# Presentation: 057596

## Energy Modeling Techniques

- Zia Haq
- Energy Information Administration
- South Asia Regional Initiative – Energy Workshop
- Pokhara, Nepal
- January 2004

## Income Growth and Energy Demand - Bangladesh

- 1990

- 1980

- 2000

- 1971

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  Problems with the reliability of the data are there for all countries.
  Bangladesh data has significant uncertainty since Bangladesh’s war of independence occurred in 1971 (the beginning of this series) and much of the civil authority to collect and publish the data was in a state of flux for several years after that.
  Bangladesh’s energy consumption trend can be classified into two periods: civil war and its aftermath 1971 – 1980, and stability 1980-2000.

## Income Growth and Energy Demand - Nepal

- 1990

- 1980

- 2000

- 1971

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  Problems with the reliability of the data are there for all countries.
  Nepal’s energy consumption shows a period of instability from 1971 through 1990 and then relatively stable growth from 1990 through 2000.

## Income Growth and Energy Demand – Sri Lanka

- 1990

- 1980

- 2000

- 1971

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  Problems with the reliability of the data are there for all countries.
  In Sri Lanka the GDP per capita and the energy consumption are both higher than in for Bangladesh or Nepal.  However, the correlation between GDP and energy consumption is not as good as it is for the other SARI countries.  This is evident in the R2 data.

## Income Growth and Energy Demand – India

- 1990

- 1980

- 2000

- 1971

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  Problems with the reliability of the data are there for all countries.
  India has excellent correlation between energy consumption and GDP.  The economy shows stable performance through the entire dataset from 1971 through 2000.
  The only concern in this case is the negative correlation in the equation, indicating a potential for flattening out of the growth rate, or a downward curved graph, or some kind of asymptotic behavior.  One can look at the dataset from 1980 onward to derive different correlation factors.
  What contributes to India’s historical performance as contrasted to the unstable performances of Bangladesh, Nepal, and Sri Lanka is worth investigating.  Possible causes:  Size of economy and its inherent diversity, technology sector growth, skilled manpower, low cost labor, political stability, ability to attract FDI.

## Income Growth and Energy Demand – Pakistan

- 1990

- 1980

- 2000

- 1971

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  Problems with the reliability of the data are there for all countries.
  I have included Pakistan even though it is not a part of SARI because it provides some interesting observations.  Like India, Pakistan has an excellent correlation between energy consumption and GDP.  The economy shows stable performance through the entire dataset from 1971 through 2000.
  Unlike India, the correlation for the first term is positive, indicating an upward sloping curve, and the potential for continued future growth.  Both India and Pakistan show what can be achieved in terms of economic growth.
  What contributes to India and Pakistan’s historical performance as contrasted to the performances of Bangladesh, Nepal, and Sri Lanka is worth investigating.  Possible causes:  Size of economy and its inherent diversity, technology sector growth, skilled manpower, low cost labor, political stability, ability to attract FDI.

## Income Growth and Energy Demand – Composite

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  The composite puts these five countries on the same graph to allow comparisons.  This is a log-log graph.  One can see the nearly identical performances of India and Pakistan.
  We could not obtain comparable data on Bhutan and Maldives.  A discussion on where they might lie in relationship to these countries would also be interesting.
  These are GDP per capita and energy consumption per capita, therefore, this representation is supposed to take out the effects of large versus small economies.

## Income Growth and Petroleum Demand – Composite

**Notes:**
  Per capita energy demand and per capita income are well correlated for these Asian countries.  A similar correlation can be seen for capita oil demand and income.
  The per capita petroleum consumption measures primarily the growth of the transportation sector.  Other sectors that contribute to petroleum consumption are: industrial, residential, and commercial.
  There are some interesting differences between per capita petroleum consumption and per capita energy consumption.

