28th AIM International Workshop
September 13, 2022

The impact of demographic structural changes on CO2emission: Case of Korea

Tae Yong Jung (Yonsei Univ)
Yong-Gun Kim (KEI)
Jongwoo Moon (KEI)

Published in Jung et al. 2021. The impact of demographic changes on CO2 emission profiles: Cases of East Asian
1countries. Sustainability. 13(2). 677

• One of the fastest countries heading towards aged-society➢ Experienced a negative population growth in 2020 (due to COVID-19, low birthrates, etc.)➢ Decreasing youth and working-age population while increasing aged-population
Population Prospects in 2060 (2011 vs. 2021 Estimate)
Unit: Thousand

50000

Share

45000
40000
35000

17,62230000+ 3.75%p

18,683- 1.26%p

20,660

25000
20000
15000

21,865

10000
5000
04,4722060 (2011 Estimate)
Below 15

3,274

- 2.49%p
Aged 15-64

2060 (2021 Estimate)
Aged 65 and over

Source: KOSIS.2011.Korea and World Population Prospects; KOSIS. 2021. Population Prospects: 2020-2070

2• The comparison between UN Population Prospects in 2010 and 2019
➢ The share of the population aged 65 or older in 2050
※ 32.8% (2010 Prospect) ➔ 38% (2019 Prospects)
Demographic Structure (UN 2010 and UN 2019 Prospects)

Share
10.00%

9.00%
8.00%
7.00%

UN2010 - 2010

6.00%

UN2010 - 2050

5.00%

UN2010 - 2100

4.00%

UN2019 - 2010

3.00%

UN2019 - 2050

2.00%

UN2019 - 2100

1.00%

0510
15
202530
35
40
45
50
55
60
65
70
75
80
85
90
95
100

0.00%
Age3

• Significant drop in birth rates※ Total Fertility Rate: 1.297 (2012) ➔ 0.81 (2021)※ Old-age dependency ratio (Number of people aged 65 and over per 100 people of working age (20-64)): 24.8% (2021) ➔ 47.5% (2050) [OECD Forecast]
Old-age dependency Ratio

New Birth and Fertility Rate
600

1.460500

1.250

14002012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Source: KOSTAT. (2021). Total Fertility Rate; number of new birth
KOSIS. (2022). Number of new birth2026

002023

0.2

Total Fertility
10Rate (person)

2020

100KOR

2015

0.420

2012

200JPN2009

0.6CHN

30

2006

300

New Birth(thousand)

2003

0.8

2000

400

Source: OECD. (2022), Old-age dependency ratio (indicator).
doi: 10.1787/e0255c98-en (Accessed on 06 September 2022)

4Studies
Okada (2012)

Key Findings••

26 countries (OECD/IEA countries, Japan) between 1978 and 2008
A quadratic relationship between carbon emission per capita andaged population (emission per capita starts to decrease when theshare of the aged population of a country reached a certain point)•Analyzed the changes in demographic characteristics affect thefuture energy consumption and carbon emissions of households inChina.
Suggested that the decreasing trends of household size and theincreasing aging population would lead to energy demand increase.

Yu et al. (2018)••

Found a positive impact of the aging population on electricity
consumption.

•Identified a negative effect of the aging population ratio on theresidential electricity consumption•

Identified that the aging population leads to make income elasticity
more inelastic but price elasticity more elastic.

Noh and Lee (2013)

Keum et al. (2018)

Shin (2018)5• To analyze how the demographic structure changes led by aging population and lessworking age population affects the national GDP and CO2 emissions in East AsianCountries, including Korea.

UN Population Prospects (2010 vs. 2019)•9 Region (incl. Korea, Japan,China); 13 Sectors•SSP2 Scenarios•

UN Population Scenario, ILO

GDP

Labor force participation rate,
GTAP 10 Database
Labor force Participation Rate

Global CGE Model

Population

CO2Emission
6

UN Population Prospects (2010 vs. 2019)

Labor force Participation Rate

7

CGE Model
Nesting Structure (Production Technology)

CES Production Function
𝑄 = 𝑄ത

1ൗ
λ𝑖 𝑋𝑖 𝜌 𝜌σ𝑖 𝜃𝑖;
𝑋𝑖

𝑄 𝛽 𝑃𝑖 +𝑡ഥ𝑖 𝜎ഥ 𝑃𝑖 +𝑡𝑖
𝑄 𝛽𝑋𝑖 = λ𝜎−1𝑋ഥ𝑖 ത𝑖• 𝜃𝑖 : input value share; λ𝑖 : technology; 𝜎 =substitution; 𝑡𝑖 : tax rate on input i

1: elasticity of1−𝜌

Balance of Budget
1 − 𝑡𝑖 ∙ ෍ 𝑃𝐹𝑓 𝑄𝐹𝑓 = ෍ 𝑃𝑖 ∙ 1 + 𝑡𝑐𝑖 ∙ 𝑄𝐶𝑖 + 𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑆𝑎𝑣𝑖𝑛𝑔
𝑓𝑖σ𝑓 𝑡𝑓𝑓 𝑄𝐹𝑓 + 𝑡𝑖 σ𝑓 𝑃𝐹𝑓 𝑄𝐹𝑓 + σ𝑖 𝑡𝑐𝑖 𝑄𝐶𝑖 + 𝑡𝑝𝑖 𝑄𝑃𝑖 + σ𝑗 𝑡𝑖𝑗 𝑄𝐴𝑃𝑖𝑗 +σ(𝑟 ′ ,𝑖) 𝑡𝑎𝑟𝑖𝑓𝑓𝑟′,𝑟,𝑖 𝑄𝑡𝑟𝑎𝑑𝑒𝑟′,𝑟,𝑖 = σ𝑖 𝑃𝑖 𝑄𝐺𝑖 + 𝐺𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡 𝑆𝑎𝑣𝑖𝑛𝑔
෍ 𝑃𝑖 𝑄𝐼𝑁𝑉𝑖𝑖= 𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑 𝑆𝑎𝑣𝑖𝑛𝑔 + 𝐺𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡 𝑆𝑎𝑣𝑖𝑛𝑔 + 𝐹𝑜𝑟𝑒𝑖𝑔𝑛 𝑆𝑎𝑣𝑖𝑛𝑔

8Difference in Population, Labor Supply, Real GDP, and CO2 Emission(UN 2010 MID Scenario vs. UN 2019 MID Scenario)

9

Range of GDP and CO2 Emissions (Difference compared to the basescenario) by Population Scenario

Note: Applied High, Mid, Low UN Population Scenarios published in 2010 and 2019 andcompared the GDP and CO2 emissions ranges
10• Population and Labor participation rates are important drivers of the CO2emission projection. It is necessary to consider both the demographic

changes, such as changes in the share of each age group, and the population
changes.

• The low fertility rate and aging population in Korea would lead to thedecrease of the Korean population in the future. However, the increase in
the labor participation rate may lead to a relatively gradual decreasing trendof GDP and CO2 emissions compared to decreasing trends of population•Aging factors may reduce the greenhouse gas emissions. However, morelabor force participation somewhat offsets the reductions in the working
labor force caused by low-birth rates and aging population
11