EconPapers    
Economics at your fingertips  
 

Estimating high-resolution interregional input–output tables: a Bayesian spatial approach

Andrzej Torój

Economic Systems Research, 2024, vol. 36, issue 3, 353-377

Abstract: Due to the scarcity of subnational interregional input–output (IRIO), various approaches to their estimation are actively under investigation in the literature. This paper focuses on the application of spatial econometric method. It determines intra- and interregional coefficients through a joint procedure which successfully avoids the direct recycling of estimates for other geographies and granularities. Instead, the use of Bayesian methods is proposed, which formally integrate limited evidence from existing regional tables (Finland) with a set of sectoral data on value added for 73 NUTS-3 regions in Poland, the latter being dominant. An empirical test of replicating the Korean survey-based IRIO table demonstrates that the accuracy of this approach slightly outperforms an alternative IRIOLQ procedure. The incorporation of time-based distance measurement has only modest effects on empirical fit, and the use of big geolocation dataset to account for commuting relocates 18.9% of the induced effect from a city to its periphery.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/09535314.2024.2358357 (text/html)
Access to full text is restricted to subscribers.

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:taf:ecsysr:v:36:y:2024:i:3:p:353-377

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CESR20

DOI: 10.1080/09535314.2024.2358357

Access Statistics for this article

Economic Systems Research is currently edited by Bart Los and Manfred Lenzen

More articles in Economic Systems Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:ecsysr:v:36:y:2024:i:3:p:353-377