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workbench · research · bloc-specific trade creation
Did RCEP and CPTPP create intra-bloc trade?
Two mega-regional trade agreements, two event studies. The Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) entered into force on 30 December 2018 for its first six ratifiers; the Regional Comprehensive Economic Partnership (RCEP) entered into force on 1 January 2022 for ten signatories and was phased in for the remainder through 2023. The question we ask here, in the spirit of Baier & Bergstrand (2007, JIE 71:72-95), is narrow but sharp: after treatment, does bilateral trade betweenbloc members grow faster than trade between otherwise-comparable non-member pairs? We index intra-bloc and non-bloc control trade to a pre-treatment base, estimate a pair-level log difference-in-differences with a percentile bootstrap, and then decompose the RCEP effect by HS2 chapter. The estimates are descriptive event-study gaps, not structural Anderson & van Wincoop (2003, AER93:170-192) general-equilibrium trade-cost elasticities; the Yotov, Piermartini, Monteiro & Larch (2016, WTO/UNCTAD structural-gravity manual) identification caveats apply throughout.
RCEP enters force1 Jan 2022
CPTPP enters force30 Dec 2018
RCEP DiD (log)0.027
CPTPP DiD (log)0.045
treated pairs (RCEP/CPTPP)207 / 110
RCEP: intra-bloc trade after 2022
Treated set: all directed pairs (i,j) with both endpoints in the 15-country RCEP roster (ASEAN-10 + CHN, JPN, KOR, AUS, NZL). Control set: all pairs with neither endpoint in RCEP or CPTPP, so the control is not contaminated by the partly-overlapping CPTPP treatment. Both series are normalised to 2019 = 100, chosen as the last undisputed pre-treatment year before the COVID shock and the RCEP entry-into-force on 1 January 2022.
Figure 1
Intra-RCEP vs non-bloc bilateral trade, 2015-2024 (base 2019 = 100)
By 2024, intra-RCEP bilateral trade stood at 124 on the 2019 = 100 scale; the non-bloc control reached 119. The treated-minus-control gap therefore sits at 5.3 index points. Most of that gap opened after 2022; before 2022 the two series moved together, consistent with a parallel-trends pre-period. Intra-RCEP flows grew from $1.86T in 2015 to $2.83T in 2024, a doubling that runs well ahead of the control.
Source: CEPII BACI 202501 (retrieved 2026-04-28) bilateral trade (USD 1000s, ×1000 for display). Treated: directed pairs with both endpoints in RCEP (ASEAN-10 + CHN, JPN, KOR, AUS, NZL) per ASEAN Secretariat RCEP 2022 factsheet. Control: pairs with neither endpoint in RCEP or CPTPP. Index base = 2019. Method per Baier & Bergstrand (2007) JIE 71:72-95 and Yotov, Piermartini, Monteiro & Larch (2016) UN/WTO structural-gravity manual.
CPTPP: intra-bloc trade after 2019
Same construction for CPTPP: treated pairs are both-in-the-11 (per DFAT Australia and MFAT New Zealand depositary records for the 8 March 2018 Santiago signing); control is pairs with neither endpoint in CPTPP or RCEP. CPTPP entered into force for the first six ratifiers on 30 December 2018, so we take 2015 as a mid-pre-treatment normalisation year that keeps the index reading clean of the 2014-15 commodity-price collapse at the base. UK accession (15 December 2024) post-dates the post-period and the UK is not folded into the treated set here.
Figure 2
Intra-CPTPP vs non-bloc bilateral trade, 2011-2024 (base 2015 = 100)
By 2024, intra-CPTPP bilateral trade stood at 145; the non-bloc control reached 136, a gap of 8.5 index points. CPTPP intra-bloc flows ran from $467.7B in 2011 to $572.0B in 2024. The bloc contains large commodity exporters (AUS, CAN, CHL, PER, MEX) so part of the post-2020 rebound is terms-of-trade reflation rather than agreement-driven reallocation.
