction allows a nuanced understanding of individuals’ preferences in a time of growing geopoliticization of trade policy and weak support for open markets generally.
The paper proceeds as follows. Section 2 outlines baseline differences in support for trade policies in the EU and elaborates on whether and why individuals in border regions are more likely to have differential attitudes towards international trade. Section 3 provides the research design and the results of regression analysis conducted against a battery of controls drawn from the literature. Section 4 provides a summary of the results and avenues for future research.
2. Border Regions and Attitudes towards International Trade
I start with the empirical observation that individual-level support for international trade differs across regions. Consider Figures 1 and 2 that outline the mean support for two key trade policies. Figure 1 plots the average (mean) level of support for EU trade agreements by region type, while Figure 2 displays average (mean) opposition to import duties. Both figures rely on individual-level responses from Eurobarometer 91.4 at the NUTS-3 level and are grouped according to regional classification (EU border, non-EU border, non-border, and maritime border).
Average support for trade agreements across different regions.
Average opposition to import duties across different regions.
As a starting point, this variation is an interesting one. An intuitive expectation is that as EU borderlands see an upsurge in commercial activity on a daily basis, consisting of cross-border trade flows, shopping, and commuting, their tendency to support open trade policies can be expected to be stronger. Yet the descriptive data in Figure 1 shows that EU border residents are characterized by the lowest support for trade agreements, well below average and about 20% less then maritime border residents. In addition, EU border residents also show relatively lower opposition to duties – compared to non-EU border areas as shown in Figure 2. While EU and non-border regions see the free flow of goods and services without import duties, non-EU border residents are actually affected by duties, which is likely reflected in their opposition to import costs.
I also observe that maritime border regions are characterized by the highest support for EU trade agreements – as shown on Figure 1. This is an important observation, as maritime regions rely on trade and related industries (such as logistics) to generate employment (Musso and Ferrari, Reference Musso, Benacchio and Ferrari2000; OECD, 2014). It is possible that residents of these regions are relatively more receptive to open trade policies.
2.1 Unpacking Types of Border and Types of Policy
Few would disagree that individuals’ social and political experiences are in part shaped by where they live. Inhabitants of a particular city or region operate through social networks in their vicinity, go through daily experiences with issues resonating at the local level, and often mobilize over political issues channelled through local institutions. Therefore, where a person lives shapes their experiences, perceptions, and attitudes, creating contextual effects of a geographical area (e.g. Books and Prysby, Reference Books and Prysby1991; Enos, Reference Enos2017). Scholars have shown that social contexts that dominate particular geographical areas (e.g. border regions) are crucial for inhabitants’ experiences, perceptions, and attitudes (Ethington and McDaniel, Reference Ethington and McDaniel2007). An example is location-based cleavages that have generated a rural–urban division seen across the world, both within and across countries (e.g.; Jennings and Stoker, Reference Jennings and Stoker2016; Maxwell, Reference Maxwell2020).
Starting with the observation that geography matters for attitudes, border regions are a particular kind of geography that shapes individuals’ attitudes in the EU. Studies have shown that living in a border region is associated with a more positive view of the EU (Gabel, Reference Gabel1998; Gabel and Palmer, Reference Gabel and Palmer1995; Kuhn, Reference Kuhn2012). This is because border towns are characterized by closer economic and social exchange with each other, leading to a more positive and optimistic view of the EU. Individuals in these areas have greater opportunities to take advantage of the free movement of labour and free trade (Gabel and Palmer, Reference Gabel and Palmer1995, 8). Therefore, cross-border economic activity at the borders has the potential to increase individuals’ benefit from the Single Market (Schönwald, Reference Schönwald, Lechevalier and Wielgohs2013, 120). Work that is more recent has also shown that border regions have a distinct impact on public attitudes towards European integration (Nasr and Rieger, Reference Nasr and Rieger2024).
Considering the importance of geographical location, and border regions, on attitudes, I now turn to the implications for individuals’ attitudes towards different types of international trade policy.
