metadata: authors: 0: author: Laget,Edith
1: author: Osnago,Alberto
2: author: Rocha,Nadia
3: author: Ruta,Michele
count: World
docna: 0: docna: Deep trade agreements and global value chains
docty: Policy Research Working Paper
subtopic: International Trade and Trade Rules,Industrial and Consumer Services and Products,Transport and Trade Logistics,Competition Policy,Competitiveness and Competition Policy,Trade Finance and Investment
teratopic: Industry,Transport,International Economics and Trade,Private Sector Development
abstracts: cdata!: Preferential trade agreements have
            become deeper over time, often encompassing policy areas
            that go beyond traditional trade policy, such as investment,
            competition, and intellectual property rights protection. In
            the literature, a prominent argument why countries sign
            "deep" agreements is to promote and facilitate the
            operation of global value chains. This paper exploits a new
            data set on the content of trade agreements and data on
            trade in value added and in parts and components, to
            quantify the impact of the depth of trade agreements on
            bilateral cross-border production linkages. The results show
            that adding a policy area to a trade agreement increases the
            domestic value added of intermediates (forward global value
            chain linkages) and the foreign value added of intermediates
            (backward global value chain linkages) by 0.48 and 0.38
            percent, respectively. At the sectoral level, the positive
            impact of deep trade agreements is higher for higher
            value-added industries, suggesting that deep agreements help
            countries to integrate in industries with higher levels of
            value added. For a larger sample of countries and years, the
            results confirm that an additional provision in a trade
            agreement increases bilateral trade in parts and components
            by 0.3 percent. The content of trade agreements also matters
            for global value chain integration, but the impact varies by
            income group. Provisions outside the current mandate of the
            World Trade Organization (investment and competition policy)
            drive the effect of trade agreements on North-South trade in
            parts and components. Provisions under the current World
            Trade Organization mandate (tariff reduction and customs
            facilitation) drive the effect of trade agreements on
            South-South trade in parts and components.
repnme: repnme: Deep trade agreements and global value chains
display_title: Deep trade agreements and global
            value chains
listing_relative_url: /research/2018/06/30198880/deep-trade-agreements-global-value-chains
topicv3: Industrial Clusters and Value Chains
            m1326062 1226,Global Value Chains(GVC) m1326472 767,Trade m1326924 698,Competition Policy m1326982 406,Trade in Value-Added m1504157 2613
publishtoextweb_dt: 2018-06-25T00:00:00Z
historic_topic: Industry,Transport,International Economics and Trade,Private Sector Development
no_of_pages: 39
author_keys: 0: author_key: 1558931
1: author_key: 1347529
2: author_key: 1245806
model_extractions: WPS8491 Policy Research Working Paper 8491 Deep Trade Agreements and Global Value Chains _Edith Laget Alberto Osnago Nadia Rocha Michele Ruta_ Macroeconomics, Trade and Investment Global Practice June 2018
Policy Research Working Paper 8491

# **Abstract**

Preferential trade agreements have become deeper over time, often encompassing policy areas that go beyond traditional trade policy, such as investment, competition, and intellectual property rights protection. In the literature, a prominent argument why countries sign “deep” agreements is to promote and facilitate the operation of global value chains. This paper exploits a new data set on the content of trade agreements and data on trade in value added and in parts and components, to quantify the impact of the depth of trade agreements on bilateral cross-border production linkages. The results show that adding a policy area to a trade agreement increases the domestic value added of intermediates (forward global value chain linkages) and the foreign value added of intermediates (backward global value chain linkages) by 0.48 and 0.38 percent, respectively. At the sectoral level, the positive impact of deep trade agreements is higher for higher value-added industries, suggesting that deep agreements help countries to integrate in industries with higher levels of value added. For a larger sample of countries and years, the results confirm that an additional provision in a trade agreement increases bilateral trade in parts and components by 0.3 percent. The content of trade agreements also matters for global value chain integration, but the impact varies by income group. Provisions outside the current mandate of the World Trade Organization (investment and competition policy) drive the effect of trade agreements on North-South trade in parts and components. Provisions under the current World Trade Organization mandate (tariff reduction and customs facilitation) drive the effect of trade agreements on South-South trade in parts and components.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. 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/research. The authors may be contacted at nrocha@worldbank.org.

_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
# Deep Trade Agreements and Global Value Chains

**Edith Laget, Alberto Osnago, Nadia Rocha and Michele Ruta**<sup>**1**</sup>

Keywords: Trade Agreements; Global Value Chains; Deep Integration; Regionalism. JEL Codes: F13; F15.

1 We are grateful to Michael Ferrantino, Nuno Limão, Aaditya Mattoo, Sebastien Miroudot, Alen Mulabdic, Richard Baldwin, Zhi Wang, and seminar participants at Stanford University, University of Maryland, the Graduate Institute in Geneva, University of International Business and Economics (UIBE) in Beijing, the OECD, the World Bank for helpful comments and suggestions. Errors are our responsibility only.

Disclaimer: 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.

Contact author: Nadia Rocha, World Bank, 1818 H Street, Washington DC, USA. Email: nrocha@worldbank.org.
# 1. Introduction

All members of the World Trade Organization (WTO) signed at least one Preferential Trade Agreement (PTA).<sup>2</sup> The content of these agreements changed over time as they now encompass a number of disciplines that go beyond traditional trade policy (Hofmann, Osnago and Ruta, 2017). Through PTAs, member countries commit to cut their tariffs and undertake additional obligations in policy areas covered by the WTO such as customs administration or contingent protection. But they more and more break new grounds in policy domains that are not regulated by the WTO, such as investment and competition policy. This new generation of “deep” trade agreements is at the core of a number of policy and research debates, as economists try to assess their economic effects and provide guidance on how to efficiently design and implement them.

