OSIPP Discussion Paper: DP-2014-E-003

TPP, RCEP, and Japan’s Agricultural Policy Reforms*
March 31, 2014
Hiro Lee†
Osaka School of International Public Policy, Osaka University

Ken Itakura
Graduate School of Economics, Nagoya City University

Keywords: TPP, RCEP, CGE model, Japan, agricultural policy reform
JEL codes: F15, F17
Abstract: In this paper we compare welfare effects and the extent of sectoral adjustments
under the proposed Trans-Pacific Partnership (TPP) agreement and the Regional
Comprehensive Economic Partnership (RCEP) accords using a dynamic computable
general equilibrium (CGE) model from the perspective of Japan. The ambitious goals ofboth organizations, as well as overlapping membership, make comparisons of different
scenarios particularly intriguing. Another objective of this paper is to examine the effectsof Japan’s agricultural policy reforms on its agricultural output. If agricultural reforms,
such as phasing out gentan and consolidation of agricultural land, lead to an improvementin productivity of agricultural sectors, then the extent of output contraction of agriculturaland processed food sectors in Japan would be reduced significantly except for dairy
products. This suggests the importance of carrying out agricultural reforms in Japan forregion-wide trade accords.

* We are grateful for helpful comments on earlier versions to Fukunari Kimura, Michael G.

Plummer and Raed Safadi. We gratefully acknowledge financial support from the Japan Society for
the Promotion of Science program, Grants-in-Aid for Scientific Research (B) No. 25285076.
† Corresponding author. Osaka School of International Public Policy, Osaka University, 1-31

Machikaneyama, Toyonaka, Osaka 560-0043, Japan. Email: hlee@osipp.osaka-u.ac.jp.

1. Introduction
In response to slow progress in the Doha Round, Asian countries have accelerated
bilateral and regional trade initiatives. While global free trade is the ultimate goal, many
countries strive not to be left out of the recent wave of free-trade agreements (FTAs).
Negotiations for two major FTAs in the region – Trans-Pacific Partnership (TPP) andRegional Comprehensive Economic Partnership (RCEP) – are in progress. Japan joined theTrans-Pacific Partnership (TPP) negotiations in July 2013 as the 12th member, and Korea
has decided to join TPP negotiations and has started engaging in consultations with the
TPP members. RCEP was launched in November 2012 and negotiations among 10
ASEAN countries and their six FTA partners started in May 2013. Both TPP and RCEP
are open to new members, and some other Asian countries are expected to join TPP in therelatively near future. Over the longer term, there is a strong possibility that enlarged TPP
and/or enlarged RCEP will lead to the creation of a Free Trade Area of the Asia-Pacific(FTAAP).
Using a global dynamic computable general equilibrium (CGE) model, we evaluate
the welfare and sectoral output effects of Asian-track and three TPP-track scenarios. In
Scenario 1 (Asian-track), an RCEP agreement is presumed to be implemented over the
2017-2025 period and FTAAP over the 2023-2030 period. In Scenario 2-A (TPP-track A),
we assume that the 12 countries that are currently negotiating a TPP agreement plus Korea(TPP-13) will implement a trade accord over the period 2015-22. 1 Three additionalcountries – Indonesia, the Philippines and Thailand – are assumed to join the TPP in 2018
and complete preferential liberalization with the TPP-13 countries by 2025. Finally, it ishypothesized that FTAAP is implemented during 2023-2030 as in Scenario 1. Scenario 2B (TPP-track B) adds an additional assumption that productivity of Japan’s agricultural
sectors increases by 1% per annum starting in 2016, resulting from its policy reforms. In
Scenarios 1, 2-A and 2-B, we assume that rice is excluded from trade liberalization in
RCEP, TPP and FTAAP. In Scenario 2-C (TPP-track C), we assume that tariffs on rice are

1 Although the twelve negotiating countries are likely to sign a TPP agreement first, Korea is expected

to be approved as a new member in a relatively short period thereafter.

2

cut by 50% in FTAAP over the implementation period to examine the sensitivity of thetariff cut on the rice sector in Japan.
A number of studies have quantified the effects of various FTAs in the Asia-Pacificregion using a CGE model (e.g., Itakura and Lee, 2012; Kawai and Wignaraja, 2008; Leeet al., 2009; Li and Whalley, 2012; Petri, Plummer and Zhai, 2012ab). While Petri et al.’s(2012b) study was the first to examine the effects of Asian-track and Trans-Pacific-track,
RCEP had not been launched at the time of their writing. As a result, the Asian-track of a
China-Japan-Korea FTA, followed by ASEAN+3 FTA (EAFTA) and FTAAP in theirstudy is no longer realistic. One of our aims is to construct FTA sequences that arereasonable estimates of the future sequences of region-wide FTAs in the Asia-Pacific.
Another goal of this paper is to show that agricultural policy reforms in Japan
would be indispensable to avoid sharp reductions in output of many agricultural and foodproducts resulting from region-wide FTAs. We will not know whether any agricultural
products will be exempted from tariff liberalization until an agreement is reached.
However, we assume that rice will be excluded in three of the four policy scenarios
because Japan is unlikely to join TPP without an exclusion of rice.
An overview of the model and data is given in the next section, followed bydescriptions of the baseline and policy scenarios in section 3. In section 4 assessments ofwelfare and sectoral output effects under each policy scenario are offered. Concluding
remarks are provided in the final section.
2. Analytical Framework and Data
2.1 Overview of the Dynamic GTAP Model
The numerical simulations undertaken for this study are derived from the dynamic
GTAP model, described in detail by Ianchovichina and McDougall (2001) and Walmsley
and Ianchovichina (2012). This model extends the comparative static framework of thestandard GTAP model developed by Hertel (1997) to the dynamic framework by
incorporating international capital mobility and capital accumulation. The dynamic GTAP
model allows international capital mobility and capital accumulation, while it preserves all
the features of the standard GTAP, such as constant returns to production technology,3perfectly competitive markets, and product differentiation by countries of origin, in
keeping with the so-called Armington assumption.2 At the same time, it enhances theinvestment theory by incorporating international capital mobility and ownership. In thisway it captures important FTA effects on investment and wealth that are missed by a static
model.
In the dynamic GTAP model, each of the regions is endowed with fixed physicalcapital stock owned by domestic firms. The physical capital is accumulated over time withnew investment. This dynamics are driven by net investment, which is sourced fromregional households’ savings. The savings in one region are invested directly in domestic
firms and indirectly in foreign firms, which are in turn reinvested in all regions. The
dynamics arising from positive savings in one region is related to the dynamics from thenet investment in other regions. Overall, at the global level, it must hold that all the savings
across regions are completely invested in home and overseas markets.
In the short run, an equalization of the rates of return seems unrealistic, and there
exist well-known empirical observations for “home bias” in savings and investment. Theseobservations suggest that capital is not perfectly mobile, causing some divergence in therates of return across regions. The dynamic GTAP model allows inter-regional differencesin the rates of return in the short run, which will be eventually equalized in the very longrun. It is assumed that differences in the rates of return are attributed to the errors ininvestors’ expectations about the future rates of return. During the process, these errors aregradually adjusted to the actual rate of return as time elapses, and eventually they are
eliminated and a unified rate of return across regions can be attained. Income accruing
from the ownership of the foreign and domestic assets can then be appropriately
incorporated into total regional income.
Participating in an FTA could lead to more investment from abroad. Tradeliberalization often makes prices of goods in a participating country lower due to removal