EU economic integration in the past half a century has had one undisputed effect: trade barriers between EU Member States are virtually non-existent. Starting from the European Coal and Steel Community, successive rounds of initiatives, from the Rome Treaty to secondary EU legislationFootnote 1 and European Court of Justice case law,Footnote 2 have dismantled trade barriers and have led to an extremely successful economic integration, resulting in an unprecedented increase in trade flow between members and economic growth across the board (Badinger, Reference Badinger2005; Campos et al., Reference Campos, Coricelli and Moretti2019).
Such economic integration has important trade effects in EU border regions. Due to their location, EU land border regions have a unique characteristic in hosting cross-border exchange in commuting, cross-border shopping, and rendering of services (Hanson, Reference Hanson2005). Individuals can engage in regular commuting across countries and often venture across borders to make purchases in the neighbouring region due to differences in taxation and product prices and occasionally access or provide services – such as retail or other locally available amenities – within the framework of the EU’s Single Market. With both sides of EU borders experiencing relatively more commuting, shopping, tourism, and cross-border services, residents of these regions are likely to take unique advantages of cross-border commerce.
However, this privileged position does not necessarily translate into stronger pro-trade attitudes among EU border residents. First, since import taxes within the EU have been non-existent for some time, residents are likely to be indifferent towards further import liberalization; the absence of trade barriers is already their norm. Second, residents of EU borderlands may exhibit less aversion towards external trade partners, leading to reduced support for EU trade agreements. Over the past three decades, EU trade agreements have evolved into deep agreements that extend beyond goods to cover services, labour mobility, and regulatory standards (Lechner, Reference Lechner, Elsig, Hahn and Spilker2019; Mattoo et al., Reference Mattoo, Rocha and Ruta2020). While these agreements promise certain economic benefits, they also raise concerns about competition and even cultural identity threats (Lavenex et al., Reference Lavenex, Lutz and Hoffmeyer-Zlotnik2024). Considering that EU border residents already operate within a highly integrated cross-border environment marked by shared EU regulations, labour standards, and frictionless mobility, external PTAs introduce uncertainty, new competitors, different regulations, and potential erosion of these individuals’ advantageous position. EU border residents may thus perceive preferential trade agreements (PTAs) as facilitating greater external access and disrupting their local economies, reinforcing scepticism towards trade agreements that might introduce new competitors or even alter the cultural landscape (e.g., Decoville and Durand, Reference Decoville and Durand2018; Schönwald, Reference Schönwald, Lechevalier and Wielgohs2013). Therefore, despite benefiting from the Single Market, EU border residents are likely to be less supportive of EU trade agreements because they likely prefer protecting the status quo and preserving the exclusive advantages of EU integration. This leads to the following hypotheses:
H1: Residents of EU border regions are less likely to oppose import duties compared to residents of other border regions.
H2: Residents of EU border regions are less likely to support EU trade agreements compared to residents of other border regions.
Moving on to non-EU border regions, I expect selective support for international trade. Non-EU border regions experience even more heightened out-group anxiety due to closer proximity to non-EU countries. Residents of these regions are more likely to develop negative attitudes towards outsiders, stronger than the anxieties held by EU border residents.Footnote 3 Research shows that cross-border interactions can intensify fears, anxieties, and stereotypes about out-groups (Allport, Reference Allport1954; van Heerden and Ruedin, Reference van Heerden and Ruedin2019). For example, Dinas et al. (Reference Dinas, Matakos, Xefteris and Hangartner2019) and Hangartner et al. (Reference Hangartner, Dinas, Marbach, Matakos and Xefteris2019) demonstrate that exposure to out-group members such as migrants or foreign workers can heighten exclusionary preferences, as seen in the Swiss border region of Ticino (Mazzoleni and Pilotti, Reference Mazzoleni and Pilotti2015). Consequently, individuals in non-EU border regions are more likely to associate trade agreements with greater foreign influence, immigration, and competition in local labour markets, leading to heightened scepticism towards PTAs. This is in line with research showing that individuals consider the social and cultural consequences of trade alongside its economic benefits (Margalit, Reference Margalit2012; Mansfield and Mutz, Reference Mansfield and Mutz2009).
