IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v72y2007i4p505-533.html
   My bibliography  Save this article

Multilevel Modeling with Correlated Effects

Author

Listed:
  • Jee-Seon Kim
  • Edward Frees

Abstract

No abstract is available for this item.

Suggested Citation

  • Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    • Handle: RePEc:spr:psycho:v:72:y:2007:i:4:p:505-533
    DOI: 10.1007/s11336-007-9008-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-007-9008-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11336-007-9008-1?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. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    2. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521828284.
    3. Ehrenberg, Ronald G. & Brewer, Dominic J., 1994. "Do school and teacher characteristics matter? Evidence from High School and Beyond," Economics of Education Review, Elsevier, vol. 13(1), pages 1-17, March.
    4. Peter Ebbes & Ulf Böckenholt & Michel Wedel, 2004. "Regressor and random‐effects dependencies in multilevel models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(2), pages 161-178, May.
    5. Andrew M. Jones, 2012. "health econometrics," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    6. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.
    7. Hanushek, Eric A. & Kain, John F. & Rivkin, Steven G., 2004. "Disruption versus Tiebout improvement: the costs and benefits of switching schools," Journal of Public Economics, Elsevier, vol. 88(9-10), pages 1721-1746, August.
    8. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.
    9. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    10. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    11. Fiona Steele, 2003. "Selection effects of source of contraceptive supply in an analysis of discontinuation of contraception: multilevel modelling when random effects are correlated with an explanatory variable," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(3), pages 407-423, October.
    12. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    13. Nigel Rice & Andrew Jones, 1997. "Multilevel models and health economics," Health Economics, John Wiley & Sons, Ltd., vol. 6(6), pages 561-575, November.
    14. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521535380.
    15. Breusch, Trevor S & Mizon, Grayham E & Schmidt, Peter, 1989. "Efficient Estimation Using Panel Data," Econometrica, Econometric Society, vol. 57(3), pages 695-700, May.
    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. Manzi, Jorge & San Martin, Ernesto & Van Bellegem, Sébastien, 2010. "School System Evaluation By Value-Added Analysis under Endogeneity," IDEI Working Papers 631, Institut d'Économie Industrielle (IDEI), Toulouse.
    2. Michael David Bates & Katherine E. Castellano & Sophia Rabe-Hesketh & Anders Skrondal, 2014. "Handling Correlations Between Covariates and Random Slopes in Multilevel Models," Journal of Educational and Behavioral Statistics, , vol. 39(6), pages 524-549, December.
    3. Fernando Rojas & Peter Wanke & Víctor Leiva & Mauricio Huerta & Carlos Martin-Barreiro, 2022. "Modeling Inventory Cost Savings and Supply Chain Success Factors: A Hybrid Robust Compromise Multi-Criteria Approach," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    4. M. D. R. Evans & Jonathan Kelley & S. M. C. Kelley & C. G. E. Kelley, 2019. "Rising Income Inequality During the Great Recession Had No Impact on Subjective Wellbeing in Europe, 2003–2012," Journal of Happiness Studies, Springer, vol. 20(1), pages 203-228, January.
    5. Acheampong, Albert & Elshandidy, Tamer, 2021. "Does soft information determine credit risk? Text-based evidence from European banks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    6. Pieroni, L. & d'Agostino, G., 2013. "Corruption and the effects of economic freedom," European Journal of Political Economy, Elsevier, vol. 29(C), pages 54-72.
    7. Cristina Bernini & Alessandro Tampieri, 2023. "Much Ado about Salary: A Comparison of Monetary and Non-Monetary Components of Job Satisfaction," Working Papers - Economics wp2023_06.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    8. Mark Ellison & Jon Bannister & Won Do Lee & Muhammad Salman Haleem, 2021. "Understanding policing demand and deployment through the lens of the city and with the application of big data," Urban Studies, Urban Studies Journal Limited, vol. 58(15), pages 3157-3175, November.
    9. Yi Xiang & David Soberman & Hubert Gatignon, 2022. "The Effect of Marketing Breadth and Competitive Spread on Category Growth," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 622-644, February.
    10. Yang Jiang & Yi-Chun (Chad) Ho & Xiangbin Yan & Yong Tan, 2022. "What’s in a “Username”? The Effect of Perceived Anonymity on Herding in Crowdfunding," Information Systems Research, INFORMS, vol. 33(1), pages 1-17, March.
    11. Yang, Juan & SICULAR, Terry & LAI, Desheng, 2014. "The changing determinants of high school attainment in rural China," China Economic Review, Elsevier, vol. 30(C), pages 551-566.
    12. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    13. Jorge Manzi & Ernesto San Martín & Sébastien Van Bellegem, 2014. "School System Evaluation by Value Added Analysis Under Endogeneity," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 130-153, January.
    14. Leonardo Grilli & Carla Rampichini, 2015. "Specification of random effects in multilevel models: a review," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 967-976, May.
    15. Viviana Amati & Felix Schönenberger & Tom A. B. Snijders, 2019. "Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 1068-1096, December.
    16. Jan-Michael Becker & Dorian Proksch & Christian M. Ringle, 2022. "Revisiting Gaussian copulas to handle endogenous regressors," Journal of the Academy of Marketing Science, Springer, vol. 50(1), pages 46-66, January.
    17. Chen, Chien-Ming & Chuang, Howard Hao-Chun, 2023. "Time to shift the shift: Performance effects of within-day cumulative service encounters in retail stores," Omega, Elsevier, vol. 119(C).
    18. Youmi Suk & Hyunseung Kang, 2022. "Robust Machine Learning for Treatment Effects in Multilevel Observational Studies Under Cluster-level Unmeasured Confounding," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 310-343, March.
    19. Krzysztof Zagorski & Mariah Evans & Jonathan Kelley & Katarzyna Piotrowska, 2014. "Does National Income Inequality Affect Individuals’ Quality of Life in Europe? Inequality, Happiness, Finances, and Health," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 117(3), pages 1089-1110, July.
    20. Yang, Yimin & Schmidt, Peter, 2021. "An econometric approach to the estimation of multi-level models," Journal of Econometrics, Elsevier, vol. 220(2), pages 532-543.
    21. Aleksey Oshchepkov & Anna Shirokanova, 2020. "Multilevel Modeling For Economists: Why, When And How," HSE Working papers WP BRP 233/EC/2020, National Research University Higher School of Economics.
    22. Katherine E. Castellano & Sophia Rabe-Hesketh & Anders Skrondal, 2014. "Composition, Context, and Endogeneity in School and Teacher Comparisons," Journal of Educational and Behavioral Statistics, , vol. 39(5), pages 333-367, October.

