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Estimation, Inference and Specification Analysis

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  • White,Halbert

Abstract

This book examines the consequences of misspecifications ranging from the fundamental to the nonexistent for the interpretation of likelihood-based methods of statistical estimation and interference. Professor White first explores the underlying motivation for maximum-likelihood estimation, treats the interpretation of the maximum-likelihood estimator (MLE) for misspecified probability models, and gives the conditions under which parameters of interest can be consistently estimated despite misspecification, and the consequences of misspecification, for hypothesis testing in estimating the asymptotic covariance matrix of the parameters. Although the theory presented in the book is motivated by econometric problems, its applicability is by no means restricted to economics. Subject to defined limitations, the theory applies to any scientific context in which statistical analysis is conducted using approximate models.

Suggested Citation

  • White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464, April.
  • Handle: RePEc:cup:cbooks:9780521574464
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    Cited by:

    1. Flora Felso & Sander Onderstal & Jo Seldeslachts, 2014. "What Clients want: Choices between Lawyers' Offerings," Tinbergen Institute Discussion Papers 14-020/VII, Tinbergen Institute.
    2. Mingie, James C. & Poudyal, Neelam C. & Bowker, J.M. & Mengak, Michael T. & Siry, Jacek P., 2017. "Big game hunter preferences for hunting club attributes: A choice experiment," Forest Policy and Economics, Elsevier, vol. 78(C), pages 98-106.
    3. Lin, Wei & González-Rivera, Gloria, 2016. "Interval-valued time series models: Estimation based on order statistics exploring the Agriculture Marketing Service data," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 694-711.
    4. Zhenlin Yang, 2006. "On Joint Modelling and Testing for Local and Global Spatial Externalities," Development Economics Working Papers 22487, East Asian Bureau of Economic Research.
    5. repec:bpj:jecome:v:8:y:2019:i:1:p:26:n:2 is not listed on IDEAS
    6. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    7. Franses, Philip Hans & Kunst, Robert M., 2007. "Analyzing a panel of seasonal time series: Does seasonality in industrial production converge across Europe?," Economic Modelling, Elsevier, vol. 24(6), pages 954-968, November.
    8. repec:taf:emetrv:v:35:y:2016:i:7:p:1221-1250 is not listed on IDEAS
    9. Busch, Thomas, 2005. "A robust LR test for the GARCH model," Economics Letters, Elsevier, vol. 88(3), pages 358-364, September.
    10. Gian Piero Aielli, 2013. "Dynamic Conditional Correlation: On Properties and Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 282-299, July.
    11. Abadie, Alberto & Gay, Sebastien, 2006. "The impact of presumed consent legislation on cadaveric organ donation: A cross-country study," Journal of Health Economics, Elsevier, vol. 25(4), pages 599-620, July.
    12. Bartalotti Otávio, 2019. "Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-26, January.
    13. Jan R. Magnus, 2007. "The asymptotic variance of the pseudo maximum likelihood estimator," CIRJE F-Series CIRJE-F-479, CIRJE, Faculty of Economics, University of Tokyo.
    14. Pedersen, Rasmus Søndergaard, 2017. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Journal of Econometrics, Elsevier, vol. 196(1), pages 23-36.
    15. Kevin Sheppard, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    16. Lee, Seojeong, 2014. "Asymptotic refinements of a misspecification-robust bootstrap for generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 178(P3), pages 398-413.
    17. Omar Besbes & Assaf Zeevi, 2015. "On the (Surprising) Sufficiency of Linear Models for Dynamic Pricing with Demand Learning," Management Science, INFORMS, vol. 61(4), pages 723-739, April.
    18. Carlo Grillenzoni, 2009. "Kernel Likelihood Inference for Time Series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(1), pages 127-140.
    19. Kuper, Gerard H. & Lestano, 2007. "Dynamic conditional correlation analysis of financial market interdependence: An application to Thailand and Indonesia," Journal of Asian Economics, Elsevier, vol. 18(4), pages 670-684, August.
    20. Manganelli, Simone, 2018. "Selecting models with judgment," Working Paper Series 2188, European Central Bank.
    21. Sander Barendse, 2017. "Interquantile Expectation Regression," Tinbergen Institute Discussion Papers 17-034/III, Tinbergen Institute.
    22. Andrew J. Patton & Kevin Sheppard, 2008. "Evaluating Volatility and Correlation Forecasts," OFRC Working Papers Series 2008fe22, Oxford Financial Research Centre.
    23. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    24. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Integrated Deviance Information Criterion for Latent Variable Models," Economics and Statistics Working Papers 6-2018, Singapore Management University, School of Economics.
    25. Omar Besbes & Robert Phillips & Assaf Zeevi, 2010. "Testing the Validity of a Demand Model: An Operations Perspective," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 162-183, June.

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