IDEAS home Printed from https://ideas.repec.org/a/ags/gewipr/259263.html
   My bibliography  Save this article

Isoelastische und aus einer Symmetrie Generalized McFadden- Gewinnfunktion abgeleitete Angebotssysteme: Ein Vergleich

Author

Listed:
  • Grethe, H.
  • Weber, G.

Abstract

No abstract is available for this item.

Suggested Citation

  • Grethe, H. & Weber, G., 2006. "Isoelastische und aus einer Symmetrie Generalized McFadden- Gewinnfunktion abgeleitete Angebotssysteme: Ein Vergleich," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 41, March.
  • Handle: RePEc:ags:gewipr:259263
    DOI: 10.22004/ag.econ.259263
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/259263/files/Bd41Nr20.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.259263?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
    ---><---

    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.
    2. Wahl, Olaf & Weber, Gerald & Frohberg, Klaus, 2000. "Documentation Of The Central And Eastern European Countries Agricultural Simulation Model (Ceec-Asim Version 1.0)," IAMO Discussion Papers 14942, Institute of Agricultural Development in Transition Economies (IAMO).
    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. Weber, Gerald, 2003. "Russia's and Kazakhstan's agro-food sectors under liberalized agricultural trade: a case for national product differentiation," Economic Systems, Elsevier, vol. 27(4), pages 391-413, December.
    2. 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.
    3. Christopher F Baum & Teresa Linz, 2009. "Evaluating concavity for production and cost functions," Stata Journal, StataCorp LP, vol. 9(1), pages 161-165, March.
    4. 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.
    5. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    6. Frédéric Reynès, 2011. "The cobb-douglas function as an approximation of other functions," SciencePo Working papers Main hal-01069515, HAL.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Tsionas, Mike G., 2020. "Quantile Stochastic Frontiers," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1177-1184.
    20. Hossain, A K M Nurul & Serletis, Apostolos, 2020. "Technical change in U.S. industries," Economic Modelling, Elsevier, vol. 91(C), pages 579-600.

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    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:ags:gewipr:259263. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/gewisea.html .

    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.