IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v107y2002i1-2p17-40.html
   My bibliography  Save this article

Information indices: unification and applications

Author

Listed:
  • Soofi, E. S.
  • Retzer, J. J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Soofi, E. S. & Retzer, J. J., 2002. "Information indices: unification and applications," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 17-40, March.
    • Handle: RePEc:eee:econom:v:107:y:2002:i:1-2:p:17-40
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(01)00111-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Theil, Henri, 1980. "The entropy of the maximum entropy distribution," Economics Letters, Elsevier, vol. 5(2), pages 145-148.
    2. Mazzuchi, T.A & Soofi, E.S & Soyer, R, 2000. "Computation of maximum entropy Dirichlet for modeling lifetime data," Computational Statistics & Data Analysis, Elsevier, vol. 32(3-4), pages 361-378, January.
    3. Theil, Henri & Lightburn, Richard O., 1981. "The positive maximum entropy distribution," Economics Letters, Elsevier, vol. 8(1), pages 67-72.
    4. Tinsley, P. A. & Spindt, P. A. & Friar, M. E., 1980. "Indicator and filter attributes of monetary aggregates : A nit-picking case for disaggregation," Journal of Econometrics, Elsevier, vol. 14(1), pages 61-91, September.
    5. Brockett, Patrick L. & Charnes, Abraham & Cooper, William W. & Learner, David & Phillips, Fred Y., 1995. "Information theory as a unifying statistical approach for use in marketing research," European Journal of Operational Research, Elsevier, vol. 84(2), pages 310-329, July.
    6. Clive Granger & Jin‐Lung Lin, 1994. "Using The Mutual Information Coefficient To Identify Lags In Nonlinear Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(4), pages 371-384, July.
    7. Mohsen Pourahmadi & E. S. Soofi, 2000. "Prediction Variance and Information Worth of Observations in Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(4), pages 413-434, July.
    8. Peter Hall & Sally Morton, 1993. "On the estimation of entropy," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(1), pages 69-88, March.
    9. P. M. Robinson, 1991. "Consistent Nonparametric Entropy-Based Testing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 437-453.
    10. Theil, Henri, 1987. "How many bits of information does an independent variable yield in a multiple regression?," Statistics & Probability Letters, Elsevier, vol. 6(2), pages 107-108, November.
    11. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.
    12. Gokhale, D. V., 1983. "On entropy-based goodness-of-fit tests," Computational Statistics & Data Analysis, Elsevier, vol. 1(1), pages 157-165, March.
    13. Soofi, Ehsan S., 1990. "Effects of collinearity on information about regression coefficients," Journal of Econometrics, Elsevier, vol. 43(3), pages 255-274, March.
    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. Scharfenaker, Ellis & dos Santos, Paulo L., 2015. "The distribution and regulation of Tobin’s q," Economics Letters, Elsevier, vol. 137(C), pages 191-194.
    2. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    3. Hadi Alizadeh Noughabi & Albert Vexler, 2016. "An efficient correction to the density-based empirical likelihood ratio goodness-of-fit test for the inverse Gaussian distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2988-3003, December.
    4. Salois, Matthew & Moss, Charles, 2010. "An Information Approach to the Dynamics in Farm Income: Implications for Farmland Markets," MPRA Paper 26850, University Library of Munich, Germany.
    5. Matthew Salois & Charles Moss & Kenneth Erickson, 2012. "Farm income, population and farmland prices: a relative information approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 39(2), pages 289-307, April.
    6. Soofi, E.S. & Nystrom, P.C. & Yasai-Ardekani, M., 2009. "Executives' perceived environmental uncertainty shortly after 9/11," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3502-3515, July.
    7. Stan Lipovetsky & W. Michael Conklin, 2015. "Predictor relative importance and matching regression parameters," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 1017-1031, May.
    8. Golan, Amos & Perloff, Jeffrey M., 2002. "Comparison of maximum entropy and higher-order entropy estimators," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 195-211, March.
    9. Paulo L. dos Santos & Jangho Yang, 2019. "The persistent and informative distribution of returns on capital," Economics and Business Letters, Oviedo University Press, vol. 8(3), pages 156-165.
    10. Samuel Kotz & Johan René van Dorp, 2010. "Generalized Diagonal Band Copulas with Two-Sided Generating Densities," Decision Analysis, INFORMS, vol. 7(2), pages 196-214, June.
    11. Emanuele Citera, 2021. "Stock Returns, Market Trends, and Information Theory: A Statistical Equilibrium Approach," Working Papers 2116, New School for Social Research, Department of Economics.
    12. Jose Alejandro Coronado, 2018. "An Information-Constrained Model for Ultimatum Bargaining," Working Papers 1815, New School for Social Research, Department of Economics.
    13. Ozlem Omer, 2018. "Equilibrium-Disequilibrium Dynamics of the US Housing Market, 2000-2015: A Quantal Response Statistical Equilibrium Approach," Working Papers 1809, New School for Social Research, Department of Economics.
    14. Retzer, J.J. & Soofi, E.S. & Soyer, R., 2009. "Information importance of predictors: Concept, measures, Bayesian inference, and applications," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2363-2377, April.
    15. Emanuele Citera & Francesco De Pretis, 2023. "An Information Theory Approach to the Stock and Cryptocurrency Market: A Statistical Equilibrium Perspective," Papers 2310.04907, arXiv.org.
    16. Carpio, Carlos E. & Sydorovych, Olha & Marra, Michele C., 2007. "Relative Importance of Environmental Attributes Using Logistic Regression," 2007 Annual Meeting, February 4-7, 2007, Mobile, Alabama 34846, Southern Agricultural Economics Association.
    17. Salois, Matthew J., 2013. "Regional changes in the distribution of foreign aid: An entropy approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2893-2902.
    18. Juan Melo, 2024. "Decentralized Finance and Local Public Goods: A Bayesian Maximum Entropy Model of School District Spending in the U.S," Papers 2404.17700, arXiv.org.
    19. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.
    20. M. Laura Donnet & Dave D. Weatherspoon & Charles B. Moss, 2010. "Measuring Food Product Differentiation by Quality Ratings: A Cross‐Entropy Analysis of Specialty Coffee e‐Auctions," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(1), pages 122-137, February.
    21. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    22. Golan, Amos, 2002. "Information and Entropy Econometrics--Editor's View," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 1-15, March.