    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. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    2. Jee-Seon Kim & Edward Frees, 2006. "Omitted Variables in Multilevel Models," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 659-690, December.
    3. Doug J. Chung & Byungyeon Kim & Byoung G. Park, 2019. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove–Arrow Framework," Management Science, INFORMS, vol. 65(11), pages 5197-5218, November.
    4. Dalina-Maria Andrei, 2021. "Determinants of New Companies’ Formation in Romania at Regional Level. A Fixed Effects Model (FEM) Approach," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 18-27, August.
    5. Yang, Yimin, 2021. "Efficient estimation of multi-level models with strictly exogenous explanatory variables," Economics Letters, Elsevier, vol. 198(C).
    6. Park, Byeong U. & Sickles, Robin C. & Simar, Leopold, 2003. "Semiparametric-efficient estimation of AR(1) panel data models," Journal of Econometrics, Elsevier, vol. 117(2), pages 279-309, December.
    7. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    8. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    9. Said Hanchane & Audrey Dumas, 2008. "The Impact of Job Training on the Performances of Moroccan Firms: Empirical Evidence with Firm-Level Panel Data," Economics of Education Working Paper Series 0030, University of Zurich, Department of Business Administration (IBW).
    10. Giulio Fusco, 2022. "Climate Change and Food Security in the Northern and Eastern African Regions: A Panel Data Analysis," Sustainability, MDPI, vol. 14(19), pages 1-10, October.
    11. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    12. Antonio Ruiz Porras, 2016. "La investigación econométrica mediante paneles de datos:historia, modelos y usos en México," Archivos Revista Economía y Política., Facultad de Ciencias Económicas y Administrativas, Universidad de Cuenca., vol. 24, pages 11-32, Julio.
    13. Farbmacher, Helmut & Tauchmann, Harald, 2021. "Linear fixed-effects estimation with non-repeated outcomes," FAU Discussion Papers in Economics 03/2021, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2021.
    14. Chay, Kenneth Y. & Lee, David S., 2000. "Changes in relative wages in the 1980s Returns to observed and unobserved skills and black-white wage differentials," Journal of Econometrics, Elsevier, vol. 99(1), pages 1-38, November.
    15. Park, B. U. & Sickles, R. C. & Simar, L., 1998. "Stochastic panel frontiers: A semiparametric approach," Journal of Econometrics, Elsevier, vol. 84(2), pages 273-301, June.
    16. Jung Hur & Rasyad A. Parinduri & Yohanes E. Riyanto, 2011. "Cross‐Border M&A Inflows And Quality Of Country Governance: Developing Versus Developed Countries," Pacific Economic Review, Wiley Blackwell, vol. 16(5), pages 638-655, December.
    17. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    18. Pillai N., Vijayamohanan, 2016. "Panel Data Analysis with Stata Part 1 Fixed Effects and Random Effects Models," MPRA Paper 76869, University Library of Munich, Germany.
    19. M. Hashem Pesaran & Qiankun Zhou, 2018. "Estimation of time-invariant effects in static panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1137-1171, November.
    20. Piotr Ciżkowicz & Andrzej Rzońca & Rafał Trzeciakowski, 2015. "Windfall of Low Interest Payments and Fiscal Sustainability in the Euro Area: Analysis through Panel Fiscal Reaction Functions," Kyklos, Wiley Blackwell, vol. 68(4), pages 475-510, November.

    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:spr:psycho:v:72:y:2007:i:4:p:505-533. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.