2 See Armington (1969). The model uses a nested CES structure, where at the top nested level, eachagent chooses to allocate aggregate demand between domestically produced goods and an aggregate
import bundle, while minimizing the overall cost of the aggregate demand bundle. At the second level,
aggregate import demand is allocated across different trading partners, again using a CES specification,
wherein the aggregate costs of imports are minimized.

4

of tariffs, creating an increase in demand for the goods. Responding to the increased
demand, production of the goods expands in the member country. The expansion of
production is attained by using more intermediate inputs, labor, capital, and other primaryfactor inputs. These increased demands for production inputs raise the corresponding
prices, wage rates, and rental rates. Higher rental rates are translated into higher rates ofreturn, attracting more investment from both home and foreign countries.
2.2 Data, aggregation, and initial tariffs
In this study we employ the GTAP database version 8.1, which has a 2007 baseyear and distinguishes 129 countries/regions and 57 sectors (Narayanan et al., 2012). For
the purposes of the present study, the data has been aggregated to 22 countries/regions and
32 sectors, as shown in Table 1. Foreign income data are obtained from the International
Monetary Fund (IMF)’s Balance of Payments Statistics, which are used to track
international capital mobility and foreign wealth. The values of key parameters, such as
demand, supply and CES substitution elasticities, are based upon previous empiricalestimates. The model calibration primarily consists of calculating share and shiftparameters to fit the model specifications to the observed data, so as to be able toreproduce a solution for the base year.
The sectoral tariff rates for the 22 countries/regions in 2007 are summarized inTable 2. There are striking differences in the tariff structures across the countries/regions.
Singapore is duty free with the exception of alcohol and tobacco. The exceptionally hightariff rate on rice in Japan stands out. The tariff rates in a number of other agricultural andfood products in Japan are also high, as well as in Korea and India. With the exception ofAustralia, New Zealand and Chile, the tariff rates on some agricultural and food products
are also relatively high in other regions, such as sugar in the United States, Russia and theEU, dairy products and meats in Canada, and rice in the Philippines. In manufacturing thetariff rates on textiles and apparel are relatively high in all regions except China, Singapore,
Chile and the EU. The tariff rate on motor vehicles exceeds 20% in Thailand, Vietnam andIndia.

5

Ad valorem tariff equivalents of nontariff barriers (NTBs) in nine services sectors
are computed as weighted averages of the gravity-model estimates of Wang et al. (2009)
and the values employed by the Michigan Model of World Production and Trade (e.g.
Brown, Kiyota and Stern, 2010). There are even greater variations in tariff equivalents of
NTBs in services than in commodities.

3. The Baseline and Policy Scenarios
3.1 The Baseline Scenario
In order to evaluate the effects of region-wide FTAs in the Asia-Pacific, thebaseline scenario is first established, showing the path of each of the 22 economies/regions
over the period 2007-2030. The baseline contains information on macroeconomic variables
as well as expected policy changes. The macroeconomic variables in the baseline include
projections for real GDP, gross investment, capital stocks, population, skilled and unskilledlabor, and total labor. Real GDP projections were obtained from IMF’s World Economic
Outlook Database. The data on gross fixed capital formation were acquired from the
IMF’s IFS Online. Projections for population were taken from the U.S. Census Bureau’sInternational Data Base, while those for labor were obtained from International Labor
Organisation (ILO)’s Economically Active Population Estimates and Populations.
The projections for population, investment, skilled labor and unskilled labor
obtained for over 150 countries were aggregated, and the growth rates were calculated toobtain the macroeconomic shocks describing the baseline. Changes in the capital stocks
were not imposed exogenously, but were determined endogenously as the accumulation ofprojected investment. Any changes in real GDP not explained by the changes inendowments are attributed to technological change.
In addition, policy projections are also introduced into the baseline. The policies
included in the baseline are those which are already agreed upon and legally binding,including the ASEAN Free Trade Area (AFTA), the ASEAN-China, ASEAN-Korea,
ASEAN-Japan, ASEAN-Australia-New Zealand, ASEAN-India, EU-Korea, and Korea-US
FTAs. It is assumed that tariffs are cut by 80% among the member countries of the FTAs

6

that are being implemented. Rice is excluded from tariff liberalization in FTAs that include
Japan or Korea as a member country.
3.2 Policy Scenarios
Welfare and sectoral output effects of region-wide FTAs and their implications forJapan and Emerging Asia are to be evaluated in this study. The following four scenarios, aswell as the global trade liberalization (GTL) scenario, are designed and summarized inTable 3.
Scenario 1 (Asian-track): RCEP over the period 2017-2025 and FTAAP from 2023-2030.
Rice is excluded from tariff liberalization.
Scenario 2-A (TPP-track A): TPP-13 over the period 2015-2022, TPP-16 from 2018-2025,
and FTAAP from 2023-2030. Rice is excluded.
Scenario 2-B (TPP-track B): Same as Scenario 2-A, except that efficiency on overall
output for Japan’s agricultural sectors is assumed to increase by 1% per annum from 2016.
Scenario 2-C (TPP-track C): Same as Scenario 2-B, except that tariffs on rice are cut by
50% in FTAAP over the implementation period.
GTL: Global trade liberalization over the period 2015-2030.
It is assumed that tariff rates on commodities (except rice where noted) decline
linearly to zero and tariff equivalents of NTBs in services are reduced by 20 percent during
the periods in consideration among the member countries. In addition, time cost of trade –e.g. shipping delays arising from regulatory procedures and inadequate infrastructure – isassumed to fall by 20 percent among them.3
Petri, Plummer and Zhai (2012b) also compare Asian-track and TPP-track FTAs.
There are, however, three notable differences between their scenarios and ours. First, weallow FTAAP to start before the full implementation of RCEP or TPP. Since both of theseregion-wide FTAs are open to new members, there is a relatively strong possibility thatthey would include all the APEC members before they are fully implemented. Second,

