The IPC-IG’s Research Coordinator, Rafael Osório, participated in the Inter-Regional Workshop Experiences and Lessons Learned from ECOSOC National Voluntary Presentations, held in Kingston, Jamaica, from 2 to 4 December. Mr. Osório joined the painel “Economy-wide modelling and microsimulation to inform development policy”, which aimed at discussing the experience of the specific application of these methodologies and at identifying issues that can be used in future applications. Mr. Osório delivered a presentation on “Microsimulation as a tool to integrated SDG-based development planning”.

1. www.ipc-undp.org - www.ipea.gov.br
Rafael Guerreiro Osorio
Research Coordinator
International Policy Centre for Inclusive Growth
Institute of Applied Economic Research
Kingston, Jamaica, 2-4 December, 2015
Inter-Regional Workshop: Experiences and Lessons
Learned from ECOSOC National Voluntary Presentations
Microsimulation as a tool for
integrated SDG-based
development planning

2. * The World Bank, World Development Indicators, 2015 (2011 PPP)
of the world population
were living under
US$ 1.90/day in 2012*12.7%
almost 1 billion human beings
Yet many people in the world are
severely income deprived
Extreme poverty was more than halved
The world reached the main target of MDG 1 for 2015

3. There are SDGs related to all these issues
lack access to affordable and clean energy
lack access to clean water and sanitation
face hunger and food insecurity
Besides income deprivation, the poor:
Income is important, but poverty has other dimensions

4. An SDG-based development strategy
must address this question
"Land, energy and water are our most precious resources,
but the manner and extent to which they are exploited
contributes to climate change. Meanwhile, the systems
that provide these resources are themselves highly
vulnerable to changes in climate" (Howells et al.)
How much?
Were it not for their severe budget constraints,
and lack of access, the poor would increase
their demand for energy, water and food (land)

5. AnnualGWh
0
250
500
750
1000
1250
1500
Year
2000 2005 2010 2015 2020 2025 2030
avg. growth?
linear?
806GWh
575GWh
1160GWh
1385GWh
Household sector - electricity consumption - Mauritius

6. Fitting curves to the time series
of the outcome variable
does not allow us to relate
future variation of the outcome
with the variables on which
it depends, such as household income
and consumption patterns

7. What can be done, however, depends on the
quality and variety of data available: besides
good household surveys, statistics from registry,
population projections, price surveys...
allows to estimate the household sector
demand for energy, water and land,
by simulating changes on social and
economic variables linked with consumption
variables at the household level,
by the data from surveys and censuses
The microsimulation approach

8. Component 3
Per capita consumption
of those with access
Microsimulation
dataset
Component 2
Size and distribution
of access to resource
Resource
access model
Population
projection
Size and distribution
of the population
Component 1
Initially, the tool will cover only energy and water
IPC is developing a tool to do microsimulations
aiming at its integration with other tools to
support SDG-based development planning
The microsimulation approach

9. Component 3
Per capita consumption
of those with access
Microsimulation
dataset
Component 2
Size and distribution
of access to resource
Resource
access model
Population
projection
Size and distribution
of the population
Household electricity consumption - Mauritius
Component 1
A projected future demand of 921GWh in 2030
a 14.3% increase of the 806GWh reported in 2014
The microsimulation approach
703.6KWh100%1,309,522 * *

10. Then, we simulate changes in the income distribution
that yield new levels of poverty and inequality
and using the elasticities we calculate future
demand for electricity
In the simulations there is only one driver of consumption,
household per capita income - the income elasticity
of electricity consumption was calculated for every household
As proof of concept some simple
simulations were done for Mauritius
for the case of electricity consumption
The microsimulation approach

11. Simulation 3 - income distribution changes as it did in
any pair of years from 2007 to 2014, randomly chosen
- this is done 10,000 times, yielding interval estimates
Simulation 2 - income distribution changes as it did from
2009 to 2012
Simulation 1 - income distribution changes as it did from
2013 to 2014
In the simulations, we used information
on past changes in the income distribution
but the parameters could be theoretical
or obtained from other tools
The microsimulation approach

12. US$/day(PPP2011)
0
5
10
15
20
25
30
Year
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
sim1sim2
14.2 15.1
16.6 17.0 16.6 16.8 16.5
15.1
Average - household per capita income - Mauritius

13. Gini(0-1000)
0
200
400
600
800
1000
Year
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
sim1sim2
374 390 409 407 413 408 417 439
Inequality - household per capita income - Mauritius

14. Headcountratio
0%
5%
10%
15%
20%
25%
30%
Year
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
sim1sim2
1.6 1.4 1.7 1.6 2.0 1.7
3.1 4.3
Poverty - less than US$ 3.10/day - Mauritius

15. US$/day(PPP2011)
0
5
10
15
20
25
30
Year
2000 2005 2010 2015 2020 2025 2030
sim2
sim1
Average - household per capita income - Mauritius

16. Gini(0-1000)
0
200
400
600
800
1000
Year
2000 2005 2010 2015 2020 2025 2030
sim1
sim2
Inequality - household per capita income - Mauritius

17. Headcountratio
0%
5%
10%
15%
20%
25%
30%
Year
2000 2005 2010 2015 2020 2025 2030
sim1
sim2
Poverty - less than US$ 3.10/day - Mauritius

18. AnnualGWh
0
250
500
750
1000
1250
1500
Year
2000 2005 2010 2015 2020 2025 2030
sim1
806GWh
575GWh
921GWh
462GWh
sim2
Household sector - electricity consumption - Mauritius

19. US$/day(PPP2011)
10
15
20
25
30
35
Year
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032
Average household per capita income - Mauritius

20. Gini(0-1000)
350
400
450
500
550
600
Year
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032
Gini - household per capita income - Mauritius

21. Headcount
0%
5%
10%
15%
20%
25%
30%
35%
Year
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032
Poverty - less than US$ 3.10/day - Mauritius

22. AnnualKWhpercapita
500
550
600
650
700
750
800
850
Year
2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032
Average domestic electricity consumption - Mauritius

23. 1) a cash transfer targeted at low income families;
2) electricity subsidies and no connection charge;
3) a very progressive electricity tariff;
4) a plan to expand the grid to one remote area.
All this can be simulated together, giving planners
a good idea of what would be the social, economic,
and environmental outcomes of different policy options
Suppose that to eradicate extreme poverty and provide
clean and affordable energy for all, a country sets up:
Some very interesting ones are SDG-related
There are many other scenarios to be considered