However, when it comes to import duties, the dynamics shift. Non-EU border residents may view import liberalization as economically advantageous, given that lowering tariffs would reduce the cost of goods and enhance access to a wider range of products. This creates an incentive for residents of these regions to oppose import duties, as it would directly benefit their economic wellbeing. These considerations lead to the following hypotheses:
H3: Residents of non-EU border regions are less likely to support EU trade agreements compared to residents of other border regions.
H4: Residents of non-EU border regions are more likely to oppose import duties compared to residents of other border regions.
Lastly, maritime border regions are expected to be characterized by increased support for international trade across the board. These areas are concentrated around major ports that serve as essential nodes in international trade networks, facilitating the movement of goods across international borders – in fact, approximately 80% of global merchandise trade is conducted over maritime routes (Stopford, Reference Stopford2009; UNCTAD, 2015). Such a central role in global trade means that ports in maritime border regions significantly increase trade flows, attract investment, strengthen industrial capacity, and boost regional economies (Blonigen and Wilson, Reference Blonigen and Wilson2008; Munim and Schramm, Reference Munim and H.J2018). The development of port infrastructure and the efficiency of logistics services have historically played a significant role in economic growth, as evidenced by the success of port cities across Europe and the world – Rotterdam, Hamburg, Riga, among others (Munim and Schramm, Reference Munim and H.J2018).
Trade-related economic advantages of these regions extend to their residents in two particular ways. First, ports in these areas generate employment opportunities, both directly through port operations and indirectly through related industries such as logistics and manufacturing. They facilitate participation in global value chains and help regions diversify and increase productivity gains. Second, maritime borders tend to lower import costs by reducing transportation costs, making goods more affordable for local consumers. Consequently, individuals living in maritime border regions are more likely to experience the advantages of such a trade hub and benefit from international trade, leading to higher levels of supportive attitudes. This leads to the following hypothesis:
H5: Residents of maritime border regions are more likely to support trade agreements and oppose import duties compared to residents of other border regions.
2.2 Data and Analysis
In order to test the validity of the hypotheses formulated above, I leverage individual-level data from the special Eurobarometer 91.4 survey focusing on Europeans’ attitudes towards EU trade policy and international trade (for details on this survey, see European Commission, 2019b; Leibniz Institute for the Social Sciences, 2019). Notably, the Eurobarometer 91.4 survey (European Commission, 2019b) stands out as the most comprehensive survey with a specific focus on trade policy. The data encompass information at the most fine-grained administrative level available (NUTS3) for eight EU countries – Ireland, Croatia, Lithuania, Estonia, Latvia, Malta, Luxembourg, and Slovenia – covering 7,033 individuals.
Except Ireland and the city-states of Malta and Luxembourg, the country coverage thus primarily reflects Eastern European countries, which is an advantage of this study for several reasons. First, Eastern EU members are yet to receive scholarly attention in respect of individual attitudes. While public opinion studies (e.g. Davenport et al., Reference Davenport, Dorn and Levell2021; Hays et al., Reference Hays, Ehrlich and Peinhardt2008; Schaffer and Spilker, Reference Schaffer and Spilker2019) overwhelmingly focus on the largest EU Member States, understanding the drivers of attitudes in Eastern Europe and Baltic countries requires insights that focus on aspects that are more crucial. Trade attitudes are consistently among the least positive in Eastern Europe and the Baltic States (European Commission, 2019b, 16–20). Thus, they constitute a crucial case to test the theoretical insights that look into the relationship between geographical location and attitudes towards trade. The results from the analysis will help us better understand what additional factors can account for support for open trade policies in countries characterized by low support in an era of unilateral, protectionist measures, geopolitical tensions, and lukewarm support for international trade across the board.