This paper contributes to this broader debate on trade agreements by empirically investigating the relationship between deep trade agreements and Global Value Chains (GVCs). Using a new data set on the content of PTAs developed by the World Bank, our analysis allows us to i) quantify the impact of deep trade agreements on GVC integration among member countries, ii) disentangle the importance of specific sets of provisions in PTAs, and iii) shed light on the role of deep trade agreements in shaping the pattern of integration across countries with different levels of development. Our key finding is that the depth of trade agreements contributes to increase GVC trade among parties. This impact is higher for industries with higher share of value added in total production, suggesting that deeper trade arrangements help countries to integrate in industries with higher levels of value added. We also find that for trade agreements between developed and developing countries, this effect is mostly driven by the presence of provisions that are currently outside the domain of the WTO and that deal with behind the border policies, such as investment and competition policy. For trade agreements between developing countries, the impact of trade agreements on GVC trade is mostly driven by the reduction of traditional trade barriers such as tariffs and other border measures.

> 2 As is common in the recent trade literature, the term PTAs will be used throughout the paper and is preferred to the term ‘regional trade agreements (RTAs)’ since some of these agreements are not necessarily between countries within the same region or in regional proximity. We will also often refer to PTAs as ‘deep (trade) agreements’, in recognition of the fact that several provisions in PTAs are not preferential in nature (Baldwin and Low, 2007).

2
The argument that the rise of deep trade agreements and the increasing importance of GVCs are related is not new and has been informally made in influential studies by Lawrence (1996), Baldwin (2010) and WTO (2011), among others. Intuitively, the unbundling of stages of production across borders creates new forms of cross‐border policy spillovers and time‐ consistency problems. Deeper forms of integration may allow to solve these coordination and commitment problems, because they discipline those national policies that are needed for the smooth operation of GVCs. Formal models of the relationship between GVCs and trade agreements are presented in Antràs and Staiger (2012) and Bickwit, Ornelas and Turner (2017). Recent studies have looked at related questions from an empirical point of view: Orefice and Rocha (2011), Johnson and Noguera (2016), Osnago, Rocha and Ruta (2015, 2016).<sup>3</sup> Differently from the current study, these papers either abstract from the depth of trade agreements (Johnson and Noguera, 2016), are based on a smaller database developed by the WTO (WTO, 2011) covering only 100 agreements and use different measures for GVC related trade (Orefice and Rocha, 2011; Osnago, Rocha and Ruta, 2015, 2016).<sup>4</sup> In the econometric analysis, we use a structural gravity model at the aggregate and sectoral levels to estimate the relationship between cross‐border production linkages and the depth of PTAs. To control for selection bias deriving from the presence of zero trade flows, our estimations are preformed using a Poisson Pseudo Maximum Likelihood (PPML) model. PTA depth measures are based on the new World Bank data set on the content of PTAs which covers 260 agreements signed by around 180 countries between 1958 and 2015. This is the entire realm of PTAs in force and notified to the WTO as of December 2015.<sup>5</sup> We build several indicators of PTA depth that capture the scope and legal enforceability of trade agreements. Bilateral GVC integration is measured in two ways, using value‐added trade and trade in parts and components.

> 3 For a survey of the literature, see Limão (2016). A companion paper by Mattoo, Mulabdic and Ruta (2017) uses the new World Bank database on the content of PTAs to revisit the classic Vinerian question of trade creation and trade diversion.

> 4 Contemporaneous work by Rubinova (2017) and Boffa, Jansen and Solleder (2017) also uses the new World Bank database on the content of PTAs to analyze various aspects of the relationship between deep agreements and GVCs.

> 5 In our analysis we exclude partial scope agreements.

3
Value‐added trade measures come from Wang et al. (2012) and are based on the World Input Output data set (WIOD) for the years 1995‐2011. Value‐added trade provides a more accurate measure of GVC involvement. It also allows us to investigate the impact of deep trade agreements on both goods and services trade and across industries with different levels of value added. The information on value‐added trade, however, covers a limited sample of countries (40). Trade in parts and components records gross trade flows, which can be subject to double counting, but has the advantage of being available for the full set of countries and years covered by the new data set on PTAs. Having the whole sample of countries allows us to investigate how the effect of deep PTAs varies with the level of development of countries involved in an agreement. It also provides insights on whether certain types of provisions included in PTAs are more relevant for agreements between countries with different levels of development.

We first study how the depth of PTAs affects GVC integration in goods and services. We look at total domestic value added (DVA) in gross exports and foreign value added (FVA) in gross exports. The main finding is that deep PTAs increase the domestic value‐added content of exports mainly through GVCs. Adding a provision to a PTA boosts domestic value added of intermediate goods and services exports (i.e. forward GVC linkages) by 0.48 percent, while an additional provision in a PTA increases foreign value added of intermediate goods and services exports (i.e. backward GVC linkages) by 0.38 percent. We also find evidence that deep trade agreements improve forward linkages particularly for more complex GVCs, i.e. GVCs where exported intermediates cross borders two times or more, while we do not find a significant impact of deep trade agreements on domestic and foreign value added of final goods and services exports. Estimations performed separately for services and goods show that the impact of deep trade agreements is usually higher for value‐added trade in services compared to value‐added trade in goods.

We also analyze whether the impact of deep trade agreements on GVC integration is heterogeneous across industries. Specifically, we estimate a set of sectoral regressions. where we include an interaction term between the depth of an agreement and the share of value added that a particular sector has in overall production. The results suggest that deep trade agreements are particularly relevant for GVC integration in high value‐added industries. Not surprisingly these 4
industries are usually services sectors, which are characterized by non‐tangible activities such as research and development or retail services that have high value added.

Next, we dig further into the relationship between deep PTAs and GVCs and we empirically explore potential heterogeneity in the effects of deep PTAs across countries with different levels of development and by splitting the provisions into two categories, depending on their relationship with WTO rules.<sup>6</sup> WTO+ provisions fall under the current mandate of the WTO and are already subject to some form of commitment in WTO agreements. WTO‐X provisions, on the contrary, refer to policy obligations that are outside the current mandate of the WTO, relating to areas that are not yet regulated by the WTO. We focus on the larger sample of countries available for trade in parts and components to explore whether the impact of different provisions is heterogeneous across countries with different levels of development. The estimates suggest that WTO‐X provisions are particularly important for GVC‐related trade between North and South countries. On the other hand, WTO+ provisions are still relevant for trade among developing countries.

