IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v15y2008i5p405-409.html
   My bibliography  Save this article

Maintaining parameter invariance in seemingly unrelated regressions estimation

Author

Listed:
  • Jay Lillywhite
  • Paul Preckel
  • James Eales

Abstract

Seemingly unrelated regressions (SUR) is an important estimation methodology in demand analysis. While possessing qualities that make it attractive to applied demand analysts, the SUR estimation technique poses several difficulties, including the lack of parameter invariance in some instances e.g. estimation of consumer demand systems with micro-level data. When data includes zero consumption, corrections used to account for censoring may result in different parameter estimates when different share equations are dropped for estimation. This article proposes an alternative estimation objective which results in invariant parameter estimates when imposing adding-up by dropping equations.

Suggested Citation

  • Jay Lillywhite & Paul Preckel & James Eales, 2008. "Maintaining parameter invariance in seemingly unrelated regressions estimation," Applied Economics Letters, Taylor & Francis Journals, vol. 15(5), pages 405-409.
    • Handle: RePEc:taf:apeclt:v:15:y:2008:i:5:p:405-409
    DOI: 10.1080/13504850600706156
    as

    Download full text from publisher

    File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/13504850600706156&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504850600706156?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. Barten, A. P., 1969. "Maximum likelihood estimation of a complete system of demand equations," European Economic Review, Elsevier, vol. 1(1), pages 7-73.
    2. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
    3. BARTEN, Anton P., 1969. "Maximum likelihood estimation of a complete system of demand equations," LIDAM Reprints CORE 34, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Albert J. Reed & J. William Levedahl & Charles Hallahan, 2005. "The Generalized Composite Commodity Theorem and Food Demand Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(1), pages 28-37.
    5. Steven T. Yen & Biing-Hwan Lin & David M. Smallwood, 2003. "Quasi- and Simulated-Likelihood Approaches to Censored Demand Systems: Food Consumption by Food Stamp Recipients in the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 458-478.
    6. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-371, July.
    7. Chavas, Jean-Paul & Segerson, Kathleen, 1987. "Stochastic specification and estimation of share equation systems," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 337-358, July.
    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. Okrent, Abigail M. & Alston, Julian M., 2011. "Demand for Food in the United States: A Review of Literature, Evaluation of Previous Estimates, and Presentation of New Estimates of Demand," Monographs, University of California, Davis, Giannini Foundation, number 251908, December.
    2. Fezzi, Carlo & Bateman, Ian J., 2009. "Structural Agricultural Land Use Modelling," 2009 Conference, August 16-22, 2009, Beijing, China 51423, International Association of Agricultural Economists.
    3. Meyerhoefer, Chad D. & Ranney, Christine K. & Sahn, David E., 2003. "Consistent Estimation Of Longitudinal Censored Demand Systems: An Application To Transition Country Data," Working Papers 127252, Cornell University, Department of Applied Economics and Management.
    4. Tafere, Kibrom & Taffesse, Alemayehu Seyoum & Tamru, Seneshaw & Tefera, Nigussie & Paulos, Zelekawork, 2011. "Food demand elasticities in Ethiopia: Estimates using household income consumption expenditure (HICE) survey data," ESSP working papers 11, International Food Policy Research Institute (IFPRI).
    5. Moschini, G. & Moro, D., 1993. "A Food demand System for Canada," Papers 1-93, Gouvernement du Canada - Agriculture Canada.
    6. Femenia, Fabienne, 2019. "A Meta-Analysis of the Price and Income Elasticities of Food Demand," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(2), June.
    7. Toan Ngoc Nguyen, 2020. "The Determinants of an Econometric Demand Model for Beverages," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 383-394.
    8. Silvia Tiezzi & Stefano F. Verde, 2017. "The signaling effect of gasoline taxes and its distributional implications," RSCAS Working Papers 2017/06, European University Institute.
    9. Stockton, Matthew C. & Capps, Oral, Jr., 2005. "Demand System Analysis With Emphasis On Container Sizes Of Non-Alcoholic Beverages," 2005 Annual meeting, July 24-27, Providence, RI 19137, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Meyerhoefer, Chad D. & Ranney, Christine K. & Sahn, David E., 2004. "Consistent Estimation Of Longitudinal Censored Demand Systems," 2004 Annual meeting, August 1-4, Denver, CO 19992, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Davis, Christopher G. & Dong, Diansheng & Blayney, Donald P. & Owens, Ashley, 2010. "An Analysis of U.S. Household Dairy Demand," Technical Bulletins 184308, United States Department of Agriculture, Economic Research Service.
    12. Yen, Steven T. & Fang, Cheng & Su, Shew-Jiuan, 2004. "Household food demand in urban China: a censored system approach," Journal of Comparative Economics, Elsevier, vol. 32(3), pages 564-585, September.
    13. Kohn Karsten & Missong Martin, 2003. "Estimation of Quadratic Expenditure Systems Using German Household Budget Data / Schätzung Quadratischer Ausgabensysteme anhand der Daten der Einkommens- und Verbrauchsstichprobe," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(4), pages 422-448, August.
    14. Zhuo Chen & Steven Yen, 2005. "On bias correction in the multivariate sample-selection model," Applied Economics, Taylor & Francis Journals, vol. 37(21), pages 2459-2468.
    15. Tselepidakis, Elina, 2015. "Food Safety and the Demand for Leafy Greens," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205583, Agricultural and Applied Economics Association.
    16. Keith R. McLaren & Ou Yang, 2014. "A Class of Demand Systems Satisfying Global Regularity and Having Complete Rank Flexibility," Monash Econometrics and Business Statistics Working Papers 6/14, Monash University, Department of Econometrics and Business Statistics.
    17. Salois, Matthew J. & Tiffin, J. Richard, 2010. "The Health Effects Of A Fiscal Food Policy," 115th Joint EAAE/AAEA Seminar, September 15-17, 2010, Freising-Weihenstephan, Germany 116394, European Association of Agricultural Economists.
    18. Okrent, Abigail M. & Kumcu, Aylin, 2016. "U.S. Households’ Demand for Convenience Foods," Economic Research Report 262195, United States Department of Agriculture, Economic Research Service.
    19. Yu, Lingling & Hailu, Getu, 2010. "Household Demand for Convenience Chicken Meat Products in Canada," Consumer and Market Demand Network Papers 310299, University of Alberta, Department of Resource Economics and Environmental Sociology.
    20. Thiele, Silke, 2008. "Elastizitäten der Nachfrage privater Haushalte nach Nahrungsmitteln – Schätzung eines AIDS auf Basis der Einkommens- und Verbrauchsstichprobe 2003," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 57(05), pages 1-11.

    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:taf:apeclt:v:15:y:2008:i:5:p:405-409. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.