metadata: authors: 0: author: Barattieri,Alessandro Eugenio Maria
1: author: Mattoo,Aaditya
2: author: Taglioni,Daria
count: World
docna: 0: docna: Trade Effects of Industrial Policies : Are
            Preferential Agreements a Shield ?
docty: Policy Research Working Paper
abstracts: cdata!: This paper explores the effects of
            industrial policy on trade, focusing on the role of
            preferential trade agreements. The analysis uses data for
            the period 2012&#x2013;2022 on detailed product-level
            bilateral trade, industrial policy announcements, and rules
            on subsidies in different preferential trade agreements. The
            introduction of a new industrial policy measure in a
            destination market reduces export growth to that market on
            average by about 0.28 percent. However, exports from fellow
            members of preferential trade agreements are not adversely
            affected and may even be positively affected if the
            agreements have deep disciplines on subsidies. These
            findings suggest that preferential trade agreements have a
            shielding effect against the trade distorting effects of
            industrial policies.
display_title: Trade Effects of Industrial Policies
            : Are Preferential Agreements a Shield ?
listing_relative_url: /research/2024/06/34342334/trade-effects-industrial-policies-preferential-agreements-shield
topicv3: Trade m1326924 698,Industrial Policies m1504172 2847,Preferential Trade and Investment
            Agreements m1504283 2581
publishtoextweb_dt: 2024-06-17T00:00:00Z
dois: 10.1596/1813-9450-10806
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 26
author_keys: 0: author_key: 2055909
1: author_key: 429183
2: author_key: 1155075
model_extractions: Policy Research Working Paper 10806 Trade Effects of Industrial Policies Are Preferential Agreements a Shield?

_Alessandro Barattieri Aaditya Mattoo Daria Taglioni_ East Asia and the Pacific Region & Development Research Group August 2024 A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.
Policy Research Working Paper 10806

# **Abstract**

This paper explores the effects of industrial policy on trade, focusing on the role of preferential trade agreements. The analysis uses data for the period 2012–2022 on detailed product-level bilateral trade, industrial policy announcements, and rules on subsidies in different preferential trade agreements. The introduction of a new industrial policy measure in a destination market reduces export growth to that market on average by about 0.28 percent. However, exports from fellow members of preferential trade agreements are not adversely affected and may even be positively affected if the agreements have deep disciplines on subsidies. These findings suggest that preferential trade agreements have a shielding effect against the trade distorting effects of industrial policies.

This paper is a product of the Office of the Chief Economist, East Asia and the Pacific Region and the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at abarattieri@worldbank.org, amattoo@worldbank.org, and dtaglioni@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Trade Effects of Industrial Policies: Are Preferential Agreements a Shield?<sup>∗</sup> Alessandro Barattieri<sup>†</sup> Aaditya Mattoo<sup>‡</sup> Daria Taglioni<sup>§</sup> Originally published in the Policy Research Working Paper Series on _June 2024._ This version is updated on _August 2024._ To obtain the originally published version, please email prwp@worldbank.org.

JEL classification: F10, F14, F15, L52 Keywords: Industrial Policies, Trade, Preferential Trade Agreements

> ∗The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. We thank Maria del Mar Gomez Ortiz for outstanding research assistance. The authors acknowledge generous funding from the Umbrella Facility for Trade which is supported by the governments of The Netherlands, Norway, Switzerland, Sweden and the United Kingdom. All errors are ours.

> †World Bank & ESG UQAM. 1818 H Street, NW Washington, DC 20433 USA. abarattieri@worldbank.org

> ‡World Bank. 1818 H Street, NW Washington, DC 20433 USA. amattoo@worldbank.org

> §World Bank. 1818 H Street, NW Washington, DC 20433 USA. dtaglioni@worldbank.org

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We then investigate how Preferential Trade Agreements (PTAs) influence the impact of industrial policies. Since the second half of the 20th century, PTAs have been a significant feature of global trade, with their scope and depth increasing over the decades. According to the World Trade Organization, 369 regional trade agreements were in force in 2024, up from just 45 in 1995, the year the WTO was established (WTO, 2024). While pre-1995 agreements were primarily focused on reducing tariffs, more recent agreements are considered “deep” because they cover trade and investment in both goods and services as well as intellectual property rights, and a wider set of measures, including subsidies and labor and environmental standards.

When countries are involved in a PTA, the dynamics of how industrial policy affects trade flows can differ, generally fostering more positive outcomes for members. Most pertinently, PTAs can include rules on the types of industrial support allowed and the eligibility conditions (such as local content rules) that can be applied. These rules may alleviate the negative impact of industrial policies on imports from members.

