ESRI Japan Economic Model for the Long-Term
Outlook Using System Dynamics and AI

August 1st, 2024
Hiroshi Nomura
Research Fellow, Economic and Social Research Institute1

〇We simulated the future outlook of the Japan economy from now to
2100. The conclusion is summarized as bellow.

〇The total population of Japan is estimated to be 130 million(upper)
to 40 million(lower) in 2100, compared to the current 120 million.
〇Japan's GDP could reach $20.0 trillion(upper) to $3.0 trillion(lower)by 2100, compared to $4.4 trillion today.
〇As a result of calculations, it is estimated that the well-being inJapan may be 4.0(upper) to 0.2(lower) in 2100 if the current situationis 1.0.
2

〇With this model, we can envision a variety of future perspectives.
The key of this project is to identify the key factors that would lead us tothese different visions.
〇The various future visions are a large amount of information, so to speak,that has been simulated by generating 20,000 scenarios for each issue.
We let AI analyze this large amount of information. In this way, we will beable to confirm the characteristics of each of the future visions.
〇As a result, the importance of income distribution to young people, theimportance of accepting foreigners, the need to expand and domestically
produce renewable energy as soon as possible, and the importance of
expanding trade with the Global South are confirmed.
3

Overview of the Model

4

〇The model is a system dynamic AI model, based on the “Earth4All model” (global
model; by the Club of Rome), modified and replaced by Japanese data to analyze
Japan's characteristic issues - low birthrate, aging population, budget deficit, friction
between the US and China, etc.
〇The model consists of 11 blocks: population, production, demand, inventory, public,
finance, international economy, energy and environment, labor, social issues, andwellbeing. There are 767 causal flows and 1,146 variables.
〇The model is constructed using a system dynamics approach. The coefficients thatdefine the relationships among variables are basically calculated by regression analysisof actual values from 2000 to 2022. The equations in the model are connected with anumber of feedback loops, including equations that vary linearly, vary by a logarithmic
function and use delays.
5

6

Arrow (Blue): Negative impact
Arrow (Orange): Positive impact
Box (Yellow): Variables newly added in the model

Population Sector: Causal Flow
Wellbeing Sector

Social Trust
２

Social Capital
Index

Social Tension

Climate & Energy
Sector

Wellbeing due
to Health Life
Expectancy

Healthy Life Expectancy
３SocialParticipation

Inflow/Outflow
of Migrants

Actual Fertility
Rate(Aged 20-40)

GDP per Capita

Life
Expectancy

Population

１

Actual Births

４

GlobalWarming

Aged 0-20

Aged 20-40

Aged 40-60

Aged 60+

Death

Rate of Advanced
Maternal Age
Family-related
expenditures

Desired Numberof Children

Marriage Rate

Age at First
Marriage

Salary per
Capita(Aged 20-40)/GDP per Capita

Labor Input

GDP

Working AgePopulation

Aging Rate

Aggregate DemandWorkers Income
After Tax

Economy Sector

１Generational transitions due to births, deaths and aging

Population Sector: Main Equations

 Population by generation (0-20, 20-40, 40-60, and 60+) is determined by population changes associatedwith births, deaths and aging, as well as international population movements (immigration outflows andinflows), which is newly added in the model.
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝐴𝐴𝐴𝐴𝐴𝐴 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑋𝑋𝑡𝑡 = 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝐴𝐴𝐴𝐴𝐴𝐴 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑋𝑋𝑡𝑡−1 ＋𝑁𝑁𝑁𝑁𝑁𝑁 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑏𝑏𝑏𝑏 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑡𝑡 +𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 ⁄𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂 𝑜𝑜𝑜𝑜 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑡𝑡

２∗ 𝐴𝐴𝐴𝐴𝐴𝐴 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡 𝑓𝑓𝑓𝑓𝑓𝑓 𝐴𝐴𝐴𝐴𝐴𝐴 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 20 − 、𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑡𝑡 𝑓𝑓𝑓𝑓𝑓𝑓 𝐴𝐴𝐴𝐴𝐴𝐴 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 60 +.

Fertility Rate and Desired Number of Children The number of births is determined by (1) desired number of children and (2) percentage of desired number of children realized.
 “(1) Desired number of children” is calculated by the age at first marriage, which varies according to the social capital index.