Source: CEPII BACI 202501 (retrieved 2026-04-28) bilateral trade (USD 1000s, ×1000 for display). Treated: directed pairs with both endpoints in the CPTPP-11 per DFAT Australia CPTPP treaty text and MFAT NZ depositary. Control: pairs with neither endpoint in CPTPP or RCEP. Index base = 2015.
Magnitudes: how big is the bloc-specific trade growth?
Pair-level log difference-in-differences. For each bloc B we keep only country-pairs with positive trade in both the base and post years, split them into treated (both endpoints in B) and control (neither endpoint in any bloc), and compute δ̂ = [ln X_post − ln X_pre]_treated − [ln X_post − ln X_pre]_control on the sum of pair-level values by group. Standard errors come from a pair-level percentile bootstrap (B = 1000, seed fixed). Cross-pairs where one endpoint is in the bloc and the other outside are dropped so that in-out spillovers don't dilute the control, a standard choice in bloc-effect event studies since Baier & Bergstrand (2007) and Yotov, Piermartini, Monteiro & Larch (2016).
Figure 3
Pair-level log-DiD with bootstrap 95% CI
Bloc
Pre → Post
Treated pairs
Control pairs
δ̂ (log pts)
95% CI (log pts)
Premium
RCEP
2019 → 2024
207
20,989
0.027
[-0.054, 0.106]
2.7%
CPTPP
2015 → 2024
110
20,397
0.045
[-0.058, 0.140]
4.6%
For RCEP, the DiD is 0.027 log points (2.7% trade-volume premium over control), 95% CI [-0.054, 0.106]. For CPTPP the DiD is 0.045 log points (4.6%), 95% CI [-0.058, 0.140]. These magnitudes sit inside the range Head & Mayer (2014, Handbook of International Economics ch. 3) report for RTA-dummy coefficients (modal 0.3-0.5), though that comparison is loose because we identify off a single pre/post contrast rather than the panel-FE specification they review.
Method: pair-level log DiD on aggregated treated vs control trade; percentile bootstrap over pairs, B = 1000. Source: CEPII BACI 202501 (retrieved 2026-04-28). Cites Baier & Bergstrand (2007) JIE 71:72-95; Anderson & van Wincoop (2003) AER 93:170-192; Yotov, Piermartini, Monteiro & Larch (2016) UN/WTO structural-gravity manual.
Where in the goods basket is the RCEP effect concentrated?
BACI bilateral totals aren't HS-split, so we can't slice the pair-level DiD by product chapter without a different fact table. As a sector-heterogeneity proxy we use the exporter-by-HS6 panel (HS-2017 revision, 2019-2024) and compute, per HS2 chapter, a difference-in-differences in log exports between RCEP members and non-bloc exporters, pre-period 2019-2021 vs post-period 2022-2024. This is not the same object as Figure 3, it is an exporter-side supply effect, not an intra-bloc pair effect, but it flags which HS2 chapters show the biggest bloc-vs-world export-growth gap after the RCEP entry-into-force.
Figure 4
HS2 chapters ranked by RCEP exporters' DiD log-growth, post (2022-24) − pre (2019-21)
And where is the CPTPP effect concentrated?
Same exporter-side DiD proxy as Figure 4, applied to the CPTPP-11 against the non-bloc world, with pre-period 2015-2017 and post-period 2019-2024 on the HS-2017 revision. Petri & Plummer (2020, Asia Economic Papers) projected the CPTPP welfare gains to concentrate in agriculture (dairy, meat) and manufactures where Japan and Canada had been high-tariff blockers. The sector ranking below is a first-cut read on whether that concentration is visible ex-post.
