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An Information Theoretic Approach to Econometrics

Author

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

Abstract

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, March.
  • Handle: RePEc:cup:cbooks:9780521869591
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    1. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    2. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, pages 7-40.
    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. Manning, Willard G. & Blumberg, Linda & Moulton, Lawrence H., 1995. "The demand for alcohol: The differential response to price," Journal of Health Economics, Elsevier, vol. 14(2), pages 123-148, June.
    5. Jason Abrevaya, 2001. "The effects of demographics and maternal behavior on the distribution of birth outcomes," Empirical Economics, Springer, vol. 26(1), pages 247-257.
    6. Moshe Buchinsky, 1998. "The dynamics of changes in the female wage distribution in the USA: a quantile regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 1-30.
    7. Amanda Gosling & Stephen Machin & Costas Meghir, 2000. "The Changing Distribution of Male Wages in the U.K," Review of Economic Studies, Oxford University Press, vol. 67(4), pages 635-666.
    8. James M. Poterba & Kim S. Rueben, 1994. "The Distribution of Public Sector Wage Premia: New Evidence Using Quantile Regression Methods," NBER Working Papers 4734, National Bureau of Economic Research, Inc.
    9. Čížek, Pavel, 1999. "Quantile regression," SFB 373 Discussion Papers 1999,78, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", pages 129-137.
    11. Angel López-Nicolás & Jaume García & Pedro J. Hernández, 2001. "How wide is the gap? An investigation of gender wage differences using quantile regression," Empirical Economics, Springer, vol. 26(1), pages 149-167.
    12. Trede, Mark, 1998. "Making mobility visible: a graphical device," Economics Letters, Elsevier, vol. 59(1), pages 77-82, April.
    13. Alberto Abadie & Joshua D. Angrist & Guido W. Imbens, 1998. "Instrumental Variables Estimation of Quantile Treatment Effects," NBER Technical Working Papers 0229, National Bureau of Economic Research, Inc.
    14. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    15. Kahn, Lawrence M, 1998. "Collective Bargaining and the Interindustry Wage Structure: International Evidence," Economica, London School of Economics and Political Science, vol. 65(260), pages 507-534, November.
    16. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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    Citations

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    Cited by:

    1. 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.
    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 & 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.
    4. 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.
    5. Channing Arndt & Charles Fant & Sherman Robinson & Kenneth Strzepek, 2015. "Informed selection of future climates," Climatic Change, Springer, vol. 130(1), pages 21-33, May.
    6. 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).
    7. George Judge, 2016. "Econometric Information Recovery in Behavioral Networks," Econometrics, MDPI, Open Access Journal, vol. 4(3), pages 1-11, September.
    8. 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.
    9. repec:unu:wpaper:wp2012-60 is not listed on IDEAS
    10. 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.

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