GDP and Total Energy Consumption: causality relationship

Экономические науки/8. Математические методы в экономике

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 №37. 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 №22. 2000 - p. 615-625.

4. Sit B.M. Dynamic model “Electricity consumption – GDP” for republic of Moldova. Problems of the regional energetics, № 1. , 2007 – p. 1-8.

5. The association between unexpected changes in electricity volume and GDP. IPAT report. 2007 - 29 p.