3 For a detailed analysis of time cost of trade, see Minor and Hummels (2011).

7

while Petri et al. (2012b) assume that a China-Japan-Korea (CJK) FTA is implemented
first in the Asian-track, we assume that an RCEP agreement would be reached roughly at
the same time as a CJK FTA. This is because there are high political tensions, including
territorial disputes, between China and Japan, as well as between Japan and Korea. Such
disputes and tensions represent an additional barrier that must be surmounted innegotiations aiming to fashion an FTA. Third, mainly because RCEP negotiations started
more than three years after the first round of TPP negotiations in Melbourne, we assume
that it takes a few years longer for RCEP to reach an agreement than TPP.
Three caveats should be borne in mind when interpreting the results presented in
the next section. First, investment liberalization among the member countries is notconsidered because it requires data on foreign direct investment (FDI) flows by source andhost countries and industry, which are unavailable. A challenging extension of the paper
would be to endogenize FDI flows to consider attraction of these flows to developing
member countries, which may have a significant impact, as were the cases for Mexico
joining NAFTA in 1994 and Spain and Portugal joining the EU in 1986. Second, NTBs in
manufacturing are not incorporated in this study due to a lack of reliable empiricalestimates. NTBs also exist in a number of manufacturing sectors, including automobiles,
pharmaceutical products, and some food products. In these products regulatory and otherbarriers, such as stringent standards and testing and certification procedures, exist. Thus,
reductions of NTBs in manufacturing are expected to enlarge the benefits of the FTAs.
Third, we do not incorporate compliance costs associated with rules of origin (ROOs), nor
the cost-mitigating effects arising from consolidating FTAs. As smaller FTAs areconsolidated, the harmful “noodle bowl” effects – caused by different FTAs having
different ROOs and varying coverage – can be mitigated. The compliance cost eventually
becomes zero when all countries participate in a trade agreement because there will be no
ROOs under global trade liberalization (GTL). These issues are left for future research.

8

4. Empirical Findings
4.1 Welfare Effects
Economic welfare is largely determined by four factors: (1) allocative efficiency,(2) the terms of trade, (3) the contribution to equivalent variation (EV) of change in theprice of capital investment goods, and (4) the contribution to EV of change in equity
owned by a region. The fourth factor is determined by the change in equity income fromownership of capital endowments, and it can be further decomposed into three parts: achange in the domestic capital stock, a change in household income earned on capitalabroad, and a change in the domestic capital owned by foreigners.
With respect to these four factors, the direction of a welfare change may besummarized as follows. The allocative efficiency effect is generally positive for membersof region-wide FTAs. This effect is particularly large for a country with high average
initial tariffs. However, it may become negative when the extent of trade diversion isconsiderably large in FTAs with relatively low intraregional trade. The terms-of-tradeeffect is usually positive for the members with low average initial tariffs and negative forthose with high initial tariffs. An increase in the price of capital investment goods
generally raises welfare. A welfare change resulting from a change in the equity holdings
is positive if the sum of the region’s foreign income receipts and an increase in thedomestic capital stock is greater than the foreign income payment, and vice versa.
The welfare results for the five policy scenarios, as percentage point deviations inequivalent variation from the baseline for the years 2020, 2025 and 2030, are summarizedin Table 4. Under Scenario 1 (Asian-track), the welfare level of all RCEP countries
increases in 2020-2030, whereas that of all APEC members increases in 2030. The welfare
gains in 2025 for RCEP countries range from 1.2% (Japan) to 4.3% (Korea), while those in
2030 for the APEC members range from 0.1% (United States) to 4.9% (Korea). The
economic welfare of several nonmember regions decreases slightly in 2020 and/or 2025.
Taiwan is not a member of the RCEP grouping, and its welfare is predicted to fall by 0.5%
in 2020 largely because the shares of its trade with ASEAN+6 countries is high (about
60% of its total trade) and the extent of trade diversion would be relatively large. Thus, it
has a strong incentive to convince the other APEC members of the benefits of FTAAP, as

9its welfare is projected to increase by 4.5% in 2030 when FTAAP is assumed to be fully
implemented.
In Scenario 2-A (TPP-track A), economic welfare of prospective TPP-16 countries
increases during 2020-2030. The welfare gains in 2025 for TPP-16 countries range from
0.2% (United States) to 2.9% (Vietnam), whereas those in 2030 for the APEC members
range from 0.2% (United States) to 4.7% (Korea). Eight East Asian economies, namely
Japan, Korea, Singapore, Indonesia, Malaysia, the Philippines, Thailand and Vietnam, areboth RCEP and probable TPP-16 members. Other than Malaysia and the Philippines, these
economies’ welfare gains in 2025 are smaller under the TPP-track than under the Asiantrack, which is mainly caused by substantially smaller trade with TPP-16 members thantrade with RCEP members.4 However, the differences in welfare gains between the two
tracks are relatively small in 2030 and are sensitive to assumptions on the baseline
scenario.5
In Scenario 2-B (TPP-track B), productivity of Japan’s agricultural sectors is
assumed to increase by one percent per annum starting in 2016, resulting from its policy
reform. The Japanese government has approved a plan to phase out gentan – the systemthat has paid farmers to reduce rice crops since 1971 – by 2018. In addition, in December
2013 the Japanese Diet enacted a bill to consolidate small plots of agricultural land.6 Under
this law, prefectural governments will establish farmland banks. The banks will borrowpieces of farmland from small-scale part-time farmers or those who have stopped farming,and consolidate and lease them to large-scale farmers. Both phasing out gentan andconsolidation of agricultural land are expected to improve productivity of agricultural
sectors in Japan. Other prospective reforms include provisions of direct payments to fulltime farmers, abolitions of subsidies to part-time farmers, lessening regulations on
corporations to participate in agricultural production, and reforming the distribution system

4 Itakura and Lee (2012) find similar results.
5 In the present study, tariffs are cut by 80% among the members of the FTAs included in the baseline

scenario. Lee and Itakura (2013) show that more countries benefit from the TPP-track when tariffs are
cut by 100% among the members of the FTAs included in the baseline.
6 Honma (2010) states that agricultural land per farm in Japan is about 1/120 of that in the United States

and between 1/45 and 1/20 of that in European countries.

