IDEAS home Printed from https://ideas.repec.org/a/oup/ajagec/v83y2001i2p366-377.html
   My bibliography  Save this article

Least Squares and Entropy: A Penalty Function Perspective

Author

Listed:
  • Paul V. Preckel

Abstract

Mathematical measures of entropy as defined by Shannon and cross entropy as defined by Kullback and Leibler are currently in vogue in the field of econometrics, primarily due to the comprehensive work of Golan, Judge, and Miller. An alternative interpretation of the entropy measure as a penalty function over deviations is presented, and a number of parallels are drawn with least squares estimators. It is demonstrated that both approaches may be applied to the general linear model. The causes of differences in estimated parameter values are described, and some suggestions for the formulation of entropy-based econometric problems are presented. Copyright 2001, Oxford University Press.

Suggested Citation

  • Paul V. Preckel, 2001. "Least Squares and Entropy: A Penalty Function Perspective," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 366-377.
  • Handle: RePEc:oup:ajagec:v:83:y:2001:i:2:p:366-377
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/0002-9092.00162
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. Heckelei, Thomas & Britz, Wolfgang, 2000. "Positive Mathematical Programming with Multiple Data Points: A Cross-Sectional Estimation Procedure," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 57.
    2. Elvira Silva & Pedro Macedo & Isabel Soares, 2019. "Maximum entropy: a stochastic frontier approach for electricity distribution regulation," Journal of Regulatory Economics, Springer, vol. 55(3), pages 237-257, June.
    3. Kaplan, Jonathan D. & Howitt, Richard E. & Farzin, Y. Hossein, 2003. "An information-theoretical analysis of budget-constrained nonpoint source pollution control," Journal of Environmental Economics and Management, Elsevier, vol. 46(1), pages 106-130, July.
    4. repec:ags:aaea22:335590 is not listed on IDEAS
    5. Arndt, Channing & Robinson, Sherman & Tarp, Finn, 2002. "Parameter estimation for a computable general equilibrium model: a maximum entropy approach," Economic Modelling, Elsevier, vol. 19(3), pages 375-398, May.
    6. Kuiper, Marijke & van Tongeren, Frank, 2005. "Which road to liberalization in the Mediterranean? Analyzing different regional trade liberalization scenarios for Morocco and Tunisia," Conference papers 331404, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    7. Balcombe, Kelvin, 2006. "Cross-Entropy Estimation of Linear Cointegrated Equations," MPRA Paper 15100, University Library of Munich, Germany.
    8. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2009. "Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach," Agricultural Systems, Elsevier, vol. 99(2-3), pages 126-140, February.
    9. Esteban Fernández-Vázquez & Matías Mayor-Fernández & Jorge Rodríguez-Vález, 2009. "Estimating Spatial Autoregressive Models by GME-GCE Techniques," International Regional Science Review, , vol. 32(2), pages 148-172, April.
    10. Rui Fragoso & Maria Leonor da Silva Carvalho, 2013. "Estimation of cost allocation coefficients at the farm level using an entropy approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1893-1906, September.
    11. Esteban Fernández-Vázquez, 2014. "Estimating the effect of technological factors from samples affected by collinearity: a data-weighted entropy approach," Empirical Economics, Springer, vol. 47(2), pages 717-731, September.
    12. Hansen, Heiko & Surry, Yves R., 2006. "Die Schatzung Verfahrensspezifischer Faktoreinsatzmengen Fur Die Landwirtschaft In Deutschland," 46th Annual Conference, Giessen, Germany, October 4-6, 2006 14959, German Association of Agricultural Economists (GEWISOLA).
    13. Buschena, David E. & Atwood, Joseph A., 2011. "Evaluation of similarity models for expected utility violations," Journal of Econometrics, Elsevier, vol. 162(1), pages 105-113, May.
    14. R. Carter Hill & Randall C. Campbell, 2001. "Maximum Entropy Estimation in Economic Models with Linear Inequality Restrictions," Departmental Working Papers 2001-11, Department of Economics, Louisiana State University.
    15. Hansen, H. & Surry, Y., 2007. "Die Schätzung verfahrensspezifischer Faktoreneinsatzmengen für die Landwirtschaft in Deutschland," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 42, March.
    16. Heckelei, Thomas & Mittelhammer, Ronald C. & Jansson, Torbjorn, 2008. "A Bayesian Alternative To Generalized Cross Entropy Solutions For Underdetermined Econometric Models," Discussion Papers 56973, University of Bonn, Institute for Food and Resource Economics.
    17. Heckelei, Thomas & Wolff, Hendrik, 2002. "A Methodological Note on the Estimation of Programming Models," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24896, European Association of Agricultural Economists.
    18. Cook, Larry & Harslett, Philip, 2015. "An introduction to entropy estimation of parameters in economic models," Conference papers 332651, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    19. Jing Yi & Samantha Cohen & Sarah Rehkamp & Patrick Canning & Miguel I. Gómez & Houtian Ge, 2023. "Overcoming data barriers in spatial agri‐food systems analysis: A flexible imputation framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 686-701, September.
    20. Rehkamp, Sarah & Canning, Patrick & Birney, Catherine, 2021. "Tracking the U.S. Domestic Food Supply Chain’s Freshwater Use Over Time," Economic Research Report 327191, United States Department of Agriculture, Economic Research Service.
    21. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2004. "Generating Plausible Crop Distribution Maps For Sub-Sahara Africa Using Spatial Allocation Model," 2004 Annual meeting, August 1-4, Denver, CO 19965, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    22. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2007. "Generating plausible crop distribution and performance maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach:," IFPRI discussion papers 725, International Food Policy Research Institute (IFPRI).

    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:oup:ajagec:v:83:y:2001:i:2:p:366-377. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.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.