IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v15y1990i3p345-362.html
   My bibliography  Save this article

3.4. Set of models

Author

Listed:
  • Boyd, Gale
  • Fox, John
  • Hanson, Donald

Abstract

The use of disparate and detailed engineering and economic models is often necessary for environmental policy analysis and forecasting. However, to conduct consistent forecasting and policy analysis over all economic sectors these disparate models must be coordinated into a consistent model set. One approach to such a modeling effort is illustrated by the NAPAP Integrated Model Set, a collection of engineering, emissions-forecasting and energy-market models that is driven by and interacts with other energy-market and economic models.

Suggested Citation

  • Boyd, Gale & Fox, John & Hanson, Donald, 1990. "3.4. Set of models," Energy, Elsevier, vol. 15(3), pages 345-362.
    • Handle: RePEc:eee:energy:v:15:y:1990:i:3:p:345-362
    DOI: 10.1016/0360-5442(90)90095-J
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/036054429090095J
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/0360-5442(90)90095-J?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Diewert, Walter E & Wales, Terence J, 1987. "Flexible Functional Forms and Global Curvature Conditions," Econometrica, Econometric Society, vol. 55(1), pages 43-68, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barnett, William A. & Erwin Diewert, W. & Zellner, Arnold, 2011. "Introduction to measurement with theory," Journal of Econometrics, Elsevier, vol. 161(1), pages 1-5, March.
    2. Christopher F Baum & Teresa Linz, 2009. "Evaluating concavity for production and cost functions," Stata Journal, StataCorp LP, vol. 9(1), pages 161-165, March.
    3. Kevin J. Fox & Ulrich Kohli & Alice Shiu, 2010. "Trade Agreements and Trade Opportunities: A Flexible Approach for Modeling Australian Export and Import Elasticities," Review of International Economics, Wiley Blackwell, vol. 18(3), pages 513-530, August.
    4. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    5. Frédéric Reynès, 2011. "The cobb-douglas function as an approximation of other functions," SciencePo Working papers Main hal-01069515, HAL.
    6. W. Erwin Diewert & Robert C. Feenstra, 2021. "Estimating the Benefits of New Products," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 437-473, National Bureau of Economic Research, Inc.
    7. Bournakis, Ioannis & Tsionas, Mike G., 2023. "A Non-Parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," MPRA Paper 118100, University Library of Munich, Germany.
    8. Brox, James A. & Fader, Christina, 1996. "Production elasticity differences between just-in-time and non-just-in-time users in the automotive parts industry," The North American Journal of Economics and Finance, Elsevier, vol. 7(1), pages 77-90.
    9. Zhang, Yi & Ji, Qiang & Fan, Ying, 2018. "The price and income elasticity of China's natural gas demand: A multi-sectoral perspective," Energy Policy, Elsevier, vol. 113(C), pages 332-341.
    10. Caroline Khan & Mike G. Tsionas, 2021. "Constraints in models of production and cost via slack-based measures," Empirical Economics, Springer, vol. 61(6), pages 3347-3374, December.
    11. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
    12. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
    13. Denis Conniffe, 2006. "Indirect addilog translation of indirect utility functions," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1388-1397, November.
    14. Michalek, J., 1990. "Estimation of technological progress on the base of flexible cost function," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 26.
    15. Diewert, W, Erwin & Feenstra, Robert, 2017. "Estimating the Benefits and Costs of New and Disappearing Products," Microeconomics.ca working papers tina_marandola-2017-12, Vancouver School of Economics, revised 19 Dec 2017.
    16. Piyu Yue, 1991. "A microeconomic approach to estimating demand: the asymptotically ideal model," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 36-51.
    17. Guenter Lang, 2002. "Innovative Slowdown, Productivity Reversal? - Estimating the Impact of R&D on Technological Change," Discussion Paper Series 218, Universitaet Augsburg, Institute for Economics.
    18. Tsionas, Mike G., 2020. "Quantile Stochastic Frontiers," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1177-1184.
    19. Hossain, A K M Nurul & Serletis, Apostolos, 2020. "Technical change in U.S. industries," Economic Modelling, Elsevier, vol. 91(C), pages 579-600.
    20. Hoy, Kyle A. & Wrenn, Douglas H., 2018. "Unconventional energy, taxation, and interstate welfare: An analysis of Pennsylvania's severance tax policy," Energy Economics, Elsevier, vol. 73(C), pages 53-65.

    More about this item

    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:energy:v:15:y:1990:i:3:p:345-362. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.