10

of agricultural inputs and final products. It remains to be seen to what extent the Japanese
government would carry out agricultural policy reforms.
If the Japanese government is successful in accomplishing reforms and improving
productivity of its agricultural sectors, then Japan’s welfare gains in 2030 are projected toincrease by 0.4 percentage point (from 1.6% to 2.0%) compared with the case of noreforms. Other countries’ economic welfare is virtually unchanged. Considering that
agriculture accounted for only 1.1% of Japan’s GDP in 2012, an increase of 0.4 percentage
point in welfare is large. Lower prices of agricultural products would reduce intermediate
input cost of processed food sectors and some services sectors.
In Scenarios 1, 2-A and 2-B, we assume that rice is excluded from tariff
liberalization in RCEP, TPP and FTAAP. In Scenario 2-C (TPP-track C), we assume thattariffs on rice are cut by 50% (from 422% to 211%) in FTAAP over the implementation
period to examine the sensitivity of the tariff cut on the rice sector in Japan. This would
further increase Japan’s welfare gain in 2030 by 0.1 percentage point (from 2.0% to 2.1%).
4.2 Sectoral Output Adjustments in Japan
Structural adjustments and resource reallocations result from trade accords. The FTA
groupings and differences in the initial tariff rates across sectors and member countries
play a critical role in determining the direction of the adjustments in sectoral output. Other
factors that affect the magnitude and direction of output adjustments for each productcategory include the import-demand ratio, the export-output ratio, the share of each
imported intermediate input in total costs, and the elasticity of substitution between
domestic and imported products.7

7 A sector with a larger import-demand ratio generally suffers from proportionately larger output

contraction through greater import penetration when initial tariff levels are relatively high. In contrast, a
sector with a higher export-output ratio typically experiences a larger extent of output expansion, as aresult of the removal of tariffs in the member countries. The share of imported intermediate inputs in the
total cost of a downstream industry (e.g., the share of imported textiles in the cost of the apparelindustry) would evidently affect the magnitude and direction of output adjustments in the latter sector.
Finally, the greater the values of substitution elasticities between domestic and imported products, thegreater the sensitivity of the import-domestic demand ratio to changes in the relative price of imports,
thereby magnifying the effects of FTAs.

11

Table 5 presents the sectoral output effects for Japan for the year 2030. The change
in rice output is rather small under Scenarios 1, 2-A and 2-B because the tariff rate on thiscommodity is assumed to be fixed. Output of other grains, sugar, livestock, meats anddairy products contracts considerably under Scenarios 1 and 2-A as well as under GTL, inwhich productivity in all sectors is fixed. When agricultural productivity in Japan isassumed to increase by 1% per annum in Scenario 2-B, the extent of contraction would be
reduced significantly except for dairy products. In the meat sector output changes become
positive, suggesting that appropriate policy reforms would sufficiently strengthen thecompetitiveness of Japan’s livestock and meat sectors.
Under both the Asian-track and the TPP-track, the manufacturing and services
sectors in Japan generally increase with the exception of apparel, electronic equipment,
other transport equipment and air transport. The contraction of the apparel sector resultsfrom the removal of relatively high tariffs and sharp increase in imports from China and anumber of ASEAN countries. The reduction in output of electronic equipment in Japan
under TPP, RCEP and FTAAP is also reported by Petri et al. (2014) and might result fromfragmentation of production processes and substantial increase in imports of electronicparts and components from emerging Asia, particularly Indonesia, Thailand and Vietnam.8
For similar reasons, output of other transport equipment contracts in Japan. Finally, thereduction in air transport appears to suggest that Japan’s comparative advantage in sea
transport and the resulting substitution from air transport to sea transport.

5. Conclusion
In this paper, we have used the dynamic GTAP model to investigate how regionwide FTAs in Asia might affect the welfare changes and sectoral output adjustments. The
tariff rate on rice is assumed to be fixed in three of the four policy scenarios. A comparisonof the Asian-track (RCEP followed by FTAAP) and the TPP-track (TPP-13 followed by
8 The sectoral output effects for countries/regions other than Japan are available upon request from thecorresponding author. Kimura and Obashi (2010, 2011) show the increasing importance in machineryparts and components in intra-East Asian trade, particularly in electronic parts and components. In 2007,
17% of total intra-regional merchandise exports are accounted for by ICT-related parts and components
in East Asia, whereas the corresponding figures are only 2-3% in Europe and the Americas (Kimura andObashi, 2010, p. 10).

12

enlarged TPP and FTAAP) suggest that more Asian countries are expected to realize larger
welfare gains under the Asian-track. This is largely caused by the fact that most Asian
countries have greater trade shares with RCEP countries than with prospective TPP-16
countries. However, the differences in welfare gains between the two tracks are relatively
small in 2030 and are sensitive to assumptions on the baseline scenario.
In the second TPP-track scenario, it is assumed that Japan’s agricultural policy
reforms would result in an increase in productivity of its agricultural sectors by 1% perannum. Under this scenario, Japan’s overall welfare gains are expected to increase by 0.4
percentage point relative to the case where productivity is fixed. In the third TPP-track
scenario, tariffs on rice are cut in half during the implementation of FTAAP. It is shownthat this would further increase Japan’s welfare gain in 2030 by 0.1 percentage point.
With respect to sectoral output adjustments, there appear to be no significant
differences between the Asian-track and TPP-track for countries that are both members of
RCEP and TPP-16. In Japan, output of many agricultural and processed food sectors
contract, while that of many manufacturing and services sectors expand with the exceptionof apparel, electronic equipment, other transport equipment and air transport. In many
emerging Asian countries, output of textiles, apparel, machinery, electronic equipment andother transport equipment would increase.
When Japan’s agricultural productivity is assumed to increase by 1% per annum,
the extent of output contraction of agricultural and processed food sectors in the country
would be reduced significantly except for dairy products. Output changes in some of the
products, such as meats and other crops, are predicted to become positive, indicating thebeneficial effects of agricultural policy reforms in Japan. Finally, when tariffs on rice are
cut in half in the third TPP-track scenario, rice output in Japan is projected to fall by 13%.
This contrasts with the 53% decline in rice production under the global trade liberalization
scenario in which tariffs on all commodities are completely removed by 2030.

