Download Sector Macro

Sector Macro
Taller de Trabajo Tecnico del Programa BIEE
24-25 de marzo 2015
UPME, Ciudad de Bogota, Republica de Colombia
Bruno Lapillonne, Enerdata
Outline
1.
2.
3.
4.
5.
6.
Primary energy intensity
Primary versus final energy intensity
Sectoral intensities
Data required
Energy intensities at ppp
Annex: issues with monetary values
The primary energy intensity: interpretation
•Primary energy intensities are quite well known indicators, and often
used as easy to calculate
•They relate the total energy consumption (“oferta totale, TPES) in
energy units (eg TJ, ktoe or GWh) to the GDP (Gross Domestic Product)
measured at constant price (e.g. $2000) toe/$2000
•They assess the overall energy efficiency from an economic viewpoint
 broader than pure energy efficiency from a policy or engineering
viewpoint
•Reduction in energy intensities are often the objective targeted by
energy efficiency policies. (e.g. France, Tunisia)
•The purpose of this presentation is to better explain how energy
intensity trends can be interpreted:
•What can be concluded and what are their limits ?
•How they can be adjusted to better compare them ?
Variations over time of energy intensities are usually expressed in average
annual growth per year (%/yr) over a period: they measure overall energy
efficiency trends from an economic viewpoint
Trends in primary energy intensity in Mercosur (%/year)
3%
2%
1%
0%
-1%
-2%
Brazil
Argentina Bolivia
1990-2000
Paraguay Uruguay
2000-2009
Chile
1990-2008
Regular decrease in
Argentina, Chile and
Uruguay indicating
improvement in “overall
economic efficiency” or
“energy
productivity”..but not all
variations necessarily
explained by technical
efficiency gains or
linked to policies
Average annual growth rate (% per year) (agr) between year m
and n : agr= ((In/Im)* (1/(n-m) – 1)*100
as In= Im (1+agr) n-m (with I energy intensity)
Based on original data in toe/ M US$2000
Source : SIEE-Olade y CEPAL (2008 for Uruguay)
Outline
1.
2.
3.
4.
5.
6.
Primary energy intensity
Primary versus final energy intensity
Sectoral intensities
Data required
Energy intensities at ppp
Annex: issues with monetary values
Primary versus final energy intensities: two different level of
measurement of the overall energy efficiency
 Final energy intensity: relates the total consumption of final energy
consumers (“final energy consumption”) to the GDP,  asses energy
efficiency at the level of final consumers, i.e. of industry (excluding energy
industries), transport, households, services & agriculture
 Difference primary / final energy intensity: consumption and losses in
energy transformations , mainly in power scetor
Primary energy intensity variations
Case of Argentina
0,25
koe/M$93
Most of the losses in transformations
come from the power sector : 80% of the
gap in general , of which 3/4 losses in
thermal power generation and 5% T&D
losses
Case of Brasil
0,15
0,10
0,05
0,00
0,40
1998
2004
2010
Other transformations
Power generation
Final energy intensity
0,30
ktoe/M$2000
0,20
0,20
Source: BIEE/Secretaria de Energia
0,10
0,00
1993
Intensidade final
1998
2005
Generación eléctrica
Source: BIEE/EPE
2010
Otras transformaciones
Different trends in primary and final energy intensities
As a long term trend, primary intensity increases faster (or decrease slower)
than final intensity due to increased losses in energy transformations.
Why: for two reasons mainly
oEconomies are more and more electricity intensive, which increase
transformations losses as electricity is generally produced with conversion
losses
oThe share of renewables, that are assumed to have no loss in energy
balance (100% efficiency), is generally decreasing .... however in recent
years and in some EU countries reverse trends are observed due to the
large diffusion of wind power)
Year to year variation depend on the share of hydro and wind in power
generation, and more generally on the power mix, and on the thermal power
efficiency (development of gas combined cycles)
Different trends as to the variation of primary and final intensity in Brazil
depending on transformations l and mainly power sector
Since 1998, energy transformations contribute to increase the primary intensity
due to the development of thermal power generation and biofuels production
%/año
Primary and final intensity trends: case of Brazil
3%
3%
2%
2%
1%
1%
0%
-1%
-1%
-2%
-2%
1990-1993
Intensidad primária
1993-1998
1998-2005
Intensidad final
Source BIEE/EPE
2005-2010
Transformación
9
Share of hydro in power generation in Brazil
100%
Increase in thermal power generation ,
contribute to reduce the average
efficiency of power generation , which
increases losses in energy
transformations and contributes to
increase the primary intensity.