“(2) Percentage of desired number of children realized” is calculated by “(3) marriage rate”, which varies with income distribution among
young people, “(4) percentage of married households achieving desired number of children”, which varies with family-related

expenditures share of GDP, and “(5) percentage of children born out of wedlock”.
𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑡𝑡 = ①𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑡𝑡−1 × ②𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑡𝑡① 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑡𝑡 = －0.09 × 𝐴𝐴𝐴𝐴𝐴𝐴 𝑎𝑎𝑎𝑎 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑡𝑡＝－0.09 × （－3.2 × 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼/10）② 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁 𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑡𝑡 ＝③𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 × ④𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑜𝑜𝑜𝑜 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑡𝑡 × ⑤𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 𝑜𝑜𝑜𝑜𝑜𝑜 𝑜𝑜𝑜𝑜 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤＝③ 0.037 × 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑜𝑜𝑜𝑜 𝑌𝑌𝑌𝑌𝑌𝑌𝑌𝑌𝑌𝑌 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃＋ －1.28 × 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑜𝑜𝑜𝑜 𝐴𝐴𝐴𝐴𝐴𝐴 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 20 − 40

× ④｛20.5 × 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 − 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑜𝑜𝑜𝑜 𝐺𝐺𝐺𝐺𝐺𝐺｝ × ⑤𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 𝑜𝑜𝑜𝑜𝑜𝑜 𝑜𝑜𝑜𝑜 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤

３

Changes in the number of foreign residents in Japan

Population Sector: Main Equations

 (Net) inflow of foreign residents are calculated based on the past relationship between GDP per
capita and the number of inflow and outflow. Age structure is assumed to be constant, and inflow offoreign residents is distributed to each age group based on the age structure of 2022.
 𝑁𝑁𝑁𝑁𝑁𝑁 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑜𝑜𝑜𝑜 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑡𝑡
４∗ 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝐺𝐺𝐺𝐺𝐺𝐺 𝑝𝑝𝑝𝑝𝑝𝑝 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 7,000𝑈𝑈𝑈𝑈𝑈𝑈= 𝑁𝑁𝑁𝑁𝑁𝑁 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝐿𝐿𝐿𝐿𝐿𝐿⁄𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝐼𝐼𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝐶𝐶𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑖𝑖𝑖𝑖𝑖𝑖2022＋ 𝐺𝐺𝐺𝐺𝐺𝐺 𝑝𝑝𝑝𝑝𝑝𝑝 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑜𝑜𝑜𝑜 𝐿𝐿𝐿𝐿𝐿𝐿⁄𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑡𝑡 − 𝐺𝐺𝐺𝐺𝐺𝐺 𝑝𝑝𝑝𝑝𝑝𝑝 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 𝑜𝑜𝑜𝑜 𝐿𝐿𝐿𝐿𝐿𝐿⁄𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶2022
× 1.15

Impact of changes in healthy life expectancy on wellbeing Added a path where global warming, etc. drives down life expectancy, which drives down healthy

life expectancy.
 For additional wellbeing indicator, ratio of healthy citizens to the entire population (calculated by life
expectancy) is adopted.
𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡 = 76 × 0.839 × 𝑒𝑒 (−0.025×(𝐺𝐺𝐺𝐺𝐺𝐺 𝑝𝑝𝑝𝑝𝑝𝑝 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑡𝑡 −𝐺𝐺𝐺𝐺𝐺𝐺 𝑝𝑝𝑝𝑝𝑝𝑝 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶1980))

× 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜 𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑡𝑡 × 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 − 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡 − 1.1
𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡 = 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑜𝑜𝑜𝑜 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑝𝑝𝑝𝑝𝑝𝑝 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡 × 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡
𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 𝑑𝑑𝑑𝑑𝑑𝑑 𝑡𝑡𝑡𝑡 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡= 1 − 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 60𝑡𝑡 ×

𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡 −𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡
𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑡𝑡 −60/ 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑡𝑡

〇Using Monte Carlo methods, all variables affecting the primary outcome are shaken(including zero shaking range. Most of them oscillate within upper and lower bounds.
Some are completely random) and a wide range of scenarios is generated (20,000).
〇For Population analysis, variables affecting population and GDP per capita
are variable.
For environmental analysis, variables affecting the amount of CO2 and carbon
capture are variable.
For international economic analysis, variables affecting economic growth andexport volumes are variable.
〇Group 20,000 results into several groups by K-means method.
〇The AI’s work process then takes on the task of deciphering the key factors thatcharacterize each group.
10The variation range of coefficients and error terms are calculated as a wide range of
scenarios by changing values within a set range in a Monte Carlo simulation, which starts
from a reference value.
*： Variations in the rate of change occur
annually based on the base value when aMonte Carlo analysis is performed.
 Scenarios are generated by setting thevariation range and error term in themodel and then taking a random number
in a uniform distribution each year within
the range.
 Basically, the object to be changed is“values other than actual values” amongthe “constants” in the “structure of thereference model".