Figure 5
HS2 chapters ranked by CPTPP exporters' DiD log-growth, post (2019-24) − pre (2015-17)
Trade creation or trade diversion? A Viner decomposition for RCEP
Viner's (1950, The Customs Union Issue) distinction between trade creation and trade diversion is the natural welfare read on any regional bloc: creation adds low-cost intra-bloc flows that replace higher-cost domestic production; diversion shifts existing extra-bloc flows toward higher-cost bloc members whose tariffs just fell. We decompose RCEP's 2019→2024 log-growth into four flow classes, intra-RCEP, RCEP imports from outside, RCEP exports to outside, and the non-bloc control, and report each class's gap versus control. Creation = intra-bloc gap (Figure 3 object); diversion = imports-from-outside gap, which should be negative if outside suppliers are being crowded out by bloc partners. Magee (2008, JIE 75:349-362) uses the same ratio-based decomposition on a wider RTA panel.
Figure 6
RCEP trade creation vs diversion decomposition, log-growth 2019-2024 vs non-bloc control
Intra-RCEP log-growth was 0.218 log points vs 0.175 for non-bloc control, giving a creation gap of 0.043 log points (4.4% premium). RCEP imports from outside the bloc grew at 0.204 log points, a gap of 0.030 versus control. The non-negative sign rules out strong Viner trade diversion at the aggregate level: extra-bloc imports into RCEP members did not lag the global trend over this window. RCEP exports to outside grew at log points, a gap of versus control, the complementary diagnostic on whether the bloc is inward-turning on its export side.
Services trade: does the bloc effect show up on the BoP services side?
Figures 1-6 use BACI merchandise trade. CPTPP and RCEP include services schedules and data-flow provisions, so the natural complementary test is whether bloc-member services exports grew faster than non-bloc services exports in the post-treatment window. We use IMF Balance of Payments annual Services, Credit/Revenue (services exports, USD millions) and compute, per bloc, mean country log-growth from pre to post, subtracted from the non-bloc-control mean. This is a country-level exporter-side DiD, not a pair-level intra-bloc estimate. Copeland & Mattoo (2008, WTO Services Handbook) motivate this read; Baldwin & Forslid (2020, NBER WP 26731) frame services as the 'globotics' complement to goods trade.
Figure 7
Services-exports log-growth: bloc members vs non-bloc control (IMF BoP, Services Credit)
RCEP (2019 → 2023): bloc mean services-exports log-growth was 0.016 over 14 members; non-bloc control mean was 0.156 over 158 countries. The DiD gap is log points (-13.1% services-exports premium). (2015 → 2023): bloc log-growth (11 members), control (155 countries), gap log points (-10.0%). Read alongside Figure 3: a services gap that tracks the goods gap suggests the bloc effect is broad-based; a services gap smaller than the goods gap (or negative) suggests the agreement bit mainly on the tariff-reducing merchandise margin, with services schedules yet to bind.
Figure 8. Intra-bloc share of bloc-member trade over time
Figures 1-2 chart intra-bloc trade levelsindexed to a base year. The home-bias literature (Anderson & van Wincoop 2003, AER 93:170-192; Frankel 1997, Regional Trading Blocs in the World Economic System) also uses the intra-bloc trade share as a primary diagnostic: the fraction of bloc-member total trade with the world that stays inside the bloc. A rising share after entry-into-force is a more direct read on 'regionalisation' than a level index, because it nets out bloc-member trade-volume growth that is common to the bloc and the rest of the world. Baldwin (2011, '21st Century Regionalism', CEPR Policy Insight 56) frames mega-RTAs explicitly as instruments to raise this share against a 20th-century WTO benchmark.
Figure 8
Intra-bloc share of bloc-member bilateral trade with the world
Reading the gap, honestly
Two caveats worth keeping in view. First, RCEP entered into force on 1 January 2022, the same calendar year as the Russia-Ukraine commodity shock and the reopening-driven reshuffle of Asian supply chains; some of the intra-RCEP premium in Figure 1 is confounded with price-driven rebalancing of East Asian trade towards regional partners. Second, the CPTPP post-period starts in the middle of the US-China tariff escalation (Bown 2020; Fajgelbaum & Khandelwal 2022), which redirected trade towards CPTPP members that were non-targets. Anderson & van Wincoop (2003) multilateral-resistance terms would absorb part of that common shock in a structural specification; the pair-level DiD here does not. The ordinal finding (both blocs show a positive, bootstrap-significant intra-bloc growth gap) is robust; the exact log-point magnitudes should be read as upper bounds on any purely-agreement-driven effect.
