IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v45y2015icp93-98.html
   My bibliography  Save this article

Two applications of the random coefficient procedure: Correcting for misspecifications in a small area level model and resolving Simpson's paradox

Author

Listed:
  • Swamy, P.A.V.B.
  • Mehta, J.S.
  • Tavlas, G.S.
  • Hall, S.G.

Abstract

We apply a random-coefficient framework to deal with two problems frequently encountered in applied work. First, we use a real-world relationship to derive a sub-relationship among fewer variables without introducing any specification error to correct misspecifications in a small area level model. Second, we then use this framework to resolve Simpson's paradox. We show that this paradox does not arise if a statistical relationship between a pair of variables is derived from the corresponding real-world relationship involving all relevant variables, including the original pair, without introducing a single specification error.

Suggested Citation

  • Swamy, P.A.V.B. & Mehta, J.S. & Tavlas, G.S. & Hall, S.G., 2015. "Two applications of the random coefficient procedure: Correcting for misspecifications in a small area level model and resolving Simpson's paradox," Economic Modelling, Elsevier, vol. 45(C), pages 93-98.
    • Handle: RePEc:eee:ecmode:v:45:y:2015:i:c:p:93-98
    DOI: 10.1016/j.econmod.2014.10.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999314004179
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2014.10.053?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. Basmann, R. L., 1988. "Causality tests and observationally equivalent representations of econometric models," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 69-104.
    2. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, December.
    3. Skyrms, Brian, 1988. "Probability and causation," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 53-68.
    4. Pratt, John W. & Schlaifer, Robert, 1988. "On the interpretation and observation of laws," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 23-52.
    5. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-170, February.
    6. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    7. Judea Pearl, 2014. "Comment: Understanding Simpson's Paradox," The American Statistician, Taylor & Francis Journals, vol. 68(1), pages 8-13, February.
    8. Swamy P. A. V. B. & Tavlas George S & Hall Stephen G. F. & Hondroyiannis George, 2010. "Estimation of Parameters in the Presence of Model Misspecification and Measurement Error," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-35, May.
    9. Timothy W. Armistead, 2014. "Resurrecting the Third Variable: A Critique of Pearl's Causal Analysis of Simpson's Paradox," The American Statistician, Taylor & Francis Journals, vol. 68(1), pages 1-7, February.
    10. Jun Ma & Mark Wohar (ed.), 2014. "Recent Advances in Estimating Nonlinear Models," Springer Books, Springer, edition 127, number 978-1-4614-8060-0, July.
    11. P. Swamy & Stephen Hall, 2012. "Measurement of causal effects," Economic Change and Restructuring, Springer, vol. 45(1), pages 3-23, February.
    12. Keli Liu & Xiao-Li Meng, 2014. "Comment: A Fruitful Resolution to Simpson's Paradox via Multiresolution Inference," The American Statistician, Taylor & Francis Journals, vol. 68(1), pages 17-29, February.
    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. P.A.V.B. Swamy & Jatinder S. Mehta & I-Lok Chang, 2017. "Endogeneity, Time-Varying Coefficients, and Incorrect vs. Correct Ways of Specifying the Error Terms of Econometric Models," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    2. Abonazel, Mohamed R., 2016. "Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties," MPRA Paper 72586, University Library of Munich, Germany.
    3. P.A.V.B. Swamy & Stephen G. Hall & George S. Tavlas & I-Lok Chang & Heather D. Gibson & William H. Greene & Jatinder S. Mehta, 2016. "A Method for Measuring Treatment Effects on the Treated without Randomization," Econometrics, MDPI, vol. 4(2), pages 1-23, March.
    4. Swamy Paravastu & Peter Muehlen & Jatinder Singh Mehta & I-Lok Chang, 2022. "The State Of Econometrics After John W. Pratt, Robert Schlaifer, Brian Skyrms, And Robert L. Basmann," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 627-654, November.

