IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v34y2012i5p1475-1483.html
   My bibliography  Save this article

Accounting for household heterogeneity in general equilibrium economic growth models

Author

Listed:
  • Melnikov, N.B.
  • O'Neill, B.C.
  • Dalton, M.G.

Abstract

We describe and evaluate a new method of aggregating heterogeneous households that allows for the representation of changing demographic composition in a multi-sector economic growth model. The method is based on a utility and labor supply calibration that takes into account time variations in demographic characteristics of the population. We test the method using the Population-Environment-Technology (PET) model by comparing energy and emissions projections employing the aggregate representation of households to projections representing different household types explicitly. Results show that the difference between the two approaches in terms of total demand for energy and consumption goods is negligible for a wide range of model parameters. Our approach allows the effects of population aging, urbanization, and other forms of compositional change on energy demand and CO2 emissions to be estimated and compared in a computationally manageable manner using a representative household under assumptions and functional forms that are standard in economic growth models.

Suggested Citation

  • Melnikov, N.B. & O'Neill, B.C. & Dalton, M.G., 2012. "Accounting for household heterogeneity in general equilibrium economic growth models," Energy Economics, Elsevier, vol. 34(5), pages 1475-1483.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1475-1483
    DOI: 10.1016/j.eneco.2012.06.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988312001168
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Creedy, John & Guest, Ross, 2008. "Population ageing and intertemporal consumption: Representative agent versus social planner," Economic Modelling, Elsevier, vol. 25(3), pages 485-498, May.
    2. Dalton, Michael & O'Neill, Brian & Prskawetz, Alexia & Jiang, Leiwen & Pitkin, John, 2008. "Population aging and future carbon emissions in the United States," Energy Economics, Elsevier, vol. 30(2), pages 642-675, March.
    3. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-1185, July.
    4. Fehr, Hans & Jokisch, Sabine & Kotlikoff, Laurence J., 2008. "Fertility, mortality and the developed world's demographic transition," Journal of Policy Modeling, Elsevier, vol. 30(3), pages 455-473.
    5. Kehoe, Timothy J., 1991. "Computation and multiplicity of equilibria," Handbook of Mathematical Economics,in: W. Hildenbrand & H. Sonnenschein (ed.), Handbook of Mathematical Economics, edition 1, volume 4, chapter 38, pages 2049-2144 Elsevier.
    6. Manne, Alan & Mendelsohn, Robert & Richels, Richard, 1995. "MERGE : A model for evaluating regional and global effects of GHG reduction policies," Energy Policy, Elsevier, vol. 23(1), pages 17-34, January.
    7. Sebastian Rausch & Thomas Rutherford, 2010. "Computation of Equilibria in OLG Models with Many Heterogeneous Households," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 171-189, August.
    8. Jaume Ventura & Francesco Caselli, 2000. "A Representative Consumer Theory of Distribution," American Economic Review, American Economic Association, vol. 90(4), pages 909-926, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. van Ruijven, Bas J. & O’Neill, Brian C. & Chateau, Jean, 2015. "Methods for including income distribution in global CGE models for long-term climate change research," Energy Economics, Elsevier, vol. 51(C), pages 530-543.
    2. Volker Krey, 2014. "Global energy-climate scenarios and models: a review," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(4), pages 363-383, July.

    More about this item

    Keywords

    Computable general equilibrium; Demographic heterogeneity; Consumer preferences; Labor supply; Aggregation; Energy demand;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1475-1483. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eneco .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.