Introduction
The first level of OEP reflects micro-level interactions, including how individuals, firms, and industries form preferences and interests. Individual preferences are fundamental in the framework, and actors’ preferences can be deduced from economic theories (Lake, 2009). Two models have been influential in studying how the distributional consequences of trade shape individual preferences based on one’s production profile. The first is the Heckscher-Ohlin (HO) theorem, according to which countries should export and import goods based on their factor endowments. For example, a country with abundant labor and relatively scarce capital factors should export labor-intensive goods and import capital-intensive products and services.
Main body
Based on this theory, Stolper and Samuelson (1941) found out that factor endowment variance in a specific country determines the winner or loser of trade. In developed countries, this has meant that high-skill individuals will support trade openness, and low-skill individuals will support protection. Rogowski (1989) is the first work to test the validity of the Stolper-Samuelson (SS) model domestically. He argued that the SS model resolved conclusively that abundant factors suffer from protection and benefit from the liberalization of trade, and scarce factors benefit from trade and are harmed by trade liberalization (Rogowski, 1989). Rogowski (1989) hypothesizes that if the Stolper-Samuelson theorem is correct, coalitions should form along the factor lines based on the increasing or decreasing international trade.
The validity of the factor-endowment model in the research holds for various assumptions. Frieden utilized different assumptions “about mobility (the “Ricardo-Viner” or “specific factors” model) and collective action to predict coalition formation over international finance policy” (Alt & Gilligan, 1994, p. 167). Scheve and Slaughter (2001) innovatively apply a survey experiment to study individual trade preferences. Their work supports the factor-endowment model. Furthermore, Mayda and Rodrik (2005) find that the factor-endowment model holds worldwide.
The HO model assumes that factors are mobile across sectors. In contrast, the Ricardo-Viner (RV) model assumes that factors are not perfectly mobile. Thus, in the RV model, the distributional consequences of trade fall across industries. Those in import-competing industries suffer from falling incomes, while those in export-oriented industries benefit from trade. Thus, individuals working in import-competing industries would prefer protection over free trade. The findings based on these two models are mixed and inconclusive, but Scheve and Slaughter (2001) argue about the validity of the HO model. Hiscox (2002) finds that when factors are mobile, factor-based cleavages are formed. However, he also finds that when factors are immobile, industry-based coalitions are formed. Hiscox (2002) uses the different scales of return in different areas as a proxy for factor mobility. He argues that a class-based coalition is formed when mobility is high, as Rogowski (1989) suggested. However, when low intra-factory factor mobility is present, the coalition would emerge along the factory lines.
Notably, Irwin (1994) used British voting in 1906 to show that voting behavior was linked to the economic interests of constituents as determined by the international trade performance of the sector in which they are employed. Irwin’s (1994) work is the first to support the RV model using voting behavior in the 1906 British election in which trade was the crucial issue dividing two parties.
Recently, scholars have further examined the heterogeneity of firms and occupations. The logic behind the firm-based model is that only a small portion of firms engage in global economic activities. This makes more productive firms benefit from trade while less productive firms do not. In this case, the distributional consequence falls across firms, and we would expect firm–based cleavages. Kim (2017) found that firms within the same industry have different preferences for trade liberalization based on the extent to which their products are differentiated. “High levels of product differentiation eliminate the collective action problem faced by exporting firms while import-competing firms need not fear product substitution” (Kim, 2017, p.1). Bombardini’s (2005) set-up, firm size determines the benefits of lobbying. “New-new” trade theory attributes an even larger importance to the notion of firm size as it links the benefits from trade reform to firm size. These findings reflect a high variance in the heterogeneity of firms and occupations.
In addition, there is a model which provides an alternative perspective on the issue. According to the Occupation model, the winners and losers of globalization are determined by occupation characteristics (Owen and Johnston 2017). Specifically, the welfare consequences of trade depend upon the degree to which job tasks can be provided from abroad and the degree to which those tasks are competitive internationally. In this model, offshorability and task routineness determine trade preference.
Scholars have examined the non-economic and cultural factors shaping individuals’ preferences toward trade policy. Cultural factors include ideas/values and nootropic considerations. Mansfield and Mutz (2009) found that preferences toward globalization are based on nootropic evaluations rather than an individual’s economic self-interest. In other words, preferences are culturally shaped by people’s perceptions of how the economy is affected. Guisinger (2017) also finds support in favor of the nootropic mechanism. She finds that people’s perceptions about the impacts of trade are based on their beliefs and considerations of the costs and benefits of trade for the community and the country rather than on economic self-interest.
Conclusion
I think the OPE in individuals missed the rise of a non-state actor, such as social media can play a huge role in shaping individual preferences. Nowadays, any social media platform such as TikTok can be used as a soft power to spread misleading information about free trade. For example, Saudi Arabia is trying to bring more FDI to the countries, but a huge amount of misleading information on social media platforms targets uneducated people against that move. So, the rise of these new actors can affect individual decisions. Accordingly, individuals’ beliefs might be wrong because they received the information from low-credibility sources. Mansfield and Mutz (2009) tested Ricardo-Viner against the Heckscher-Olin Models, but neither model holds up empirically because people do not understand how free trade impacts them or their industry. Their attitudes are determined by how they believe trade impacts the country (economy and, in some cases, fear of others – an ethnographic impact). They find that the interpretation of education can be attributed to skill level because their results show that education level has similar impacts on trade preference for people in the workplace and retirees.
References
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