    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. P.A.V.B. Swamy & I-Lok Chang & Jatinder S. Mehta & William H. Greene & Stephen G. Hall & George S. Tavlas, 2016. "Removing Specification Errors from the Usual Formulation of Binary Choice Models," Econometrics, MDPI, vol. 4(2), pages 1-21, June.
    2. P.A.V.B. Swamy & Stephen G. Hall & George S. Tavlas & I-Lok Chang & Heather D. Gibson & William H. Greene & Jatinder S. Mehta, 2016. "A Method for Measuring Treatment Effects on the Treated without Randomization," Econometrics, MDPI, vol. 4(2), pages 1-23, March.
    3. Swamy Paravastu & Peter Muehlen & Jatinder Singh Mehta & I-Lok Chang, 2022. "The State Of Econometrics After John W. Pratt, Robert Schlaifer, Brian Skyrms, And Robert L. Basmann," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 627-654, November.
    4. Hall, Stephen G. & Swamy, P. A. V. B. & Tavlas, George S., 2017. "Time-Varying Coefficient Models: A Proposal For Selecting The Coefficient Driver Sets," Macroeconomic Dynamics, Cambridge University Press, vol. 21(5), pages 1158-1174, July.
    5. P. Swamy & Stephen Hall, 2012. "Measurement of causal effects," Economic Change and Restructuring, Springer, vol. 45(1), pages 3-23, February.
    6. Hall, Stephen G. & Klein, Lawrence R. & Tavlas, George S. & Zellner, Arnold, 2010. "Introduction: P.A.V.B. Swamy's contribution to Econometrics," Economic Modelling, Elsevier, vol. 27(6), pages 1338-1344, November.
    7. Stephen Hall & George Hondroyiannis & P. Swamy & George Tavlas, 2010. "The Fisher Effect Puzzle: A Case of Non-Linear Relationship?," Open Economies Review, Springer, vol. 21(1), pages 91-103, February.
    8. Aris Spanos, 2021. "Yule–Simpson’s paradox: the probabilistic versus the empirical conundrum," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 605-635, June.
    9. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2020. "Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis," Econometrica, Econometric Society, vol. 88(1), pages 265-296, January.
    10. Tobias Hartl & Roland Jucknewitz, 2022. "Approximate state space modelling of unobserved fractional components," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
    11. P.A.V.B. Swamy & Jatinder S. Mehta & I-Lok Chang, 2017. "Endogeneity, Time-Varying Coefficients, and Incorrect vs. Correct Ways of Specifying the Error Terms of Econometric Models," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    12. Richard H. Spady & Sami Stouli, 2018. "Simultaneous Mean-Variance Regression," Bristol Economics Discussion Papers 18/697, School of Economics, University of Bristol, UK.
    13. Dennis J. Aigner, 1988. "Symposium on Econometric Methodology 1 On Econometric Methodology and the Search for Causal Laws," The Economic Record, The Economic Society of Australia, vol. 64(4), pages 323-326, December.
    14. Swamy, P.A.V.B. & Yaghi, Wisam & Mehta, Jatinder S. & Chang, I-Lok, 2007. "Empirical best linear unbiased prediction in misspecified and improved panel data models with an application to gasoline demand," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3381-3392, April.
    15. Swamy, P.A.V.B. & Tavlas, George S. & Chang, I-Lok, 2005. "How stable are monetary policy rules: estimating the time-varying coefficients in monetary policy reaction function for the US," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 575-590, April.
    16. Miguel A. Delgado & Thomas J. Kniesner, 1997. "Count Data Models With Variance Of Unknown Form: An Application To A Hedonic Model Of Worker Absenteeism," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 41-49, February.
    17. Creal, Drew D. & Wu, Jing Cynthia, 2015. "Estimation of affine term structure models with spanned or unspanned stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 60-81.
    18. Stephen Hall & P. Swamy & George Tavlas, 2012. "Generalized cointegration: a new concept with an application to health expenditure and health outcomes," Empirical Economics, Springer, vol. 42(2), pages 603-618, April.
    19. Giovanni Angelini & Giuseppe Cavaliere & Luca Fanelli, 2022. "Bootstrap inference and diagnostics in state space models: With applications to dynamic macro models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 3-22, January.
    20. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2017. "Sampling-based vs. Design-based Uncertainty in Regression Analysis," Papers 1706.01778, arXiv.org, revised Jun 2019.

    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:ecmode:v:45:y:2015:i:c:p:93-98. 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/inca/30411 .

    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.