IDEAS home Printed from https://ideas.repec.org/p/zbw/iwqwdp/092019.html
   My bibliography  Save this paper

Fixed-effects estimation of the linear discrete-time hazard model: An adjusted first-differences estimator

Author

Listed:
  • Tauchmann, Harald

Abstract

No abstract is available for this item.

Suggested Citation

  • Tauchmann, Harald, 2019. "Fixed-effects estimation of the linear discrete-time hazard model: An adjusted first-differences estimator," FAU Discussion Papers in Economics 09/2019, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    • Handle: RePEc:zbw:iwqwdp:092019
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Jenkins, Stephen P, 1995. "Easy Estimation Methods for Discrete-Time Duration Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(1), pages 129-138, February.
    2. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    3. Horowitz, Joel L. & Lee, Sokbae, 2004. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," Journal of Econometrics, Elsevier, vol. 119(1), pages 155-198, March.
    4. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    5. William Greene, 2004. "The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 98-119, June.
    6. Antonio Ciccone, 2013. "Estimating the Effect of Transitory Economic Shocks on Civil Conflict," Review of Economics and Institutions, Università di Perugia, vol. 4(2).
    7. Horrace, William C. & Oaxaca, Ronald L., 2006. "Results on the bias and inconsistency of ordinary least squares for the linear probability model," Economics Letters, Elsevier, vol. 90(3), pages 321-327, March.
    8. 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.
    9. Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
    10. Dan Bogart, 2018. "Party Connections, Interest Groups and the Slow Diffusion of Infrastructure: Evidence from Britain's First Transport Revolution," Economic Journal, Royal Economic Society, vol. 128(609), pages 541-575, March.
    11. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    12. Antonio Ciccone, 2011. "Economic Shocks and Civil Conflict: A Comment," American Economic Journal: Applied Economics, American Economic Association, vol. 3(4), pages 215-227, October.
    13. Ana M. Fernandes & Caroline Paunov, 2015. "The Risks of Innovation: Are Innovating Firms Less Likely to Die?," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 638-653, July.
    14. Bera, Anil K. & Galvao, Antonio F. & Wang, Liang & Xiao, Zhijie, 2016. "A New Characterization Of The Normal Distribution And Test For Normality," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1216-1252, October.
    15. Paul D. Allison, 1994. "Using Panel Data to Estimate the Effects of Events," Sociological Methods & Research, , vol. 23(2), pages 174-199, November.
    16. Kristine M. Brown & Ron A. Laschever, 2012. "When They're Sixty-Four: Peer Effects and the Timing of Retirement," American Economic Journal: Applied Economics, American Economic Association, vol. 4(3), pages 90-115, July.
    17. Stammann, Amrei & Heiß, Florian & McFadden, Daniel, 2016. "Estimating Fixed Effects Logit Models with Large Panel Data," VfS Annual Conference 2016 (Augsburg): Demographic Change 145837, Verein für Socialpolitik / German Economic Association.
    18. Tor Jacobson & Erik Schedvin, 2015. "Trade Credit and the Propagation of Corporate Failure: An Empirical Analysis," Econometrica, Econometric Society, vol. 83(4), pages 1315-1371, July.
    19. Javier Alejo & Anil Bera & Antonio Galvao & Gabriel Montes-Rojas & Zhijie Xiao, 2016. "Tests for normality based on the quantile-mean covariance," Stata Journal, StataCorp LP, vol. 16(4), pages 1039-1057, December.
    20. Edward Miguel & Shanker Satyanath & Ernest Sergenti, 2004. "Economic Shocks and Civil Conflict: An Instrumental Variables Approach," Journal of Political Economy, University of Chicago Press, vol. 112(4), pages 725-753, August.
    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. 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.
