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Centering and reference groups for estimates of fixed effects: Modifications to felsdvreg

Author

Listed:
  • Kata Mihaly

    (The RAND Corporation)

  • Daniel F. McCaffrey

    (The RAND Corporation)

  • J. R. Lockwood

    (The RAND Corporation)

  • Tim R. Sass

    (Florida State University)

Abstract
Availability of large, multilevel longitudinal databases in various fields including labor economics (with workers and firms observed over time) and ed- ucation research (with students and teachers observed over time) has increased the application of panel-data models with multiple levels of fixed-effects. Existing software routines for fitting fixed-effects models were not designed for applications in which the primary interest is obtaining estimates of any of the fixed-effects parameters. Such routines typically report estimates of fixed effects relative to arbitrary holdout units. Contrasts to holdout units are not ideal in cases where the fixed-effects parameters are of interest because they can change capriciously, they do not correspond to the structural parameters that are typically of inter- est, and they are inappropriate for empirical Bayes (shrinkage) estimation. We develop an improved parameterization of fixed-effects models using sum-to-zero constraints that provides estimates of fixed effects relative to mean effects within well-defined reference groups (e.g., all firms of a given type or all teachers of a given grade) and provides standard errors for those estimates that are appropriate for shrinkage estimation. We implement our parameterization in a Stata routine called felsdvregdm by modifying the felsdvreg routine designed for fitting high- dimensional fixed-effects models. We demonstrate our routine with an example dataset from the Florida Education Data Warehouse. Copyright 2010 by StataCorp LP.

Suggested Citation

  • Kata Mihaly & Daniel F. McCaffrey & J. R. Lockwood & Tim R. Sass, 2010. "Centering and reference groups for estimates of fixed effects: Modifications to felsdvreg," Stata Journal, StataCorp LP, vol. 10(1), pages 82-103, March.
    • Handle: RePEc:tsj:stataj:v:10:y:2010:i:1:p:82-103
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    References listed on IDEAS

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    Cited by:

    1. Elizabeth Dhuey & Justin Smith, 2018. "How school principals influence student learning," Empirical Economics, Springer, vol. 54(2), pages 851-882, March.
    2. Goldhaber, Dan & Liddle, Stephanie & Theobald, Roddy, 2013. "The gateway to the profession: Assessing teacher preparation programs based on student achievement," Economics of Education Review, Elsevier, vol. 34(C), pages 29-44.
    3. Alexander Ahammer & Thomas Schober, 2020. "Exploring variations in health‐care expenditures—What is the role of practice styles?," Health Economics, John Wiley & Sons, Ltd., vol. 29(6), pages 683-699, June.
    4. Sacarny, Adam, 2018. "Adoption and learning across hospitals: The case of a revenue-generating practice," Journal of Health Economics, Elsevier, vol. 60(C), pages 142-164.
    5. Elizabeth Dhuey & Justin Smith, 2014. "How important are school principals in the production of student achievement?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 47(2), pages 634-663, May.
    6. Koedel, Cory & Mihaly, Kata & Rockoff, Jonah E., 2015. "Value-added modeling: A review," Economics of Education Review, Elsevier, vol. 47(C), pages 180-195.
    7. Carlson, Deven & Lavertu, Stéphane, 2016. "Charter school closure and student achievement: Evidence from Ohio," Journal of Urban Economics, Elsevier, vol. 95(C), pages 31-48.
    8. Sandra Cavaco & Patricia Crifo & Antoine Rebérioux & Gwenael Roudaut, 2014. "Independent directors: less informed, but better selected? New evidence from a two-way director-firm fixed effect model," Working Papers hal-04141284, HAL.
    9. Kevin C. Bastian & Gary T. Henry & Charles L. Thompson, 2013. "Incorporating Access to More Effective Teachers into Assessments of Educational Resource Equity," Education Finance and Policy, MIT Press, vol. 8(4), pages 560-580, October.
    10. Bartanen, Brendan & Husain, Aliza N., 2022. "Connected networks in principal value-added models," Economics of Education Review, Elsevier, vol. 90(C).
    11. Goel, Deepti & Barooah, Bidisha, 2018. "Drivers of Student Performance: Evidence from Higher Secondary Public Schools in Delhi," GLO Discussion Paper Series 231, Global Labor Organization (GLO).
    12. Sass, Tim R. & Hannaway, Jane & Xu, Zeyu & Figlio, David N. & Feng, Li, 2012. "Value added of teachers in high-poverty schools and lower poverty schools," Journal of Urban Economics, Elsevier, vol. 72(2), pages 104-122.
    13. Cavaco, Sandra & Crifo, Patricia & Rebérioux, Antoine & Roudaut, Gwenael, 2017. "Independent directors: Less informed but better selected than affiliated board members?," Journal of Corporate Finance, Elsevier, vol. 43(C), pages 106-121.
    14. Goldhaber, Dan & Walch, Joe, 2012. "Strategic pay reform: A student outcomes-based evaluation of Denver's ProComp teacher pay initiative," Economics of Education Review, Elsevier, vol. 31(6), pages 1067-1083.
    15. Andrew McEachin & Allison Atteberry, 2017. "The Impact of Summer Learning Loss on Measures of School Performance," Education Finance and Policy, MIT Press, vol. 12(4), pages 468-491, Fall.
    16. J. R. Lockwood & Daniel F. McCaffrey, 2014. "Correcting for Test Score Measurement Error in ANCOVA Models for Estimating Treatment Effects," Journal of Educational and Behavioral Statistics, , vol. 39(1), pages 22-52, February.
    17. Harris, Douglas N. & Sass, Tim R., 2014. "Skills, productivity and the evaluation of teacher performance," Economics of Education Review, Elsevier, vol. 40(C), pages 183-204.

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