IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v36y2017i6-9p781-795.html
   My bibliography  Save this article

Interval estimation: An information theoretic approach

Author

Listed:
  • Amos Golan
  • Aman Ullah

Abstract

We develop here an alternative information theoretic method of inference of problems in which all of the observed information is in terms of intervals. We focus on the unconditional case in which the observed information is in terms the minimal and maximal values at each period. Given interval data, we infer the joint and marginal distributions of the interval variable and its range. Our inferential procedure is based on entropy maximization subject to multidimensional moment conditions and normalization in which the entropy is defined over discretized intervals. The discretization is based on theory or empirically observed quantities. The number of estimated parameters is independent of the discretization so the level of discretization does not change the fundamental level of complexity of our model. As an example, we apply our method to study the weather pattern for Los Angeles and New York City across the last century.

Suggested Citation

  • Amos Golan & Aman Ullah, 2017. "Interval estimation: An information theoretic approach," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 781-795, October.
    • Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:781-795
    DOI: 10.1080/07474938.2017.1307573
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2017.1307573
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474938.2017.1307573?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
    ---><---

    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. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    2. Judge,George G. & Mittelhammer,Ron C., 2012. "An Information Theoretic Approach to Econometrics," Cambridge Books, Cambridge University Press, number 9780521869591.
    3. Judge,George G. & Mittelhammer,Ron C., 2012. "An Information Theoretic Approach to Econometrics," Cambridge Books, Cambridge University Press, number 9780521689731.
    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. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
    2. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    3. Chen, Simiao & Prettner, Klaus & Kuhn, Michael & Bloom, David E., 2021. "The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach," The Journal of the Economics of Ageing, Elsevier, vol. 20(C).
    4. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.

    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. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    2. 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.
    3. Villas-Boas, Sofia B. & Fu, Qiuzi & Judge, George, 2019. "Entropy based European income distributions and inequality measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 686-698.
    4. Debowicz, Dario & Dorosh, Paul A. & Robinson, Sherman & Haider, Syed Hamza, 2012. "A 2007-08 social accounting matrix for Pakistan:," PSSP working papers 1, International Food Policy Research Institute (IFPRI).
    5. Darío Debowicz & Paul Dorosh & Hamza Haider & Sherman Robinson, 2013. "A Disaggregated and Macro-consistent Social Accounting Matrix for Pakistan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 2(1), pages 1-25, December.
    6. repec:unu:wpaper:wp2012-60 is not listed on IDEAS
    7. Villas-Boas, Sofia B. & Judge, George, 2013. "An Information Theoretic Approach to Understanding the Micro Foundations of Macro Processes," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt82f7m32n, Department of Agricultural & Resource Economics, UC Berkeley.
    8. Fu, Qiuzi & Villas-Boas, Sofia B & Judge, George, 2019. "Entropy-based China income distributions and inequality measures," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt03n491s7, Department of Agricultural & Resource Economics, UC Berkeley.
    9. Sofia B. Villas-Boas & Qiuzi Fu & George Judge, 2015. "Is Benford’s Law a Universal Behavioral Theory?," Econometrics, MDPI, vol. 3(4), pages 1-11, October.
    10. Henry, Miguel & Mittelhammer, Ron & Loomis, John, 2018. "An Information-Theoretic Approach to Estimating Willingness To Pay for River Recreation Site Attributes," MPRA Paper 89842, University Library of Munich, Germany.
    11. Ellis Scharfenaker & Duncan Foley, 2017. "Maximum Entropy Estimation of Statistical Equilibrium in Economic Quantal Response Models," Working Papers 1710, New School for Social Research, Department of Economics, revised May 2017.
    12. Tiziano Squartini & Enrico Ser-Giacomi & Diego Garlaschelli & George Judge, 2015. "Information Recovery in Behavioral Networks," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-11, May.
    13. Henry-Osorio, Miguel & Mittelhammer, Ronald C., 2012. "An Information-Theoretic Approach to Modeling Binary Choices: Estimating Willingness to Pay for Recreation Site Attributes," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123432, Agricultural and Applied Economics Association.
    14. Villas-Boas, Sofia B & Fu, Jenny & Judge, George, 2016. "Measuring The Inequality Nature Of European Micro Income Data," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6445w1s5, Department of Agricultural & Resource Economics, UC Berkeley.
    15. Channing Arndt & Charles Fant & Sherman Robinson & Kenneth Strzepek, 2015. "Informed selection of future climates," Climatic Change, Springer, vol. 130(1), pages 21-33, May.
    16. T. Krishna Kumar, 2023. "Professor C. R. Rao, the Founder President of the Indian Econometric Society is Awarded the International Prize in Statistics, 2023," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 473-480, September.
    17. George Judge, 2016. "Econometric Information Recovery in Behavioral Networks," Econometrics, MDPI, vol. 4(3), pages 1-11, September.
    18. Chipeniuk, Karsten O. & Walker, Todd B., 2021. "Forward inflation expectations: Evidence from inflation caps and floors," Journal of Macroeconomics, Elsevier, vol. 70(C).
    19. Channing Arndt & Charles Fant & Sherman Robinson & Kenneth Strzepek, 2015. "Informed selection of future climates," Climatic Change, Springer, vol. 130(1), pages 21-33, May.
    20. repec:lrk:lrkwkp:fiirs016 is not listed on IDEAS
    21. Axel Tonini & Roel Jongeneel, 2009. "The distribution of dairy farm size in Poland: a markov approach based on information theory," Applied Economics, Taylor & Francis Journals, vol. 41(1), pages 55-69.
    22. Hyeok Lee & Yong Kyun Kim, 2018. "The effects of external shocks on the Korean economy: CGE model-based analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-14, December.

    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:taf:emetrv:v:36:y:2017:i:6-9:p:781-795. 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: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.