    2. Achim Ahrens, 2015. "Civil conflicts in Africa: Climate, economic shocks, nighttime lights and spill-over effects," SEEC Discussion Papers 1501, Spatial Economics and Econometrics Centre, Heriot Watt University.
    3. Jean-François Maystadt & Margherita Calderone & Liangzhi You, 2015. "Local warming and violent conflict in North and South Sudan," Journal of Economic Geography, Oxford University Press, vol. 15(3), pages 649-671.
    4. Markus Brückner & Antonio Ciccone, 2011. "Rain and the Democratic Window of Opportunity," Econometrica, Econometric Society, vol. 79(3), pages 923-947, May.
    5. P. Dorian Owen, 2017. "Evaluating Ingenious Instruments for Fundamental Determinants of Long-Run Economic Growth and Development," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    6. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    7. Muhammad Kabir Salihu & Andrea Guariso, 2017. "Rainfall inequality, trust and civil conflict in Nigeria," Working Papers 205618510, Lancaster University Management School, Economics Department.
    8. Manuel Denzer & Constantin Weiser, 2021. "Beyond F-statistic - A General Approach for Assessing Weak Identification," Working Papers 2107, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    9. Ciccone, Antonio, 2018. "International Commodity Prices and Civil War Outbreak: New Evidence for Sub-Saharan Africa and Beyond," CEPR Discussion Papers 12625, C.E.P.R. Discussion Papers.
    10. Liu, De-Chih & Chang, Yu-Chien, 2022. "Systematic variations in exchange rate returns," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 569-583.
    11. Phoebe W. Ishak & Mohammad Reza Farzanegan, 2022. "Oil price shocks, protest, and the shadow economy: Is there a mitigation effect?," Economics and Politics, Wiley Blackwell, vol. 34(2), pages 298-321, July.
    12. Gerling Lena, 2017. "Urban Protests, Coups d’état and Post-Coup Regime Change," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 23(4), pages 1-8, December.
    13. Mathieu Couttenier & Raphael Soubeyran, 2014. "Drought and Civil War In Sub‐Saharan Africa," Economic Journal, Royal Economic Society, vol. 124(575), pages 201-244, March.
      • Couttenier, Mathieu & Hofstetter, Annie & Soubeyran, Raphael, 2013. "Drought and civil war in sub-Saharan Africa," INRAE Sciences Sociales, Institut national de recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2), vol. 2013, pages 1-6, March.
    14. Castells-Quintana, David & Lopez-Uribe, Maria del Pilar & McDermott, Thomas K.J., 2022. "Population displacement and urban conflict: Global evidence from more than 3300 flood events," Journal of Development Economics, Elsevier, vol. 158(C).
    15. William W. Olney & Dario Pozzoli, 2021. "The Impact of Immigration on Firm-Level Offshoring," The Review of Economics and Statistics, MIT Press, vol. 103(1), pages 177-195, March.
    16. Oeindrila Dube & Joshua E. Blumenstock & Michael Callen & Michael J. Callen, 2022. "Measuring Religion from Behavior: Climate Shocks and Religious Adherence in Afghanistan," CESifo Working Paper Series 10114, CESifo.
    17. Jacob Moscona & Nathan Nunn & James A. Robinson, 2020. "Segmentary Lineage Organization and Conflict in Sub‐Saharan Africa," Econometrica, Econometric Society, vol. 88(5), pages 1999-2036, September.
    18. Unfried, Kerstin & Kis-Katos, Krisztina & Poser, Tilman, 2022. "Water scarcity and social conflict," Journal of Environmental Economics and Management, Elsevier, vol. 113(C).
    19. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    20. Joshua D. Angrist & Jörn-Steffen Pischke, 2017. "Undergraduate Econometrics Instruction: Through Our Classes, Darkly," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 125-144, Spring.

    More about this item

    Keywords

    linear probability model; individual fixed effects; short panel; discrete-time hazard; duration analysis; survival analysis; non-repeated event; absorbing state; survival bias; misscaling bias;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

    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:zbw:iwqwdp:092019. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vierlde.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.