F copack |
T21 China: An Initial Application and Analysis
By Weishuang Qu and Gerald 0. Bamey
MILLENNIUM INSTITUTE
1117 North 19th Street, Suite 900
Arlington, VA 22209, USA
Phone: (1-703) 841-0048
Fax: (1-703) 841-0050
E-mail: wqu@ threshold21.com
Web: www.threshold21.com.
7 December 2000
Abstract
The purpose of this paper is to demonstrate the uses and capabilities of the
Threshold 21 (T21) model through an application to China. The first section, “Results
for the Baseline Scenario,” provides the baseline projections for China to the year 2020.
In the “baseline” scenario, it is assumed that the past policy and a peaceful condition
continue, and the scenario shows what is likely to happen over the next 20 years in five
areas: population, prices and income, production, environment, and social issues. The
second section, “Results for Alternative Scenarios,” provides scenario analysis, or “what-
if” analysis for a number of alternative policy scenarios, including two child per family
policy, stricter pollution control policy, and HIV/AIDS policy. The major results of the
policy change are compared to the baseline projection.
Contents
Introduction oid
Results for the Baseline Scenario. 3
Population: a)
Economy... 6
Production. 10
Environment and non-renewable resources 12
Social isSues..........cesseesees 14
Results for Alternative Scenarios. 19
Two child family policy...... 19
Agricultural land loss scenario .. 19
Non-renewable (NR) resource scenario. 20
Stricter pollution reduction scenario..
HIV/AIDS scenario. ............++
Attachment: An Overview of T21
Introduction
The purpose of this paper is to demonstrate the uses and capabilities of the
Threshold 21 (T21) model through an application to China.
T21 is a computer simulation model designed as a tool for national long term
development planning. It includes economic, resource, environmental and social
sectors in an integrated system. Compared to all other national planning models, it
is more transparent, easier to understand, and easier to be applied and transferred to
any country.
The T21 model is not for making precise predictions of the future. Rather, itis a
tool for exploring alternative policy scenarios in an effort to identify sets of
policies that may improve conditions in the future.
Overall, the T21 model is a system of products: The T21 Core and a collection of
individual sectors. T21 Core is the nucleus of the system, a highly aggregated,
model with three parts: population, economy/production, and simplified non-
renewable and pollution sectors (indices). Other sectors are ready to be added to
T21 Core as need arises. They include: unemployment, income distribution,
education, health care, HIV/AIDS, nutrition, energy, land, forest, water, water
pollution, air pollution (greenhouse gas emission), and government debt. A variety
of output indicators used by the World Bank, IMF, UN agencies, and many
governments, can be added. For further details on the T21 Core model, see the
Attachment: An Overview of T21.
For the preparation of this paper, three sectors were added to the T21 Core:
unemployment, income distribution, and HIV/AIDS.
The first section, “Results for the Baseline Scenario,” provides the baseline
projections for China to the year 2020. In the “baseline” scenario, it is assumed
that the past policy and a peaceful condition continue, and the scenario shows what
is likely to happen over the next 20 years.
The second section, “Results for Alternative Scenarios,” provides scenario
analysis, or “what-if” analysis for a number of alternative policy scenarios. The
major results of the policy change are compared to the baseline projection.
With the T21 Core model, users can analyze a wide variety of scenarios. The
scenarios presented in this paper are only a small sample of what is possible.
In application, the T21 model is used to simulate the past decade or more and the
simulation results are compared to available data. Data came from three
international sources, including the World Bank’s World Development Indicators,
UN Population Data, and UN Food and Agriculture Organization A gricultural
Data.
In the following sections, historical data are included for reference purposes: the
World Bank’s World Development Indicators is identified by “WDICHNO00” in the
graphs; the UN Population Data is identified by “PopCHN” in the graphs; and UN
Food and Agriculture Organization data is identified by “FAOCHN” in the graphs.