Efficiency of power generation in Brazil
80%
60%
40%
20%
0%
1990
1995
2005
2010
Eficiencia del sector eléctrico
Source BIEE/EPE
Eficiencia del sector eléctrico (térmico)
10
Decreasing share of hydro and wind in power generation  decrease in the average
efficiency of power generation and increased transformation losses in power
generation
Share of hydro and wind in electricity production
2010
2004
1998
1995
1990
80%
70%
60%
50%
40%
30%
20%
10%
0%
Increasing share of electricity result in
increasing losses in transformations as
significant part of power generation in thermal
power plants, i.e. with losses
25%
20%
15%
10%
5%
0%
Share of electricity in final
consumption in Argentina
1990 1995 1998 2004 2010
% electrcity
11
Outline
1.
2.
3.
4.
5.
6.
Primary energy intensity
Primary versus final energy intensity
Sectoral intensities
Data required
Energy intensities at ppp
Annex: issues with monetary values
Sectoral intensities
Industry: energy consumption to VA
Agriculture: energy consumption to VA
Services GDP: energy consumption to VA
Households = energy consumption to private consumption
Transport: energy consumption to GDP
Definition of GDP and value added by service sector
 Gross Domestic Product = sum of value added of 3 main sectors:
agriculture, industry and services (also called tertiary);
 Two definition of GDP:
 GDP at market price: sum of value added at market prices of agriculture,
industry and services + indirect taxes;
 GDP at factor cost: sum of value added at factor cost of agriculture, industry
and services;
 Definition of sectors standardised in the ISIC classification, as follows
• Agriculture and fishing activities (Section A)
• Industry (Section B to F):
• Services (Section G to U) , includes public services (administrations) and
private services (commercial sector); it includes all other economic
activities, apart from industry and agriculture.
 GDP expenditure = private consumption of households (about 60-70% of
GDP) + gross investment + government consumption + import - export
14
Sectoral intensities : case of Argentina
Industry 14 times more energy intensive than services
Intensidad energética sectorial (ktep/M$1993)
0,3
0,025
0,25
0,02
0,2
Intensidad e
0,015
0,15
0,01
0,1
0,005
0,05
0
0
1993 1994 1995 1996 1997 1998
1999 2000 2001 2002 2003 2004
AGRICULTURA
INDUSTRIA
Source: BIEE/Secretaria de Energia
2005 2006 2007 2008 2009 2010
TERCIARIO
Outline
1.
2.
3.
4.
5.
6.
Primary energy intensity
Primary versus final energy intensity
Sectoral intensities
Energy intensities at ppp
Data required
Annex: issues with monetary values
Energy intensity levels depend on currency
To compare energy productivity performance, energy intensities are measured
in the same monetary units by converting national currencies in $ or €
Conversion are usually made on the basis of market exchange rates, which
raised two problems :
 the relative energy intensity between countries (the “ranking”) are
affected by the fluctuations in market exchange rates, which can vary quite
a lot, even if the relative energy productivity did not change ;
This conversion does not reflect the fact that in less developed countries
consumer prices are on average much lower than in OECD countries (for
instance, the average cost of living in 2008 according to World Bank/IMF as
measured with purchasing power parities is 3.5 times lower in Bolivia than
in France (2.4 times for Argentina and 1.7 times for Brazil) this means
that an income of 1000 $ in Bolivia is equivalent to 3500 $ in France;
Difference of 1.3 for Brazil , 1.7 for Argentina and 2.5 for Bolivia between
exchange rate and purchasing power parities in 2008 (ppp respectively 1.3
and 2.5 times higher than exchange rates
For France , this goes the other way around, the ppp is 0,75 lower than
exchange rate  a difference of 1.7, 2.4 and 3,5 in the cost of living
between France Brazil , Argentina and Bolivia
GDP per capita (2008)
16
$2008
14
at ppp
10
8
6
4
2
Chile
Argentina
Uruguay
Brazil
Paraguay
0
Bolivia
(kUS$)
12
18
Why using Purchasing Power Parities for cross country
comparisons of energy performance
•Let us take 2 factories producing cars : one in France and one in Argentina,
with the same technical performance, i.e. the same energy input by car
produced (in toe or GJ per car)
•The value added of each car is mainly made from salaries (capital costs and
profits also included) , whose relative level across countries are mainly
influenced by the average difference in the cost of living (2.5 times lower for
Argentina)
 With the same technical performance, the energy used per unit of value
added (« energy intensity » for the car industry will be 2.5 times higher in
Argentina than in France with exchange rates but the same at PPP
Primary energy intensity measured at purchasing power parities (ppp)
are more relevant for comparison of energy intensities as they
measure the real level of economic activity and narrow significantly
the differences across regions
Source: Enerdata (IEA accounting for hydro)
Paraguay
Bolivia
Argentina
Chile
at ppp
Brazil
at exchange rate
EU
0,55
0,50
0,45
0,40
0,35
0,30
0,25
0,20
0,15
0,10
0,05
0,00
Uruguay
(koe/$05p)
Primary energy intensity (2008)
20
Primary energy intensity at purchasing power parities (2008)
0,20
at ppp
0,10
0,05
Source: Enerdata (IEA accounting for hydro)
Paraguay
Bolivia
Argentina
Chile
Brazil
EU
0,00
Uruguay
(koe/$05p)
0,15
21
Energy intensities trends: exchange rate versus at
purchasing power parities
Use of PPP increases GDP and, thus, decreases energy intensity of countries
with low cost of living; conversely intensity of rich countries increases (e.g.