Branching Scenario

Branching ScenarioMonte Carlo analysis is used to calculate
scenarios in which the coefficients andother factors vary within the variation
range and error term.
(The error term is not presented in theform of a confidence interval, but
actually varied within the error term andcalculated as one scenario.)

Variation in rate of change *Base ScenarioMonte Carlo analysis is used to calculate
scenarios in which the coefficients andother factors vary within the variation range
and error term.

Variation in rate of change
Percentage change in standard
value（Annual change)
Actual Value of 2022

Branching Scenario
Time

11

© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Using the Monte Carlo method, all parameters affecting the objective variable are varied
within upper and lower bounds to obtain 20,000 possible combinations (simulation results).
Method Random annual variation of all parameters affecting the objective variable within a pre-determined upper and lower limit
within a maximum annual variation range.
e.g. Method of variation*In case of Family-related expenditure’s share of GDP

5%bounds0%(割合)
Vary parameters randomly togenerate 20,000 variations(as well as other variables).

+0.2%
….

1.7%

Family-related expenditure’s share of GDP-0.2%
Standard Value(Actual Value of 2022)
2022
2023
(Actual Value)

….

2100

Maximum annual variation range

12© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Eliminate human arbitrariness and mechanically classify explanatory variables.
Method Classify time series data of explanatory variables to calculate the objective variable for each sector into groups of similar
scenarios using K-means (DTW*) with reference to the degree of similarity.
e.g.）Population Sector
Population (Explanatory)

GDP (Objective)

Population (Explanatory)

GDP (Objective)

36 classification
combinations
obtained

GDP per Worker(Explanatory)

GDP per Worker(Explanatory)

Automaticallyclassified into 6
groups***: A method for measuring the similarity between two time series data. Allows for expansion and contraction along the timeaxis, allowing for robust comparisons against slight temporal deviations. **: For the number of classifications, the “elbow
method” and actual classification results were checked, and the minimum value that was significantly classified was adopted.

13© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Reclassification of classified results of the obtained explanatory variables by hand.
Method Reclassifying classified results of the obtained explanatory variables by hand, with reference to the values of 2100.

e.g.) Population Sector
Population (Explanatory)
A1
>1.0

A2
>0.9

A3
>0.8

A4
>0.7

A5
>0.6

A6
>0.5

B1
>x5

High

High

High

Med.

Med.

Med.

B2
>x4

High

High

Med.

Med.

Med.

Med.

B3
>x3.
5

High

Med.

Med.

Med.

Med.

Med.

B4
>x3

Med.

Med.

Med.

Med.

Med.

Med.

B5
>x2

Med.

Med.

Med.

Med.

Med.

Low

B6
<X2

Med.

Med.

Med.

Med.

Med.

Low

A1

GDP per Worker(Explanatory)
B1

B6

GDP per worker (Compared toAutomaticallyclassified into
6 groups**

A6

GDP (Objective)

Population (billion)

20
22

High-level
Economic
GrowthScenario

Low-level
Economic
GrowthScenario)14© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Check the transition of explanatory variables (percentiles*) in each scenariogroup to identify the points and factors that diverge to other scenario groups.
Method Check the transition (percentiles) of the explanatory variables for each scenario group.
 Using 5%, 50%, and 95% percentile (p5, p50, p95).
 Identifies points (calculated within a certain range) and branching factors that lead to other scenario groups.
e.g.) Population Factor *Group A3 (0.80-0.90 billion in 2100) and A4 (70-80 million in 2100)
Identify points and factors by tracing back explanatory variables.
Age at First Marriage
Division point
existsSocial Trust
Division point
existsSocial Participation
Division point
does not exist

Desired number of children (Division factor)
Black:p50(Median)
Red:p95
Blur:p5

Division Point

Solid:80-90 million
Dashed:70-80 million

𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛
𝑜𝑜𝑜𝑜 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
Division point does not exist

Fertility Rate
Division
point exists

Life Expectancy
Division point
does notexist
Foreign residents…

Division point
does notexist

Population

A3
A4【Required Information】
Division point of A3,A4 is year 20XX,
division factor is XXX*： X percentile refers to the value that is in the Xth percentile of the total when the data are sorted in decreasing order,
15
counting from the beginning.
© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Population