We combine data for the period 2012-2022 on detailed product level bilateral trade, industrial policy (IP) announcements, and rules on subsidies in different PTAs. The econometric analysis controls for various confounding factors, and it yields three main conclusions. First, the introduction of a new industrial policy measure in a destination market reduces export growth to that market on average by about 0.28 percent. Second, exploring the interaction of industrial policy and the existence of a preferential trade agreement, we find that a newly introduced industrial policy measure reduces imports from non-members of a PTA while leaving imports from members of the PTA roughly unchanged. Third, using a measure of the depth of disciplines on subsidies in a PTA, we find that deep disciplines can lead to increased imports from members of a deep trade agreement, effectively making them beneficiaries of industrial policy. For a level of depth equal to that in the top 5 percent of the PTAs in the sample, the introduction of an industrial policy measure increases imports from other members by about 0.39 percent. These effects are robust to alternative econometric specifications, and to the exclusion of potential outliers. We suggest that PTAs provide a shielding effect against the potentially distortive trade effects of discriminatory industrial policies. This shielding effect appears to be heterogeneous across products and regions: it is more pronounced in industries such as chemicals and transport equipment, and for advanced and developing East Asian economies.

**Related Literature** Our work connects to several strands of the literature. Re- cent papers have studied the measurement of industrial policies and their

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potential effects.<sup>1</sup> Another strand or work connected to ours explored PTAs and their potential effects.<sup>2</sup> . Third, recent papers have explored the trade effects of subsidies, including those by the WorldBank (2023) and Rotunno and Ruta (2024). Finally, studies have investigated the interconnections between industrial and trade policies. Lashkaripour and Lugovskyy (2023) show that when unilateral adoption of corrective industrial policies is associated with trade barriers, countries risk _immiserizing growth_ and a global race to the bottom. Ju et al. (2024) provide a quantitative evaluation of the US-China trade and industrial policy competitions.

The rest of the paper is structured as follows: Section 2 illustrates the data and the empirical specification for the analysis. Section 3 illustrates the main findings. Finally, Section 4 concludes.

# **2 Data and Empirical Strategy**

## **2.1 Data**

We use three different datasets. The dependent variable consists of bilateral, product-level (HS 6-digit) trade data from Comtrade-BACI Gaulier and Zignago (2010), covering the period 2012-2022.<sup>3</sup> There are two key explanatory variables: a measure of new industrial policy announcements as catalogued by the Global Trade Alert database; and measures of preferential trade agreement membership and depth, as documented in the World Bank’s Deep Trade Agreements Database (Mattoo et al., 2020).

### **2.1.1 Global Trade Alert Database**

Established in response to the 2008 financial crisis, the Global Trade Alert (GTA) is the only comprehensive database and independent monitoring platform that provides timely information on state measures likely to affect world trade. The database includes measures that are traditionally considered protective, such as tariffs and quotas, as well as subsidies and other mechanisms that governments use to support domestic industries (see Figure 4). The database also classifies the measures into “restrictive” (red), “neutral” (amber) and “liberalizing” (green).

> 1See for instance Kalouptsidi (2018), Criscuolo et al. (2019), Liu (2019), Bartelme et al. (2019), Choi and Levchenko (2021), Juhasz et al. (2022), Lane (2022). Juhasz et al. (2023) offer an extended critical review of the literature.

> 2See for instance Freund and Ornelas (2010), Fernandes et al. (2021), Limao (2006), Limao (2007), Lim ̃ao (2016),Mattoo et al. (2021), Mattoo et al. (2022), Mattoo et al. (2021) and Romalis (2007)

> 3To eliminate possible distortions from outliers, we exclude bilateral product-level flows accounting for less than USD 1 million yearly. We still cover 96 percent of world trade.

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Figure 5 reports the total number of restrictive measures registered between 2003 and 2022, where it is evident that there was a large increase starting in 2020. Figure 6 disentangles the measures into three types: export barriers, import barriers and industrial policies. Clearly, the latter ones are the predominant force leading the total number of measures reported in Figure 5.

The data suggest that the most prevalent restrictive measures take the form of subsidies, followed by trade related investment measures (see Figure 7a). In terms of liberalizing measures, the most frequent ones appear to be linked to the elimination of non-automatic licensing or quotas (see Figure 7b).

To capture the significance of the new trade restrictions and industrial policy measures, we also investigate the information at the most granular level offered by the Global Trade Alert database. We find that these measures include diverse, finely targeted, and technocratic forms of public support to production and exports, as well as financial guarantees. Unsurprisingly, the measures are mostly implemented by rich countries and some of the larger developing countries. For example, we see a significant increase in the use of export bans and subsidies in ICT and technology.

