IDEAS home Printed from https://ideas.repec.org/p/ags/ucdavw/11966.html
   My bibliography  Save this paper

Sensitivity Of The Gme Estimates To Support Bounds

Author

Listed:
  • Paris, Quirino
  • Caputo, Michael R.

Abstract

The claim has been made that the Generalized Maximum Entropy (GME) estimator of Golan, Judge and Miller is not sensitive to variations in the support bounds of either the parameters or the error terms. In this paper, we scrutinized this claim by means of Monte Carlo experiments and found that the parameter estimates are impacted in a substantial way by these changes. We also analyzed the famous data sample on the US manufacturing industry used by Cobb and Douglas in 1934 and found that the GME estimator is very sensitive to changes in support bounds. We conclude with a general result by Caputo and Paris according to which any support bound variation produces unexpected responses in the parameter estimates.

Suggested Citation

  • Paris, Quirino & Caputo, Michael R., 2001. "Sensitivity Of The Gme Estimates To Support Bounds," Working Papers 11966, University of California, Davis, Department of Agricultural and Resource Economics.
    • Handle: RePEc:ags:ucdavw:11966
    DOI: 10.22004/ag.econ.11966
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/11966/files/wp01-008.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.11966?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. Douglas J. Miller & Andrew J. Plantinga, 1999. "Modeling Land Use Decisions with Aggregate Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(1), pages 180-194.
    2. Caputo, Michael R. & Paris, Quirino, 2008. "Comparative statics of the generalized maximum entropy estimator of the general linear model," European Journal of Operational Research, Elsevier, vol. 185(1), pages 195-203, February.
    3. Sergio H. Lence & Douglas J. Miller, 1998. "Recovering Output-Specific Inputs from Aggregate Input Data: A Generalized Cross-Entropy Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 852-867.
    4. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    5. Barnett, William A. & Jonas, Andrew B., 1983. "The Muntz-Szatz demand system : An application of a globally well behaved series expansion," Economics Letters, Elsevier, vol. 11(4), pages 337-342.
    6. Miller, Douglas & Plantinga, Andrew J., 1999. "Modeling Land Use Decisions with Aggregate Data," Staff General Research Papers Archive 1487, Iowa State University, Department of Economics.
    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. Fuller, Frank H. & Beghin, John C. & Rozelle, Scott, 2007. "Consumption of dairy products in urban China: results from Beijing, Shangai and Guangzhou," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(4), pages 1-16.
    2. Louhichi, Kamel & Jacquet, Florence & Butault, Jean Pierre, 2012. "Estimating input allocation from heterogeneous data sources: A comparison of alternative estimation approaches," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 13(2), pages 1-20.
    3. Howitt, Richard E. & Msangi, Siwa, 2002. "Reconstructing Disaggregate Production Functions," 2002 Annual meeting, July 28-31, Long Beach, CA 19585, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. 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.
    5. 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.
    6. Bert D'Espallier & Sigrid Vandemaele & Ludo Peeters, 2008. "Investment-Cash Flow Sensitivities or Cash-Cash Flow Sensitivities? An Evaluative Framework for Measures of Financial Constraints," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7-8), pages 943-968.
    7. Msangi, Siwa & Howitt, Richard E., 2006. "Estimating Disaggregate Production Functions: An Application to Northern Mexico," 2006 Annual meeting, July 23-26, Long Beach, CA 21080, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Bert D'Espallier & Sigrid Vandemaele & Ludo Peeters, 2008. "Investment‐Cash Flow Sensitivities or Cash‐Cash Flow Sensitivities? An Evaluative Framework for Measures of Financial Constraints," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7‐8), pages 943-968, September.
    9. 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).

    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. Maples, Chellie H. & Hagerman, Amy D. & Lambert, Dayton M., 2022. "Ex-ante effects of the 2018 Agricultural Improvement Act’s grassland initiative," Land Use Policy, Elsevier, vol. 116(C).
    2. Raja Chakir, 2009. "Spatial Downscaling of Agricultural Land-Use Data: An Econometric Approach Using Cross Entropy," Land Economics, University of Wisconsin Press, vol. 85(2), pages 238-251.
    3. Tack, Jesse, 2013. "A Nested Test for Common Yield Distributions with Applications to U.S. Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(01), pages 1-14, April.
    4. Louhichi, Kamel & Jacquet, Florence & Butault, Jean Pierre, 2012. "Estimating input allocation from heterogeneous data sources: A comparison of alternative estimation approaches," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 13(2), pages 1-20.
    5. 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.
    6. Qiuqiong Huang & Richard Howitt & Scott Rozelle, 2012. "Estimating production technology for policy analysis: trading off precision and heterogeneity," Journal of Productivity Analysis, Springer, vol. 38(2), pages 219-233, October.
    7. Wade, Tara & Kurkalova, Lyubov & Secchi, Silvia, 2016. "Modeling Field-Level Conservation Tillage Adoption with Aggregate Choice Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    8. KURKALOVA, Lyubov A. & WADE, Tara R., 2013. "Aggregated Choice Data And Logit Models: Application To Environmental Benign Practices Of Conservation Tillage By Farmers In The State Of Iowa," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 13(2), pages 119-128.
    9. CARPENTIER, Alain & GOHIN, Alexandre & SCKOKAI, Paolo & THOMAS, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 96(01), March.
    10. Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
    11. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2016. "Research Needs and Challenges in the FEW System: Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models for Sustainable Food, Energy, and Water Systems," Center for Agricultural and Rural Development (CARD) Publications 16-wp563, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    12. Msangi, Siwa & Howitt, Richard E., 2006. "Estimating Disaggregate Production Functions: An Application to Northern Mexico," 2006 Annual meeting, July 23-26, Long Beach, CA 21080, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Basak Bayramoglu & Raja CHAKIR & Anna LUNGARSKA, 2016. "Land Use and Freshwater Ecosystems in France," EcoMod2016 9420, EcoMod.
    14. Hyunseok Kim & GianCarlo Moschini, 2018. "The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era," Land Economics, University of Wisconsin Press, vol. 94(4), pages 593-613.
    15. Kurkalova, Lyubov A. & Rabotyagov, Sergey S., 2003. "Estimation Of A Discrete Choice Model When Individual Choices Are Not Observable," 2003 Annual meeting, July 27-30, Montreal, Canada 22230, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Li, Sheng & Nadolnyak, Denis & Hartarska, Valentina, 2019. "Agricultural land conversion: Impacts of economic and natural risk factors in a coastal area," Land Use Policy, Elsevier, vol. 80(C), pages 380-390.
    17. Chonabayashi, Shun, 2014. "Accounting for Land Use Adaptation to Climate Change Impacts on US Agriculture," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170710, Agricultural and Applied Economics Association.
    18. Andrew J. Plantinga & JunJie Wu, 2003. "Co-Benefits from Carbon Sequestration in Forests: Evaluating Reductions in Agricultural Externalities from an Afforestation Policy in Wisconsin," Land Economics, University of Wisconsin Press, vol. 79(1), pages 74-85.
    19. Oltmer, K. & Nijkamp, P. & Florax, R. & Brouwer, F., 2009. "Sustainability and Agri-Environmental Policy in the European Union: A Meta-Analytic Investigation," Serie Research Memoranda 0025, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    20. Gouel, Christophe & Laborde, David, 2021. "The crucial role of domestic and international market-mediated adaptation to climate change," Journal of Environmental Economics and Management, Elsevier, vol. 106(C).

    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:ucdavw:11966. 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/daucdus.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.