16

Mechanically classified the results of 20,000 different simulations on GDP.
② Mechanically classify scenarios using K-means Explanatory variables of “GDP” such as “population” and “GDP per worker” are mechanically classified by K-means.
 Based on the results, classified GDP into high/low economic growth scenarios

GDP

A

High-level
Economic
GrowthScenarioB

Low-level
Economic
GrowthScenario

GDP: More than 3 times higher than 2022 at 2100
A growth scenario that is comparable to the future GDP
growth multiples of OECD countries. Two patterns exist.
• A-1. Slight decline in population but increase in GDP• A-2. Population decline but increase in GDP
GDP: Less than 2022 at 2100
A scenario in which GDP stagnates or declines, which could
occur if various indicators decline to a certain level due toirregular events such as contingencies or natural disasters.

17© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

GDP will increase by accepting a certain number of foreign residents,
maintaining the birth rate, and promoting technological development andcapital investment on a large scale.

2022

GDP (USD)

Population• 4,4trl.

• 124
millionLife
Expectancy

Fertility
Rate

Foreignresidents

GDP per
worker (USD)

Investment intechnology(USD)

Investment incapital (USD)• 84• 1.24• 3mil.

• 54,000• 275bil.

• 123bil.

1.3% increase(annually)

2.6% increase(annually)• 400bil.
(annually)• 250bil.
(annually)

1.8-4.1%
increase(annually)

1.8-3.6%
increase(annually)

Rapid Increase• 8mil.

2040
2050• 5,08,0trl.

• 110120mil.

• 86-88• 1.1-1.4• 10-12mil.

• 60,000100,000

2060

2100

• 12.016.0trl.

• 110120mil.

<Japan in 2100>
 GDP：3 times higher than 2022
 Population: more than 100 million
 GDP per worker: 3.5 times higher
than 2022• 92-94• 1.1-1.3• 170,000250,000

GDP

Population(million)• 7-14mil.

(billion)•

1,0003,000bil.
(annually)/
44,400bil.
(total)•600-1,500bil.
(annually)/
265,00bil.
(total)GDP per worker(thousand)18© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Fertility rate can be maintained by increasing marriage rates
and desired number of children.
2022

Marriage
Rate

Labor shareamong young
peopleDesired noof children

Age at First Social
Marriage
Participation Social trust• 1.24

• 74%

• 11%

• 1.7

• 30

• 0.37• 0.34• 0.92• 1.7%• 1.5-1.7• 31• 0.280.32• 0.300.38• 1.0-1.2• 3.0%• 1.4-1.8• 30• 0.320.36• 0.300.38• 1.0-1.4• 2.03.5%

2040
2050

• 1112%• 1.1-1.4• 7075%

2060

2100

Desired no Family-relatedof children expenditureachieved(share of GDP)

Fertility
Rate

• 10%

• 1.1-1.3• 7585%• 1213%19© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

GDP per capita growth is lower than G20 and purchasing power is lower,
but disposable income is growing and wellbeing is increasing.
Well-being(derive frompurchasing power(compared to foreigncountries))

GDP per capita(Japan, USD)

Well-being(derive from
Health life
expectancy)

Healthy life
expectancy

Well-being(derive from
disposable
income)Disposable income
(USD)

2022

• 1

• 35,000

• 1

• 74

• 1

• 11,0002050• 0.75-0.8• 55,000• 0.92-1.035• 70-77• 1.5• 15,00018,000• 0.6-0.7• 110,000130,000• 0.88-1.12• 70-85• 3.25-3.75• 35,00040,000

2100<Japan in 2100>
 Well-being Deriving from purchasing power: decreasing Deriving from Health life expectancy: level off Deriving from disposable income: Significantly improved20© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Climate & Energy

21

２

Population Sector

Life
expectancy

natural disasters,
food shortages, etc.