## Demand Response to Oil Price Changes

**Oil Price (1992$/barrel)**

**Oil Demand (tons/person)**

- 3.0

- 3.5

- 4.0

- 4.5

- $0

- 2.5

- $20

- $30

- $40

- $50

- $10

- symmetric

- asymmetric

- Year 3

- Year 4

- Year 2

- Year 1

- Year 1

- Year 2

- Year 3

- Year 4

**Notes:**
  Energy demand (including oil demand) often does not have symmetric responses to price changes.
 One reasons for imperfect price reversibility is because energy use is highly related to the capital stock of energy using equipment.  An example of the capital stock issue: older power plants running on imported oil are not going to switch fuels because of short-run increases in the price of oil.
  Similarly, in the transportation sector, automobiles in South Asian markets are already very fuel efficient and if the price of imported oil decreases they are not going to be replaced very quickly.  However, reduced oil prices may encourage people to drive more pushing energy consumption up.
  Other reasons for asymmetric behaviour can be due to distortionary effects of price controls and taxes, alternative fuel mixes, imperfect market behavior such as price gouging or hording, the need to use energy regardless of cost (discretionary versus compulsory need for energy), bad or incomplete data.
  Since data on delivered price of oil in these countries was not available, this is being shown as a representative graph.
  Energy demand can also be imperfectly reversible with changes in income.  Possible explanations include: some sectors may expand more strongly than others when the economy grows and these sectors may have different energy intensities, urbanization may continue even with declining income requiring more commercial fuels.
  This asymmetric behavior makes modeling of energy use and demand more complex.

## Demand Response to Income Growth and Decline

**Oil Demand (tons/person)**

**Per-capita Income**

- $500

- $1,000

- $1,500

- $2,000

- 0

- $0

- 2.0

- 3.0

- 4.0

- 5.0

- 1.0

- symmetric

- asymmetric

- Year 3

- Year 4

- Year 2

- Year 1

- Year 1

- Year 2

- Year 3

- Year 4

**Notes:**
  Energy demand (including oil demand) often does not have symmetric responses to price changes.
 One reasons for imperfect price reversibility is because energy use is highly related to the capital stock of energy using equipment.  An example of the capital stock issue: older power plants running on imported oil are not going to switch fuels because of short-run increases in the price of oil.
  Similarly, in the transportation sector, automobiles in South Asian markets are already very fuel efficient and if the price of imported oil decreases they are not going to be replaced very quickly.  However, reduced oil prices may encourage people to drive more pushing energy consumption up.
  Other reasons for asymmetric behaviour can be due to distortionary effects of price controls and taxes, alternative fuel mixes, imperfect market behavior such as price gouging or hording, the need to use energy regardless of cost (discretionary versus compulsory need for energy), bad or incomplete data.
  Since data on delivered price of oil in these countries was not available, this is being shown as a representative graph.
  Energy demand can also be imperfectly reversible with changes in income.  Possible explanations include: some sectors may expand more strongly than others when the economy grows and these sectors may have different energy intensities, urbanization may continue even with declining income requiring more commercial fuels.
  This asymmetric behavior makes modeling of energy use and demand more complex.
 Rates of growth differ widely among these countries.
  Income growth rates of 5% or greater: South Korea, Singapore, Malaysia, Indonesia, Thailand, and China.
  Negative income growth rates: Zaire, Angola, Zimbabwe, Cote d’Ivoire, Haiti, Saudi Arabia, Nigeria, Jamaica, and Venezuela.
  Notice that richness of natural resources and export of these resources do not necessarily guarantee income growth rates (e.g. Angola, Saudi Arabia, Nigeria, Venezuela).
  Some countries with relatively little indigenous resources and heavy export reliance experienced high sustained income growth rates (South Korea, Singapore).
  This scatter among countries makes modeling energy demand more complicated.  One approach to solve this problem is to divide the countries into groups: oil exporters, income growers, and others.