    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. Nikolay Iskrev, 2018. "Are asset price data informative about news shocks? A DSGE perspective," Working Papers REM 2018/33, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Iskrev, Nikolay, 2019. "On the sources of information about latent variables in DSGE models," European Economic Review, Elsevier, vol. 119(C), pages 318-332.
    3. repec:wyi:journl:002087 is not listed on IDEAS
    4. Asok K. Nanda & Shovan Chowdhury, 2021. "Shannon's Entropy and Its Generalisations Towards Statistical Inference in Last Seven Decades," International Statistical Review, International Statistical Institute, vol. 89(1), pages 167-185, April.
    5. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    6. Matilla-García, Mariano & Marín, Manuel Ruiz, 2010. "A new test for chaos and determinism based on symbolic dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 600-614, December.
    7. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    8. Neshat Beheshti & Jeffrey S. Racine & Ehsan S. Soofi, 2015. "Information Measures for Nonparametric Kernel Estimation," Department of Economics Working Papers 2015-03, McMaster University.
    9. Menéndez, M. & Morales, D. & Pardo, L., 1997. "Maximum entropy principle and statistical inference on condensed ordered data," Statistics & Probability Letters, Elsevier, vol. 34(1), pages 85-93, May.
    10. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Testing Serial Independence via Density-Based Measures of Divergence," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 627-641, September.
    11. Ashis K. Gangopadhyay & Robert disario & Dipak K. Dey, 1997. "A nonparametric approach to k-sample inference based on entropy-super-," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 8(3), pages 237-252, September.
    12. Yongmiao Hong & Xia Wang & Wenjie Zhang & Shouyang Wang, 2017. "An efficient integrated nonparametric entropy estimator of serial dependence," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 728-780, October.
    13. Wu, Ximing, 2010. "Exponential Series Estimator of multivariate densities," Journal of Econometrics, Elsevier, vol. 156(2), pages 354-366, June.
    14. Arthur Lewbel, 2000. "Asymptotic Trimming for Bounded Density Plug-in Estimators," Boston College Working Papers in Economics 479, Boston College Department of Economics, revised 30 Oct 2000.
    15. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
    16. Diks Cees & Manzan Sebastiano, 2002. "Tests for Serial Independence and Linearity Based on Correlation Integrals," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    17. C. W. Granger & Esfandiar Maasoumi, 2000. "A Dependence Metric for Nonlinear Time Series," Econometric Society World Congress 2000 Contributed Papers 0421, Econometric Society.
    18. Henry Lam, 2018. "Sensitivity to Serial Dependency of Input Processes: A Robust Approach," Management Science, INFORMS, vol. 64(3), pages 1311-1327, March.
    19. Soofi, E.S. & Nystrom, P.C. & Yasai-Ardekani, M., 2009. "Executives' perceived environmental uncertainty shortly after 9/11," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3502-3515, July.
    20. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    21. Marcelo Fernandes & Breno Neri, 2010. "Nonparametric Entropy-Based Tests of Independence Between Stochastic Processes," Econometric Reviews, Taylor & Francis Journals, vol. 29(3), pages 276-306.

    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:eee:econom:v:107:y:2002:i:1-2:p:17-40. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.