Wellbeing Sector

Well-being

３

GlobalWarming

CO2 from
demand forfossil fuelGDP
Cost ofelectricity

DemandFor Hydrogen

４

Renewableenergygeneration

GHG
Emissions１

Economy Sector

Nuclearpower
generation

Thermalpower
generation

Arrow (Blue): Negative impact
Arrow (Orange): Positive impact
Box (Yellow): Variables newly added in the model

CO2 absorption inforestry land

Climate & Energy Sector: Causal Flow

Difference in
Decarbonization
between theWorld and Japan

CO2 captured
by CCUS

ExportInternational
Economy &Geopolitics
Sector

CO2 from nonfossil industrial
processes

CO2 from demand
for fossil fuel for
non-electric use

demand forelectricpower
GDP per capita
Economy Sector

Population Sector

Economy Sector

CH4
Emissions

N2O
Emissions

Grain
Production(SelfSufficiency)

Grain
Production

Grain
Production(Imports)

Population

GDP

22

GHG Emissions from
Grains for Japan byOverseasClimate & Energy Sector: Main Equations

1

Greenhouse gas (GHG) emissions are determined by CO2, N2O, and CH4 emissions GHG emissions are calculated as the sum of CO2 emissions (from fossil/non-fossil fuels), N2O
emissions and CH4 emissions. CO2 emissions from fossil fuels are composed of those fromthermal power generation and others.
𝑮𝑮𝑮𝑮𝑮𝑮 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒕𝒕 = CO2 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 (𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇)𝒕𝒕＋CO2 𝒆𝒆𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎 (𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒏𝒏𝒏𝒏𝒏𝒏 − 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇)𝒕𝒕 ＋𝑵𝑵𝑵𝑵𝑵𝑵 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒕𝒕 ＋𝑪𝑪𝑪𝑪𝑪𝑪 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒕𝒕

CO2 𝒆𝒆𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎 (𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇)𝒕𝒕= CO2 𝒆𝒆𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎 (𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕𝒕 𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑 𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈)𝒕𝒕＋𝑪𝑪𝑪𝑪𝑪𝑪 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅 𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒇𝒇𝒇𝒇𝒇𝒇 𝒏𝒏𝒏𝒏𝒏𝒏 − 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒖𝒖𝒖𝒖𝒖𝒖 𝒕𝒕

２＋𝑪𝑪𝑪𝑪𝑪𝑪 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 𝒃𝒃𝒃𝒃 𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 𝒕𝒕

Global Warming through GHG emissions lowers the Well-being and the Life Expectancy
𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾 − 𝒃𝒃𝒃𝒃𝒃𝒃𝒃𝒃𝒃𝒃𝒕𝒕 = 𝒂𝒂. ・・・𝒕𝒕 －𝒃𝒃. 𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮 𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝒕𝒕 + 𝒄𝒄. ・・・𝒕𝒕 + 𝒅𝒅. ・・・𝒕𝒕 + ・・・

𝑳𝑳𝑳𝑳𝑳𝑳𝑳𝑳 𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝒕𝒕 = ・・・𝒕𝒕 －𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰 𝒐𝒐𝒐𝒐 𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮 𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾 𝒐𝒐𝒐𝒐 𝒍𝒍𝒍𝒍𝒍𝒍𝒍𝒍 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒕𝒕 ＋・・・

23

Climate & Energy Sector: Main Equations
３

Delays in promoting decarbonization lower Exports and GDP If the gap in decarbonization efforts between Japan and the rest of the world widens, Exports
could decrease by up to 3%, and GDP would also decline.

４

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝒕𝒕 = 𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝒕𝒕−1 －𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫 𝒊𝒊𝒊𝒊 𝒅𝒅𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒃𝒃𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒕𝒕𝒕𝒕𝒕𝒕 𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾𝑾 𝒂𝒂𝒂𝒂𝒂𝒂 𝑱𝑱𝑱𝑱𝑱𝑱𝑱𝑱𝑱𝑱 𝒕𝒕－𝑼𝑼. 𝑺𝑺./𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫𝑫 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒐𝒐𝒐𝒐 𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝒕𝒕 ＋𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭𝑭 𝒊𝒊𝒊𝒊 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒇𝒇𝒇𝒇𝒇𝒇 𝒕𝒕𝒕𝒕𝒕𝒕 𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺 𝒕𝒕“Energy Mix” fluctuates the amount of thermal power generation and energy costs

 The CO2 emissions (from thermal power generation) increase as the thermal power
generation increase.

 The Thermal power generation is calculated from the demand for electric power, which
varies with the population and the GDP per capita, minus the renewable energy generationand the nuclear power generation.
𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻𝑻 𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑 𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈 𝒕𝒕 = 𝑫𝑫𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒇𝒇𝒇𝒇𝒇𝒇 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑 𝒕𝒕－𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈 𝒕𝒕 －𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵 𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑 𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒈𝒕𝒕

 The Electricity costs fluctuate through thermal, renewable, and nuclear power generation,and the Electricity costs affect GDP.

