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Intraregional trade shares for goods‐producing industries: RPC esimates using EU data

Authors

Lahr,  Michael L.
External Organizations;

Ferreira,  João Pedro
External Organizations;

/persons/resource/Johannes.Toebben

Többen,  Johannes
Potsdam Institute for Climate Impact Research;

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Citation

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


Cite as: https://publications.pik-potsdam.de/pubman/item/item_25209
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.