In order to operationalize my outcome of interest and capture attitudes towards the following two facets of international trade, I rely on several survey items from Eurobarometer 91.4. Opposition to import duties is captured by survey questions 8 and 12 that directly ask respondents whether the EU should increase duties on imported goods. Attitudes towards EU trade agreements are similarly captured by survey question 13 that asks individuals whether EU trade agreements help to create jobs in the EU, bring more choice and lower prices, and strengthen the EU’s position in the world as an economic power (see the online appendix for details on the survey items). As detailed below, I also estimate a latent variable on trade attitudes to capture a broad sentiment on international trade, similar to measures used in previous literature (e.g. Mayda and Rodrik, Reference Mayda and Rodrik2005).
The main independent variables are binary indicators of (non-)border residency, indicating whether a respondent resides in an EU border region, a non-EU border region, a maritime border region, or a non-border area that is primarily inland. I borrow the strategy employed by Nasr and Rieger (Reference Nasr and Rieger2024) and code all available NUTS3 regions in the data: an EU border area is coded if a NUTS3 region borders a European Union member state, a non-EU border region is coded if a NUTS3 region borders an extra-EU partner, a maritime border region is coded if a region is along a coastline and has a major commercial port,Footnote 4 and a non-border region is coded for the remaining regions that are primarily inland. If a region overlaps across border categories, I assign it to the category reflecting its predominant economic orientation. To illustrate this, and to show various border regions, I draw attention to Figure 3 that shows Lithuania, which borders Russia, Belarus, Latvia, and Poland as well as having a maritime border in the Baltic Sea. EU border regions at the NUTS3 level can be seen in blue stripes (primarily bordering Latvia), non-EU border regions in red stripes (e.g. Belarusian border), the maritime border region with the largest port of Klaipeda in dark blue, and non-border regions in green. Although Klaipeda borders both an EU and a non-EU country, its maritime commercial activity clearly dominates regional economic life; it is therefore coded as a maritime border region. It should be noted that such overlaps are rare – only around 10% of border regions exhibit multiple border types – and each was classified exclusively according to the most economically dominant boundary.
Coding of borders for the study: Lithuania.
An array of control variables are included in line with the literature. Respondents’ cosmopolitan views are captured with an index measure that takes into account individuals’ views on diversity and inclusion through several survey items, as outlined in the online appendix. Unemployment is included and operationalized as a binary variable equal to 1 for respondents who reported being unemployed. Occupational skill is coded 1 for respondents in skilled or technical occupations. Similarly, economic difficulty is included as a binary variable indicating whether respondents experienced financial hardship during the survey period. Education is coded 1 for respondents with tertiary education. Political orientation is coded 1 for respondents identifying as right leaning. Additionally, regional GDP (per capita) is integrated as well as demographic controls including age (a binary indicator coded as 1 for individuals aged 65 or older and 0 otherwise), gender, education level, political affiliation, and working-class self-identification. Lastly, the analysis incorporates regional (NUTS2) fixed effects in order to account for local unobserved heterogeneity across EU regions. Table 1 outlines the descriptive summary of the variables.
Summary statistics of the variables
2.3 Analysis and Discussion
An ordinary least squares (OLS) regression is used to unpack the relationship between living in different types of border regions and attitudes toward international trade. The results are presented in Tables 2 and 3. The left panel shows the models for the latent trade attitude index, which captures respondents’ overall sentiment toward international trade (explained below). The middle panel focuses on opposition to import duties, while the right panel presents results for support for EU trade agreements. Each panel reports a baseline model and a full model including all controls, with NUTS2 fixed effects applied in all specifications. Robust standard errors are used throughout, and full results including controls are reported in online appendix Table 1.
Impact of border residency on trade attitudes in the EU (OLS with NUTS2 fixed effects)
Notes: Robust standard errors in parentheses.
