Transcript Presentation – Advanced Session on using the RAP

Module 12: Advanced Session
on using the RAP
ILO, 2013
Key questions
• What is the structure of the ILO RAP model?
• What are the main sources of historical data and projections?
• Dealing with POP
– How to project the population?
– How to calculate the survivors and newborns?
– How to take into account migration?
• Dealing with EAP and LPR/AR
– What are the parameters of the labour market?
– How to project labour market data and unemployment rate?
• Dealing with ECO
– How to project GDP and GDP deflator?
Structure of RAP
1. Input data
General government
operations (GGO)
2. Estimated
cost of benefits in
absolute terms, as
% of GDP, and as %
of government
expenditure
Labour market
(EAP)
Demographic data
(POP)
Macroeconomic
data (ECO)
Costing of
benefits
Summary and
results
3. Projected cost of
combined benefit
packages
Structure of RAP
1. Input
worksheets
POP
BS 1
AR
EAP
BS 2
ECO
BS 3
SUM
BS 4
GGO
(SQ)
BS 5
3. Summary of
benefit costs
2. Benefit
worksheets to
estimate the
cost of
scenarios
Sources of data
• national statistical offices
• census and surveys
• social security institutions and line ministries
 ministry of planning: GDP and population projections
 ministry of interior: registration for social benefits
 ministry of commerce: inflation
 ministry of finance: budget, economic indicators
• central banks
• research institutes, universities
• UN/ILO population models, IMF’s World Economic Outlook
(alternative data sources)
Sources of data
• High, medium, and low projections of data reduce chances
of error
• Finding reliable data is a challenge
• Assumptions and projections may need to be done by
ourselves
• Data from different sources may be conflicting and need to
be cleaned up and validated
• Partnering with institutions (e.g. Institute of Statistics in
Indonesia, HISRO in Thailand) can provide comprehensive
and coherent data, and validate assumptions and projections
Coresia RAP: ‘Population’
Dealing with POP
• Projected population by age and gender is used in other
projections like labour force, number of unemployed, etc.
• Population projections can be obtained from official sources
or self-projected using the cohort component method
• Cohort component method uses current year (t) population
data, no. of newborns (linked to fertility), survivors (linked to
mortality), and net migration, to project next year (t+1)
population
Cohort component method
Population
in year t
Survival
rate
Net
migration
Population in
year t +1
(for ages > 1)
Fertility
rate
Sex ratio at
birth
Population
in year t+1
(for all ages)
Population in
year t +1
(for ages < 1
i.e. newborns)
Cohort component method
Estimating mortality rates
• The mortality rate is derived from life tables, from which the
number of survivors can be determined
• Life tables can be used to depict life expectancy of the
population and thus, estimate the number of deaths
• We can use life tables of a country, UN life tables and the
Coale-Demeny life tables
UN life tables
• 5 life expectancy patterns
were mapped.
• The geographical region
predominant within each
patterns gives the name to
that pattern:
 Latin American pattern
 Chilean pattern
 South Asian pattern
 Far Eastern pattern
 General pattern
0.350
0.300
0.250
Mortality pattern of females:
e0=75 years
General
South Asia
Far East
Latin America
Chile
0.200
0.150
0.100
0.050
0.000
0 7 14 21 28 35 42 49 56 63 70 77 84 91 98
Estimating mortality rates
Deaths(2010) =
Mortality(2010) x Pop(2010)
Age
Mortality
Male
0
0.0084
356,209
2,992
1
0.0007
373,622
262
353,217
2
0.0007
403,800
283
373,360
3
0.0007
449,310
315
403,517
4
0.0007
414,605
290
448,995
5
Pop
2010
Survival(2011) = Pop(2010) Deaths(2010)
Deaths
2010
Survival
2011
414,315
Fertility rate
• Age-specific fertility rate: Number of child births for women of
a particular age.
• Total fertility rate: Average number of children a woman can
give birth to during her lifetime; it is the sum of the agespecific fertility rates during the child bearing period
• Typical child-bearing period is from age 15 to 49
• Sex ratio: Ratio of males to females in the population
Estimating number of newborns
Newborns =
Fertility x Female pop
Age group
Fertility
rate
Female
Pop
15-19
0.00980
2,552,600
25,015
12,872
12,143
20-24
0.06910
2,557,443
176,719
90,933
85,786
25-29
0.12430
2,617,716
325,382
167,430
157,952
30-34
0.07960
2,671,012
212,613
109,403
103,210
35-39
0.03080
2,824,040
86,980
44,757
42,223
40-44
0.00740
2,830,251
20,944
10,777
10,167
0.00080
2,733,680
TFR =1.609 18,786,742
2,187
849,840
1,125
437,297
1,062
412,543
45-49
Total
Newborns Newborns Newborns
(M)
(F)
Estimating net migration
• Net migration = Immigration (inbound migrants) – Emigration
(outbound migrants)
• International migration can fluctuate widely every year
depending on socioeconomic and political factors. Thus, it is
primarily forecast in numbers by age group and gender, rather
than as rates.
• International migration is usually small compared to total
population.
• Usually we assume net migration = 0
Coresia RAP: ‘Economically Active
Population’
Labour force data
We need historical data, projected distribution of the
parameters by age group and gender:
• Labour force or Economically Active Persons (EAP)
• Labour market participation rate or activity rate
• Employed persons
• Unemployed persons
• Unemployment rate
Labour force data
Population
(>15)
Labour force or
Economy Active
Population
Employed
Labour force
participation rate (%) =
Labour force / Total
population above legal
working age
Non Labour Force
(including students,
retirees, disabled)
Unemployed
Unemployment rate (%) =
No. of unemployed /
Labour force
Labour force data
Demographic and labour force data: Thailand, 2007
700,000
600,000
Pop_M
500,000
LAB_M
400,000
300,000
200,000
100,000
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
0
Age
Estimating unemployment data
• Unemployed persons = Projected male EAP x Male
unemployment rate + Projected female EAP x Female
unemployment rate
• Unemployment rate = Unemployed persons / EAP
• Historical unemployment rates are used to calculate a trend
• The trend is used to project unemployment rates
Estimating unemployment data
Historical data and trend lines for unemployment rate in Coresia
4
3.5
y = -0.86ln(x) + 3.2216
R² = 0.9721
3
2.5
Males
Females
2
Log. (Males)
1.5
Log. (Females)
1
y = -0.927ln(x) + 3.2008
R² = 0.9474
0.5
0
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Coresia RAP: ‘Economic’
Dealing with ECO
• Mainly concerned with projections of economic growth
• Macroeconomic projections can be obtained from official
sources, research institutes, national authorities, international
organizations, or be self-projected
• GDP at current price = GDP at constant price (volume effect) x
GDP deflator (price effect)
• Using the formulas, participants can project one parameter
provided the other two are available
• GDP at constant price = Productivity * Employment
• Employment = Labour force (EAP) – Unemployment
Dealing with ECO
Dealing with ECO
• Inflation is the rate of increase in the average price level of
the economy. It is commonly measured by CPI, headline
inflation, GDP deflator
• GDP deflator compares prices of all goods and services
produced within the country in the current year, with the base
year prices
• CPI reflects the prices of goods and services purchased by the
consumers
• Headline inflation reflects the prices of all goods and services
consumed in the country, including fuel and food
• In developing countries, headline inflation may be preferred