Our results might suffer from endogeneity deriving from omitted variables and simultaneity bias. Omitted variables bias arises when the error term is correlated with some unobservable country‐ specific policy variables (e.g. restrictive domestic policy regulation), which at the same time affect both GVC‐related trade and the probability of forming a deep PTA. Reverse causality may arise from the fact that firms in country pairs involved in GVC may lobby for deeper trade agreements to secure the supply of intermediates in partner countries. The set of fixed effects included in the structural gravity estimation partially deals with both sources of endogeneity (Baier and Bergstrand, 2007; Piermartini and Yotov, 2016).

As an alternative approach, a set of leads and lags of the variable capturing the depth of trade agreements are included in the regression. This allows to control for the dynamic effect of the impact of deep trade agreements on GVC‐related trade. The results suggest that there is some anticipation effect of deep trade agreements, but this is limited to one year before the agreement enters into force. The positive trade effect of deep agreements persists after the first year and it

> 6 See Horn, Mavroidis and Sapir (2010).

5
generally stabilizes over time. This is especially true for domestic value added of intermediates. As to the dynamics for trade in parts and components, the results confirm that there are one‐ year anticipation effects and that the impact of deep agreements persists after the entry into force of the agreements. The broader country‐coverage uncovers that this dynamic is driven by deep PTAs involving North and South countries.

Finally, a concern is that in a world where production is fragmented internationally, GVC trade between two countries is not only affected by their trade agreements but also by the trade agreements signed by any country along the value chain (Noguera, 2012). As deep agreements may have a stronger impact on bilateral GVC trade than shallow agreements, it is well possible that the level of depth of preferential trade agreements signed by third countries along the supply chain could indirectly affect GVC‐related trade between two countries. We build on the approach by Noguera (2012) to control for the indirect effect of deep trade agreements and find that the coefficients of the modified gravity regressions are larger than those of the standard gravity, confirming the existence of indirect effects of signing deep PTAs through third countries.

The rest of the paper is organized as follows. Section 2 discusses the data used in the paper. Section 3 presents the empirical analysis focusing on the impact of PTA depth on GVC integration, while Section 4 focuses on the impact that different sets of provisions in deep trade agreements have on countries with different levels of development. Section 5 presents robustness tests. Concluding remarks follow.

# 2. Data

In this section, we take a first look at the data on the content of trade agreements and present the measures of PTA depth and GVC trade used in the analysis.

## a. Deep trade agreements

In the literature, the effects of PTAs on trade are generally estimated by including a dummy equal to one when two countries are involved in an agreement (Limão, 2016). In our econometric analysis, we also estimate the coefficient of a dummy for PTAs, but we take a step forward by estimating the effects of deep trade agreements using three new measures of depth. The data on the content of deep agreements come from a new database at the World Bank that covers 260 6
PTAs, which is the realm of preferential agreements excluding partial scope agreements in force and notified to the WTO up to the end of 2015 (Hofmann, Osnago and Ruta, 2017). The methodology is based on the work of Horn, Mavroidis and Sapir (2010), which was also used in the World Trade Report 2011 (WTO, 2011). The data provide information on two key aspects of the content of PTAs: (i) what policy areas are covered in each agreement, based on a list of 52 policy areas; (ii) whether each provision is legally enforceable or not, based on an analysis of the legal language of the treaty text and the possibility of recourse to dispute settlement.<sup>7</sup> As a first measure of depth, we use the number of legally enforceable provisions that are included in an agreement from the World Bank database. While an imperfect metric, this is a logical first step to capture the level of depth of PTAs, as the extent of policy commitments depends on the number of areas that are covered by an agreement. Specifically, we define the variable ������������� �∑����� �������� ‐ i.e. the simple count of ‐legally enforceable‐ provisions � 8 ( ������� ) included in the agreement between countries � and � at time � .

An alternative measure of depth can be constructed on a subset of “core” border and behind the border provisions –i.e. those provisions that have a clear economic content, as opposed to other provisions that do not (e.g. cultural cooperation, anti‐terrorism). Core provisions include tariff liberalization for industrial and agriculture goods, technical barriers to trade (TBT) and sanitary and phytosanitary (SPS) measures, export taxes and anti‐dumping and countervailing measures, trade related intellectual property (TRIPs) and trade related investment measures (TRIMs), movement of capital, state owned enterprises, state aid, competition policies, intellectual property rights (IPR), investment, public procurement and services. The 18 “core” provisions are also those most often included in PTAs (Hofmann, Osnago and Ruta, 2017). We define the variable ��������� as the number of core provisions ( �������� ) included in the agreement �� � between country � and � at time � : ������������ �∑��� ������� .

> 7 Annex Table A1 presents the list of provisions. More details on the methodology and the data on deep trade agreements can be found in Hofmann, Osnago and Ruta (2017). The data are freely available at the following website: https://datacatalog.worldbank.org/dataset/content‐deep‐trade‐agreements.

> 8 Unless otherwise stated, all provisions included in measures of PTA depth are legally enforceable.

7
PCADepth Wy PCADepthij, = L221 0,Provis, TotalDepth WTOplus;j, = Yp21 Proviig WTOextrajj, = Lee, Provii, Provij, Provijt ij t
several value‐added components (see Figure 1). Our first measure of interest is domestic value added (DVA). It simply measures the amount of value added by the exporting country contained in its exports, i.e. the sum of the first 4 components in the figure. While this is not a direct measure of GVCs, the comparisons of the results for this variable with our second variable of interest (discussed next) sheds light on the relationship between deep trade agreements and GVCs.

