The economic impact of the Trans‐Pacific Partnership: What have we learned from CGE simulation?

• Author: Robert Scollay,John Gilbert,Taiji Furusawa
• DOI: http://doi.org/10.1111/twec.12573
• Published date: 01 March 2018
• Date: 01 March 2018

ORIGINAL ARTICLE

The economic impact of the Trans-Pacific Partnership:

What have we learned from CGE simulation?

John Gilbert

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Taiji Furusawa

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Robert Scollay

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Department of Economics & Finance, Utah State University, Logan, UT, USA

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Graduate School of Economics, Hitotsubashi University, Kunitachi, Tokyo, Japan

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Department of Economics, University of Auckland, Auckland, New Zealand

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INTRODUCTION

Negotiations for the Trans-Pacific Partnership (TPP) agreement were concluded in October 2015.

If implemented as concluded, the TPP would be among the largest and most comprehensive free

trade agreements (FTAs) ever seen. Together, the 12 original TPP member economies (Australia,

New Zealand, Japan, Brunei, Malaysia, Singapore, Vietnam, USA, Canada, Mexico, Chile and

Peru) generate 36% of the value of global production and over a quarter of world trade. Providing

rationalisation and intensification of a substantial part of the “noodle bowl”of overlapping and

intersecting FTAs that have expanded among countries of the Asia–Pacific, the TPP would not

only liberalise trade barriers on goods and services and free up investment flows, but would also

enhance trade facilitation, encourage the development of production and supply chains, strengthen

intellectual property provisions and make provisions for investor-state arbitration.

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The outlook for the TPP changed dramatically in January 2017, when the USA indicated that it

would withdraw from the agreement and instead pursue bilateral FTAs. Implementation of the TPP in

its current form thus looks unlikely. Nevertheless, the TPP remains the only exemplar to date of a

mega-regional FTA for which negotiations have been successfully concluded. As such, assessments of

its potential effects are of considerable interest in the context of widespread attention on “mega-regio-

nal”FTAs and their implications both for their prospective members and for the global trading system.

Assessments of the TPP are also of interest as a basis for comparison with proposals for alternative

arrangements that may emerge in the coming months or years, including the bilateral FTAs foreshad-

owed by the USA, as well as with other “mega-regional”FTAs currently under negotiationor study.

Answers to a number of quantitative questions are central to any assessment of the potential effects of

the TPP. What is the likely magnitude of the economic gains from the TPP as envisaged? How depende nt

are those gains on the details of the agreement? How do the gains compare to other proposals? Are they

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The TPP evolved from the so-called “P4”or Trans-Pacific Strategic Economic Partnership (TPSEP) between Singapore,

Chile, New Zealand and Brunei–Darussalam. In 2008, the USA identified TPSEP as an expedient entry point for the trade

element of its pivot to Asia, and in 2010, TPP negotiations were launched between the USA, the four original TPSEP mem-

bers, Australia and Peru. Malaysia and Vietnam joined soon after. Canada and Mexico joined in 2011 and Japan in 2013,

the latter after a ferocious 3-year domestic debate, primarily over the implications of the TPP for Japanese agriculture.

DOI: 10.1111/twec.12573

World Econ. 2018;41:831–865. wileyonlinelibrary.com/journal/twec ©2017 John Wiley & Sons Ltd

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evenly distributed across member economies and across societies within the members? How would the

TPP affect non-members, especially the least developed economies? What would be the consequences of

expanding the TPP, or of members dropping out? What types of resulting changes might we observe in

the pattern of economic activity in the member economies? This list is n ot exhaustive.

One of the most widely used techniques for evaluating the potential economic implications of large-

scale changes in trade policy is computable general equilibrium, or CGE, modelling. General equilib-

rium is the branch of economics concerned with the simultaneous determination of prices and quantities

in multiple interconnected markets. CGE models are numerical simulations built on general equilibrium

principles, designed with the objective of turning the theory into a practical tool of policy analysis.

While the approach hasits strengths and weaknesses (and its detractors, see Kehoe, 2003), it has proven

a useful tool for the ex-ante analysis of trade policy. CGE models are multisectoral, often multiregional,

flexible and logically consistent. Designed to track linkages across an economic system, they are well

suited to examining the economywide implications of large changes in the economic environment and/

or changes that affect multiple parts of the economic systemat the same time.

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There have now been a large number of studies written that use CGE methods to analyse the

TPP (around 40 of which we are aware). In this paper, we provide a comprehensive survey of the

existing studies and a synthesis of the key results that have emerged. The information should be

useful to both policymakers looking to evaluate key themes and contextualise results from what is

now a substantial body of literature and to researchers in the area looking both to compare their

results to existing work and to identify gaps that new research may gainfully address.

We also provide some new simulation results, examining the trade liberalisation component of the

TPP in comparison with two other proposed “mega-regional”FTAs: the Regional Comprehensive Econ-

omic Partnership (RCEP) and the Free Trade Area of the Asia–Pacific (FTAAP).

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We also consider the

implications of excluding “sensitive”products from the TPP agreement, of possible expansions of the

TPP to include countries which have expressed an interest in joining at a future date and of the withdrawal

of the USA from the agreement. Our simulations are among the first to utilise the GTAP9 database, with

its substantially updated data and improved regional coverage.

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They are also among the first to have tariff

and TRQ liberalisation scenarios constructed from a detailed examination of the actual agreement.

In the following section, we provide a broad overview of the CGE work on the TPP. We next consider

the results of the models, organised thematically. Our own new simulation results are used throughout to

anchor the discussion. The final section contains concluding comments and suggestions for future work. In

the Appendix, we present a table summarising the studies with their key model features and results.