13

References
Armington, P. (1969), A theory of demand for products distinguished by place of
production. IMF Staff Papers, 16, 159-178.
Brown, D. K., K. Kiyota, and R. M. Stern (2010), Computational analysis of the menu of
U.S.-Japan trade policies. RSIE Discussion Paper No. 611, Ford School of Public
Policy, University of Michigan.
Hayakawa, K. and F. Kimura (2013), How do free trade agreements reduce tariff rates andnon-tariff barriers? Unpublished manuscript.
Hertel, T. W., ed. (1997), Global Trade Analysis: Modeling and Applications. Cambridge:
Cambridge University Press.
Honma, M. (2010), Agricultural trade policy reform in Japan. In: R. Meléndez-Ortiz, C.
Bellmann, and J. Hepburn, eds., Agricultural Subsidies in the WTO Green Box:
Ensuring Coherence with Sustainable Development Goals. Cambridge: Cambridge
University Press.
Ianchovichina, E. and R. McDougall (2001), Theoretical structure of Dynamic GTAP.
GTAP Technical Paper No. 17. West Lafayette: Center for Global Trade Analysis,
Purdue University.
Ianchovichina, E. and T. L, Walmsley, eds. (2012), Dynamic Modeling and Applications
for Global Economic Analysis. Cambridge: Cambridge University Press.
Itakura, K. and H. Lee (2012), Welfare changes and sectoral adjustments of Asia-Pacificcountries under alternative sequencings of free trade agreements. Global Journal of
Economics, 1(2), 1250012.
Kawai, M. and G. Wignaraja (2008), EAFTA or CEPEA: Which way forward? ASEAN
Economic Bulletin, 25(2), 113-139.
Kimura, F. and A. Obashi (2010), International production networks in machineryindustries: Structure and its evolution. Working Paper DP-2010-09. Jakarta: Economic
Research Institute for ASEAN and East Asia (ERIA).
Kimura, F. and A. Obashi (2011), Production networks in East Asia: What we know so far.
ADBI Working Paper No. 320. Tokyo: Asian Development Bank Institute.
Lee, H. and K. Itakura (2013), What might be a desirable FTA path towards global free
trade for Asia-Pacific countries? Paper presented at the 16th Annual Conference on
Global Economic Analysis, Shanghai, June 12-14.

14

Lee, H., R. F. Owen, and D. van der Mensbrugghe (2009), Regional integration in Asiaand its effects on the EU and North America. Journal of Asian Economics, 20(3), 240254.
Li, C. and J. Whalley (2012), China and the TPP: A numerical simulation assessment of
the effects involved. NBER Working Paper No. 18090. May.
Minor, P. and D. Hummels (2011), Time as a barrier to trade: A GTAP database of advalorem trade time costs. A paper presented at the 13th Annual Conference on Global
Economic Analysis, Penang, Malaysia. An updated version is available at URL:
https://www.gtap.agecon.purdue.edu/resources/res_display.asp?RecordID=3301
Narayanan, B. G, A. Aguiar, and R. McDougall, eds. (2012), Global Trade, Assistance,
and Production: The GTAP 8 Data Base. West Lafayette: Center for Global Trade
Analysis, Purdue University.
Petri, P. A., M. G. Plummer, and F. Zhai (2012a), The ASEAN Economic Community: A
general equilibrium analysis. Asian Economic Journal, 26(2), 93-118.
Petri, P. A., M. G. Plummer, and F. Zhai (2012b), Trans-Pacific Partnership and AsiaPacific Integration: A Quantitative Assessment. Washington, DC: Peterson Institute ofInternational Economics.
Petri, P. A., M. G. Plummer, and F. Zhai (2014), Sectoral results. Asia-Pacific Trade
website. http://asiapacifictrade.org/. Accessed January 15, 2014.
Wang, Z., S. Mohan, and D. Rosen (2009), Methodology for estimating services tradebarriers. Rhodium Group and Peterson Institute for International Economics.

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Table 1: Regional and sectoral aggregation
A. Regional aggregation
Country/region
1 Japan
2 China
3 Korea
4 Taiwan
5 Singapore
6 Indonesia
7 Malaysia
8 Philippines
9 Thailand
10 Vietnam
11 Rest of ASEAN
12 India
13 Australia
14 New Zealand
15 United States
16 Canada
17 Mexico
18 Chile
19 Peru
20 Russia
21 EU-28

22 Rest of world

Corresponding economies/regions in the GTAP 8 databaseJapan
China, Hong Kong
Korea
TaiwanSingapore
Indonesia
Malaysia
Philippines
Thailand
Vietnam
Cambodia, Lao People’s Democratic Republic, Myanmar, rest ofSoutheast Asia
India
Australia
New ZealandUnited States
CanadaMexicoChile
Peru
Russian Federation
Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark,Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy,
Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal,
Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom
All the other economies/regions

16

Table 1 (continued)
B. Sectoral aggregation
Sector
1 Rice2 Other grains
3 Sugar
4 Other crops
5 Livestock
6 Fossil fuels
7 Natural resources
8 Meats
9 Dairy products
10 Other food products
11 Textiles
12 Apparel
13 Wood and paper
14 Petroleum products
15 Chemical products
16 Steel
17 Nonferrous metal
18 Metal products
19 Machinery
20 Electronic equipment
21 Motor vehicles
22 Other transport equip.
23 Other manufactures
24 Construction and utilities
25 Trade
26 Sea transport
27 Air transport
28 Other transport
29 Communication
30 Financial services
31 Other private services
32 Government services