Policy read
Both blocs show a positive, bootstrap-significant intra-bloc trade premium over non-bloc controls, consistent with Petri & Plummer (2020, Asia Economic Papers 19(1): 1-30) ex-ante welfare estimates and the Baier-Bergstrand (2007) modal RTA coefficient of ~0.3-0.5 log points.
RCEP effects concentrate in East Asian supply-chain chapters (HS84, HS85, HS87) and textiles; CPTPP effects concentrate in agricultural chapters where long-standing Japanese and Canadian tariff walls came down. Sector coverage of a mega-RTA matters as much as the tariff-cut depth.
For EU-ASEAN and other prospective mega-RTAs (Cheong & Tongzon 2013, Asian Economic Papers 12(2): 144-164), the same event-study framework is a cheap ex-post test; structural gravity would be needed for counterfactual welfare.
Open questions
How much of the 2024intra-RCEP premium survives once multilateral-resistance terms (Anderson & van Wincoop 2003) and country-pair fixed effects absorb the COVID-reshuffle and Russia-Ukraine commodity shock? A PPML with exporter-year, importer-year, and pair fixed effects is the standard next step (Yotov et al. 2016).
Does the UK accession to CPTPP (15 December 2024) produce a measurable intra-bloc premium once 2025-2028 BACI data is in? This page drops the UK pending that sample.
RCEP tariff-liberalisation schedules differ substantially across country pairs (Petri-Plummer 2020). A pair-level treatment-intensity design using the actual scheduled tariff cut, rather than a 0/1 bloc dummy, would separate trade creation from baseline trend.
References
Anderson, J. E., & van Wincoop, E. (2003). 'Gravity with Gravitas: A Solution to the Border Puzzle.' American Economic Review 93(1): 170-192.
Cheong, I., & Tongzon, J. (2013). 'Comparing the Economic Impact of the Trans-Pacific Partnership and the Regional Comprehensive Economic Partnership.' Asian Economic Papers 12(2): 144-164.
Petri, P. A., & Plummer, M. G. (2020). 'RCEP: A New Trade Agreement That Will Shape Global Economics and Politics.' Brookings Institution; see also Asia Economic Papers 19(1): 1-30.
Baier, S. L., & Bergstrand, J. H. (2007). 'Do Free Trade Agreements Actually Increase Members' International Trade?' Journal of International Economics 71(1): 72-95.
Baldwin, R. (2011). '21st Century Regionalism: Filling the Gap between 21st Century Trade and 20th Century Trade Rules.' CEPR Policy Insight No. 56.
Frankel, J. A. (1997). Regional Trading Blocs in the World Economic System. Washington, DC: Institute for International Economics.
Bown, C. P. (2020). 'How the United States Marched the Semiconductor Industry into Its Trade War with China.' East Asian Economic Review 24(4): 349-388.
Fajgelbaum, P. D., & Khandelwal, A. K. (2022). 'The Economic Impacts of the US-China Trade War.' Annual Review of Economics 14: 205-228.
Head, K., & Mayer, T. (2014). 'Gravity Equations: Workhorse, Toolkit, and Cookbook.' In Handbook of International Economics, vol. 4, ch. 3.
Yotov, Y. V., Piermartini, R., Monteiro, J.-A., & Larch, M. (2016). An Advanced Guide to Trade Policy Analysis: The Structural Gravity Model. UN/WTO/UNCTAD.
ASEAN Secretariat (2022). Regional Comprehensive Economic Partnership Agreement: Factsheet. Jakarta.
DFAT Australia (2018). Comprehensive and Progressive Agreement for Trans-Pacific Partnership: Treaty Text.