**** p < 0.001; *** p < 0.01; ** p < 0.05. * p < 0.1.
Pairwise tests of regional residence as predictor (marginal differences, EU-border residency as baseline)
**** Notes: p < 0.001; *** p < 0.01; ** p < 0.05. * p < 0.1.
The results reveal distinct patterns across the three trade-related outcomes, with particularly clear effects for opposition to import duties. First, I estimate a two-parameter logistic Item Response Theory (IRT) model to capture respondents’ overall trade sentiment. The model first attempts to use all theoretically relevant survey items on trade – perceived personal benefits from trade (QA1 and QA2), beliefs about protectionist import tariffs (QA6, QA8, and QA12), and positive evaluations of EU trade agreements (QA13) – to construct a continuous latent score representing each respondent’s underlying pro-trade orientation. However, several items (QA2, QA6, QA8, QA12) could not be included in the IRT because they produced convergence failures and near-zero/implausible discriminate on parameters. I therefore retained two key underlying trade-related policies:opposition to import duties and support for EU trade agreements as separate policy-specific outcomes. With regards to results, the differences between regions are modest. Residents of non-EU border regions exhibited a somewhat more positive overall orientation toward trade than EU-border residents (β = +0.120***), while respondents in maritime and non-border regions did not differ systematically from the EU-border baseline once controls were included (Table 2). Pairwise comparisons in Table 3 confirm that only the difference between EU and non-EU border residents reaches statistical significance. Adjusted marginal predictions from the full model (online appendix Figures 1–3) otherwise confirm this uniformity, suggesting that overall trade optimism is broadly shared across the EU.
Secondly, and most notably, geographic variation is highly pronounced for opposition to import duties. Residents of non-EU border (β = +0.075****), maritime (β = +0.086***), and non-border (β = +0.083****) regions are all significantly more likely to oppose import duties than EU-border residents. These differences remain stable across model specifications and are strongly supported by the pairwise tests (EU vs. all other categories: p ≤ 0.003). This pattern directly supports H1, which hypothesized lower support for duty reduction among EU-border residents, and H4, which proposed stronger pro-liberalization preferences among non-EU border residents. The equally strong effect for maritime regions is also consistent with H5, suggesting that coastal economies especially oppose import duties. The adjusted predictions (online appendix Figures 1–3) visualize this result clearly: most border regions cluster at higher levels of opposition to import duties relative to EU borders.
Thirdly, for support for EU trade agreements, the results suggest little systematic regional differentiation once controls are accounted for. Maritime region residents initially show a marginally higher likelihood of supporting EU trade agreements, but these differences disappear in the full model (Tables 2 and 3). Non-EU border and non-border residents display similar levels of support to their EU-border counterparts. Predicted values (online appendix Figure 3) similarly overlap across all border categories, pointing to a comparable consensus on supporting trade agreements within the EU. Accordingly, the results do not corroborate H2–H3, which suggest lower support for EU trade agreements among EU and non-EU border residents, and offer no clear evidence that maritime residents are more supportive of preferential trade agreements than other regions on this dimension of trade policy.
Beyond border types, several control variables display significant direction of association but are not discussed in detail to maintain focus on the main argument. For example, cosmopolitanism, higher education level, and regional GDP are positively associated with pro-trade views, while working-class identification and older age correspond with more protectionist attitudes (see online appendix Table 1). These results are consistent with previous research and confirm that individuals with a cosmopolitan outlook are more likely to endorse economic openness – except for trade agreements – respondents who are older tend to oppose trade liberalization, and those identifying as working class exhibit consistently negative trade attitudes, in line with evidence suggesting that labour, as a factor of production, captures only limited benefits from trade openness (Carrère et al., Reference Carrère, Olarreaga and Raess2022; Raess et al., Reference Raess, Dür and Sari2018).
In sum, the analysis provides strong evidence for H1 and H4 and partial support for H5, while H2 and H3 are not corroborated. The analysis underscores that while broad sentiment on trade is relatively uniform across Europe, residents’ exposure to different border environments strongly shapes their preferences for specific trade-related policies. EU-border residents – embedded within the Single Market – are markedly less concerned with import duties, whereas non-EU, maritime, and inland residents oppose import duties to a greater degree. In addition, non-EU border residents exhibit somewhat more positive overall trade attitudes. These patterns overall confirm that the geographic and economic context of borders remains a significant determinant of trade policy attitudes in the European Union.
