English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Intraregional trade shares for goods‐producing industries: RPC esimates using EU data

Lahr, M. L., Ferreira, J. P., Többen, J. (2020): Intraregional trade shares for goods‐producing industries: RPC esimates using EU data. - Papers in Regional Science, 99, 6, 1583-1605.
https://doi.org/10.1111/pirs.12541

Item is

Files

show Files
hide Files
:
25209.pdf (Publisher version), 3MB
 
File Permalink:
-
Name:
25209.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Lahr, Michael L.1, Author
Ferreira, João Pedro1, Author
Többen, Johannes2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: The lack of subnational trade data has dampened the development of reliable regional and multiregional models for regional policy development. So, most researchers and vendors of regional and interregional economic models continue to rely on location quotients, supply–demand pool techniques, or minor modifications of them, despite knowing that they under‐estimate interregional trade. In this piece, we analyse the relative viability of estimates of intraregional trade—so called “regional purchase coefficients” (RPCs). We do so for manufacturing sectors in 28 EU countries using the World Input–Output Database. We introduce an RPC‐estimating technique using a quasi‐binomial regression approach for goods‐producing industries; we apply standard supply/demand ratios as RPCs for service‐based industries. We then apply the estimates to an aggregate EU input–output (I‐O) table and measure how closely the results approximate the I‐O tables (direct requirements matrices) for each of the 28 EU nations. We compare these findings to those obtained by other conventional approaches. We also evaluate their ability to replicate the country Leontief inverses and output multipliers. We find quasi‐binomial regression approaches superior across the board.

Details

show
hide
Language(s):
 Dates: 2020-07-092020-07-09
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1111/pirs.12541
PIKDOMAIN: FutureLab - Social Metabolism and Impacts
Organisational keyword: FutureLab - Social Metabolism and Impacts
MDB-ID: Entry suspended
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Papers in Regional Science
Source Genre: Journal, SCI, Scopus
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 99 (6) Sequence Number: - Start / End Page: 1583 - 1605 Identifier: Publisher: Wiley-Blackwell - SSH
Other: 1435-5957
ISSN: 1056-8190
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/papers-in-regional-science
Publisher: Wiley