Corresponding commodities/sectors in the GTAP 8 database
Paddy rice, processed rice
Wheat, cereal grains nec
Sugar, sugar cane and sugar beet
Vegetables and fruits, oil seeds, plant-based fibers, crops nec
Cattle, sheep and goats, animal products nec, raw milk, wool
Coal, oil, gas
Forestry, fishing, minerals nec
Cattle, sheep, goat, and horse meat products, meat products nec
Dairy products
Vegetable oils, food products nec, beverages and tobacco products
TextilesWearing apparel, leather products
Wood products, paper products, publishing
Petroleum, coal products
Chemical, rubber, plastic products
Iron and steel
Nonferrous metal
Fabricated metal products
Machinery and equipment
Electronic equipment
Motor vehicles and parts
Transport equipment nec
Mineral products nec, manufactures nec
Construction, electricity, gas manufacture and distribution, water
Trade
Sea transport
Air transport
Other transport
Communication
Insurance, financial services nec
Business services, recreation and other services
Public administration and defense, education, health services

Source: GTAP database, version 8.1.
Note: nec = not elsewhere classified.

17

Table 2: Tariff rates on merchandise imports and tariff equivalents of nontariff barriers on services, 2004 (%)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32

Sector

Japan

China

Korea

TaiwanRice
Other grains
Sugar
Other crops
Livestock
Fossil fuels
Natural resources
Meats
Dairy products
Other food products
TextilesApparelWood and paper
Petroleum products
Chemical products
Steel
Nonferrous metal
Metal products
Machinery
Electronic equipment
Motor vehicles
Other transport equip.
Other manufactures
Construction and utilities
Trade
Sea transport
Air transport
Other transport
Communication
Financial services
Other private services
Government services

421.7
27.4
39.4
4.6
5.7
0.0
0.2
24.1
53.3
9.9
6.3
9.6
1.0
0.3
1.0
0.9
0.4
0.4
0.1
0.0
0.0
0.0
0.6
5.0
22.7
7.6
19.5
20.2
17.8
17.1
16.6
25.9

1.4
1.7
0.1
2.8
15.7
0.1
0.3
4.7
6.4
4.7
5.3
4.0
1.7
4.5
6.1
3.9
2.8
8.2
6.1
1.2
14.6
2.8
6.0
25.2
109.6
21.5
61.5
74.3
48.1
83.3
81.2
84.1

4.7
5.2
3.6
51.2
6.5
2.7
1.1
29.3
45.0
30.6
8.4
8.9
1.9
4.4
4.8
0.3
2.4
5.3
5.3
1.2
7.2
1.2
6.0
13.0
33.0
15.7
29.4
30.2
27.4
30.4
29.2
34.3

0.2
2.9
10.4
8.2
5.2
1.0
1.5
16.3
11.2
14.3
7.6
8.1
0.9
2.6
3.0
0.4
1.0
6.1
3.1
1.9
12.1
3.9
5.0
10.8
28.8
12.6
25.4
26.1
23.6
27.5
26.7
29.1

Singapore Indonesia Malaysia Philippines Thailand
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.3
1.3
1.3
1.3
1.3
1.5
1.5
2.8

18

8.6
2.6
20.4
2.2
3.0
0.0
1.0
3.6
4.3
7.0
7.5
7.5
3.1
0.7
3.7
4.1
2.8
6.0
2.7
0.6
11.9
1.8
6.5
64.4
98.5
67.3
91.9
93.4
88.4
92.5
91.1
97.8

39.7
0.0
0.0
10.6
0.1
2.2
0.2
0.3
0.8
10.6
7.1
7.9
4.6
0.4
3.8
17.4
3.4
8.4
2.2
0.1
14.0
2.0
6.7
17.4
36.0
17.6
32.1
33.0
30.0
30.2
29.8
36.5

49.9
5.1
21.7
6.7
5.9
3.0
2.9
15.8
1.8
5.6
7.2
9.1
5.0
2.4
4.0
2.9
2.0
6.5
2.4
0.5
11.6
3.9
5.3
52.6
80.2
53.5
74.6
75.8
71.5
72.6
70.8
76.9

5.8
2.5
12.1
13.1
4.7
0.0
1.5
15.5
9.1
14.6
6.6
20.2
5.8
9.2
7.0
4.1
1.5
11.2
5.1
1.5
23.6
3.8
8.7
44.9
63.5
40.5
58.7
59.7
56.1
58.1
54.9
61.5

VietnamRest of
ASEAN

13.5
4.2
16.5
13.0
1.3
1.1
2.1
18.8
17.3
16.3
28.8
19.1
7.8
14.7
4.5
3.9
0.9
10.9
4.4
4.7
23.2
12.2
15.8
53.7
82.7
54.4
76.7
78.0
73.5
74.7
73.7
84.2

2.6
1.5
6.2
8.0
3.3
1.1
2.9
4.7
7.1
10.9
7.7
11.6
5.3
8.4
3.8
2.2
3.6
4.1
4.5
6.2
19.1
7.2
6.0
20.6
32.5
6.4
28.4
14.9
32.8
20.0
7.3
24.1

Table 2 (continued)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32

SectorIndia

Australia

New
ZealandUnitedStatesCanadaMexico

Chile

Peru

RussiaEU-27

Rest ofworld

Rice
Other grains
Sugar
Other crops
Livestock
Fossil fuels
Natural resources
Meats
Dairy products
Other food products
TextilesApparelWood and paper
Petroleum products
Chemical products
Steel
Nonferrous metal
Metal products
Machinery
Electronic equipment
Motor vehicles
Other transport equip.
Other manufactures
Construction and utilities
Trade
Sea transport
Air transport
Other transport
Communication
Financial services
Other private services
Government services

39.0
98.9
91.7
34.1
11.9
11.1
9.6
21.7
31.9
79.8
15.9
13.2
13.5
13.9
13.8
19.0
14.9
14.9
14.0
2.4
24.7
6.5
14.7
109.7
153.3
109.6
144.1
146.1
139.2
139.5
137.1
154.8

0.0
0.0
0.0
0.4
0.1
0.0
0.1
0.2
2.1
1.6
9.1
11.7
3.0
0.0
1.9
3.4
0.6
4.3
2.3
0.9
12.4
0.8
2.8
4.3
18.2
3.3
15.1
15.7
13.4
13.5
13.5
23.5