24

Classified the results of 20,000 different simulations of CO2 emissions
 CO2 emissions are classified into the scenario of “Achieving government targets for
decarbonization”/ “Delayed Achievement scenario on decarbonization”.

CO2 Emissions

Delayed
Achievement
scenario on
decarbonization

Achieving
government
targets for
decarbonization

Achieving
governmentAtargets for
decarbonization

Delayed
B Achievement
scenario on
decarbonization

Decarbonization achieved by 2050
A scenario in which carbon neutrality is achieved andoverall greenhouse gas emissions are reduced to zeroby 2050, the target set by the government.

Decarbonization is achieved after 2061
A scenario in which decarbonization occurs after 2061,
well behind government targets.

25

Decarbonization can be achieved by 2050 by increasing the ratio of low-carbon
energy and the proportion of electrification, and by absorbing a certain amountof CO2 through CCUS
CO2
Emissions

From theelectricity
demandFrom the nonelectricity
demandFrom non-fossil
industrial
processes

2022年• 1.16 Gt• 0.36 Gt• 0.78 Gt• 0.06 Gt

2050年• 0 Gt• Almost
zero
(less
than
0.05 Gt)• Lessthan
0.15 Gt

2100年• 0 Gt• 0 Gt• 0-0.1 Gt

CO2 Emissions

Renewableenergy ratio

Proportion ofelectrification(Starting from
2022)

Renewableenergy ratio• 0.0006
Gt

• 0%

• 20%

• 0.05 Gt
approx.

• 0.1 Gtor more• 60% ormore

• 70% ormore

• 0.030.05 Gt• 0.15 Gt• 70%• 60100%

Captured by
CCUS

Proportion ofelectrification

CO2 captured
by CCUS26

In most of the scenarios for achieving government targets for decarbonization,
the share of renewable energy will increase, mainly solar (household) and
offshore wind power.

2022年

Solar power
generation
capacity(Business)

Solar power
generation
capacity(Household)Biomass power
generation
capacity

Offshore Windpower generation
Capacity

Onshore wind
power generation
capacity

Hydroelectric
power generation
capacity• 62.2 GW• 7 GW• 6.9 GW

• 0.09 GW• 4.61 GW• 44.7 GW• 9.86 GW• 44.8 GWApproximately
700-foldincrease

Approx. 4-foldincrease

2050年• 399 GW

• 45.9 GW• 32.5 GW• 71.6 GW

Power generation capacity is declining due to population decline
and energy efficiency improvements

2100年• 130 GW
Solar power generation
capacity (Business)• 14 GW• 12 GW

Offshore Wind power
generation Capacity• 45 GW
Biomass power
generation capacity• 3.5 GW

• 45 GW

Solar power generation
capacity (Business)

27

While achieving government targets on decarbonization requires allowing fornegative short-term impacts on GDP, there are a number of scenarios with acumulative positive impact on GDP as of 2050
Cumulative impact on GDP from renewable energy deployment and energy costs*.
(billions ofdollars)+$800 billion

 What can be said from the simulation

 To achieve government targets on decarbonization, a certain
amount of negative GDP impact (up to a cumulative maximum of
about -$400 billion in 2035) must be allowed for.

 The cumulative GDP impact from the environmental domain will bein the range of -$600~+800 billion in 2050.

-600 billion

 Background of the simulation

 When introducing renewable energy, a high domestic procurement
rate will have a positive impact on GDP, vice versa.
 A 10% increase in energy costs will decrease GDP by 0.15%**,whereas a decrease in energy costs will increase economic activity
and positively affect GDP.

*：It shows the entire scenario, not just “scenarios for achieving government targets on decarbonization.”**：How energy prices shape OECD economic growth: Panel evidence from multiple decades - ScienceDirect28

It is important to push down energy costs and reduce the amount of energy
while continuously investing in renewable energy-related facilities.

(billions ofdollars)

Cumulative impact on GDP fromrenewable energy deployment
and energy costs+$800 billion【Results】

 Cumulative impact of renewable energy deployment and energy costs on GDP
will start to rise after 2035, reaching +$800 billion by 2050
 CAPEX of renewable energy will increase to more than $40 billion per year
between 2030 and 2045.

 GDP impact from energy costs turns upward after 2035-2040, reaching $30
billion in 2050.
 Energy imports are reduced to almost zero after 2035-2040.