There are many limitations of both the T21 model presented here and the analysis
in this paper. China is a huge, diverse country, not easily represented in a
nationally aggregated model. While China has achieved great success over the last
20 years, it still faces huge problems. Some of the important sectors to China, such
as education, water, energy, land, forest, and social stability, are not even included
in the current model. The analysis presented here is incomplete and much more
can be said and added to each of the graphs by way of using the model and using
expert knowledge in each of the topics. However, for the purpose of
demonstrating the uses and capabilities of T21, we hope what follows are adequate
to make the point clear.
This work has been supported by grants or contracts from the General Motors
Corporation and several US foundations.
Results for the Baseline Scenario
Population:
The following graphs show that total population will be 1.42 billion by the year
2020, if total fertility rate continues a slow decrease from 1.9 (2000) to 1.7 (2020).
Life expectancy will continue to increase from 72 for female and 69 for male at
present to about 76 for female and 73 for male by 2020. Age structure will also
change, resulting in a growing proportion of older population.
Graph for total population
800 M
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
total population : base Person
total population : PopCHN Person
Figure 1: Total population (The simulation result and the data line are
overlapping)
Graph for life expectancy
80
75
70 eet tee ey
_ ee eel
60
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
life expectancy[FEMALE] : WDICHN00 Dmnl
life expectancy[FEMALE] : base Dmnl
life expectancy[MALE] : WDICHNO0 Dmnl
life expectancy[MALE] : base Dmnl
Figure 2: Life expectancy:
Graph for total fertility rate
3.25,
2.5
1.75
1
1980 1984 1988 1992 1996, 2000 2004 2008 2012 2016 2020
Time (¥ ear)
total fertility rate : WDICHN0O Dmal
total fertility rate : base Dmani
Figure 3: Total fertility rate:
sim-hist
Population Pyramids
Male Female
A 80 AND
“"R75 to 79
A 70 to 74
A 65 to 69
A 60 to 64
A55 to 59
A 50 to 54
A 45 to 49
A 40 to 44
A 35 to 39
A 30 to 34
A 25 to 29
A 20 to 24
A 1570 19
A10 to 14
A5to9
AOTO4
100M. 75M 50M 25M 0 0 25 M 50M 75M 100M
Figure 4: Age structure for 2000:
base
Population Pyramids
Male Female
A 80 AND OVE
A 75079
A70 to 74
A 65 to 69
A 60 to 64
A585 to 59
A50 to 54
A 45 to 49
A 40 to 44
A 35 to 39
A 30 to 34
A 25 to 29
A 20 to 24
A 15TO 19
A 10to 14
A5t09
A0TO4
100M 75M 50M 25M 0 0 25M 50M 75M 100M
Figure 5: Age structure for 2020
Economy
Producer price index (value equal to 1 for all three sectors): It is interesting to
notice that agricultural price index grows to be highest, and the reason is that when
Chinese people get better off, they first improve their diet.
Graph for sector producer prices
8
6
4
2
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
sector producer prices[agri] : WDICHNOO Dmal
sector producer prices agri] : base Dmnl
sector producer prices{ind] : WDICHNOO Dmnl
sector producer pricesfind] : base Dmnl
sector producer prices{serv] : WDICHNOO Dmnl
sector producer prices{serv] ; base Dmnl
Figure 6: Producer price index
Relative price index is derived from producer price index, and is shown in Figure 7
below.
Graph for relative prices
2
1.5
1
0.5
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
relative prices[agri] : WDICHNOO Dmal
relative prices{agri] : base Dmal
relative prices[ind] : WDICHN0O Dmal
relative pricesfind] : base Dmal
relative prices[serv] : WDICHN00 Dmal
relative prices{serv] : base Dmal
Figure 7: Relative prices
Real GDP: From 1980 to 2000, China’s real GDP increased almost 6 times. In the
next twenty years, China’s real GDP will grow at an average rate of 5% per year,
or about 265% in 20 years.
Graph for real GDP mp
204013
1.5e4013
1e+013
5e+012
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Year)
real GDP mp : WDICHNOO RMBQ0/Y ear
real GDP mp : base RMBQO/Y ear
Figure 8: Real GDP
With the GDP growth, per capital real disposable income will also grow, from a
little over 2,000 RMB90 at present to over 6,000 by 2020.
