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Decomposition Analysis of Aggregate Energy Intensity Changes in Tunisia over the Period 1980–2007

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Abstract

The aim of this paper is to investigate the main factors that have contributed to the decline in aggregate energy intensity of the Tunisian economy, during the period 1980–2007. Using the Logarithmic Mean Division Index (LMDI) decomposition method, we decompose the total changes in energy intensity into inter-fuel substitution effects, technological effects, and structural effects. The decomposition analysis is carried out at two levels of sectoral disaggregation (3 sectors and 13 sub-sectors) and uses three energy sources: petroleum, natural gas, and electricity. Our results show that the main contributor to the decline in energy intensity of the Tunisian economy throughout the period studied is the technological effect. This result was confirmed when we decomposed the energy intensity changes in the industrial and service sectors. On the other hand, the inter-fuel substitution effect contributed to increasing energy intensity, but without affecting its general downward trend. Finally, for the structural effects, we observed a significant mutual effect of cancellation at sector and sub-sector levels.

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Notes

  1. Two articles have already studied the interactions between energy consumption, economic growth, and pollutant emissions for the Tunisian economy. Belloumi [11] analyzes the link between energy consumption and GDP, while Fodha and Zaghdoud [19] investigate the relationship between economic growth and pollutant emissions. Nevertheless, they do not explain the structural determinants of the changes in energy consumption.

  2. See Boyd et al. [13], Sato [37], and Ang and Choi [4] for more details about the different types of discrete approximation.

  3. See Ang [2] and Ang et al. [7] for more details on the form and the relationship between the additive and the multiplicative values of the IDA.

  4. The LMDI approach has been adopted by the Department of Energy in the United States of America to construct an aggregate energy efficiency index at the national level.

  5. In our study, we only use macroeconomic variables and a high level of sector aggregation (no firm-level data); hence, our data set does not contain any zero values. Furthermore, there is no residual term in our results, which means that our decomposition method satisfies the factor reversal test (Ang et al. [8]).

  6. On July 1995, Tunisia was the first Mediterranean country to sign an Association Agreement with the European Union. This replaced the co-operation agreement of 1976 and cancelled the advantages previously accorded to Tunisia. The new agreement anticipated the creation of a free trade area over a period of 12 years and committed Tunisia on the path to greater co-operation at technological, economic, social, and financial levels and in professional training.

  7. Due to data limitations, final energy consumption is used as a proxy for total energy consumption (final energy consumption and energy used by the energy sector, including deliveries and transformation).

  8. In 1988, the ECA became the National Agency for Energy Conservation (NAEC), and since 2002, it has been part of the Tunisian Ministry of Industry.

  9. In the current study, the technological effect is measured using energy intensity changes at the sub-sector level, since several studies assume that the improvements in sub-sector intensity (i.e., the reduced energy use per unit of economic activity) are the result of technological advances, e.g., Huang [22], Ma and Stern [29], and Metcalf [32].

  10. From a pure theoretical point of view, as the level of disaggregation becomes finer, the proportion of the change in energy intensity explained by structural shift rises (Ang [3]; Petchey [36]). However, in practice, the choice of the level of the sector disaggregation is often limited by the data availability. This is also the case for Tunisia where the data are only available for this very specific sector disaggregation (3 sectors and 13 sub-sectors). Moreover, following the Arab spring revolution (2010), the availability and the robustness of such energy consumption data are likely to be less dependable. Nevertheless, our data set (28 years, 13 sub-sectors) is in line with (and even more detailed than) the majority of the articles that use the LMDI methodology to explain trends in energy consumption.

  11. For these reasons, our disaggregation of the energy consumption does not generate any bias in the results.

  12. The quality of the various energy carriers refers to the difference in economic productivity of fuels and electricity. In fact, there are several definitions and measures of energy quality. The concept that we use in this paper is the different marginal productivity of fuels (Cleveland et al. [16]).

  13. The IMP, started in 2003 and funded by a grant from the European Union, is part of the policy to support the modernization process of the industry to prepare the Tunisian economy for integration into the free trade zone, provided by the association agreement with the European Union of 17 July 1995 and whose final establishment was implemented in 2008.

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Authors and Affiliations

  1. Paris School of Economics, University Paris 1 Pantheon-Sorbonne, 106-112 Boulevard de l’Hopital, 75013, Paris, France

    Mouez Fodha

  2. Department of Economics, College of Business Administration, King Faisal University, P.O.Box 400, Al Hassa, Kingdom of Saudi Arabia

    Oussama Zaghdoud

Authors
  1. Mouez Fodha
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  2. Oussama Zaghdoud
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Correspondence to Mouez Fodha.

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Fodha, M., Zaghdoud, O. Decomposition Analysis of Aggregate Energy Intensity Changes in Tunisia over the Period 1980–2007. Environ Model Assess 20, 509–520 (2015). https://doi.org/10.1007/s10666-015-9460-8

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