The second variable of interest is value added in intermediates. It includes the value of exports that has been produced domestically, exported as an intermediate good, reprocessed by the importing countries and either directly absorbed there (component (2) in the figure), further exported to third countries (component (3)) or re‐exported to the original country (component 4). We define a third variable from the sub‐set of re‐exported intermediates (components (3) and (4)). The re‐exported intermediates variable represents the most fragmented parts of a production process in which goods and services cross at least two borders before being eventually absorbed. These two variables capture the bilateral forward linkages between two countries. We also use foreign value added in gross exports that can be further decomposed between final and intermediate goods and services (components (5) and (6)). It measures all value that has not been produced domestically and that is contained in gross exports. This variable captures backward linkages. At this stage, the decomposition does not allow us to identify the country of origin of the foreign value and hence it is an imperfect measure of bilateral GVC linkages.<sup>12</sup> Second, for the analysis based on gross trade flows, we use trade in parts and components to proxy for global production sharing. There is no broadly accepted definition of trade in parts and components that we can refer to, so our classification builds on the existing literature in this area (WTO, 2011 and Orefice and Rocha, 2011). Specifically, for our analysis, we define as parts and components all non‐fuel intermediates from the Broad Economic Categories (BEC) classification

> 12 The sum of the six above‐mentioned value‐added components does not match exactly the official trade statistics in gross value terms. The difference is due to double counting (column (7)) that tends to increase when goods and services cross borders multiple times.

9
(codes 111, 121, 21, 22, 42 and 53), supplemented with unfinished textile products in division 65 of the SITC classification.

These various measures have advantages and disadvantages, which is the reason why we chose to employ a broader set of indicators rather than focusing on a single one. In particular, measures based on value added trade are more precise as they allow to directly deal with the problem of double counting in gross trade data and account for the input‐output relationships in production. WIOD data also have the advantage of covering trade in both goods and services. The data on (goods) trade in parts and components are available for a large set of countries and years,<sup>13</sup> thus allowing us to rely on a broader panel which includes many more developing countries than WIOD. The correlation between gross and value‐added trade variables for the sub‐sample of WIOD countries and years is however large and ranges between 0.75 and 0.88 (see first column of Table 1).

# 3. Depth of trade agreements and GVC integration

In this section, we present the empirical strategy and the analysis of the impact of deep agreements on value added trade. We also investigate whether the impact of deep trade agreements is heterogeneous for industries with high and low value added incorporated in their production.

## a. Empirical strategy

To assess the impact of deep agreements on GVC integration, we estimate the following structural gravity equation for the time period 1995‐2011 with a Pseudo‐Poisson Maximum Likelihood (PPML) estimator. The regression equation is: where ����������� is a measure of value added trade between country � and � at time � and is captured either by different components of value added trade or by gross trade in intermediates; �������� is one of the three measures of the depth of PTAs and are defined in section 2a above. ������ controls for the presence of a Bilateral Investment Treaty between country � and country

> 13 Regressions using gross trade data are estimated for 184 countries between 1995‐2014.

10
� at time � ;<sup>14</sup> ������ is a dichotomous variable that takes the value of 1 whenever there is a preferential trade agreement, either active or inactive, between two countries at time � ;<sup>15</sup> � s are sets of country‐pair, importer‐time and exporter‐time fixed effects.

# b. Baseline results

Table 2 reports the coefficients of total depth, core depth and PCA depth for the regressions using DVA and FVA as dependent variables. All coefficients of depth are positive and significant. Adding a policy area is associated to an average increase 0.4 percent of total domestic value added and an average increase of 0.26 percent of foreign value added. The coefficients increase substantially when looking at core depth only, suggesting that those policy areas are particularly important as they reduce the governance gap between countries in areas that are relevant for GVC‐related trade.<sup>16</sup> Also, the coefficients of PCA depth show a similar pattern to the one of total number of provisions. Control variables such as BITs have the expected sign, suggesting that signing BITs has a positive impact on domestic and foreign value added in exports.<sup>17</sup> The PTA dummy is non‐significant in most of the estimations. This variable controls for the presence of shallow PTAs and for agreements no longer in force for which we have no information on depth. The lack of statistical significance indicates that it is the depth of PTAs, and not the mere presence of shallow agreements, that matters for domestic and foreign value added in exports.

A concern is that the trade variables in our first set of regressions may be driven by traditional trade in final goods and services rather than by GVC trade. To address this concern, we assess the impact of deep trade agreements on FVA and on DVA exports separately for intermediate and final goods and services. Results presented in Table 3 decompose domestic value added into DVA in final exports (columns 1‐3), DVA in intermediate exports (columns 4‐6) and DVA of re‐ exported intermediates (columns 7‐9). The coefficients capturing PTA depth are only significant for DVA of intermediate exports, suggesting that deep trade agreements are particularly

> 14 Data on BITs come from UNCTAD.

> 15 The variable ������ is taken from Egger and Larch (2008).

> 16 See Baldwin (2011) and WTO (2011).

> 17 The magnitude of the BITs coefficient needs to be interpreted carefully, given that these agreements often focus on specific sectors or areas. Therefore, in our regressions, which are aggregated at the country level, their impact might be positively biased.

11
important in the context of global value chains compared to trade in final goods. In terms of magnitudes, the coefficients capturing the impact of adding one additional provision on domestic value added in intermediates are slightly higher compared to the aggregate variables presented in Table 2 and are equal to 0.48 percent on average. In addition, the positive relationship between deeper trade agreements and GVC integration is particularly important for the subset of re‐exported intermediates that cross the border at least twice, suggesting that deep agreements are particularly important in the context highly fragmented production processes.

Results on the impact of deep agreements on foreign value‐added trade of final and intermediate exports are presented in Table 4. In this case also, the positive impact of our variable of interest is significant only for FVA of intermediate exports. The magnitude of the coefficients is also higher compared to the baseline regression. Adding an extra provision in an agreement increases foreign value added of intermediate exports by 0.38 percent.

In Table 5 and Table 6 the results on the impact of deep trade agreements on GVC integration are presented for goods and services separately. For simplicity results are presented for one of our depth variables.<sup>18</sup> In the case of goods, the relationship between deep trade agreements and forward GVC linkages is mainly driven by domestic value added in intermediate exports and is significant only at a 10 percent level. For foreign value added, depth is positive and significant only for intermediates. For services, deeper agreements have a positive impact on domestic value‐added services with results once again driven by intermediate exports, and foreign value‐ added services. Notice that the coefficients capturing the impact of deeper trade agreements on services are usually of a higher magnitude compared to the coefficients capturing the impact of deeper agreements on goods, suggesting that agreements going beyond pure market access are particularly important for GVC integration in services.

