microsimulation as a tool to integrated sdg-based development planningmicrosimulation as a tool to...

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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

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www.ipc-undp.org - www.ipea.gov.br

Rafael Guerreiro OsorioResearch Coordinator

International Policy Centre for Inclusive GrowthInstitute of Applied Economic Research

Kingston, Jamaica, 2-4 December, 2015

Inter-Regional Workshop:�Experiences and LessonsLearned from ECOSOC National Voluntary Presentations

Microsimulation as a tool forintegrated SDG-baseddevelopment planning

* The World Bank, World Development Indicators, 2015 (2011 PPP)

of the world populationwere living under

US$ 1.90/day in 2012*12.7%almost 1 billion human beings

Yet many people in the world areseverely income deprived

Extreme poverty was more than halvedThe world reached the main target of MDG 1 for 2015

There are SDGs related to all these issueslack access to affordable and clean energylack access to clean water and sanitation

face hunger and food insecurityBesides income deprivation, the poor:

Income is important, but poverty has other dimensions

An SDG-based development strategymust address this question

"Land, energy and water are our most precious resources, but the manner and extent to which they are exploitedcontributes to climate change. Meanwhile, the systems

that provide these resources are themselves highlyvulnerable 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)

Ann

ual G

Wh

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

Fitting curves to the time seriesof the outcome variable

does not allow us to relatefuture variation of the outcome

with the variables on whichit depends, such as household income

and consumption patterns

What can be done, however, depends on thequality and variety of data available: besides

good household surveys, statistics from registry,population projections, price surveys...

allows to estimate the household sectordemand for energy, water and land,by simulating changes on social and

economic variables linked with consumptionvariables at the household level,

by the data from surveys and censuses

The microsimulation approach

Component 3

Per capita consumptionof those with access

Microsimulationdataset

Component 2

Size and distributionof access to resource

Resourceaccess model

Populationprojection

Size and distributionof the population

Component 1

Initially, the tool will cover only energy and water

IPC is developing a tool to do microsimulationsaiming at its integration with other tools tosupport SDG-based development planning

The microsimulation approach

Component 3

Per capita consumptionof those with access

Microsimulationdataset

Component 2

Size and distributionof access to resource

Resourceaccess model

Populationprojection

Size and distributionof the population

Household electricity consumption - MauritiusComponent 1

A projected future demand of 921GWh in 2030a 14.3% increase of the 806GWh reported in 2014

The microsimulation approach

703.6KWh100%1,309,522 * *

Then, we simulate changes in the income distributionthat yield new levels of poverty and inequalityand 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 simplesimulations were done for Mauritius

for the case of electricity consumption

The microsimulation approach

Simulation 3 - income distribution changes as it did inany 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 from2009 to 2012

Simulation 1 - income distribution changes as it did from2013 to 2014

In the simulations, we used informationon past changes in the income distribution

but the parameters could be theoreticalor obtained from other tools

The microsimulation approach

US$

/day

(PP

P 20

11)

0

5

10

15

20

25

30

Year

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

sim1sim2

14.2 15.116.6 17.0 16.6 16.8 16.5 15.1

Average - household per capita income - Mauritius

Gin

i (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

Hea

dcou

nt r

atio

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

US$

/day

(PP

P 20

11)

0

5

10

15

20

25

30

Year

2000 2005 2010 2015 2020 2025 2030

sim2

sim1

Average - household per capita income - Mauritius

Gin

i (0-

1000

)

0

200

400

600

800

1000

Year

2000 2005 2010 2015 2020 2025 2030

sim1

sim2

Inequality - household per capita income - Mauritius

Hea

dcou

nt r

atio

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

Ann

ual G

Wh

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

US$

/day

(PP

P 20

11)

10

15

20

25

30

35

Year

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032

Average household per capita income - Mauritius

Gin

i (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

Hea

dcou

nt

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

Ann

ual K

Wh

per

capi

ta

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

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 plannersa good idea of what would be the social, economic,

and environmental outcomes of different policy options

Suppose that to eradicate extreme poverty and provideclean and affordable energy for all, a country sets up:

Some very interesting ones are SDG-related There are many other scenarios to be considered