Graph for mean pc income
8,000
6,000
4,000
2,000
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
mean pe income : Base RMB90/(Person*Y ear)
Figure 9: per capita disposable income
Central government revenue and total government (including local and central) are
expected to grow as well.
Government Revenue
2e+013
1.5e+013
1e+013
5e+012
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
All government revenue from Base RMB/Y ear
Not available from data RMB/Y ear
Central government revenue from Base RMB/Y ear
From WDICHNOO RMB/Y ear
Figure 10: Central and total government revenue
International trade is quite difficult to project, as the model only includes domestic
components. By setting world real prices as constants, and world GDP growth at a
constant rate, the model estimates imports and exports:
Graph for imports
4e+012
3e+012
2e+012
le+012
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
imports[agri] : WDICHNOO RMB/Y ear
importsfagri] : base RMB/Y ear
imports[ind] : WDICHN00 RMB/Y ear
imports[ind] : base RMB/Y ear
imports[serv] : WDICHNOO RMB/Y ear
imports{serv] : base RMB/Y ear
Figure 11: Imports
Graph for exports
8e+012
6e+012
4e+012
2e+012
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
exports[agri] : WDICHNOO RMB/Y ear
exports[agri] : base RMB/Y ear
exports{ind] : WDICHNOO RMB/Y ear
exports[ind] : base RMB/Y ear
exports[serv] : WDICHN00 RMB/Y ear
exports[serv] : base RMB/Y ear
Figure 12: Exports
Production
Labor productivity (per worker output) in industry and services increased
tremendously over the 1980-2000 period, and will continue to grow.
Labor Productivity
60,000
45,000
30,000
15,000
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
industrial labor productivity : Base RMB9O/(Person*Y ear)
industrial labor productivity : WDICHNOO RMB 90/(Person*Y ear)
service labor productivity : Base RMB90/(Person*Y ear)
service labor productivity : WDICHNOO ee _ RMB90/(Person*Y ear)
Figure 13: Labor productivity
10
Industry and Service Emplyment
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
ind employed : Base Person
ind employed : WDICHNOO Person
serv employed : Base Person
serv employed : WDICHNOO Person
Figure 14: Employment in industry and services
Grain yield will grow to 5.4 ton/hectare, about 720 Jin/Mu as a nation wide
average. Two critically important factors facing China’s agriculture are water
availability and soil erosion. These two factors are included in the model only as
placeholders. Currently they do not have any consequences on yield because we
do not have enough data to develop an appropriate algorithm.
Graph for yield
2
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
yield{grain] : WDICHNO0O Ton/(Y ear*Hectare)
yield{grain] : base Ton/(Y ear*Hectare)
Figure 15: Grain yield
11
Agricultural land is a scarce resource, and is probably going to shrink in the future
due to urbanization and soil erosion. In the model it is assumed that agricultural
land will stay constant. It is also assumed (following FAO) that 58% of
agricultural land will be used to grow grain, and the crop intensity index for grain
is kept at a constant level: 1.56.
Agriculture Land and Harvested area
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
Agricultural Land in Use : Base Hectare
Agricultural Land in Use : FAOCHN Hectare
Grain harvested area from Base Hectare
Grain harvested area from WDICHNO0 Hectare
Figure 16: Agricultural land and grain harvested area
Environment and non-renewable resources
There are many types of pollutants, such as chemicals, heavy metal, radioactive
material, greenhouse gases, and SPM (Suspended Particulate Matter). Instead of
modeling each of them separately, the T21 Core model uses a single index to
represent the weighted sum of all the pollutants. In cases where more detailed
analysis is needed, there are separate sector models available to be added to the
T21 Core.
It is assumed that the generation of pollution is related to production levels
(represented by real GDP) and technology. The higher the real GDP becomes, the
higher the rate of pollution generation grows. Technology has an opposite effect:
the higher the technology, the lower the pollution generation. Assimilation half-
life is assumed to be 5 years.
Pollution index is standardized to be of the value 1 for 1980. By 2020, it increases
to almost 4.5, or 4.5 times as bad as in 1980, as the following picture shows.