## Simple Model Specifications

- Demand as a function of current income only:Dt = k + a*Yt
- Demand as a function of current and past income, weights of past income decline geometrically:Dt = k + a*Yt + a*b*Yt-1 + a*b2*Yt-1 +...
- This is equivalent to: Dt = k + a*Yt + b*Dt-1
- b is a lagged-demand coefficient with a value between 0 and 1 to measure speed of adjustment to change in income
- Demand as a function of income, price, and lagged demand: Dt = k + a*Pt + b*Yt + c*Dt-1

**Notes:**
  Dt = Log per-capita demand in year t
  Yt = Log per-capita GDP in year t
  Pt = Log real price of oil in year t

## Complex Model Specification

- Dt = k + a*Pt + a*b*Pt-1 + a*b2*Pt-2 + ... + c*e*Yt-1 + c*e2*Yt-2 + ...
- This formulation allows the speed of demand adjustment to changes in price to be different from the speed of demand adjustment to changes in income
- More complicated demand specifications can account for imperfect price reversibility and imperfect income reversibility

## Results for Specific Group of Countries

- Non-OECD income growers: 14 countries with steady growth in average annual per-capita income of over 2%/year over 1971-1997
- Excludes China and Indonesia
- Results of analysis
- Energy demand Dt = k - 0.03*Pt + 0.24*Yt + 0.80*Dt-1
- Oil demand Dt = k – 0.02*Pt + 0.23*Yt + 0.76*Dt-1
- Demand adjusts faster to income changes than price changes
- An important variable is non-transportation oil use – which has been estimated to be about 67% of total oil demand for non-OECD countries
- Non-transportation oil use can be cut back much more rapidly if income declines, transportation sector is entirely dependant on oil

**Notes:**
14 countries are (in order of growth rates): South Korea, Thailand, Malaysia, Tunisia, Syria, India, Sri Lanka, Egypt, Colombia, Israel, Singapore, Malta, Morocco, and Bangladesh.
  China excluded due to size and Indonesia categorized as an “oil exporting country”.

## Motorization and Income

**Source:** World Bank

-   Motorization is highly correlated with income
-   Differences in land use can lead to different levels, but not different paths, of motorization
-   Severe constraint, as in Singapore and Hong Kong, is the only way to limit motorization

## Bangladesh Petroleum Demand Model - I

- Bangladesh variables
- Demand = total annual average petroleum demand (thousand barrels/day)
- GDP = real GDP (billion Taka, 1985 basis)
- Price = real oil price (US$/barrel)
- Demand = 3.675 +0.0804*GDP – 0.412*Price

**Forecast**

**Predicted**

**Actual**

**Demand = 3.675 + 0.0804 ******** GDP - 0.412 ******** Price**
**R****2**** = 0.929 **

## Bangladesh Petroleum Demand Model - II

- Bangladesh variables
- Demand = total annual average petroleum demand (thousand barrels/day)
- GDP = real GDP (billion Taka, 1985 basis)
- Price = real oil price (US$/barrel)
- Demandt = 12.22 +0.013*GDP – 0.747*Price + 0.806*Demandt-1

**Forecast**

**Predicted**

**Actual**

**Demand = 3.675 + 0.0804*GDP – 0.747*Price + 0.806*Demand(t-1)**
**R****2**** = 0.973 **

## Philippine Petroleum Demand Model

**Variables:**
- PDCAP = Philippine petroleum demand per capita
- YCAP = Philippine real GDP per capita
- RPOIL = Philippine real oil price
- UPOPSH = Philippine urban population share
- TIME = Integer trend variable
**Coefficients:** B0, B1, B2, B3, B4
**Model 1 (Linear)**
- PDCAP = B0 + B1*YCAP + B2*RPOIL + B3*UPOPSH + B4*TIME
**Model 2 (log-linear)**
- PDCAP = exp(B0 + B1*log(YCAP) + B2*log(RPOIL) + B3*log(UPOPSH) + B4*TIME)

| Coefficients | Model 1 | Model 2 |
| --- | --- | --- |
| B0 | -0.0251 | -6.028 |
| B1 | 7.649E-04 | 3.257 |
| B2 | 1.381E-04 | -0.226 |
| B3 | 0.0712 | 5.854 |
| B4 | -6.842E-04 | -0.159 |

## Philippine Petroleum Demand History

**0.0000 **

**0.0010 **

**0.0020 **

**0.0030 **

**0.0040 **

**0.0050 **

**0.0060 **

**0.0070 **

- Barrels per Person-Day

**1975**

**1977**

**1979**

**1981**

**1983**

**1985**

**1987**

**1989**

**1991**

**1993**

**1995**

**Actual**

**Pred.**