IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0231349.html
   My bibliography  Save this article

Interpretation and identification of within-unit and cross-sectional variation in panel data models

Author

Listed:
  • Jonathan Kropko
  • Robert Kubinec

Abstract

While fixed effects (FE) models are often employed to address potential omitted variables, we argue that these models’ real utility is in isolating a particular dimension of variance from panel data for analysis. In addition, we show through novel mathematical decomposition and simulation that only one-way FE models cleanly capture either the over-time or cross-sectional dimensions in panel data, while the two-way FE model unhelpfully combines within-unit and cross-sectional variation in a way that produces un-interpretable answers. In fact, as we show in this paper, if we begin with the interpretation that many researchers wrongly assign to the two-way FE model—that it represents a single estimate of X on Y while accounting for unit-level heterogeneity and time shocks—the two-way FE specification is statistically unidentified, a fact that statistical software packages like R and Stata obscure through internal matrix processing.

Suggested Citation

  • Jonathan Kropko & Robert Kubinec, 2020. "Interpretation and identification of within-unit and cross-sectional variation in panel data models," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-22, April.
    • Handle: RePEc:plo:pone00:0231349
    DOI: 10.1371/journal.pone.0231349
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231349
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0231349&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0231349?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
    ---><---

    References listed on IDEAS

    as
    1. Daniela Donno, 2013. "Elections and Democratization in Authoritarian Regimes," American Journal of Political Science, John Wiley & Sons, vol. 57(3), pages 703-716, July.
    2. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    4. Andrew Goodman-Bacon, 2018. "Difference-in-Differences with Variation in Treatment Timing," NBER Working Papers 25018, National Bureau of Economic Research, Inc.
    5. Shahidur R. Khandker & Gayatri B. Koolwal & Hussain A. Samad, . "Handbook on Impact Evaluation : Quantitative Methods and Practices," World Bank Publications, The World Bank, number 2693, September.
    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. Nour Mohamad Fayad, 2024. "The Causality Between Corruption and Economic Growth in MENA Countries: A Dynamic Panel-Data Analysis," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 14(1), pages 28-49.
    2. Yugang He, 2024. "E-commerce and foreign direct investment: pioneering a new era of trade strategies," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    3. Robert Kubinec & David Reinstein, 2023. "Evaluation 1 of "Does the Squeaky Wheel Get More Grease? The Direct and Indirect Effects of Citizen Participation on Environmental Governance in China" (Buntaine et al)," The Unjournal Evaluations 2023-91, The Unjournal.
    4. Maria Elena Bontempi & Jan Ditzen, 2023. "GMM-lev estimation and individual heterogeneity: Monte Carlo evidence and empirical applications," Papers 2312.00399, arXiv.org, revised Dec 2023.
    5. Yugang He, 2024. "Artificial intelligence and socioeconomic forces: transforming the landscape of religion," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    6. Ugur, Mehmet, 2024. "Innovation, market power and the labour share: Evidence from OECD industries," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    7. Luis Costa & Vivek F. Farias & Patricio Foncea & Jingyuan (Donna) Gan & Ayush Garg & Ivo Rosa Montenegro & Kumarjit Pathak & Tianyi Peng & Dusan Popovic, 2023. "Generalized Synthetic Control for TestOps at ABI: Models, Algorithms, and Infrastructure," Interfaces, INFORMS, vol. 53(5), pages 336-349, September.