Table 1 reports two examples that allow understanding the virtues and potential limits of the GTA. Example #1 is an intervention by the US government to support General Motors and Chrysler through a capital injection. The intervention was announced on March 30, 2009, and is recorded as affecting only specific firms. The HS6 products affected by this interventions represent different types of cars (of different cylinder capacities), which, as is well known, are the main final products produced by General Motors and Chrysler. Example #2 reports instead the establishment of a China-backed state fund to promote the domestic integrated circuit industry. The fund was announced in 2014 for a duration of 10 years. The form of the intervention was state loans available to all firms. The HS6 products reported as potentially affected by this intervention include products at different stages of the semiconductor value chains, from the “Machines and apparatus for the manufacture of boules or wafers” (HS code 858610) to the “Processors And Controllers, Electronic Integrated Circuits” (HS code 854231). Examples #1 and #2 illustrate the virtues of a comprehensive cross-country database of rich information about many different aspects of different types of policies. On the other hand, the association of these measures with the potentially affected products is inevitably imperfect. This might introduce significant measurement error in an important explanatory variable of interest.<sup>4</sup>

> 4We consider for our exercise all the measures reported by the GTA for which a set of potentially products is reported. The alternative would be to consider only the interventions directed to specific firms, with the benefit of isolating better discriminatory measures, but the cost would be excluding important industrial policy episodes such as the establishment of the “Big Fund” in China in 2013.

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## **2.1.2 Deep Trade Agreements Database**

Against the trend of increasing restrictions by the main trading nations, many countries continue to pursue deeper trade integration and international cooperation. Even those countries implementing protectionist measures have continued to discuss, sign and implement “deep” trade agreements, i.e. those agreements that affect domestic policy areas beyond trade, such as the international flows of investment and labor, and the protection of intellectual property rights and the environment. Fortunately, the Deep Trade Agreements (DTA) database reports extensive information on the exact provisions included in each trade agreement signed up to 2023. As many as 61 percent of PTAs that were signed before 1995 covered fewer than 10 policy areas, while in the decade from 2013 to 2023, this figure dropped to just 8 percent.

For our purposes, following the spirit of Mattoo et al. (2022), we are interested in a specific aspect of the “depth” of a preferential trade agreement, namely the extent to which it regulates subsidies. Table 2 reports 12 questions that are included in the DTA database that can be used to construct a suggestive measure of the depth of an agreement with respect to subsidies.<sup>5</sup> . We define the variable _PTA_ _~~D~~ epth_ as a measure going from zero to (potentially) one, representing the share of affirmative responses to the 12 questions listed in table 2.<sup>6</sup> The median value of _PTA_ _~~D~~ epth_ is 0.16, and the range is from zero to 0.75. Interesting examples include the EU (0.58), CPTPP (0.33), USMCA (0.25), NAFTA (0.16), and RCEP (0.00).

# **2.2 Empirical Strategy**

The dependent variable is the growth rate of trade from origin country _i_ to destination country _j_ of product _k_ (included in sector _s_ ) between year _t_ and _t −_ 1.<sup>7</sup> The choice of a specification in growth rates is motivated by two factors. First, the main explanatory variable of interest is a flow measure of newly announced 5Examples of these questions are “Does the agreement prohibit or regulate subsidies distorting trade or competition (within domestic, export or third markets)?” or “Does the agreement prohibit or regulate local-content subsidies?” 6 Formally, we define where _Subsidies_ _~~C~~ overage_<sup>_q_</sup> is the _q_<sup>_th_</sup> question in Table 2 referring to the PTA between countries _i_ and _j_ entered into force at time _t_ .

> 7For ease of interpretation, the dependent variable is already multiplied by 100: ∆ _TRADEijkst_ = 100 _∗_ ( _lnEXPijks,t − lnEXPijks,t−_ 1).

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industrial policies, which represent a change rather than a level of protection. Second, using the growth attenuates a potential selection effect of industrial policies targeting larger importer-exporter-product trade flows.

The baseline regression equation can be specified as follows: where _IPjkt_ represents a new IP measure potentially affecting product _k_ is implemented in year _t_ by destination country _j_ . _PTAijt_ is an indicator variable equal to one if a Preferential Trade Agreement is in force at time _t_ between _i_ and _j_ . _Xjkt_ includes some controls, specifically whether a new import barrier measure, potentially affecting product _k_ , is implemented in year _t_ by destination country _j_ ( _IMP_ _~~B~~ ARRjkt_ ) and its interaction with the variable _PTA_ ( _IMP_ _~~B~~ ARRjkt ∗ PTAijt_ ).