12
When pollution index grows high, the model assumes that people’s health will be
affected and their life expectancy will be shortened. Such developments could also
push the government to adopt tighter emission regulations, forcing industries to
spend more on emission control, and thus less on direct production.
Graph for pollution index
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
pollution index : base Dmnl
Figure 17: Pollution index
Non-renewable (NR) resource means fossil fuels and metals in this model. We use
a single index to represent the weighted average of all. It is assumed that at the
beginning of the simulation in 1980, NR resources are available in such an amount
that it can last for 200 years at the use rate of 1980. Again, more detailed natural
resource sectors are available to add to the T21 Core model.
The model uses the variable “fraction NR resource remaining” to measure the NR
remaining fraction of the 1980 total. When this fraction goes under a certain
margin (60%), part of the production capital will become unproductive, because it
will be used to develop substitute, or to develop infrastructure to handle more
imports, or to develop higher efficiency technologies.
Because of the fast growth of China’s economy and similar growth in NR resource
use, natural resources are depleted quite rapidly. By 2020, only about 20% of the
original 1980 total is left.
13
Graph for fraction NR resource remaining
0.5
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
fraction NR resource remaining : base Dmnl
Figure 18: Fraction of remaining non-renewable resources
By 2020, a substantial part of capital in industry will be used for seeking
substitutes or developing new technologies, thus growth will be slowed. Further to
the future, we may even see a negative growth of real GDP.
Social issues
This model assumes that industry and services only employ people in the urban
area. It also assumes that by 2020, urban population will be 45% of total
population, as the following graph shows.
Graph for FRACTION URBAN POP
06
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (¥ ear)
FRACTION URBAN POP : WDICHNOO Dmal
FRACTION URBAN POP : base Dmal
Figure 19: fraction of population living in urban area
14
Based on these two assumptions, unemployment in cities is not a problem until
about 2014, where urban unemployment start to emerge and will reach 10% by
2020.
Graph for urban unemployment rate
0.2
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
urban unemployment rate : Base Dmnl
Figure 20: Urban unemployment rate
In 2000, the income distribution in urban China looks like the following.
income distribution[IncClass,urban] @ 2020
4e-005
3e-005 1a
2e-005 . Ze
. a
1e-005 - Ma
mn,
= i el
o | Sethe tiers ee
Class1 Class19 Class37 Class55 Class73 Class91
IncClass
income distribution[IncClass,urban] : base RGuSEUSAMeREGREEERISBNURCEEEOSEES) Din
Figure 21: Urban income distribution in year 2020
15
The horizontal axis is the income, with each class representing 1000 RMB90/year,
so Class19 means the income level of 19,000 RMB90/year. The vertical axis is the
probability density function.
Using 2,000 RMB/Y ear as the poverty line, the income distribution shows that
there are about 0.5 million urban families and 3 million rural families that are still
under poverty in 2000. It also shows that 20% of urban households are living
below 6,700 RMB90/Y ear at the year 2000.
Total grain production measured in tons is shown below.
Graph for agricultural production in tons
600M
500M
400 M
300M
200M
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 72020
Time (Y ear)
agricultural production in tons{ grain] : base TonlY ear
agricultural production in tons{ grain] : FaoCHN Ton ear
Figure 22: Grain production in tons
Per capita grain from domestic production stays around 350 kg per year as the
following picture shows.
16
Graph for pe grain
400
a LIK EYVT TT TPP
300
250
200
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (¥ ear)
pe grain : Base kg/(Person*Y ear)
Figure 23: Per capita grain production
Per capita meat demand (including pork, beef, lamb, poultry, fish, egg, and milk) is
going to grow after 2000, but the growth rate may slow down, as the following
picture shows.
Graph for pc meat demand
60
45
15
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
pc meat demand : base kg/(Person*Y ear)
Figure 24: Per capita meat consumption
Can China produce all the meat for domestic demand? Does China have the range
land to feed the livestocks? Does China have enough grain to feed its livestocks?
If not, should China import meat, or import grain? With some additions to the
current model, it will be able to address these issues.
