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A Monte Carlo study of the effect of design characteristics on the inequality restricted maximum entropy estimator

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  • Campbell, Randall C.
  • Hill, R. Carter
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    Abstract

    In this paper, we conduct a set of Monte Carlo sampling experiments to examine the effect of design characteristics on the inequality restricted maximum entropy (RME) estimator. We generate data under varying design characteristics, and estimate the parameters using maximum entropy and least squares estimation, both with and without parameter inequality restrictions. As part of the experimental design we vary the sample size, the distribution of the regressors, the distribution of the errors, the degree of collinearity, the signal-to-noise ratio, and the specification error. We compare the alternative estimators on the basis of mean square error.

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    File URL: http://purl.umn.edu/143485
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    Bibliographic Info

    Article provided by Review of Applied Economics in its journal Review of Applied Economics.

    Volume (Year): 1 (2005)
    Issue (Month): 1 ()
    Pages:

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    Handle: RePEc:ags:reapec:143485

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    Web page: http://www.lincoln.ac.nz/story11874.html

    Related research

    Keywords: Maximum Entropy; Generalized Maximum Entropy; Linear Inequality Restrictions; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; C13; C14; C49;

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    1. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
    2. Mittelhammer,Ron C. & Judge,George G. & Miller,Douglas J., 2000. "Econometric Foundations Pack with CD-ROM," Cambridge Books, Cambridge University Press, number 9780521623940, April.
    3. Shen, Edward Z. & Perloff, Jeffrey M., 2001. "Maximum entropy and Bayesian approaches to the ratio problem," Journal of Econometrics, Elsevier, vol. 104(2), pages 289-313, September.
    4. Judge, G. G. & Hill, R. Carter & Bock, M. E., 1990. "An adaptive empirical Bayes estimator of the multivariate normal mean under quadratic loss," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 189-213.
    5. 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.
    6. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    7. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
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    Cited by:
    1. Rui Fragoso & Maria Leonor Carvalho, 2011. "Estimation of Cost Allocation Coefficients at the Farm Level Using an Entropy Approach," CEFAGE-UE Working Papers 2011_21, University of Evora, CEFAGE-UE (Portugal).

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