IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v112y2003i1p115-120.html
   My bibliography  Save this article

Econometric issues in using the AHEAD panel

Author

Listed:
  • Geweke, John

Abstract

No abstract is available for this item.

Suggested Citation

  • Geweke, John, 2003. "Econometric issues in using the AHEAD panel," Journal of Econometrics, Elsevier, vol. 112(1), pages 115-120, January.
    • Handle: RePEc:eee:econom:v:112:y:2003:i:1:p:115-120
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(02)00153-7
    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. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-587.
    2. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
    3. John Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
    4. Geweke, John & Keane, Michael, 2000. "An empirical analysis of earnings dynamics among men in the PSID: 1968-1989," Journal of Econometrics, Elsevier, vol. 96(2), pages 293-356, June.
    5. Dufour, Jean-Marie, 1984. "Unbiasedness of Predictions from Estimated Autoregressions When the True Order Is Unknown," Econometrica, Econometric Society, vol. 52(1), pages 209-215, January.
    6. Geweke, John & Keane, Michael, 2001. "Computationally intensive methods for integration in econometrics," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 56, pages 3463-3568, Elsevier.
    7. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
    8. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
    Full references (including those not matched with items on IDEAS)

    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. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    2. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    3. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
    4. Mittelhammer, Ron C. & Judge, George, 2011. "A family of empirical likelihood functions and estimators for the binary response model," Journal of Econometrics, Elsevier, vol. 164(2), pages 207-217, October.
    5. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    6. Ron Mittelhammer & George Judge, 2009. "A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model," International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 33-49, April.
    7. Chen, Le-Yu & Lee, Sokbae, 2019. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," Journal of Econometrics, Elsevier, vol. 210(2), pages 482-497.
    8. Charlier, Erwin & Melenberg, Bertrand & van Soest, Arthur, 2001. "An analysis of housing expenditure using semiparametric models and panel data," Journal of Econometrics, Elsevier, vol. 101(1), pages 71-107, March.
    9. Coppejans, Mark, 2001. "Estimation of the binary response model using a mixture of distributions estimator (MOD)," Journal of Econometrics, Elsevier, vol. 102(2), pages 231-269, June.
    10. Gao, Yichen & Li, Cong & Liang, Zhongwen, 2015. "Binary response correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 421-434.
    11. Bruins, Marianne & Duffy, James A. & Keane, Michael P. & Smith, Anthony A., 2018. "Generalized indirect inference for discrete choice models," Journal of Econometrics, Elsevier, vol. 205(1), pages 177-203.
    12. Satimanon, Monthien & Lupi, Frank, 2010. "Comparison of Approaches to Estimating Demand for Payment for Environmental Services," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61288, Agricultural and Applied Economics Association.
    13. Jason R. Blevins, 2013. "Non-Standard Rates of Convergence of Criterion-Function-Based Set Estimators," Working Papers 13-02, Ohio State University, Department of Economics.
    14. Gary Koop, 2004. "Modelling the evolution of distributions: an application to Major League baseball," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(4), pages 639-655, November.
    15. Magnac, Thierry & Maurin, Eric, 2007. "Identification and information in monotone binary models," Journal of Econometrics, Elsevier, vol. 139(1), pages 76-104, July.
    16. Sadat Reza & Paul Rilstone, 2016. "Semiparametric Efficiency Bounds and Efficient Estimation of Discrete Duration Models with Unspecified Hazard Rate," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 693-726, May.
    17. Aradillas-Lopez, Andres, 2012. "Pairwise-difference estimation of incomplete information games," Journal of Econometrics, Elsevier, vol. 168(1), pages 120-140.
    18. Mogens Fosgerau, 2014. "Nonparametric approaches to describing heterogeneity," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 11, pages 257-267, Edward Elgar Publishing.
    19. Xun Tang, 2009. "Binary Regressions with Bounded Median Dependence," PIER Working Paper Archive 09-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Michael P. Keane, 2011. "Labor Supply and Taxes: A Survey," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 961-1075, 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:eee:econom:v:112:y:2003:i:1:p:115-120. 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.