Predicting Resource Policy Outcomes via Meta-Regression: Data Space, Model Space, and the Quest for 'Optimal Scope'

Klaus Moeltner and Rosenberger Randall S ()
Additional contact information
Rosenberger Randall S: Oregon State University

The B.E. Journal of Economic Analysis & Policy, 2008, vol. 8, issue 1, 1-31

Abstract: Resource-managing agencies are increasingly relying on secondary data to predict economic benefits for planned policy interventions. This `transfer of benefits' is often based on a quantitative synthesis of aggregate results for similar past interventions via Meta-Regression Models. However, this approach is generally plagued by the paucity of available studies and related small sample problems. A broadening of scope of the Meta-Regression Model by adding data from ``related, yet different" contexts or activities may circumvent these issues, but may not necessarily enhance the efficiency of transfer functions if the different contexts do not share policy-relevant parameters. We illustrate how different combinations of contexts can be interpreted as `data spaces' which can then be explored for the most promising transfer function using Bayesian Model Search techniques. Our results indicate that model-averaged benefit predictions for scope-augmented data spaces can be more robust and efficient than those flowing from the baseline context and data.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://doi.org/10.2202/1935-1682.2028 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
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:bpj:bejeap:v:8:y:2008:i:1:n:31

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/bejeap/html

DOI: 10.2202/1935-1682.2028

Access Statistics for this article

The B.E. Journal of Economic Analysis & Policy is currently edited by Hendrik Jürges and Sandra Ludwig

More articles in The B.E. Journal of Economic Analysis & Policy from De Gruyter
Bibliographic data for series maintained by Peter Golla ().