Skip to main content

Advertisement

SpringerLink
Log in

Modelling useful energy demand system as derived from basic needs in the household sector

  • Original Article
  • Published:
Energy Efficiency Aims and scope Submit manuscript

Abstract

Inter-fuel substitution in the household sector depends on whether their target energy use is similar or not. To account for the effect of end-use application on energy demand, the concept of useful energy is utilized in which energy carriers are grouped according to their end-use applications. Useful energy is assumed as a commodity demanded to satisfy needs. Therefore, it should possess certain characteristics in accordance with the nature of basic needs. These characteristics were investigated through a two-level budgeting system with demographic variables indicating rural and urban households of Iran. The model has been applied to estimate the behavioural parameters such as income and price elasticities of useful energy demand. The estimated values of income and own-price elasticity show that all categories of useful energy are necessities with a relatively inelastic demand. Among them, cooling and non-substitutable electricity has the highest income and own-price elasticity, while lighting and water heating are ranked as the most necessary types of useful energy due to their low-income elasticity. In addition, small values of cross price elasticities support the idea that different types of useful energy are almost independent. Therefore, the results confirm that useful energy demands could be considered as basic needs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. The latest data available for aggregate energy consumption are for the year 2010.

  2. See Bhattacharjee and Reichard (2011) for a recent review and classification of factors affecting household energy demand.

  3. Non-substitutable electricity refers to the remaining electrical appliances that households use.

  4. Model for Analysis of Energy Demand

  5. This term has been utilized by Becker to refer to the outputs of household production function (Becker 1965).

  6. The mentioned conditions and specification of useful energy demand (or in some literature, energy services) are expected to hold where there is no energy poverty.

  7. Linear Expenditure System

  8. Constant Elasticity of Substitution

  9. It is defined as the ratio of end-use energy provided by an end-use device to the final energy consumed.

  10. It is defined as the ratio of provided useful energy to the end-use energy consumed. In household sector, availability of useful energy is generally a measure of energy performance in dwellings.

  11. Classification of end-use energy is identical with that of useful energy.

  12. The relevant data have been calculated by authors based on Statistical Consumer Surveys (SCI). The methodology was explained in Methodology section.

  13. In 2007, electricity was sold to households at an average price of 34.4 Rs/MJ while natural gas was 112 Rs/m3 which is roughly equal to 3 Rs/MJ.

  14. Only data on household size are available. Number of families in household is not known. Hence, all data are expressed in unit of households, not families.

  15. Seemingly Unrelated Regression

  16. Please refer to Eq. (6).

Abbreviations

E:

Expenditure elasticity

L:

Likelihood function

p:

Commodity price

pe:

Price of final energy

U:

Utility

x:

Final energy

y:

Quantity variable of either household size or household’s living area

Z:

Commodity

µ :

Expenditure

Av:

Availability of appliance

Pavg:

Average rate of energy consumption

PF:

Average utilization time

α:

Marginal budget share in LES

β:

Subsistence bundle of commodities

ε:

Useful energy availability

η:

Energy efficiency of appliance

i:

Counter on useful energy

j:

Counter on final energy

k:

Counter on appliance type

n:

Household expenditure decile

o:

Counter on household characteristic (household size or living area)

UD:

Useful energy

EN:

Final energy

AIDS:

Almost ideal demand system

CES:

Constant Elasticity of Substitution

LES:

Linear Expenditure System

MAED:

Model for Analysis of Energy Demand

QAIDS:

Quadratic AIDS

References

  • Anandarajah, G., Kesicki, F. (2010). Global climate change mitigation: what is the role of demand reduction. In: (Proceedings) 11th IAEE European Conference.

  • Attfield, C. L. F. (2005). A time series aggregate demand model with demographic and income distribution indices. UK: University of Bristol.

    Google Scholar 

  • Barnett, W. A., & Serletis, A. (2008). Consumer preferences and demand systems. Journal of Econometrics, 147, 210–224.

