Home > Research > Publications & Outputs > Estimating outcomes in the presence of endogene...

Electronic data

  • rdpaper_final

    Accepted author manuscript, 939 KB, PDF document

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


Text available via DOI:

View graph of relations

Estimating outcomes in the presence of endogeneity and measurement error with an application to R&D

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>30/04/2023
<mark>Journal</mark>Quarterly Review of Economics and Finance
Number of pages17
Pages (from-to)278-294
Publication StatusPublished
Early online date14/02/23
<mark>Original language</mark>English


We adopt a Bayesian econometric technique to address issues of endogeneity and measurement error when estimating outcomes while also tackling censoring. We motivate our study based on the theoretical framework laid out by Dasgupta and Stiglitz [1980] to highlight the endogeneity issue by investigating the relationship between market structure and innovation. We apply our method to estimate the R&D expenditures for Chinese manufacturing firms to highlight the importance of the econometric issues. Reduced-form results suggest a nonlinear relationship between market concentration and R&D expenditures, while our approach suggests a strictly positive relationship consistent with canonical theoretical models built on oligopolistic competition.