(billions ofdollars)

CAPEX of renewable energy(10-year average)

GDP Impact of Energy Costs(billions ofdollars)+ over$40 billion+$30 billion

Energy imports(billions ofdollars)

Almost zero29How quickly energy costs rise due to the introduction of renewable energy will
determine the impact on the economy (GDP).
GDP Impact of Energy Costs(billions ofdollars)+$30 billion

Energy Cost
(billions ofdollars)【Results】
 Energy costs peak at around $160 billion in 2035, when renewable energy substitution becomes more active.
 After 2035, the replacement with renewable energy is completed and energy costs are pushed down,reaching the 2022 level ($113 billion) in the decade 2035-2045.
By 2050, the Energy Costs are reduced to about $60 billion, about half of the 2022 level, with a GDP impact
of +$30 billion.
30

By updating function for selecting temperature scenarios, a wide range oftemperature increases is calculated.
Temperature Rise from 2022
*Significant change observed

Effect of temperature rise on productivity（℃）

 Temperature
increase calculated in
the range of+0.2~3.3 ℃.

 0.3%~5.3% decreasein labor productivity
is projected.

 Covers most of therange shown in IPCC
scenarios (+0.1~3.6 ℃
increase from 2022).

Change in Wellbeing due to temperature rise

 Range from 0.2(lower limit) toapproximately 0.7.

31

Increase in the rate of change in renewable energy
introduction due to temperature rise

 Due to risingtemperatures,
introduction ofrenewable energy
facilities is accelerated
by up to 20%.

© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

International Economy

32Decoupling was modeled to occur due to relative changes in national power
between the U.S. and China
U.S.-China Bilateral
Decoupling

Modeling method

Model Image Calculating trade volume with thedegree of proximity of U.S. andChina's national power as
explanatory variables

Proximity of U.S.
and China’s
national power The GDP forecast in purchasing
power parity terms is used to
calculate the degree of proximity interms of national power.

U.S.-China partial decoupling

US-China
trade volume（-1.7% per gross tradevolume）⇒Japan's exports up 1%

U.S.-China full decoupling（-5.8% per gross tradevolume）

 Cases in which trade decreases
beyond a certain level areconsidered decoupling.

Betweenliberal/authoritarian
camps decoupling Assumes that if bilateraldecoupling occurs, Japan will be
required to promptly participate
 Assumes that each decoupling
occurs and then develop into intercamp decoupling in 1 year

⇒ Japan's exports up 2%

U.S.-China partial decoupling⇒Japan's exports up 1.05%

U.S.-China full decoupling⇒Japan's exports up 2.15%

After 1 year

Partial decoupling between
camps⇒Japan’s export down 5%
Full decoupling between camps

After 1 year ⇒Japan’s export down 15%※Depending on the percentageof exports to the Global South.
33© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

International Economy & Geopolitics Sector: Causal Flow
【Newly established】
２

１

Export Changes to
the Global South

Economy Sector

GDP

Impact of U.S.China Decoupling
U.S.-China power
differential

Arrow (Blue): Negative impact
Arrow (Orange): Positive impact
Box (Yellow): Variables newly added in the model

Export ofgoods

３

Fiscalbalance

Import ofgoods

Supply chain risk
impactEnergy-related
imports

World and Japan difference about
promotion decarbonization

Service
exportServicebalance

ServiceimportExternal
assetsIncomebalance

Inward assets

Current balance34

International Economy & Geopolitics Sector: Main equations
１

Newly establishment of an international economy and geopolitics part

 A new pathway for changes in the balance of goods and services to affect GDP is added, andthe current balance can also be calculated.
２

Factors affecting goods exports

 Goods exports fluctuate due to the following factors

 Economic development of the Global South（＋）

 World and Japan difference about promotion decarbonization（－）
 U.S.-China Decoupling（－）
３

Factors affecting goods imports

 Goods imports vary depending on the following factors
 Supply chain risk manifestation（－）

 Increase in energy-related imports（＋）

35

International Economy & Geopolitics Sector: Main Equations
4

Decoupling impact varies depending on the U.S.-China power differential
and the share of exports to the Global South The difference in GDP in purchasing power parity terms between the U.S. and Chinachanges the volume of China’s export to the U.S.
Decoupling is judged to have occurred when the rate of decrease exceeds a certain level
due to the same factors.
 Impact of decoupling depends on the ratio of exports to the Global South
𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷𝑷 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄= −𝟎𝟎. 𝟓𝟓𝟓𝟓 ×𝒊𝒊𝒊𝒊 𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝒂𝒂′ 𝒔𝒔 𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆𝒆 𝒕𝒕𝒕𝒕 𝒕𝒕𝒕𝒕𝒕𝒕 𝑼𝑼𝑼𝑼 𝒅𝒅𝒅𝒅𝒅𝒅 𝒕𝒕𝒕𝒕 𝑮𝑮𝑮𝑮𝑮𝑮 𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅𝒅 𝒕𝒕

𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 𝑮𝑮𝑮𝑮𝑮𝑮𝒕𝒕
𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 GDP𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐
ー
𝑼𝑼.𝑺𝑺.𝑮𝑮𝑮𝑮𝑮𝑮𝒕𝒕𝑼𝑼.𝑺𝑺.𝑮𝑮𝑮𝑮𝑮𝑮𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐

36

Derive the status and bifurcation points of the no/negative impact scenario forexport value due to DC* from the results of 20,000 simulation scenarios.
Derive status and bifurcation points for high/low scenarios
Decoupling impact on Japan’s export value is classified into two scenarios: “noimpact on export value” scenario and “negative impact on export value” scenario.
Decoupling Effects on Japanese Export ValueA

No impact
on Export
value
Scenario

Decoupling has no effect on Japan’s exportvalue
A scenario in which decoupling occurs between
the U.S. and China or between the liberal andauthoritarian camps, but export value is
unaffected.

B

Negative
impact on
Exportvalue
Scenario

Decoupling has negative effects on Japan’s
export value
A scenario in which decoupling occurs between
the U.S. and China or between the liberal andauthoritarian camps, with a negative impact on
the value of export.

No Impact
an Export
value
Scenario
Negative
impact on
Export value
Scenario*：DC=Abbreviation for decoupling37© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

If decoupling between the camps is a late occurrence and there is a shift ofexports to the Global South, the negative impact on export value will beminimal.
Decoupling
Impact (USD)

Decoupling
Impact(GDP ratio)

2022
2065～
2070

• ±20bil.

• Less than ±1%

Percentage ofexports to the
Global South

NominalGDP(U.S.)(USD)

NominalGDP(China)(USD)• 23％• About 21tril.

• About 26tril.

• Around 35%• 60-70tril.

• 70-90tril.

Small-scale decoupling between camps occurs
2090～
2100

• Less than ±1%• +70bil.
*Slightly positive
impact• Around 50%• 105-125tril.

• 170~250tril.

Large-scale decoupling between camps occurs
2100• Less than ±1%• +700bil.
*Slightly positive
impactDecoupling Impact
(USD)

38

• Around 50%

Decoupling Impact(GDP ratio)• About 125tril.

• About 250tril.

Percentage of exports to
the Global South© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

If decoupling between camps occurs early, the shift of exports to the Global
South will not occur in time, which will have a negative impact on the valueof exports.
Decoupling
Impact (USD)

Decoupling
Impact(GDP ratio)

2022
2035～
2040

• About 50bil.

• About -1%

Percentage ofexports to the
Global South

NominalGDP(U.S.)(USD)

NominalGDP(China)(USD
)

• 23％

• About 21tril.

• About 26tril.

• 7-20％• 25-30tril.

• About 30-40tril.

Small-scale decoupling between camps occurs
2050～
2100

2100

• -500bil. to -200bil. • About -5%• 7-20％Large-scale decoupling between camps occurs• -500bil. to -200bil. • About -5%

Decoupling Impact(USD)• 7-20％Decoupling Impact(GDP ratio)• 30-120tril.

• 50~430tril.

Percentage of exports
to the Global South39© 2024. For information, contact Deloitte Tohmatsu Consulting LLC.

Conclusion〇Japan society is facing a rapidly declining population. Under such circumstances,what are the necessary conditions for maintaining a sustainable economy and society?
The answer to this model was a combination of a generous income distribution toyoung people, increased family spending, community stability, and aggressive
investment in technology development.
〇What are the conditions necessary to realize a decarbonized society? The answer tothis model was to make a bold shift to renewable energy, invest in the development of
CO2 capture and storage technologies, increase domestic energy self-sufficiency, andcontrol energy costs.
〇What is Japan's desired response to the US-China decoupling? The answer thismodel leads to is that the most desirable thing is that decoupling does not occur. The
second answer is that it should not lead to decoupling between factions. The third
answer is to develop trade with the Global South.
40

Predicting the future using AI.
We would like to further pursue this possibility.

41

Thank you for your attention.

42