IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/31459.html
   My bibliography  Save this paper

Estimates of Armington parameters for a landlocked economy

Author

Listed:
  • Nganou, Jean-Pascal

Abstract

One of the most debated issues in the Computable General Equilibrium (CGE) literature concerns the validity of the key behavioral parameters used in the calibration process. CGE modelers seldom estimate those parameters, preferring to borrow from the handful of estimates available in the literature. The lack of data is often cited as a reason for this type of modus operandi (technique). Estimating key parameters is very crucial since CGE results are quite sensitive to parameter specification. This paper proposes a new and robust econometric technique, the Generalized Maximum Entropy (GME), to estimate Armington elasticities for selected commodities. All the parameters estimated are intended for use in a Lesotho CGE model.

Suggested Citation

  • Nganou, Jean-Pascal, 2005. "Estimates of Armington parameters for a landlocked economy," MPRA Paper 31459, University Library of Munich, Germany, revised 10 Aug 2008.
    • Handle: RePEc:pra:mprapa:31459
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/31459/1/MPRA_paper_31459.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thurlow, James & van Seventer, Dirk Ernst, 2002. "A standard computable general equilibrium model for South Africa," TMD discussion papers 100, International Food Policy Research Institute (IFPRI).
    2. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    3. 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.
    4. Iain Fraser, 2000. "An application of maximum entropy estimation: the demand for meat in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 32(1), pages 45-59.
    5. Clinton R. Shiells & Kenneth A. Reinert, 1993. "Armington Models and Terms-of-Trade Effects: Some Econometric Evidence for North America," Canadian Journal of Economics, Canadian Economics Association, vol. 26(2), pages 299-316, May.
    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. Josef Bajzik & Tomas Havranek & Zuzana Irsova & Jiri Schwarz, 2019. "Estimating the Armington Elasticity: The Importance of Data Choice and Publication Bias," Working Papers IES 2019/19, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2019.
    2. Josef Bajzik & Tomas Havranek & Zuzana Irsova & Jiri Schwarz, 2019. "The Elasticity of Substitution between Domestic and Foreign Goods: A Quantitative Survey," Working Papers 2019/12, Czech National Bank.

    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. Esteban Fernandez-Vazquez, 2011. "Estimating spatial weighting matrices in cross-regressive models by entropy techniques," ERSA conference papers ersa10p503, European Regional Science Association.
    2. repec:lrk:lrkwkp:fiirs016 is not listed on IDEAS
    3. Fernández, Esteban & Fernández, Paula, 2008. "An extension to Sun's decomposition methodology: The Path Based approach," Energy Economics, Elsevier, vol. 30(3), pages 1020-1036, May.
    4. 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.
    5. Tarp, Finn & Arndt, Channing & Jensen, Henning Tarp & Robinson, Sherman & Heltberg, Rasmus, 2002. "Facing the development challenge in Mozambique: an economywide perspective," Research reports 126, International Food Policy Research Institute (IFPRI).
    6. Aydin, Levent, 2009. "The Impacts of the Trade and Factor Market Liberalization on the Carbon Abatement Policies in the Enlargement of European Union," Conference papers 331842, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    7. 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.
    8. 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.
    9. Marsh, Thomas L. & Mittelhammer, Ronald C., 2001. "Adaptive Truncated Estimaton Applied To Maximum Entropy," 2001 Annual Meeting, July 8-11, 2001, Logan, Utah 36169, Western Agricultural Economics Association.
    10. Campbell, Randall C. & Hill, R. Carter, 2005. "A Monte Carlo study of the effect of design characteristics on the inequality restricted maximum entropy estimator," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(1), pages 1-30, June.
    11. McDonald, Scott & Punt, Cecilia, 2005. "General equilibrium modelling in South Africa: What the future holds," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(1), pages 1-39, March.
    12. Go, Delfin S. & Lofgren, Hans & Ramos, Fabian Mendez & Robinson, Sherman, 2016. "Estimating parameters and structural change in CGE models using a Bayesian cross-entropy estimation approach," Economic Modelling, Elsevier, vol. 52(PB), pages 790-811.
    13. Rezek, Jon P. & Campbell, Randall C., 2007. "Cost estimates for multiple pollutants: A maximum entropy approach," Energy Economics, Elsevier, vol. 29(3), pages 503-519, 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. 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.
    16. Nicola Branson, 2009. "Re-weighting the OHS and LFS National household Survey Data to create a consistent series over time: A Cross Entropy Estimation Approach," SALDRU Working Papers 38, Southern Africa Labour and Development Research Unit, University of Cape Town.
    17. Rodriguez-Vález, Jorge & Álvarez, Antonio & Arias, Carlos & Fernández, Esteban, 2005. "Estimating the Productivity of Public Infrastructure using Maximum Entropy Econometrics," Efficiency Series Papers 2005/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    18. Manh Toan Nguyen & Tung Lam Dang & Thi Hong Hanh Huynh, 2020. "Trade Liberalization and Income Distribution in Vietnam: Dynamic CGE Approach," Asian Economic Journal, East Asian Economic Association, vol. 34(4), pages 404-429, December.
    19. Fernández Vázquez, Esteban & Los, Bart, 2007. "A Maximum Entropy Approach to the Indenitication of Productive Technology Spillovers," Discussion Papers 1106, The Research Institute of the Finnish Economy.
    20. 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.
    21. 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.

    More about this item

    Keywords

    CGE; Maximum Entropy (GME); Armington; Africa; Lesotho;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    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:pra:mprapa:31459. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.