GDP and Total Energy Consumption: causality relationship
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Lavrenchuk Valentyna
Taras Shevchenko National University of Kyiv
Researches
of the series “GDP-Total Energy Consumptions” aim at finding causal relationships
between these effects. The results of this article allow to answer the question
about causality direction and understand long- or short-term of this
influence. These conclusions
will allow to affect on realization
energy efficiency policy in any economy sector of the country.
There are main tasks of this research:
1. Estimation of “increasing GDP – total energy consumptions” VAR model;
2. Evaluation of the Granger-causality direction.
Identification of the Granger-causality direction
between GDP and Total Energy Consumption will give an opportunity to estimate
perspective of the energy efficiency technologies.
In case of one-way causality from GDP to Energy
consumptions the energy efficiency policy will not induce expected economic
growth rate. In the other way, in case of one-way causality from Energy
consumption to GDP we can bargain for an increase of a national economy. [4, p.1]
For researching level of energy consumption it’s
necessary to consider modern conditions of Ukrainian fuel and energy complex.
As energy consumption it is necessary to use indexes, such
as:
TENG – total energy consumption;
PTL – fuel consumption;
GAS – natural gas;
ELEC – electricity consumption.
It’s necessary to circumstantiate each impact factor.
For more detailed analysis of causality we propose to split each of the above
factors by source of origin.
It is necessary to analyze consumption of imported
natural gas (GAS (1)) and gas produced domestically (GAS (2)).
Fuel consumption is necessary to estimate the
proportional to the territory of production:
PTL(1) – imported fuel;
PTL(2)– fuel processed in the country.
An important point in the analysis of fuel consumption
can be analysis by use of this energy, namely household expenses or costs of
carriers and farming machines.
The power consumption in pure form for a more detailed
analysis should be divided by source of origin:
ELEC(1) – electricity produced by nuclear power plants;
ELEC(2) – electricity produced by fuel-burning power
plant;
ELEC(3) – electricity produced by hydroelectric power
plant;
ELEC(4) – from alternative sources, including small hydroelectric
power plant.
As an analysis of economic growth should consider GDP
per capita - GDP.
The first step in implementing the algorithm of this
model should be the test of time series for stationarity, to exclude further
the possibility of building a false regression. Given the specific problems of
information-statistical nature, the analysis associated with processing small
sample volume. So, to test the series for stationarity should be preferred KPSS
test, rather than expanded Dickey–Fuller test.
Using VAR models allow us to evaluate
reaction parameters on the energy shock of change factors, and to draw
conclusions about errors, which each factor brings in forecast.
To
consider the causality problem between GDP and TEND use Granger approach. Its
essence is that TEND considered causal in relation to GDP, if the other
conditions of equal importance GDP may be a better prediction using past values
TEND than without them.
,
,
- constants,
- uncorrelated
residuals.
So, the conclusions from the model can be drawn from
these points [1, p.700]:
If are statistically
different from zero as a group and
are not statistically different from zero as a group,
then unidirectional causality from TEND to GDP is indicated.
If are statistically
different from zero as a group,
- are not statistically different from zero as a group,
then unidirectional causality from GDP to TEND is indicated.
If ,
,
and
are statistically
significantly different from zero in both regression, then we can state fact of
feedback or bilateral causality.
If
and
are not statistically
significantly different from zero in both regression, then we say that GDP and TEND
are independent.
Accordingly, this theory can be extended to the full
range of indicators of energy consumptions.
Literature:
1.
Damodar N. Gujarati - Basic Econometrics, 4 Ed. McGraw-Hill. 2003-1003 p.
2.
Ghosh,
S. Electricity supply, employment and real GDP in India: evidence from
cointegration and Granger-causality tests. Energy Policy ¹37. 2009 - p.
2926-2929.
3.
J.
Asafu-Adjaye. The relationship between energy consumption, energy prices and
economic growth: times series evidence from Asian developing countries. Energy
Economics ¹22. 2000 - p. 615-625.
4.
Sit
B.M. Dynamic model “Electricity consumption – GDP” for republic of Moldova.
Problems of the regional energetics, ¹ 1. , 2007 – p. 1-8.
5.
The
association between unexpected changes in electricity volume and GDP. IPAT
report. 2007 - 29 p.