Portugal and Japan)PPP affects the ranking of intensities among countries,…
but does not change the trends
Outline
1.
2.
3.
4.
5.
Primary energy intensity
Primary versus final energy intensity
Sectoral intensities
Data required
Annex: issues with monetary values
Overview of macro data and indicators
• Macro-economic data: GDP by sector,
exchange rates
• Demography (population)
• Energy balances data: primary and final
energy consumption by sector : industry,
transport, households, services, et
agriculture
• Degree-days for cspace heating and
climatic corrections (cooling degreedays)
Data
INDICATORS
• Primary intensity*
• Final intensity: total and by
sector*
• Ratio final/primary intensity
Main lessons from macro data and indicators
Good coverage of macro indicators that are calculated from energy balance
data and national accounts, therefore for which there is no problem of data
availability;
The main problems encountered are:
1. Macro economic data in different base years for constant prices (e.g.
case of Chile, Mexico)  need to do additional calculation to
convert in a single base year; an example has been prepared on
Excel for that purpose. (Example conversion_GDP_constant
prices.xlsx);
2. Lack of data on degree days, which limits the possibility of doing
climatic corrections and later to adjust the indicators for differences
in climate.
25
Outline
1.
2.
3.
4.
5.
Primary energy intensity
Primary versus final energy intensity
Sectoral intensities
Data required
Annex: issues with monetary values
Main issues with monetary values
Three main issues may be encountered with monetary indicators
Issues
Response
Lack of data at constant prices
Need of calculation of constant prices based:
• On nominal price and price deflator
• On indicators of volumes
Change of reference year for
constant prices without
retropolation
Need of construction of time series in
constant prices with the same reference year
27
Calculation of economic data at constant prices
Two possibilities :
1.
Data only available at current price: use of deflators (price index)
GDP xx = GDP / DEFL * DEFLxx with:
1.

GDPxx: GDP at constant price of year xx (e.g. 2005);

DEFLxx: deflator of the GDP with xx as base year (= 100 for base year)
(exist deflators by sector or sub sector )
Existence of index of volume or rate of change in volume compared to the
previous year, which measures the increase in the volume of activity:

We start from the GDP (or VA) at current prices for the reference year of
the constant prices (ge 2000) and build the series of constant price year
by year from the rate of change in volume (TCVOLt)
GDPxx (2000)= GDP (2000)
GDPxx (2001)= GDPxx (2000) *(1+TCVOL2001 /100)
GDPxx (2002)= GDPxx (2001) *(1+TCVOL2002 / 100)
………
GDPxx (t)= GDPxx (t-1) *TCVOLt
Before 2000, GDPxx (t-1)= GDPxx (t) /TCVOLt
Calculation of economic data at constant prices with
different reference year with the same reference year
If data series at constant prices are available for different base year of constant
prices (e.g. from 2005 to 2012 at 2005 price and from 2000 to 2005 at 2005
prices), a series with the same constant price (e.g. 2005) can be obtained for the
whole period by calculating the annual variation of the GDP at constant price
(%/yr), i.e. the variation in volume,
Taking into account that the variation in volume is the same whatever the base
year for constant prices, we start from the GDP at constant prices for the most
recent reference year and retropolate the values year by year based on the rate of
change in volume (TCVOLt)
GDPxx (2000)= GDP (2000)
GDPxx (2001)= GDPxx (2000) *(1+TCVOL2001 /100)
GDPxx (2002)= GDPxx (2001) *(1+TCVOL2002 / 100)
………
GDPxx (t)= GDPxx (t-1) *TCVOLt
Before 2000, GDPxx (t-1)= GDPxx (t) /TCVOLt