# c. Sector‐level regressions

In this section we investigate whether the impact of deep trade agreements on GVC participation is heterogeneous across industries with different levels of value added shares in total production. We estimate the following specification:

> 18 Results for the other depth variables are qualitatively similar and available upon request.

12
<!-- Start of picture text --> GVC trade; = exp {B Depth,, + B Depth,, * Industry VA, + B BITje + B PTAs + Sin +<br>Oixe + Sine} + Eijxt<br>GVCtrade;jtx i J<br>t Industry VA;<br><!-- End of picture text --> i J Depthjj, PTAijt BITje <!-- Start of picture text --> Oijx Sixt Ojkt<br><!-- End of picture text -->
GVC trade;ji, = exp{B,WTO plus;jt + B2WTO extraj;j, + Bz WTO plus;j, * LevDevij + LevDevj;
the other hand, South‐South GVC‐trade is mostly affected by WTO+ provisions. For North‐North agreements, the coefficients on WTO+ and WTO‐X are not significant.<sup>20</sup> While there is no formal theory to guide the analysis, the differential effects of deep agreements across countries’ levels of development may have a simple intuitive explanation. Deep trade agreements affect GVC trade directly, as they lower trade barriers between members, and indirectly, as they improve institutions through commitments to reform. Deep PTAs may matter less for developed countries as trade is already liberalized and domestic institutions are robust. On the contrary, weak institutions in developing economies are likely to be a constraint for GVC integration with developed countries. Deep provisions in PTAs can offer a commitment device to implement reform that contributes to boost GVC‐related trade. Finally, since tariffs and other border barriers are often still high between developing countries, PTAs may affect GVC trade mostly through traditional trade liberalization in South‐South relationships.

# 5. Robustness

In this section, we undertake three robustness tests. First, we consider indirect effects of PTAs. The second robustness exercise allows for slow adjustment in trade policy. Finally, we account for dynamic effects in the regressions.

## a. PTAs indirect effects

In a world where production is fragmented across countries, the level of depth of preferential trade agreements signed by third countries along the supply chain could indirectly affect GVC‐ related trade between two countries. Intuitively, deeper trade agreements in third countries lower trade costs along the entire supply chain, thus encouraging trade in intermediates also among countries that are not part of the agreement. To control for the indirect effect of deep trade agreements, we follow Noguera (2012) and estimate the impact of deep PTAs on the level of integration in GVCs using the following modified gravity framework:

> 20 Estimations using WIOD, which covers only a few developing countries, are similar to this last set of results.

15
Where the variables and the set of controls and fixed effects are the same as in equation (1), but the PTA depth variable is weighted using two different shares. Specifically, ����� is the share of value added from country � to country � embodied in country � 's final products that reaches country � ; ������ is the share of value added from country � embodied in intermediate inputs produced in country � that are absorbed as final demand in country � after traveling through possibly multiple countries � .

The estimates in Table 11 are in line with the standard gravity estimates for the total depth variable.<sup>21</sup> Deep PTAs tend to increase forward and backward linkages, with stronger effects for exports in intermediates. The coefficients of the modified gravity regressions are larger than those of the standard gravity, suggesting the existence of indirect effects of signing deep PTAs through third countries.

# b. Adjustment to trade policy changes

As suggested by Trefler (2004), the adjustment of trade flows between two countries after signing a PTA is not instantaneous but it may take some time. Therefore, estimations using consecutive years will not allow our dependent variable to properly adjust. To reduce this bias, estimations are performed using 3‐year intervals. Results presented in Table 12 and Table 13 have the same sign as the ones presented in the baseline regressions and are slightly higher in terms of magnitude, confirming the positive relationship between PTA depth and GVC‐related trade.<sup>22</sup> In particular, adding a policy area is associated to an average increase of 0.43 percent of total domestic value added (column (1) Table 12), an average increase of 0.49 percent of value added in intermediate exports (column (3) Table 12), and an average increase of 0.37 percent of foreign value added in intermediates (column (7) Table 12). With respect to gross trade flows, including one more provision increases trade in parts and components by 0.44 percent on average (column (1) Table 13).

> 21 Results for the other depth variables are qualitatively similar and available upon request.

> 22 Similar results are also found when regressions are performed using 4‐ and 5‐year intervals. Results for the other depth variables are qualitatively similar and available upon request for the data on value added (Table 12).

16
## c. Dynamic effects

As an alternative control for reverse causality and to shed light on potential adjustment of trade over time, regressions are performed including leads and lags using our full samples. More specifically, we run the following regression where we add all the lags of depth until ��3 and the leads until ��3 to our baseline specification.

Results for trade in value added, presented in Figure 2, suggest that there are some anticipation effects of deep PTAs which are however limited to one year before the agreement enters into force. This may not be surprising given the time gaps between the time an agreement is signed by the parties and the time it enters into force. Figure 2 also disentangles the dynamic effects of deep PTAs on the value‐added components of gross exports by splitting domestic and foreign value added intermediate and final goods value added. The key insight is that both contemporaneous and cumulative effects tend to be larger for domestic and foreign intermediate value added than domestic and foreign final value added.

In the case of trade in parts and components, the results point to some interesting patterns in the data across different income groups. Figure 3 shows the values of the coefficients of three different measures of depth between ��3 and ��3 for the three country groups analyzed above (North‐North, North‐South and South‐South). While the coefficients of depth are not significantly different from zero in any year before the entry into force of the agreement for any income groups, the figure suggests that the effect of deep PTAs cumulates over time for the North‐South and for South‐South pairs. For the former group of trade agreements, the cumulative effect is particularly strong, consistently with the view that deep agreements may have offered a commitment device for reforms in developing economies that have helped them anchor to GVCs. The cumulative effect for the South‐South country‐pairs is not significant.