3. Conclusion
This paper has argued that individual attitudes on international trade are, at least in part, shaped by their residency in border regions. I hypothesized that residing in border regions of different types influences individuals’ attitudes towards specific aspects of international trade policies, focusing on opposition to import duties, support for EU trade agreements, and a latent measure of general trade sentiment to assess whether these effects extend to broader orientations towards trade.
Relying on regression models using individual-level data from the Eurobarometer 91.4 survey, I demonstrated that geographic proximity to different borders does indeed have a significant impact on attitudes towards specific trade policies. Specifically, residents of non-EU and maritime borders are more likely to oppose import duties, whereas EU-border residents are less so. By contrast, support for EU trade agreements shows limited regional variation once controls are included, with only a weakly positive tendency among maritime residents. Differences in the latent trade attitude index are also modest overall: non-EU border residents display a somewhat more positive general trade sentiment than EU-border residents, but other contrasts remain statistically indistinct.
Additionally, cosmopolitan self-identity emerged as an important predictor of support for international trade across various models. This highlights the importance of non-economic factors – global-mindedness and a broader openness to international integration – in shaping positive trade attitudes. Importantly, the study also found that individual-level factors such as political affiliation, education, skill level, and economic experiences significantly contribute to shaping individuals’ trade attitudes.
These results contribute to the literature in several ways. First, they demonstrate that borders shape attitudes primarily through specific policy instruments rather than broad trade sentiment. Second, by integrating insights from border studies (Kuhn, Reference Kuhn2012; Schimmelfennig, Reference Schimmelfennig2021), the paper conceptualizes borders as economic and social spaces that condition exposure to trade flows and shape how individuals perceive the benefits and risks of trade openness. In doing so, it highlights that borders are not merely political demarcations but active economic interfaces that continue to structure perceptions of openness within the EU’s integrated market. This is particularly relevant in the European context, where the fluidity of borders is a hallmark of regional integration. Lastly, better understanding individual attitudes on trade help situate current debates on the geopoliticization of trade policy and the conditions under which free trade policies can be better maintained in the wake of growing challenges facing the global trade regime (De Bièvre and Poletti, Reference De Bièvre and Poletti2020; De Bièvre et al., Reference De Bièvre, Yildirim, Poletti, Elsig, Hoekman and Pauwelyn2017; Yildirim, Reference Yildirim2020; Meunier and Nicolaidis, Reference Meunier and Nicolaidis2019).
Further avenues of further research can be drawn. For example, in order to increase the external validity of the argument proposed, additional analyses should be conducted using individual-level data from a more extensive array of EU countries and border regions. Such an analysis could help determine whether the patterns observed here hold universally across the EU or are more pronounced in certain economic or geographic contexts. Additionally, expanding this research to include countries outside the EU, such as those within other economic unions like NAFTA or ASEAN, could provide comparative insights into how similar dynamics unfold in different institutional frameworks and cultural contexts. This broader approach would offer valuable perspectives on the generalizability of the findings and could illuminate whether the interplay of border proximity, perceived benefits, and trade policy support is a global phenomenon or uniquely an EU single market phenomenon.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S1474745625101432.
Acknowledgements
I extend my thanks to the anonymous reviewers and the editor of the World Trade Review, as well as to Theresa Kuhn, Frank Schimmelfennig, Giorgio Malet, and the audiences at the ECPR Standing Group on the European Union (SGEU) 2024 conference in Lisbon for helpful comments.
Funding
This work was supported by the European Union, European Research Council Advanced Grant number 101018300, EUROBORD.
Data Availability Statement
The data that support the findings of this study are openly available in Harvard Dataverse at: Yildirim, Aydin Baris, 2025, “Replication Data for: Border Regions and Attitudes Toward International Trade in the European Union”, https://doi.org/10.7910/DVN/59YFRC , Harvard Dataverse.
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