    Article  MathSciNet  Google Scholar 

  • Barten, A. P. (1968). Maximum likelihood estimation of a complete system of demand equations. European Economic Review, 1, 7–73.

    Article  Google Scholar 

  • Becker, G. S. (1965). A theory of the allocation of time. The Economic Journal, 75(299), 493–517.

    Article  Google Scholar 

  • Bhattacharjee, S., Reichard, G., (2011). Socio-economic factors affecting individual household energy consumption: a systematic review, proceedings of the ASME 2011 5th International Conference on Energy Sustainability, USA.

  • Bhattacharyya, S C., Timilsina, G R. (2009). Energy demand models for policy formulation: a comparative study of energy demand models, World Bank Policy Research Working paper WPS 4866.

  • Böhringer, C., Rutherford, T.F. (2006). Combining top-down and bottom-up in energy policy analysis: a decomposition approach, ZEW Discussion Paper No. 06-007, Mannheim.

  • Daioglou, V., van Ruijven, B. J., & van Vuuren, D. (2012). Model projections for household energy use in developing countries. Energy, 37, 601–615.

    Article  Google Scholar 

  • Deaton, A., & Muellbauer, J. (1980). An almost ideal demand system. The American Economic Review, 70(3), 312–326.

    Google Scholar 

  • Deaton, A., & Muellbauer, J. (1983). Economics and consumer behavior. United Kingdom: Cambridge University Press.

    Google Scholar 

  • Edgerton, D. L. (1997). Weak separability and the estimation of elasticities in multistage demand. American Journal of Agricultural Economics, 79(1), 62–79.

    Article  Google Scholar 

  • Filippini, M. (2011). Short- and long-run time-of-use price elasticities in Swiss residential electricity demand. Energy Policy, 39(5811), 5817.

    Google Scholar 

  • Fouquet, R. (2013). Long run demand for energy services: the role of economic and technological development, Working Papers 2013-03, BC3.

  • Fullerton, T. M., Jr., Juarez, D. A., & Walke, A. G. (2012). Residential electricity consumption in Seattle. Energy Economics, 34, 1693–1699.

    Article  Google Scholar 

  • Geary, R. C. (1950). A note on ‘A constant utility index of the cost of living’. The Review of Economic Studies, 18(1), 65–66.

    Article  Google Scholar 

  • Gouveia, J. P., Fortes, P., & Seixas, J. (2012). Projections of energy services demand for residential buildings: Insights from a bottom-up methodology. Energy, 47(1), 430–441.

    Article  Google Scholar 

  • Grubler, A., Johansson, T. B., Mundaca, L., Nakicenovic, L., Pachauri, S., Riahi, K. et al. (2012). Chapter 1—Energy primer. In Global energy assessment—toward a sustainable future, Cambridge University Press, Cambridge, UK and New York, NY, USA and the International Institute for Applied Systems Analysis, Laxenburg, Austria, pp. 99–150.

  • Guertin, C., Kumbhakar, S. C., & Duraiappah, A. K. (2003). Determining demand for energy services: Investigating income-driven behaviors. Winnipeg: International Institute for SustainableDevelopment (IISD).

    Google Scholar 

  • Guta, D. D. (2012). Application of an almost ideal demand system (AIDS) to Ethiopian rural residential energy use: panel data evidence. Energy Policy, 50, 528–539.

    Article  Google Scholar 

  • Hafele, W. (1977). On energy demand. 21st general conference of the International Atomic Energy Agency, Vienna, IAEA Bulletin 19:6.

  • IAEA. (2006). Model for Analysis of the Energy Demand (MAED), Users’ manual for version MAED-2. Vienna: International Atomic Energy Agency.

    Google Scholar 

  • Iran Energy Balance Sheet (2010). Power and Energy Planning Department, Ministry of Energy of I.R.IRAN (available in Persian).

  • Iranian Fuel COnservation company (IFCO). Applied information on efficient standards and energy labels. http://ifco.ir/building/standard/standard_inform.asp.

