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An Information Theoretic Approach to Econometrics


  • Judge,George G.
  • Mittelhammer,Ron C.


This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic econometric models and methods. Because most data are observational, practitioners work with indirect noisy observations and ill-posed econometric models in the form of stochastic inverse problems. Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems. In succeeding chapters, a family of power divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-model problems. Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family.

Suggested Citation

  • Judge,George G. & Mittelhammer,Ron C., 2012. "An Information Theoretic Approach to Econometrics," Cambridge Books, Cambridge University Press, number 9780521869591, December.
  • Handle: RePEc:cup:cbooks:9780521869591

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    Cited by:

    1. George Judge, 2016. "Econometric Information Recovery in Behavioral Networks," Econometrics, MDPI, Open Access Journal, vol. 4(3), pages 1-11, September.
    2. 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.
    3. Sofia B. Villas-Boas & Qiuzi Fu & George Judge, 2015. "Is Benford’s Law a Universal Behavioral Theory?," Econometrics, MDPI, Open Access Journal, vol. 3(4), pages 1-11, October.
    4. 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.
    5. 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 qt0hz5g3cj, Department of Agricultural & Resource Economics, UC Berkeley.
    6. 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.
    7. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, Open Access Journal, vol. 7(1), pages 1-16, March.
    8. 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.
    9. Channing Arndt & Charles Fant & Sherman Robinson & Kenneth Strzepek, 2015. "Informed selection of future climates," Climatic Change, Springer, vol. 130(1), pages 21-33, May.
    10. repec:unu:wpaper:wp2012-60 is not listed on IDEAS
    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. Amos Golan & Aman Ullah, 2017. "Interval estimation: An information theoretic approach," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 781-795, October.
    13. 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).
    14. 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.

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