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.8
1.3
1.0
6.0
11.5
1.3
0.1
1.5
1.6
0.9
3.0
2.5
0.9
7.2
0.6
2.6
1.0
8.2
3.3
5.7
6.2
4.3
4.3
3.7
10.2

1.9
0.0
24.2
2.1
0.3
0.0
0.1
2.4
15.0
2.1
7.0
9.8
0.2
0.7
1.1
0.2
0.6
1.4
0.7
0.3
0.6
0.4
1.2
2.3
6.8
6.8
6.8
6.8
6.8
7.8
7.8
6.3

0.0
0.0
0.4
0.2
16.3
0.0
0.0
31.0
146.0
10.9
6.5
11.7
0.6
0.3
0.6
0.1
0.0
1.0
0.4
0.2
1.0
0.7
1.1
9.2
20.7
6.0
17.6
18.3
15.9
19.8
19.2
17.5

0.2
12.2
5.1
1.3
0.5
0.0
1.6
0.7
6.1
2.5
4.6
16.7
1.6
0.8
1.3
2.4
0.6
2.8
2.8
1.4
3.5
1.6
3.4
40.8
61.8
38.8
56.9
58.0
54.3
57.6
58.2
60.3

5.8
0.5
2.6
1.1
0.3
2.4
0.1
3.4
0.9
1.1
3.3
3.8
0.9
1.7
0.8
1.2
0.8
1.1
0.8
0.6
3.1
0.2
1.1
25.8
33.8
16.7
30.2
31.0
28.3
27.5
26.5
33.0

17.7
8.0
2.5
8.0
6.7
0.0
6.9
10.8
16.3
4.0
13.5
16.3
5.8
2.5
6.1
6.0
4.4
7.1
5.4
5.1
7.2
8.9
9.0
27.2
51.0
30.7
46.7
47.7
44.4
46.4
43.8
47.3

9.3
2.4
50.1
5.7
4.3
0.1
2.6
23.8
7.4
12.9
12.4
16.5
11.3
4.0
8.7
3.0
3.9
12.1
4.4
6.0
10.6
9.3
12.3
52.9
73.5
48.2
68.1
69.3
65.3
65.9
65.1
69.7

8.9
1.3
25.7
1.5
0.4
0.0
0.1
5.1
1.4
1.5
2.1
3.4
0.1
0.2
0.4
0.1
0.4
0.4
0.4
0.7
0.9
0.7
0.6
5.6
12.0
5.4
11.1
10.3
9.3
8.7
9.7
14.2

15.9
9.9
15.0
8.5
3.8
1.3
1.5
19.8
14.0
13.1
9.6
10.0
5.4
4.5
4.0
4.8
1.3
6.8
4.9
3.6
9.7
4.7
6.0
26.7
48.2
22.0
49.5
39.9
36.6
43.3
40.5
45.8

Sources: Sectors 1-23: GTAP database, version 8.1. Sectors 24-32: averages of the gravity-model estimates of Wang et al. (2009) and the values employed by theMichigan Model of World Production and Trade.

19

Table 3: Policy scenarios and assumptions
2015-162017 2018-19

2020-222023-252026-2030

RCEP (ASEAN+6 FTA) (2017-2025)
Scenario 1:
Asian-track

FTAAP (2023-2030)
Assumptions:1) NTBs on services and logistic time in merchandise trade are cut by 20%.
2) Rice is excluded from trade liberalization.
TPP-13 (2015-2022)
TPP-16 (2018-2025)

Scenario 2-A:
TPP-track A

FTAAP (2023-2030)
Assumptions:1) NTBs on services and logistic time in merchandise trade are cut by 20%.
2) Rice is excluded from trade liberalization.
TPP-13 (2015-2022)
TPP-16 (2018-2025)

Scenario 2-B:
TPP-track B

FTAAP (2023-2030)
Assumptions:1) NTBs on services and logistic time in merchandise trade are cut by 20%.
2) Rice is excluded from trade liberalization.
3) Starting in 2016, efficiency on overall output (ao) for sectors 1-5 in Japan increases
by 1% every year, resulting from Japan's agricultural policy reform.
TPP-13 (2015-2022)
TPP-16 (2018-2025)
FTAAP (2023-2030)

Scenario 2-C:
TPP-track C

Assumptions:1) NTBs on services and logistic time in merchandise trade are cut by 20%.
2) Rice is excluded from trade liberalization in TPP-13 and TPP-16. Tariffs on rice
are cut by 50% in FTAAP over the implementation period.
3) Starting in 2016, efficiency on overall output for sectors 1-5 in Japan increases by
1% per annum, resulting from Japan's agricultural policy reform.

GTL

Global trade liberalization (2015-2030)

Note: RCEP: 10 ASEAN members plus China, Japan, Korea, India, Australia and New Zealand. TPP-13:
Australia, Canada, Brunei, Chile, Japan, Korea, Malaysia, Mexico, New Zealand, Peru, Singapore, UnitedStates and Vietnam. TPP-16: TPP-13 plus Indonesia, the Philippines and Thailand.

20

Table 4: The welfare effects of region-wide FTAs
(Percentage deviations in utility from the baseline)
Scenario 1 (Asian-track)

Japan
China
Korea
TaiwanSingapore
Indonesia
Malaysia
Philippines
Thailand
VietnamRest of ASEAN
India
Australia
New ZealandUnited States
CanadaMexicoChile
Peru
RussiaEU-28
Rest of world

Scenario 2-A (TPP-track A)

Scenario 2-B (TPP-track B)

2020

2025

2030

2020

2025

2030

2020

2025

2030

0.4
0.6
1.5
-0.5
0.7
0.6
0.3
0.6
1.0
1.2
0.6
1.3
0.8
0.3
-0.1
-0.1
-0.1
0.0
0.0
-0.1
-0.1
-0.1

1.2
1.4
4.3
0.3
2.2
1.9
1.4
1.4
2.5
3.6
2.2
1.5
3.0
0.8
-0.1
0.3
0.4
0.4
0.2
0.3
-0.3
-0.1

1.5
1.6
4.9
4.5
2.0
2.2
1.9
1.6
2.3
4.4
2.9
0.5
3.5
1.4
0.1
1.1
1.2
1.4
0.5
1.1
-0.6
0.2

