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Energy modeling in developing countries

Jean-Guy Devezeaux de Lavergne



This paper describes some of the features of developing countries that are relevant to energy modeling, provides an overview of what is meant by energy modeling, summarizes the features of different types of demand, supply, and global models, and suggests ways to improve the design and use of these models.


The energy sector plays several important roles in the economic activity of developing countries. Energy commodities are an input into the production of goods and services. Energy is a final consumption good that provides cooking, transportation, and other services. The energy sector also contributes to GDP and affects trade balances and the balance of payments. Therefore, there is great interest in modeling energy demand, energy supply, and energy-economy interactions.

Relevant Characteristics of Developing Countries

Developing countries share a number of economic and energy characteristics that affect energy modeling. Economic traits include

· Rapid population growth and low educational standards,

· High degrees of central planning,

· Regulated and constrained domestic markets,

· Significant traditional (agricultural and artisanal) sectors,

· Narrowly specialized economic structures and production,

· Constrained levels of capital and investment, and

· Weak currencies.

Energy characteristics shared by most developing countries include a lack of understanding of the concepts of energy planning, a scarcity of reliable long-term statistical data, and the importance of noncommercial energy (more than 90% in many developing countries). Despite these similarities, there are sufficient differences among developing countries to argue against the use of a single multicountry model. There are differences in the level of development, technical know-how, geographic size, and degree of openness of the economy. As well, the majority of energy-importing countries face different issues than the energy-exporting countries, and indigenous energy supplies vary among developing nations. These economic and energy features must be taken into account by energy models.

Energy Modeling

A model is a set of equations that represents the real world. Although both the data and the theory underlying the model may be imperfect, models are important tools. They can be used to plan and analyze the economic and energy impacts of policies and external events and to assess competing technologies that supply energy. Energy models are either hierarchical (open-loop) or global (closed-loop). Open-loop models use economic indicators as exogenous variables to define energy demand but do not include feedback from the energy sector to the rest of the economy. In contrast, closed-loop models consider the two-way interaction between energy and economic variables. The level of economic activity influences energy demand, which in turn affects the economy.

Hierarchical Demand Models

One-sector models use ratio analysis (energy demand per unit of output) and statistical time-series analysis to determine sectoral energy demand. This approach is simple, but this simplicity is also a limitation because the models consider neither substitutions among various energy forms, nor changes in the structure of the economy.

Multisector models overcome some of these problems. They distinguish between the traditional and modern sectors (for example, Parikh's model of India-Parikh 1976; Parikh and Srinivasan 1977), among several economic sectors (for example, Resources for the Future), and among sectors and end uses of energy (for example, the MEDEE model-Modele d'evolution de la demande d'energie). All of these approaches are useful because they are relatively simple to develop and understand, and they provide a better understanding of the energy system than one-sector models. But they are not without limitations. They ignore price effects, lack a macroeconomic forecasting framework, and do not provide sufficient treatment of inertias and time lags. One way to enhance the macroeconomic coherence of open-loop models is to use input-output (IO) tables. The World Bank's MSEDM (Minimum Standard Energy Demand Model), for example, uses 10 tables to convert fine] demand into gross output and demand for various energy forms.

Hierarchical Supply Model.

Linear programing models are the oldest optimization models. They were used initially to develop least-cost investment plans in the power sector (for example, the WASP-Wein Automatic System Planning Package-dynamic linear program). More recently, the models have been combined with IO tables to compute alternative and minimum-cost investment plans for the energy sector as a whole. Two limitations of these models are that the data used are more technological than economic and that IO tables embody fixed technical coefficients that must be (but are seldom) updated regularly.

Global Models

Global models of supply and demand incorporate feedback from the energy sector (particularly price effects) into the macroeconomy. Global models of supply can be used to assess the price at which a given energy technology becomes feasible and to determine the impact of changes in energy prices on energy supply industries and on various macroeconomic indicators. Global models of demand (for example, Mukherjee's (1981) energy-economy model) combine demand functions with macroeconomic production functions to trace the effects of exogenous changes (for example, energy prices) on energy demand and economic variables (for example, capacity utilization, aggregate prices, and domestic energy prices). A feedback loop is used to start the next iteration, which determines the impact of energy prices on energy demand and the economy. The lack of an integrated energy demand-supply block, especially with regard to investment requirements, is the main limitation of these models. An extension of Mukherjee's model (SIMA, Simulation of Macroeconomic Scenarios to Assess Energy Demand) was an early attempt to build an integrated supply-demand tool.

Suggestions for Further Research

These models can be adapted for use in most developing countries. To enhance the applicability of the models, several things are needed:

· Better data collection because lack of data is the main problem in energy modeling,

· Improvements in the structure of demand models to include additional price variables, the traditional (noncommercial) sector, and emerging types of energy commodities,

· Use of a coherent set of exogenous values,

· Improvements in the models to include monetary and financial variables (for example, interest and exchange rates), and

· Expansion of the supply models to include noncommercial and renewable energy and the impact that the use of these forms of energy has on the environment.