# 6. Conclusions

This paper contributes to the existing literature on the relationship between trade agreements and cross‐border production linkages. There are three main novelties in the paper. First, it uses 17
new data on trade in value added in addition to more standard data on trade flows of parts and components to separately assess the impact of deeper trade agreements on goods and services and to investigate whether the relationship between trade agreements and GVC participation is heterogeneous across industries with different levels of value added shares in production. Second, it exploits new information on the content of PTAs and attempts to identify which type of provisions matter the most for GVC‐related trade. Third, it looks at how the effect of the content of deep PTAs changes depending on the level of development of the countries involved in trade agreements.

With this new approach, we are able to establish three main results.

1. The depth of trade agreements increases GVC‐related trade among participating countries. The positive impact of deep agreements on GVC integration is driven by value‐ added trade in intermediates rather than in final goods and services. Adding a policy area to a PTA increases domestic value added of intermediates (forward GVC linkages) and foreign value added of intermediates (backward GVC linkages) by 0.48 and 0.38 percent, respectively.

2. At the sectoral level, the positive impact of deep trade agreements is higher for industries with higher value‐added shares in total production, suggesting that deeper trade arrangements help countries to integrate in industries with higher levels of value added.

3. Provisions outside the current WTO mandate such as competition policy and investment are key drivers of the relationship between deep trade agreements and GVC‐related trade, particularly for North‐South PTAs. Border provisions are still an important driver of GVC trade for South‐South PTAs.

While these are important new findings, more work is needed in this area. There is little that we know on the detailed content of specific provisions in trade agreements and how this content may affect trade, GVC participation or other variables of interest. Future work could aim at collecting data for core policy areas and study how the detailed content of these provisions in deep trade agreements affects economic outcomes.

18
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Table 1: Correlation between gross and value‐added trade in good

||Parts and<br>components|DVA|DVA<br>final|DVA<br>interm.|DVA interm.<br>re‐exported|<br>FVA|FVA<br>final|FVA<br>interm.|
|---|---|---|---|---|---|---|---|---|
|Parts and components|1.00||||||||
|DVA|0.87|1.00|||||||
|DVA final|0.80|0.97|1.00||||||
|DVA intermediate|0.88|0.97|0.88|1.00|||||
|DVA int. re‐exported|0.82|0.85|0.72|0.91|1.00||||
|FVA|0.79|0.89|0.87|0.85|0.67|1.00|||
|FVA final|0.77|0.88|0.90|0.81|0.63|0.98|1.00||
|FVA intermediate|0.75|0.84|0.77|0.85|0.68|0.96|0.88|1.00|

Table 2: Deep trade agreements and GVC integration, PPML

||(1)<br>|(2)<br>DVA of exports|(3)|(4)<br>|(5)<br>FVA of exports|(6)<br>|
|---|---|---|---|---|---|---|
|No. of provisions|0.00400***|||0.00258*|||
||(0.00125)|||(0.00133)|||
|Core provisions||0.00777***|||0.00520*||
|||(0.00266)|||(0.00273)||
|PCA depth (1st)|||0.0292***|||0.0203*|
||||(0.0101)|||(0.0105)|
|BIT|0.121***|0.118***|0.119***|0.0924**|0.0910**|0.0914**|
||(0.0440)|(0.0441)|(0.0441)|(0.0379)|(0.0379)|(0.0379)|
|PTA (in force or|||||||
|inactive)|‐0.0296|‐0.0611|‐0.041|‐0.00848|‐0.0302|‐0.0189|
||(0.0433)|(0.0492)|(0.0461)|(0.0410)|(0.0481)|(0.0440)|
|Observations|26,520|26,520|26,520|26,520|26,520|26,520|
|R‐squared|0.994|0.994|0.994|0.996|0.996|0.996|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 22
Table 3: Deep trade agreements and Domestic Value‐added exports – intermediates vs final, PPML

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|---|---|---|---|---|---|---|---|---|---|
||DV|A of final expo|rts|DVA of|intermediate e|xports|DVA of int|ermediates re|‐exported|
|No. of provisions|0.00220|||0.00480***|||0.00484***|||
||(0.00158)|||(0.00139)|||(0.00158)|||
|Core provisions||0.00424|||0.00940***|||0.0106***||
|||(0.00312)|||(0.00300)|||(0.00331)||
|PCA depth (1st)|||0.0181|||0.0345***|||0.0376***|
||||(0.0122)|||(0.0113)|||(0.0126)|
|BIT|0.117**|0.116**|0.116**|0.121**|0.117**|0.119**|0.115**|0.111**|0.113**|
||(0.0551)|(0.0552)|(0.0551)|(0.0472)|(0.0472)|(0.0473)|(0.0528)|(0.0526)|(0.0527)|
|PTA (in force or inactive)|0.118***|0.0990*|0.106**|‐0.107**|‐0.144***|‐0.118**|‐0.0754|‐0.124**|‐0.0937|
||(0.0442)|(0.0539)|(0.0485)|(0.0492)|(0.0553)|(0.0519)|(0.0578)|(0.0628)|(0.0597)|
|Observations|26,520|26,520|26,520|26,520|26,520|26,520|26,520|26,520|26,520|
|R‐squared|0.996|0.996|0.996|0.991|0.991|0.991|0.989|0.989|0.989|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

