Testing the sensitivity of CGE results: A Monte Carlo Filtering approach to an application to rural development policies in Aberdeenshire
Sébastien Mary (),
Euan Phimister (),
Deborah Roberts and
No JRC85290, JRC Working Papers from Joint Research Centre (Seville site)
Parameter uncertainty has fuelled criticisms on the robustness of CGE results and has led to the development of alternative approaches to sensitivity analyses. Researchers have used Monte Carlo (MC) for systematic sensitivity analysis (SSA) because of its flexibility. However, MC may provide biased simulation results. Gaussian Quadratures (GQ) have then been developed, but they are much more difficult to apply in practical modelling and may not always be desirable. This report applies an alternative approach to SSA, Monte Carlo Filtering, and examines how its results compare to MC and GQ approaches, in an application to rural development policies in Aberdeenshire.
Keywords: Rural Development; bi-regional CGE model; NUTS3 regions; European Union; Monte Carlo Filtering (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ipt:iptwpa:jrc85290
Access Statistics for this paper
More papers in JRC Working Papers from Joint Research Centre (Seville site) Contact information at EDIRC.
Bibliographic data for series maintained by Publication Officer ().