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OVERVIEW OF THE MODELLING APPROACHES

CGE studies of the TPP have adopted a range of theoretical structures, data and simulation design

strategies. By far, the most common theoretical structure is the GTAP model described in

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Applications of CGE to trade policy are numerous. See Scollay and Gilbert (2000) for APEC, Gilbert and Wahl (2002) for

Chinese trade reform, Bekkers and Rojas-Romagosa (2016) for the TTIP and Robinson and Thierfelder (2002) and Lloyd

and MacLaren (2004), for more general overviews of regional trade agreements. Also see the meta-analysis of Hess and

von Cramon-Taubadel (2008). Introductions to the structure of typical CGE models include Gilbert and Tower (2013) and

Hosoe, Gasawa, and Hashimoto (2010). An overview of recent developments is Dixon and Jorgenson (2013).

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The former aims to consolidate and deepen trade liberalisation among the economies of ASEAN and those economies with

which ASEAN already has a plurilateral trade agreement (i.e. Australia, New Zealand, Japan, South Korea, China and

India), while the latter is conceived as an FTA among all 21 member economies of APEC.

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See also Nguyen, Nguyen, Itakura, Nguyen, and Nguyen (2015), Petri, Plummer, and Zhai (2012) and USITC (2016).

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Hertel (1997), which is used in its base form in around half of the studies, and in a modified form

in several more. GTAP is a multiregional model that is in widespread use; hence, we dispense with

a detailed description. In brief, it is a static, perfectly competitive, Armington global trade model.

Within the GTAP-based studies, most assume fixed factor supplies and variable factor prices.

Kawasaki (2015) and Whittaker, Scollay, and Gilbert (2013) allow for capital accumulation effects.

Narayanan and Sharma (2016) allow for unemployment of labour. Several papers modify the

underlying theory of GTAP. Changes range from minor, as in Whittaker et al. (2013), who allow

for regional variation in key parameters, and Cabinet Secretariat (2015) and USITC (2016), who

introduce an elastic labour supply, to the more substantive changes in Akgul, Villoria, and Hertel

(2014), who introduce firm heterogeneity in an interesting proof of concept. Examples of linking

GTAP results to other models include Ganesh-Kumar and Chatterjee (2014), who use the World

Bank’s POVCAL tool in conjunction with CGE simulation to assess poverty impacts.

Ciuriak and Xiao (2014) use a modified version of the GTAP model with recursive dynamics

and a treatment of FDI. The approach is similar to that of the GTAPDyn model described in Ian-

chovichina and McDougall (2000), and utilised in several studies (Cheong & Tongzon, 2013; Ita-

kura & Lee, 2012; Lee & Itakura, 2013, 2014; Strutt, Minor, & Rae, 2015). USITC (2016) also

uses a recursive dynamic version of GTAP. The PEP model used by Cororaton and Orden (2015),

the MIRAGE model used in Disdier, Emlinger, and Foure (2016), and the model employed by Li

(2014), are other examples of applications of recursive dynamic models with a competitive Arm-

ington structure.

In other innovations, Li and Whalley (2014) employ an Armington-type model, but introduce

money and generalised trade costs (see also Li, Wang, & Whalley, 2014). In a well-known series

of studies (Lakatos, Maliszewska, Ohnsorge, Petri, & Plummer, 2016; Petri, 2013; Petri & Plum-

mer, 2016; Petri et al., 2012; Petri, Plummer, & Zhai, 2013, 2014), the framework of Zhai (2008)

is adopted. This model introduces monopolistic competition into manufactures product ion and

allows for firm heterogeneity. The model is able to capture potential trade changes at both the

intensive and extensive margin. Roh and Oh (2016) also introduce firm heterogeneity.

The base data for almost all of the studies is GTAP. For computational purposes, it is generally

aggregated. The level of regional and commodity detail ranges from “toy”models with 3

regions 92 commodities (Akgul et al., 2014) to models with 27 regions (Li, 2014) and up to 57

commodities (Ciuriak & Xiao, 2014), with most in the range of 20–25 regions and commodities.

The regional aggregations are focused on the Asia–Pacific for obvious reasons, and the commodity

aggregation often emphasises agriculture. The earliest studies were based on GTAP7 data, with a

base year of 2004 (Areerat, Kameyama, Ito, & Yamauchi, 2012; Itakura & Lee, 2012; Oduncu,

Mavus, & G€

unesß, 2014), while most of the remainder use GTAP8, with a base year of 2007. The

work of Nguyen et al. (2015), Petri and Plummer (2016) (see also the extended discussion in

Lakatos et al., 2016), Cabinet Secretariat (2015), and USITC (2016), along with this paper, use the

more recent GTAP9 database, which has a base year of 2011.

Despite the consistency in the primary data source, there is a lot of variation in terms of modifica-

tions. Several of the static models update the data to a more recent base year (Kawasaki, 2015;

USITC, 2016) or project the equilibrium forward to the presumed time of liberalisation (e.g. 2020 in

the case of Whittaker et al., 2013; and 2025 for Burfisher et al., 2014). The recursive dynamic stud-

ies, by design, all develop baselines going out as far as 2030 (Itakura & Lee, 2012; Petri & Plummer,

2016) and even 2047 (USITC, 2016). A number of studies incorporate information on other FTAs

that have already been agreed upon (e.g., Cheong & Tongzon, 2013; Disdier et al., 2016; Narayanan

& Sharma, 2016; Petri & Plummer, 2016; Petri et al., 2012). Several studies incorporate infor mation

on NTBs from various sources into the base data (Cabinet Secretariat, 2015; Cororaton & Orden,

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