23
Table 4: Deep trade agreements and foreign value‐added exports ‐intermediates vs final, PPML

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||FVA|of final expo|rts|FVA of|intermediate|exports|
|No. of provisions|0.000645|||0.00385***|||
||(0.00168)|||(0.00124)|||
|Core provisions||0.000806|||0.00765***||
|||(0.00340)|||(0.00265)||
|PCA depth (1st)|||0.00553|||0.0290***|
||||(0.0131)|||(0.0101)|
|BIT|0.105**|0.105**|0.105**|0.0736*|0.0710*|0.0720*|
||(0.0473)|(0.0474)|(0.0473)|(0.0413)|(0.0412)|(0.0413)|
|PTA (in force or|||||||
|inactive)|0.143***|0.142**|0.139**|‐0.106**|‐0.134***|‐0.117**|
||(0.0503)|(0.0592)|(0.0542)|(0.0451)|(0.0507)|(0.0474)|
|Observations|26,520|26,520|26,520|26,520|26,520|26,520|
|R‐squared|0.996|0.996|0.996|0.995|0.995|0.995|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 24
Table 5: Deep trade agreements and GVC integration in goods, PPML

||(1)<br>DVA|(2)<br>DVA<br>final|(3)<br>DVA<br>intermediate|(4)<br>DVA int. re‐<br>exported|(5)<br>FVA|(6)<br>FVA final|(7)<br>FVA<br>intermediate|
|---|---|---|---|---|---|---|---|
|No. of provisions|0.00235*|0.00195|0.00230*|0.00111|0.00161|5.89e‐05|0.00259**|
||(0.0013)|(0.0017)|(0.0013)|(0.0015)|(0.0014)|(0.0017)|(0.0013)|
|BIT|0.139***|0.131**|0.142***|0.148***|0.0920**|0.110**|0.0608|
||(0.0436)|(0.0596)|(0.0443)|(0.0468)|(0.0389)|(0.0502)|(0.0398)|
|PTA (in force or||||||||
|inactive)|0.0254|0.174***|‐0.0667|‐0.0527|0.00409|0.159***|‐0.0939**|
||(0.0425)|(0.0455)|(0.0464)|(0.0646)|(0.0428)|(0.0521)|(0.0413)|
|Observations|26,520|26,520|26,520|26,520|26,520|26,520|26,520|
|R‐squared|0.997|0.997|0.996|0.996|0.997|0.996|0.997|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 Table 6: Deep trade agreements and GVC integration in services, PPML

||(1)<br>DVA|(2)<br>DVA<br>final|(3)<br>DVA<br>intermediate|(4)<br>DVA int.<br>re‐exported|(5)<br> <br>FVA|(6)<br>FVA<br>final|(7)<br>FVA<br>intermediate|
|---|---|---|---|---|---|---|---|
|No. of provisions|0.00474**|0.00310|0.00468**|0.00493**|0.00450**|0.00353|0.00453*|
||(0.0022)|(0.0024)|(0.0023)|(0.0024)|(0.0023)|(0.0023)|(0.0025)|
|BIT|0.0632|‐0.0670|0.0868|0.0980|0.133|0.0394|0.173**|
||(0.0759)|(0.0948)|(0.0750)|(0.0765)|(0.0830)|(0.0938)|(0.0841)|
|PTA (in force or||||||||
|inactive)|‐0.0856|‐0.108|‐0.0476|0.0323|0.0188|0.0334|0.0298|
||(0.0833)|(0.0964)|(0.0797)|(0.0744)|(0.0904)|(0.110)|(0.0828)|
|Observations|26,401|26,350|26,401|26,401|26,401|26,350|26,401|
|R‐squared|0.959|0.959|0.957|0.966|0.951|0.946|0.951|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 25
# Table 7: Deep trade agreements and GVC integration in goods ‐sectoral estimations, PPML

||(1)|(2)<br>DVA|(3)|(4)|(5)<br>FVA|(6)|
|---|---|---|---|---|---|---|
|No. of provisions|0.00208***|‐0.000205|0.00293***|0.00127|‐0.00315|0.00230*|
||(0.000808)|(0.00471)|(0.00108)|(0.00103)|(0.00611)|(0.00134)|
|No. of provisions* VA share||0.00734|||0.0145||
|||(0.0140)|||(0.0185)||
|No. of provisions*High VA share {0,1}|||‐0.00252*|||‐0.00355**|
||||(0.00133)|||(0.00151)|
|BIT|0.122***|0.122***|0.122***|0.0848***|0.0845***|0.0848***|
||(0.0232)|(0.0232)|(0.0232)|(0.0253)|(0.0254)|(0.0253)|
|PTA (in force or inactive)|0.0368|0.0373|0.0354|0.0357|0.0365|0.0350|
||(0.0297)|(0.0297)|(0.0296)|(0.0362)|(0.0361)|(0.0361)|
|Observations|365,535|365,535|365,535|365,370|365,370|365,370|
|R‐squared|0.975|0.975|0.975|0.990|0.990|0.990|
|Country‐pair‐industry FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Importer‐industry‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Exporter‐industry‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|
|p‐value F‐test No. ofprovisions||0.4472|0.6487||0.3600|0.1808|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 26
Table 8: Deep trade agreements and GVC integration in services ‐sectoral estimations, PPML

||(1)|(2)<br>DVA|(3)|(4)|(5)<br>FVA|(6)|
|---|---|---|---|---|---|---|
|No. of provisions|0.00288*|‐0.0140*|‐0.00155|0.00249|‐0.00635|‐0.000882|
||(0.00170)|(0.00760)|(0.00216)|(0.00167)|(0.00726)|(0.00218)|
|No. of provisions* VA share||0.0320**|||0.0178||
|||(0.0143)|||(0.0139)||
|No. of provisions*High VA share {0,1}|||0.00730***|||0.00734***|
||||(0.00282)|||(0.00282)|
|BIT|0.00389|0.00397|0.00348|‐0.0252|‐0.0253|‐0.0263|
||(0.0608)|(0.0608)|(0.0609)|(0.0531)|(0.0532)|(0.0532)|
|PTA (in force or inactive)|‐0.0442|‐0.0385|‐0.0455|0.0563|0.0647|0.0589|
||(0.0657)|(0.0667)|(0.0662)|(0.0602)|(0.0619)|(0.0618)|
|Observations|295,381|295,381|295,381|295,076|295,076|295,076|
|R‐squared|0.922|0.922|0.922|0.950|0.950|0.950|
|Country‐pair‐industry FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Importer‐industry‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Exporter‐industry‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|
|p‐value F‐test No. ofprovisions||0.0117|0.0095||0.1017|0.0020|

Clustered standard errors at the country pair level in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