17
HIV/AIDS is beginning to emerge in China. The first case was discovered in
1985, and UNAIDS estimated that by the end of 1999, the cumulative number of
adults and children living with HIV/AIDS is 500,000.
It is assumed in the model that the Chinese government will do a very good job
and in five years from now, in 2005, HIV infection will start to fall as the
following picture shows. Annual infection will reach 128,000 persons and then
gradually fall. Even so, cumulative AIDS death will reach 2 million of China’s
most active and productive people. AIDS orphans (at least one parent died of
AIDS) will exceed 600,000, and annual expenditure on HIV/AIDS care will
exceed 6 billion RMB.
Graph for HIV infection
200,000
150,000
100,000
50,000
HIV infection : base
Toot
1988 1992 1996 2000 2008 2008 212
Time (Year)
216 2020
Figure 25: HIV annual infection rate
18
Person/Y ear
Results for Alternative Scenarios
The previous section described the projected results for the Baseline Scenario,
which assumes past policies and peaceful conditions continue. This section
explores some alternative scenarios.
Two child family policy.
In this altemative, it is assumed that, starting from 2000, the government changes
its one-child policy to a two-child policy. Due to policy implementation
difficulties, it is assumed that by 2005, total fertility rate will grow to 2.5
nationally, and then stays at 2.5 through to 2020. The new scenario, called
HighTFR, will have much higher population then the baseline scenario. Total
population will change from 1.42 billion to 1.56 billion in 2020. The difference is
equal to about half of US’s current population, and they are all under the age of 20!
Graph for total population
2B
1.7B
14B
11B
800 M
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
total population : HighT FR. Person
total population : base Person
Figure 26: Total population comparison
Agricultural land loss scenario
If we allow agricultural land to be lost to urbanization and other purposes at a rate
of 0.5% per year, or 500,000 hectares (7,500,000 mu) per year, by the end of 2020,
we will have lost 10% of our arable land. Per capita grain from domestic
production will be lower than the base case as the following picture shows. This is
a scenario we certainly want to avoid.
19
Graph for pe grain
400
300
250
200
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
‘Time (Y ear)
pe grain : Base kg/(Person*¥ eat)
pe grain : Landloss kg/(Person*Y ear)
Figure 27: Per capita grain production comparison
Non-renewable (NR) resource scenario
It is assumed that when fraction NR resource remaining decreases, an increasing
amount of capital will be used to seek substitutes or develop technologies for more
efficient use of the NR resources. In the following picture, the horizontal axis
represent fraction NR resource remaining, and the vertical axis is the fraction of
capital that will be used for non-productive us.
astral capital allocated to obtaining resources table
i -
0 i ae
0 1
Figure 28: Table function relating industrial capital and fraction of remaining non-
renewable resources
If it tus out in the future that more capital, 50% more, will be needed to deal with
the shortage of NR resources, the industrial and service production in this HighNR
scenario will be considerably lower than the base scenario.
20
Production
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
Base Case Industry GDP RMB9O/Y ear
High NR Cost Case Industry GDP RMB90/¥ ear
Base Case Service GDP RMB90/Y ear
High NR Cost Case Service GDP RMB90/Y ear
Figure 29: Comparison of production due to non-renewable resources
The industry GDP for the HighNR case is already declining before 2020, as then
almost 50% of the capital in the sector needs to be used on non-renewable
resources, thus becoming not directly productive. The difference in service
between the two scenarios is much smaller, as service is less resource intensive.
Stricter pollution reduction scenario
Cleaning up pollution after it is produced and reducing emission both takes away
valuable investment from production, but they also produce many benefits. If the
Government issues more strict pollution regulations, all production sectors have to
spend more on emission control, and less on direct production. The resulting
pollution index is much lower now, which produces benefits for health and life
expectancy:
21
Graph for pollution index
45
0
1980 1984 7988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
pollution index : Base Dmal
pollution index : LowPoll Dmnl
Figure 30: Comparison of pollution index
Industrial production will also be lower as the following picture shows.