  • Ivanco, M., Karney, B., Waher, K. (2010). Impact of conversion to compact fluorescent lighting, and other energy efficient devices, on greenhouse gas emissions, air pollution. V. Villanyi (Ed.).

  • Lancaster, K. J. (1966). A new approach to consumer theory. The Journal of Political Economy, 74(2), 132–157.

    Article  MathSciNet  Google Scholar 

  • Lula, J., & Antille, A. (2010). Estimation of private consumption functions for Switzerland (pp. 10–16). Trujillo: The Fifteenth World In forum Conference.

    Google Scholar 

  • Magnus, J. R. (1982). Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood. Journal of Econometrics, 19, 239–285.

    Article  MATH  MathSciNet  Google Scholar 

  • Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396.

    Article  Google Scholar 

  • McNeil, M., Letschert, V., de la Rue de Can, S., & Ke, J. (2013). Bottom–Up Energy Analysis System (BUENAS)—an international appliance efficiency policy tool. Energy Efficiency. doi:10.1007/s12053-012-9182-6.

    Google Scholar 

  • Ministry of Industries and Mines (MIM). (2010). Active producers of industrial products. Tehran: Ministry of Industries and Mines (Available in Persian).

    Google Scholar 

  • NIORDC (National Iranian Oil Refining & Distribution Company). (2010). Statistical yearbook. Tehran: Public Relation of National Iranian Oil Refining & Distribution Company (Available in Persian).

    Google Scholar 

  • Pachauri, S. (2007). An energy analysis of household consumption: changing patterns of direct and indirect use in India. India: Springer.

    Google Scholar 

  • Pachauri, S., & Spreng, D. (2003). Energy use and energy access in relation to poverty. CEPE Working Paper Nr. 25. Switzerland: Centre For Energy Policy andEconomics.

    Google Scholar 

  • Pollak, R. A., & Wale, T. J. (1981). Demographic variables in demand analysis. Econometrica, 49, 1533–1551.

    Article  Google Scholar 

  • Samuelson, P. A. (1947). Some implications of linearity. The Review of Economic Studies, 15, 88–90.

    Article  Google Scholar 

  • Schermerhorn, J. R., Hunt, J. G., & Osborn, R. N. (2002). Organizational behavior (8th ed.). Hoboken: John Wiley & Sons, Inc.

    Google Scholar 

  • SCI (Statistical Center of Iran) (2010). Household Expenditure and Income Surveys. Statistical Center of Iran, Tehran. (Available in Persian).

  • Stone, R. (1954). Linear expenditure systems and demand analysis: an application to the pattern of British demand. The Economic Journal, 64(255), 511–527.

    Article  Google Scholar 

  • Swan, L. G., & Ugursal, V. I. (2009). Modeling of end-use energy consumption in the residential sector: a review of modeling techniques. Renewable and Sustainable Energy Reviews, 13, 1819–1835.

    Article  Google Scholar 

  • Thoma, J. (1977). Energy, entropy, and information. Laxenburg: International Institute for Applied Systems Analysis.

    Google Scholar 

  • Tiezzi, S. (2005). The welfare effects and the distributive impact of carbon taxation on Italian households. Energy Policy, 33, 1597–1612.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Mechanical Engineering Department, Sharif University of Technology, P.O. Box 11365-9567, Tehran, Iran

    Zahra A. Barkhordar

  2. Sharif Energy Research Institute (SERI), Sharif University of Technology, P.O. Box 11365-9567, Tehran, Iran

    Yadollah Saboohi

Authors
  1. Zahra A. Barkhordar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yadollah Saboohi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yadollah Saboohi.

Appendix

Appendix

Table 7 Summary of input data for the second stage budgeting model
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Barkhordar, Z.A., Saboohi, Y. Modelling useful energy demand system as derived from basic needs in the household sector. Energy Efficiency 7, 903–921 (2014). https://doi.org/10.1007/s12053-014-9257-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12053-014-9257-7

Keywords

Search

Navigation