27
Table 9: Deep trade agreements and trade in parts and components, PPML

||(1)|(2)|(3)|
|---|---|---|---|
|No. of provisions|0.00294**|||
||(0.00130)|||
|Core provisions||0.00589**||
|||(0.00273)||
|PCA depth|||0.0224**|
||||(0.0107)|
|BIT|0.127***|0.126***|0.127***|
||(0.0316)|(0.0316)|(0.0316)|
|PTA (in force or inactive|‐0.0492|‐0.0737|‐0.0574|
||(0.0470)|(0.0505)|(0.0489)|
|Observations|336,976|336,976|336,976|
|R‐squared|0.990|0.990|0.990|
|Country‐pair FE|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

28
Table 10: The content of PTAs and trade in parts and components by income groups, PPML

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|||<br>Imports|<br>ofparts and com|<br> ponents|
|No. of WTO+ provisions|0.00557|0.0160|0.0125*|‐0.00984|
||(0.00553)|(0.00989)|(0.00661)|(0.00683)|
|No. of WTO‐X provisions|0.00102|‐0.00956*|0.0151|0.0220***|
||(0.00328)|(0.00538)|(0.00959)|(0.00663)|
|No. of WTO+ provisions * South‐South||‐0.00359||0.0223**|
|||(0.0112)||(0.00990)|
|No. of WTO‐X provisions * South‐South||0.0246**||‐0.00691|
|||(0.0110)||(0.0113)|
|No. of WTO+ provisions *North‐South||‐0.0259**|‐0.0223**||
|||(0.0117)|(0.00990)||
|No. of WTO‐X provisions * North‐South||0.0315***|0.00691||
|||(0.00896)|(0.0113)||
|No. of WTO+ provisions *North‐North|||0.00359|0.0259**|
||||(0.0112)|(0.0117)|
|No. of WTO‐X provisions * North‐North|||‐0.0246**|‐0.0315***|
||||(0.0110)|(0.00896)|
|BIT|0.127***|0.130***|0.130***|0.130***|
||(0.0316)|(0.0319)|(0.0319)|(0.0319)|
|PTA (in force or inactive)|‐0.0619|‐0.0744|‐0.0744|‐0.0744|
||(0.0490)|(0.0465)|(0.0465)|(0.0465)|
|Observations|336,976|336,976|336,976|336,976|
|R‐squared|0.990|0.991|0.991|0.991|
|Country‐pair FE|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|

Clustered standard errors at the country‐pair level in parenthesis. *** p<0.01, ** p<0.05, * p<0.1 29
Table 11: Deep trade agreements and GVC integration, indirect effect PPML

||(1)<br>DVA|(2)<br>DVA final|(3)<br>DVA<br>intermediate|(4)<br>DVA int.<br>re‐exported|(5)<br>FVA|(6)<br>FVA final|(7)<br>FVA<br>intermediate|
|---|---|---|---|---|---|---|---|
|No. of provisions|0.0133***|0.00982***|0.0138***|0.0150***|0.0104***|0.00815***|0.0107***|
||(0.00209)|(0.00255)|(0.00213)|(0.00231)|(0.00201)|(0.00241)|(0.00184)|
|BIT|0.380***|0.322***|0.359***|0.334***|0.309***|0.291***|0.276***|
||(0.0944)|(0.0947)|(0.0914)|(0.0933)|(0.0785)|(0.0817)|(0.0820)|
|PTA (in force or||||||||
|inactive|0.143|0.359***|0.0224|0.127|0.221**|0.500***|0.0208|
||(0.113)|(0.0943)|(0.115)|(0.120)|(0.102)|(0.110)|(0.0942)|
|Observations|26,520|26,520|26,520|26,520|26,520|26,520|26,520|
|R‐squared|0.980|0.987|0.974|0.972|0.988|0.988|0.986|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 Table 12: Deep trade agreements and GVC integration‐ interval estimations, PPML

||(1)<br>DVA|(2)<br>DVA final|(3)<br>DVA<br>intermediate|(4)<br>DVA int. re‐<br>exported|(5)<br>FVA|(6)<br>FVA final|(7)<br>FVA<br>intermediate|
|---|---|---|---|---|---|---|---|
|No. of provisions|0.00431***|0.00308*|0.00488***|0.00565***|0.00337**|0.00227|0.00379***|
||(0.00137)|(0.00173)|(0.00151)|(0.00179)|(0.00142)|(0.00179)|(0.00130)|
|BIT|0.123***|0.0827|0.145***|0.119**|0.0794**|0.0491|0.104**|
||(0.0452)|(0.0580)|(0.0486)|(0.0551)|(0.0385)|(0.0513)|(0.0414)|
|PTA (in force or||||||||
|inactive)|‐0.0457|0.154***|‐0.148***|‐0.138*|‐0.000971|0.233***|‐0.149***|
||(0.0514)|(0.0559)|(0.0570)|(0.0715)|(0.0486)|(0.0592)|(0.0478)|
|Observations|9,360|9,360|9,360|9,360|9,360|9,360|9,360|
|R‐squared|0.995|0.996|0.992|0.990|0.997|0.996|0.996|
|Country‐pair FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Period|3‐year|3‐year|3‐year|3‐year|3‐year|3‐year|3‐year|

Clustered standard errors at the country pair level in parentheses. *** p<0.01, ** p<0.05, * p<0.1 30
Table 13: Deep trade agreements and trade in parts and components interval estimations, PPML

||(1)|(2)|(3)|
|---|---|---|---|
|No. of provisions|0.00439***<br>(0.00158)|||
|Core provisions||0.00777**<br>(0.00355)||
|PCA depth|||0.0305**<br>(0.0138)|
|BIT|0.146***|0.144***|0.145***|
||(0.0349)|(0.0350)|(0.0350)|
|PTA (in force or inactive)|‐0.0520|‐0.0771|‐0.0581|
||(0.0560)|(0.0555)|(0.0555)|
|Observations|116,400|116,400|116,400|
|R‐squared|0.988|0.989|0.988|
|Country‐pair FE|Yes|Yes|Yes|
|Country‐time FE|Yes|Yes|Yes|
|Period|3‐year|3‐year|3‐year|

Clustered standard errors at the country‐pair level in parenthesis. *** p<0.01, ** p<0.05, * p<0.1 31