Graph for industy produced
8e+012
6e+012
4e+012
2e+012
0
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016 2020
Time (Y ear)
industry produced : Base RMBQO/Y ear
industry produced : LowPoll RMBOO/ ear
Figure 31: Comparison of industrial production due to pollution
HIV/AIDS scenario.
If the government is inefficient or slow to in adopting effective measures to stop
the spread of HIV infection, the peak infection will be delayed 5 years until 2010,
and the consequence will be quite startling compared with the baseline scenario.
The following is the annual HIV infection rate.
22
Graph for HIV infection
400,000
300,000
200,000
100,000
0
1980 1984 1988 1992 1996 72000 2004 2008 2012 2016 72020
Time (¥ ear)
HIV infection : Base Person/Y ear
HIV infection : HighHIV Person/Y ear
HIV infection : HIVsim Person/Y ear
Figure 32: Comparison of HIV annual infection rate
Cumulative AIDS death will reach almost 3 million (compared to 2 million in the
baseline scenario), AIDS orphans will exceed 1 million (compared to 600,000 in
the base case), and annual expenditure on HIV/AIDS care will be doubled in 2020,
about 12 billions.
So far five scenarios have been presented and compared to the baseline scenario.
These five scenarios are only a small sample of what T21 model can do to help
national planners see the possible consequences of various policy choices.
23
Attachment: An Overview of T21
The T21 Core model is based on the culmination of more than 20 person-years of
work collecting, studying, and developing national development models. Almost
all the sectors are inspired and based on respected models and documentation, such
Computable General Equilibrium (CGE) economic models(“From Stylized to
Applied Models: Building Multisector CGE Models for Policy Analysis”,
Devarajan, Lewis, and Robinson), the Intergovernmental Panel on Climate
Change’s (IPCC) Greenhouse Gas Inventory Workbook, the US Department of
Energy’s Fossil2 model and the IDEALS model, the Population Council’s FIV-
FIV model, the RIVM’s (National Institute of Public Health and Environmental
Protection of the Netherlands) Targets model, the DICE Integrated Climate-
Economy model, and the US Department of A griculture’s CPPA model.
The figure below presents a conceptual overview of the components in the T21
core model and their inter-linkages. The diagram focuses on three general types of
capital— human capital, natural capital and produced capital— with economic
production in the center. The arrows are meant to convey the causal effects
between the different types of capital. For example, human capital affects
economic production through the employment of workers, and economic
production, in tum, affects human capital by providing food and income.
24
(Pop, health, literacy, and income)
human waste generation ea income
Human distribution
human land demand Capital ea J
Gini Coef
water, air, fncome,
and forest food
<income>
Govt | demand
Tand, water, alr Forelgn
' Debt
Natural foeall fuel production
Capital. relative prices
cropland ,
forestland | capital wecement any
asticity
water enrollment rate N~ <production:
fetes total fertility rate
‘access to basic health care imports
Produced ta
capital open
(including factories, schools, and hospitals)
The figure provides insight into some of the key concepts found in the T21 core
model including the following:
Economic production is affected by each of the three types of capital - human
capital, natural capital and produced capital.
Economic production, in turn, affects the three types of capital - income and
food affect human capital, investment affects produced capital and pollution
and resource depletion affect natural capital.
Production also affects the income distribution (in the top right comer) and
supply (lower right comer). The model uses the log normal distribution to
approximate income distribution. It uses the Gini coefficient and the mean
household income to drive the log normal distribution.
Imports and exports of the production sectors are endogenously determined.
Together with production, they determine the supply of goods and services.
Both income and relative prices are used to determine demand for goods and
services.
¢ Relative prices change with the imbalance between demand and supply. The
change of relative prices will affect the distribution of investment between
sectors and further affects the production and supply of the sector.
¢ The government obtains revenue from domestic sources (tax and non-tax
income) and foreign sources (grants and loans).
¢ Government expenditure includes public consumption, public investment, and
interest payments. If expenditure exceeds revenue, the government needs to
borrow either from domestic or from foreign sources, thereby increasing its
debt and future interest payments.
For further information, see www.threshold21.com, or contact the Institute using
the information on the cover page of this paper.
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