0.5
-0.2
1.2
-0.1
0.9
0.4
0.8
0.5
0.5
2.1
-0.1
-0.1
0.3
0.7
0.1
0.6
0.8
0.7
0.1
-0.1
0.0
-0.1

1.1
0.5
2.8
1.4
1.8
1.5
1.5
1.7
2.4
2.9
0.7
-0.7
0.6
1.5
0.2
0.8
1.3
1.5
0.3
0.3
-0.2
-0.1

1.6
1.7
4.7
5.2
1.7
1.8
1.9
2.2
2.5
3.6
2.6
-1.6
0.9
1.6
0.2
1.0
1.3
1.2
0.5
0.9
-0.6
0.0

0.7
-0.2
1.2
-0.1
0.9
0.4
0.8
0.5
0.5
2.0
-0.1
-0.1
0.3
0.7
0.1
0.6
0.8
0.7
0.1
-0.1
0.0
-0.1

1.3
0.5
2.8
1.4
1.8
1.5
1.5
1.7
2.3
2.8
0.7
-0.7
0.6
1.5
0.2
0.8
1.3
1.5
0.3
0.3
-0.2
-0.1

2.0
1.7
4.7
5.3
1.7
1.8
1.9
2.2
2.4
3.6
2.6
-1.6
0.9
1.6
0.2
1.0
1.3
1.1
0.5
0.9
-0.6
0.0

21

Table 4 (continued)

Japan
China
Korea
TaiwanSingapore
Indonesia
Malaysia
Philippines
Thailand
VietnamRest of ASEAN
India
Australia
New ZealandUnited States
CanadaMexicoChile
Peru
RussiaEU-28
Rest of world

Scenario 2-C (TPP-track C)

Global Trade Liberalization

2020

2025

2030

2020

2025

2030

0.7
-0.2
1.2
-0.1
0.9
0.4
0.8
0.5
0.5
2.0
-0.1
-0.1
0.3
0.7
0.1
0.6
0.8
0.7
0.1
-0.1
0.0
-0.1

1.4
0.5
2.8
1.4
1.8
1.5
1.5
1.7
2.3
2.9
0.7
-0.7
0.6
1.5
0.2
0.8
1.3
1.5
0.3
0.3
-0.2
-0.1

2.1
1.7
4.7
5.3
1.7
1.8
1.9
2.2
2.4
3.6
2.6
-1.6
0.9
1.6
0.2
1.0
1.3
1.1
0.5
0.9
-0.6
0.0

0.5
1.1
1.9
1.4
0.8
0.9
1.1
0.4
1.8
2.7
0.9
2.3
0.6
0.4
0.0
0.4
0.4
0.1
-0.1
0.7
0.2
0.0

0.9
1.7
3.7
2.7
1.8
2.0
2.4
0.3
3.2
4.8
2.3
4.0
1.5
0.8
0.0
1.0
0.6
0.3
-0.2
2.0
0.4
0.4

1.3
2.2
5.5
4.1
3.0
3.3
3.6
0.2
4.1
6.9
3.8
4.6
2.8
1.3
0.0
1.5
0.7
0.5
-0.1
3.1
0.7
0.9

Definitions of scenarios:
Scenario 1 (Asian-track): RCEP over the period 2017-2025 and FTAAP from 2023-2030. Rice is excluded. Scenario 2-A (TPP-track A): TPP-13 over theperiod 2015-2022, TPP-16 from 2018-2025, and FTAAP from 2023-2030. Rice is excluded. Scenario 2-B (TPP-track B): Same as scenario 2-A, exceptthat efficiency on overall output for Japan’s agricultural sectors is assumed to increase by 1% per annum from 2016. Scenario 2-C (TPP-track C): Same as
scenario 2-B, except that tariffs on rice are cut by 50% in FTAAP over the implementation period.
Source: Model simulations.

22

Table 5: Japan’s sectoral output adjustments for the year 2030
(Percentage deviation from the baseline)
Scenarios
SectorRice
Other grains
Sugar
Other crops
Livestock
Fossil fuels
Natural resources
Meats
Dairy products
Other food products
TextilesApparelWood and paper
Petroleum products
Chemical products
Steel
Nonferrous metal
Metal products
Machinery
Electronic equipment
Motor vehicles
Other transport equip.
Other manufactures
Construction and utilities
Trade
Sea transport
Air transport
Other transport
Communication
Financial services
Other private services
Government services

1

2-A

2-B

2-C

GTL

-0.3
-36.5
-6.5
-4.3
-13.6
-2.0
2.3
-14.1
-34.0
0.4
12.6
-4.4
0.0
3.8
3.4
2.7
4.0
1.7
0.9
-3.9
4.4
-5.9
2.2
3.7
1.2
2.7
-1.1
0.9
0.9
0.5
1.0
0.6

-0.2
-37.0
-6.6
-4.3
-13.8
-2.0
2.1
-14.5
-34.2
0.6
13.9
-4.1
-0.2
3.9
3.0
2.2
5.4
1.8
0.1
-4.0
3.3
-6.8
2.8
4.6
1.2
0.8
-1.8
1.0
0.9
0.4
1.0
0.6

-2.0
-8.0
0.0
1.3
-0.2
-2.3
2.5
4.2
-27.6
1.7
13.3
-4.0
-0.2
3.9
2.8
1.9
5.1
1.8
-0.4
-4.3
2.9
-7.2
2.8
5.1
1.6
0.7
-1.9
1.1
1.1
0.6
1.2
0.8

-13.3
-7.5
0.2
0.9
-0.1
-2.4
2.5
4.4
-27.5
1.9
13.3
-4.0
-0.2
3.8
2.7
1.9
5.1
1.8
-0.4
-4.3
2.9
-7.2
2.9
5.1
1.6
0.7
-1.9
1.1
1.1
0.6
1.3
0.8

-53.1
-35.8
-11.5
-6.7
-15.6
-1.0
1.4
-14.5
-39.4
0.9
17.0
-4.9
-0.6
1.6
1.1
3.5
1.0
0.6
-0.6
-4.1
6.4
-1.4
1.0
-0.1
0.3
6.8
-2.4
-0.4
0.2
-0.2
0.1
0.4

Source: Model simulations.

23