    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. Backson Mwangi & Ibrahim Macharia & Eric Bett, 2021. "Ex-post Impact Evaluation of Improved Sorghum Varieties on Poverty Reduction in Kenya: A Counterfactual Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 447-467, April.
    2. Marchesano, Katia & Musella, Marco, 2020. "Does volunteer work affect life satisfaction of participants with chronic functional limitations? An empirical investigation," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    3. Giulia Bettin & Isabella Giorgetti & Stefano Staffolani, 2024. "The impact of Covid-19 lockdown on the gender gap in the Italian labour market," Review of Economics of the Household, Springer, vol. 22(1), pages 1-33, March.
    4. Yin, Runsheng & Zulu, Leo & Qi, Jiaguo & Freudenberger, Mark & Sommerville, Matthew, 2016. "Empirical linkages between devolved tenure systems and forest conditions: Challenges, findings, and recommendations," Forest Policy and Economics, Elsevier, vol. 73(C), pages 294-299.
    5. Arraiz, Irani & Calero, Carla & Jon, Songqing & Peralta, Alexandra, 2015. "Planting the seeds: The impact of training on mando producers in Haiti," 2015 Conference, August 9-14, 2015, Milan, Italy 212622, International Association of Agricultural Economists.
    6. Liu, Zhaoyang & Gong, Yazhen & Kontoleon, Andreas, 2018. "How do Payments for Environmental Services Affect Land Tenure? Theory and Evidence From China," Ecological Economics, Elsevier, vol. 144(C), pages 195-213.
    7. Francisco Pedraja-Chaparro & Daniel Santín & Rosa Simancas, 2022. "Show me the money! The impact of a conditional cash transfer on educational achievement," Empirical Economics, Springer, vol. 63(5), pages 2721-2750, November.
    8. Arraiz, Irani & Calero, Carla & Jon, Songqing & Peralta, Alexandra, 2015. "Planting the seeds: The impact of training on mando producers in Haiti," 2015 Conference, August 9-14, 2015, Milan, Italy 212622, International Association of Agricultural Economists.
    9. Alexandra Peralta & Scott M. Swinton & Songqing Jin, 2018. "The Secret to Getting Ahead Is Getting Started: Early Impacts of a Rural Development Project," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    10. Weyori, A.E. & Waibel, H. & Liebenehm, S., 2018. "Livestock interventions and farmer welfare in sub-Saharan Africa: A panel data analysis from Togo," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277379, International Association of Agricultural Economists.
    11. Sènakpon Fidèle A. Dedehouanou & Luca Tiberti & Hilaire G. Houeninvo & Djohodo Inès Monwanou, 2019. "Working while studying: Employment premium or penalty for youth in Benin?," Working Papers PMMA 2019-03, PEP-PMMA.
    12. Higgins, Daniel & Arslan, Aslihan & Winters, Paul, 2021. "What role can small-scale irrigation play in promoting inclusive rural transformation? Evidence from smallholder rice farmers in the Philippines," Agricultural Water Management, Elsevier, vol. 243(C).
    13. N'dri, Lasme Mathieu & Kakinaka, Makoto, 2020. "Financial inclusion, mobile money, and individual welfare: The case of Burkina Faso," Telecommunications Policy, Elsevier, vol. 44(3).
    14. Stacy, Brian, 2014. "Ranking Teachers when Teacher Value-Added is Heterogeneous Across Students," EconStor Preprints 104743, ZBW - Leibniz Information Centre for Economics.
    15. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    16. Stefan Boes & Michael Gerfin, 2016. "Does Full Insurance Increase the Demand for Health Care?," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1483-1496, November.
    17. Mullahy, John, 2024. "Analyzing health outcomes measured as bounded counts," Journal of Health Economics, Elsevier, vol. 95(C).
    18. Kaiyatsa, Stevier & Jumbe, Charles & Ricker-Gilbert, Jacob, 2017. "Supply-side Crowding-out and Crowding-in Effects of Malawi’s Farm Input Subsidy Program on Private-sector Input Marketing: A Quasi-experimental Field Study," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258135, Agricultural and Applied Economics Association.
    19. Del Prete, Davide & Ghins, Léopold & Magrini, Emiliano & Pauw, Karl, 2019. "Land consolidation, specialization and household diets: Evidence from Rwanda," Food Policy, Elsevier, vol. 83(C), pages 139-149.
    20. Tymon Słoczyński, 2022. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," The Review of Economics and Statistics, MIT Press, vol. 104(3), pages 501-509, May.

    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:plo:pone00:0231349. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.