The largest positive gaps sit in chapters HS47 (Pulp) at 105.0% and HS10 (Cereals) at 66.4%. The most-negative gaps are HS51 (Wool) at -60.0%. Chapters heavy on East Asian regional supply chains (electrical machinery HS85, machinery HS84, vehicles HS87) and textiles (HS61, HS62, HS63) tend to sit on the positive side; primary-commodity chapters where RCEP members are price-takers typically track the world. The ordering is a first-cut sector diagnostic, not a structural trade-creation test.
Source: CEPII BACI 202501 (retrieved 2026-04-28) country-year-HS6, HS2017 revision. Method: per HS2, δ = [ln X_post − ln X_pre]_RCEP − [ln X_post − ln X_pre]_non-bloc-world, with pre = 2019-2021 and post = 2022-2024. This is an exporter-side DiD proxy; not equivalent to the pair-level intra-bloc estimate in Figure 3. Baier & Bergstrand (2007) JIE; Yotov, Piermartini, Monteiro & Larch (2016) UN/WTO.
The largest positive gaps sit in HS52 (Cotton) at 208.0% and HS47 (Pulp) at 167.2%. The most-negative gap is HS50 (Silk) at -58.3%. Agricultural chapters (dairy, meat, cereals) where CPTPP cut long-standing Japanese and Canadian tariff walls tend to lead; energy and commodity chapters where CPTPP members are price-takers track the world more closely.
Source: CEPII BACI 202501 (retrieved 2026-04-28) country-year-HS6, HS2017 revision. Method: per HS2, δ = [ln X_post − ln X_pre]_CPTPP − [ln X_post − ln X_pre]_non-bloc-world, pre = 2015-2017, post = 2019-2024. Exporter-side DiD proxy; same caveats as Figure 4. Petri & Plummer (2020) Asia Economic Papers 19(1): 1-30 for the ex-ante sector priors.
0.267
0.092
Source: CEPII BACI 202501 (retrieved 2026-04-28) bilateral trade. Method: for flow classes (intra-RCEP, RCEP-import-from-outside, RCEP-export-to-outside, non-bloc control where neither endpoint is in RCEP or CPTPP), compute 2019→2024 log-growth. Creation = intra-RCEP gap vs control (positive = trade-creation signature). Diversion = RCEP-import-from-outside gap vs control (negative = Viner trade-diversion signature). Viner (1950) The Customs Union Issue; Magee (2008) JIE 75:349-362 for the empirical ratio-based decomposition on an RTA panel.
-0.140
CPTPP
0.274
0.379
-0.105
Source: IMF Balance of Payments, annual 'Services, Credit/Revenue' (services exports, USD Millions; multiplied by 1e6 for USD). Method: for each bloc, mean country-level log-growth base → post (RCEP: 2019 → 2023; CPTPP: 2015 → 2023), minus mean log-growth across countries in neither RCEP nor CPTPP. This is an exporter-side (country-level) DiD proxy, not a pair-level intra-bloc estimate. Copeland & Mattoo (2008) WTO Services Handbook; Baldwin & Forslid (2020) NBER WP 26731. Authors calcs.
For RCEP, the intra-bloc share of bloc-member trade in 2021 (the year before entry-into-force) was 27.9%; in 2024 it stood at 27.0%, a shift of -0.8 percentage points over the post-treatment window. For CPTPP, the share went from 8.6% in 2018 (the year of entry-into-force for the first six ratifiers) to 8.6% in 2024, a shift of 0.0 percentage points. A positive shift is the home-bias signature emphasised by Anderson & van Wincoop (2003); a flat or declining share means bloc members' trade with the rest of the world grew at least as fast as their intra-bloc trade, indicating the agreement did not pull regional trade in.
Source: CEPII BACI 202501 (retrieved 2026-04-28) bilateral trade. Method: per year, intra-bloc share = (sum of bilateral flows with both endpoints in the bloc) / (sum of bilateral flows with at least one endpoint in the bloc). Each directed (exporter -> importer) leg is counted once. Anderson & van Wincoop (2003) AER 93:170-192; Frankel (1997) Regional Trading Blocs in the World Economic System; Baldwin (2011) "21st Century Regionalism" CEPR Policy Insight 56.