Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity
Georges Bresson,
Cheng Hsiao and
Alain Pirotte ()
AStA Advances in Statistical Analysis, 2011, vol. 95, issue 4, 435-452
Keywords: R&D; Productivity; Heteroskedasticity; Hierarchical Bayes; Markov Chain Monte Carlo simulations; Panel data; Random coefficient model (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://hdl.handle.net/10.1007/s10182-011-0169-y (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Assessing the Contribution of R&D to Total Factor Productivity – a Bayesian Approach to Account for Heterogeneity And Heteroscedasticity (2007) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:alstar:v:95:y:2011:i:4:p:435-452
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10182/PS2
DOI: 10.1007/s10182-011-0169-y
Access Statistics for this article
AStA Advances in Statistical Analysis is currently edited by Göran Kauermann and Yarema Okhrin
More articles in AStA Advances in Statistical Analysis from Springer, German Statistical Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().