We include a rich series of fixed effects (FE) to control for several potential confounding factors. Specifically, an exporter-importer-time FE ( _δijt_ ) controls for any bilateral factor varying over time. These factors would include for instance exchange rate movements and the establishment of a preferential trade agreement. Note that we are not interested here in assessing the direct impact of PTAs on trade flows, but just their role in mediating the impact of industrial policies. An exporter-product-time FE ( _δijt_ ) controls for any fixed characteristics of an exporter-product pair, such as static comparative advantage, as well as for dynamic elements, such as a change in productivity, the level of market power, domestic demand for specific products, etc. Inserting an importer-product-time FE would not allow us to estimate some of the key coefficients of interest. We therefore control for static importer-product characteristics through an importer-product FE ( _δjk_ ) and dynamic sectoral characteristics through an importer-sector-time FE ( _δjst_ ), defining sector _s_ as a 2-digit sector from the ISIC classification. At the cost of being unable to identify the coefficient _β_ 1, we show in the appendix that our results on the coefficient _β_ 2 are robust (and in fact stronger) to the inclusion of a more demanding set of controls, including also an importer-product-time FE and exporter-importer-product FE. Finally, in order to study the impact of the depth of trade agreements on the trade effect of industrial policy, Equation 1 is modified as follows: ∆ _TRADEijkst_ = _β_ 1 _IPjkt_ + _β_ 2 _IPjkt ∗ PTA_ _~~D~~ epthijt_ + _β_ 3 _Xjkt_ + _FE_ + _εijkst_ (2) where _FE_ = _δijt_ + _δikt_ + _δjk_ + _δjst_ is defined as in equation (1).

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# **3 Results and Discussion**

## **3.1 Results**

Figure 3 summarizes in graphical form our main results, which are reported in Table 3 in the appendix. After including our main set of fixed effects, discussed in the previous section, we find that the introduction of a new industrial policy measure in a destination market reduces exports to that market on average by about 0.28%. However, when inserting the interaction term between the industrial policy and the existence of a preferential trade agreement ( _IP ∗ PTA_ ), the coefficient corresponding to non-members of a PTA is negative, statistically significant, and represents an export reduction of about 0.8% while the coefficient corresponding to members of a PTA is small and positive, but not statistically significant. Finally, considering specification (2), the trade effect of IP for a member of a preferential trade agreement will depend also on its depth. Taking a particularly high value of depth, 0.5 (corresponding to the top 5% of PTAs in the sample, in terms of coverage of subsidies), we obtained a combined coefficient which is positive, statistically significant, and corresponds to an increase in exports of about 0.39%. In table 3, we also show that these results are robust to the inclusion of import barriers in the destination countries.<sup>8</sup> We verified the robustness of our results through several checks. First, we considered an even more stringent specification in terms of fixed effects. By including also an importer-exporter-product ( _δijk_ ) and an importer-product-time FE ( _δjkt_ ) we are unable to identify the average effect of the introduction of an industrial policy measure in a trading partner. However, we are still able to identify the interaction terms with the variables _PTA_ and _PTA_ _~~D~~ epth_ , which are reported in Table 4 to be positive and highly statistically significant.

Second, we excluded potential outliers from the regressions, defining outliers as those bilateral-product observations experiencing a growth rate of trade lower than _−_ 200% or higher than 200%. The results, reported in table 5, are very close to those presented in Table 3.

Third, we explored a case where instead of the growth rate of trade, we use simply the log of the trade level, reported in Table 6. We find again our main result of a negative trade effect of industrial policies for non-members of PTAs and a positive trade effect for members of PTAs and deep PTAs. The coefficients are also larger in size in this case. It is interesting to notice, however, that the average trade effect appears now to be positive and statistically significant. This is in line with the results obtained by Rotunno and Ruta (2024). A potential explanation that they offer for this result is the self-selection of industrial policy

> 8In fact, on average, the imposition of a trade barrier is correlated to a reduction of trade growth by about 0.6%.

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<!-- Start of picture text --> Effect of Trading Partners' Industrial Policies on Export growth (%)<br>Average Effect Non-member of PTA Member of PTA Member of deep PTA<br>0.8<br>0.6<br>0.4<br>0.2; |<br>-0.4<br>-0.6<br>-0.8<br>-1<br>-1.2<br><!-- End of picture text -->
world regions (except the high-income countries, which are included not in their respective regions but in the single category of advanced economies). As the table shows, the shielding effect appears to be most pronounced for the advanced economies and the developing East Asian economies. Finally, table 8 reports the heterogeneity across sectors. The _shielding effect_ here seems to be stronger in industries such as the manufacture of chemicals, metals and transport equipment.

