IDEAS home Printed from https://ideas.repec.org/p/han/dpaper/dp-513.html
   My bibliography  Save this paper

Methods in empirical economics - a selective review with applications

Author

Listed:
  • Hübler, Olaf

Abstract

This paper presents some selective aspects of standard econometric methods and of new developments in econometrics that are important for applications with microeconomic data. The range includes variance estimators, measurement of outliers, problems of partially identified parameters, nonlinear models, possibilities of instrumental variables, panel methods for models with time-invariant regressors, difference-in-differences estimators, matching procedures, treatment effects in quantile regression analysis and regression discontinuity approaches. These methods are applied to production functions with IAB establishment panel data.

Suggested Citation

  • Hübler, Olaf, 2013. "Methods in empirical economics - a selective review with applications," Hannover Economic Papers (HEP) dp-513, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-513
    as

    Download full text from publisher

    File URL: http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-513.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    2. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    3. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
    4. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    5. Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen & John C. Chao & Norman R. Swanson, 2012. "Instrumental variable estimation with heteroskedasticity and many instruments," Quantitative Economics, Econometric Society, vol. 3(2), pages 211-255, July.
    6. Walter Krämer, 2011. "The Cult of Statistical Significance – What Economists Should and Should Not Do to Make their Data Talk," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 131(3), pages 455-468.
    7. repec:bla:jecsur:v:16:y:2002:i:4:p:569-89 is not listed on IDEAS
    8. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, January.
    9. Jörg Drechsler, 2011. "Multiple imputation in practice—a case study using a complex German establishment survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 1-26, March.
    10. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    11. Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 217-232, March.
    12. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
    13. Joseph P. Romano & Azeem M. Shaikh, 2010. "Inference for the Identified Set in Partially Identified Econometric Models," Econometrica, Econometric Society, vol. 78(1), pages 169-211, January.
    14. Francisco Cribari-Neto & Wilton Silva, 2011. "A new heteroskedasticity-consistent covariance matrix estimator for the linear regression model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(2), pages 129-146, June.
    15. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    16. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, July.
    17. repec:ran:wpaper:710-1 is not listed on IDEAS
    18. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    19. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
    20. Thomas Bauer & Mathias Sinning, 2008. "An extension of the Blinder–Oaxaca decomposition to nonlinear models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(2), pages 197-206, May.
    21. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    22. John Shea, 1997. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 348-352, May.
    23. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    24. Peter E. Kennedy, 2002. "Sinning in the Basement: What are the Rules? The Ten Commandments of Applied Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 16(4), pages 569-589, September.
    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. Hübler, Olaf, 2014. "Estimation of standard errors and treatment effects in empirical economics : methods and applications," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 47(1-2), pages 43-62.
    2. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    3. Xavier D’Haultfoeuille & Pauline Givord, 2014. "La régression quantile en pratique," Économie et Statistique, Programme National Persée, vol. 471(1), pages 85-111.
    4. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    5. 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.
    6. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    7. Victor Chernozhukov & Roberto Rigobon & Thomas M. Stoker, 2010. "Set identification and sensitivity analysis with Tobin regressors," Quantitative Economics, Econometric Society, vol. 1(2), pages 255-277, November.
    8. Anil K. Bera & Antonio F. Galvao Jr. & Gabriel V. Montes-Rojas & Sung Y. Park, 2014. "Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression," World Scientific Book Chapters, in: Kaddour Hadri & William Mikhail (ed.), Econometric Methods and Their Applications in Finance, Macro and Related Fields, chapter 7, pages 167-199, World Scientific Publishing Co. Pte. Ltd..
    9. Christoph Rothe, 2012. "Partial Distributional Policy Effects," Econometrica, Econometric Society, vol. 80(5), pages 2269-2301, September.
    10. Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
    11. Parente Paulo M.D.C. & Santos Silva João M.C., 2016. "Quantile Regression with Clustered Data," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 1-15, January.
    12. Pedro H. C. Sant'Anna, 2016. "Program Evaluation with Right-Censored Data," Papers 1604.02642, arXiv.org.
    13. Brantly Callaway & Weige Huang, 2020. "Distributional Effects of a Continuous Treatment with an Application on Intergenerational Mobility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 808-842, August.
    14. Sung Jae Jun & Yoonseok Lee & Youngki Shin, 2016. "Treatment Effects With Unobserved Heterogeneity: A Set Identification Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 302-311, April.
    15. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    16. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.
    17. repec:esx:essedp:728 is not listed on IDEAS
    18. Strittmatter, Anthony, 2019. "Heterogeneous earnings effects of the job corps by gender: A translated quantile approach," Labour Economics, Elsevier, vol. 61(C).
    19. Rok Spruk & Mitja Kovac, 2018. "Inefficient Growth," Review of Economics and Institutions, Università di Perugia, vol. 9(2).
    20. Katarzyna Jabłońska, 2018. "Dealing With Heteroskedasticity Within The Modeling Of The Quality Of Life Of Older People," Statistics in Transition New Series, Polish Statistical Association, vol. 19(3), pages 423-452, September.
    21. Frandsen, Brigham R. & Frölich, Markus & Melly, Blaise, 2012. "Quantile treatment effects in the regression discontinuity design," Journal of Econometrics, Elsevier, vol. 168(2), pages 382-395.

    More about this item

    Keywords

    Significance; standard errors; outliers; influential observations; partially identified parameters; unobserved heterogeneity; instrumental variables; panel estimators; quantile regressions; causality; treatment effects; DiD estimators; regression discontinuity;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • J53 - Labor and Demographic Economics - - Labor-Management Relations, Trade Unions, and Collective Bargaining - - - Labor-Management Relations; Industrial Jurisprudence

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:han:dpaper:dp-513. 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: Heidrich, Christian (email available below). General contact details of provider: https://edirc.repec.org/data/fwhande.html .

    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.