Skip to main content
Log in

The impact of estimation uncertainty on covariate effects in nonlinear models

Statistical Papers Aims and scope Submit manuscript

Cite this article


Covariate effects are a key consideration in model evaluation, forecasting, and policy analysis, yet their dependence on estimation uncertainty has been largely overlooked in previous work. We discuss several approaches to covariate effect evaluation in nonlinear models, examine computational and reporting issues, and illustrate the practical implications of ignoring estimation uncertainty in a simulation study and applications to educational attainment and crime. The evidence reveals that failing to consider estimation variability and relying solely on parameter point estimates may lead to nontrivial biases in covariate effects that can be exacerbated in certain settings, underscoring the pivotal role that estimation uncertainty can play in this context.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2


  • Brownstone D (2001) Discrete choice modeling for transportation. The leading edge, travel behaviour research. Pergamon, Amsterdam, pp 97–124

    Google Scholar 

  • Chib S, Greenberg E (1995) Understanding the Metropolis-Hastings algorithm. Am Stat 49:327–335

    Google Scholar 

  • Chib S, Jeliazkov I (2005) Accept–reject Metropolis-Hastings sampling and marginal likelihood estimation. Stat Neerl 59:30–44

    Article  MathSciNet  MATH  Google Scholar 

  • Chib S, Jeliazkov I (2006) Inference in semiparametric dynamic models for binary longitudinal data. J Am Stat Assoc 101:685–700

    Article  MathSciNet  MATH  Google Scholar 

  • Greene W (2008) Econometric Analysis, 6th edn. Prentice Hall, New Jersey

    Google Scholar 

  • Grogger J (1991) Certainty vs. severity of punishment. Econ Inquiry 29:297–309

    Article  Google Scholar 

  • Jeliazkov I, Graves J, Kutzbach M (2008) Fitting and comparison of models for multivariate ordinal outcomes. Adv Econom Bayesian Econom 23:115–156

    MATH  Google Scholar 

  • Tierney L (1994) Markov chains for exploring posterior distributions (with discussion). Ann Stat 22:1701–1762

    Article  MATH  Google Scholar 

  • Verlinda JA (2006) A comparison of two common approaches for estimating marginal effects in binary choice models. Appl Econ Lett 13:77–80

    Article  Google Scholar 

  • Wooldridge J (2002) Econometric analysis of cross section and panel data. MIT Press, Cambridge

    MATH  Google Scholar 

  • Wooldridge J (2009) Introductory Econometrics: a modern approach, 4th edn. South-Western, Mason

    Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Angela Vossmeyer.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jeliazkov, I., Vossmeyer, A. The impact of estimation uncertainty on covariate effects in nonlinear models. Stat Papers 59, 1031–1042 (2018).

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI:


JEL Classification