# **3.2 Discussion**

Several reasons could explain our results. First, PTAs typically lower bilateral tariff - and sometimes non-tariff - trade barriers and increase market access, which can counterbalance some of the protectionist effects of industrial policies.

Second, if industrial policies can be tailored to take advantage of the increased market access provided by PTAs, and these focus on sectors where the countries have complementary strengths, this can lead to a virtuous cycle of growth and integration within these sectors and for the countries in a PTA agreement. Third, when they are deep, PTAs also include regulatory harmonization or mutual recognition of standards, which further lessens the negative impacts of strict domestic standards on trade partners’ exports. Similarly, PTAs can mitigate the adverse effect of industrial policies by reducing trade distortions and establishing mechanisms to resolve trade disputes, thus helping to manage and mitigate conflicts that could otherwise damage trade relations. Finally, alignment of policies across trade partners also matters. When PTAs include specific provisions relevant to particular industries, and if industrial policies are informed by these provisions, they can enhance the underlying sectors without disrupting trade flows. The alignment of policies is also crucial in another respect: the overall impact of a country’s industrial policy on trade partners within a PTA depends significantly on how well these policies align with the shared goals of the agreement. If both countries prioritize similar industrial objectives, such as carbon emission reduction and sustainable development, digital infrastructure building, or innovation, the policies can be designed to mutually benefit rather than compete.

In conclusion, the above considerations suggest that the presence of a Preferential Trade Agreement may encourage a more collaborative approach to industrial policy between member countries, leading to an overall positive effect on bilateral trade flows by facilitating access, harmonizing standards, and reducing the tendency towards protectionist measures within the PTA.

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# **4 Conclusions**

Our work has highlighted two sets of concerns about muscular industrial policy action by globally significant economies. First, we confirm a conventional concern that subsidies limit access to markets. When these markets are large, the repercussions are likely to be global and the negative effects cannot be avoided by exporters. Two decades ago, agricultural subsidies in large developed markets provoked the most concern. Now we also need to consider the implications of industrial subsidies for industrial development and economic diversification in trade partners, especially developing countries.

Second, we identify a new concern arising from the combination of industrial policy and PTAs. Non-members of PTAs already faced the cost of exclusion, as PTAs preferentially reduced explicit trade barriers like tariffs through reciprocal liberalization and implicit barriers like technical regulations through mutual recognition and harmonization. Now, exporters from non-member states are further disadvantaged relative to producers within the PTAs that are shielded from the adverse impact of industrial policies. In fact, producers in all PTA members may benefit from subsidies in one member if value added in any member can help meet “local content” eligibility conditions. Non-member countries may therefore lose further market share in PTA regions, even if their goods or services are competitively priced and of higher quality compared to those produced within the PTAs.

A broader concern is about the likely evolution of the global trading system. The synergy between PTAs and proactive industrial strategies could create a more insular and protectionist global trading environment clustered in blocs. The blocs may prioritize internal economic goals over global trade norms and set higher barriers that further isolate non-members. As these trade blocs become more self-sufficient and less reliant on external trade, those outside may find fewer opportunities for export growth and diversification. Furthermore, non-members may be compelled to engage in less favorable trade negotiations or to adopt retaliatory measures, thereby escalating global trade tensions and undermining the stability of the international trade system.<sup>10</sup> This scenario, which underscores both the disparity in bargaining power and the broader implications for global trade dynamics and the stability of a peaceful international economic order, calls for additional research on these topics.

Importantly, future research should aim to address at least three issues. First, the availability of more granular data would overcome the limitations of the currently available datasets.<sup>11</sup> Second, it is important to address more convincingly

> 10See Gopinath et al. (2024) for a description of the similarities and differences between the current international situation and the Cold War.

> 11Banares-Sanchez et al. (2023) and Bastos et al. (2024) offer examples of promising new data

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the potential endogeneity of the industrial policy measures.<sup>12</sup> Finally, better data and more refined methodologies should also be directed at investigating channels so far unexplored, such as the role played by global value chains and production networks in the propagation of the trade effects of industrial policies.

# sources.

> 12A recent article by Barattieri and Cacciatore (2023) explores the employment effects of trade protection through the production networks, and proposes an empirical strategy to identify sectoral trade policy shocks. Applying a similar methodology to industrial policies represents a potentially fruitful venue for future investigation.

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