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

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 underestimate 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.

A new proposal to model regional input–output structures using location quotients. An application to Korean and Spanish regions

“…Thus, the expression finally proposed for the estimation of δ becomes: In parallel to this proposal, the authors recognized the difficulty for the analyst to know with sufficient certainty the value of the regressors, so they proposed alternatively to present the variable p as the propensity of each region to import from other regions and f as the average use of foreign intermediate inputs in each region. Both are measured as a proportion of gross output, leaving the regression as follows: Therefore, in order to parameterize the value of δ, it is necessary to have prior knowledge of interregional trade, the difficulty of which could lead to the impossibility of its proper establishment and even its application (Lahr et al, 2020). However, the fact that in these proposals (and even in the critique offered by Lahr et al, 2020) a direct relationship can be established between interregional trade and the value of the δ parameter leads one to estimate it from other readily available information.…”

“…Both are measured as a proportion of gross output, leaving the regression as follows: Therefore, in order to parameterize the value of δ, it is necessary to have prior knowledge of interregional trade, the difficulty of which could lead to the impossibility of its proper establishment and even its application (Lahr et al, 2020). However, the fact that in these proposals (and even in the critique offered by Lahr et al, 2020) a direct relationship can be established between interregional trade and the value of the δ parameter leads one to estimate it from other readily available information.…”

“…From the abundant literature available on this regionalization methodology (Bonfiglio & Chelli, 2008; Flegg et al, 1995, 2016; Flegg & Tohmo, 2016; Flegg & Webber, 2000; Lamonica & Chelli, 2018; Lampiris et al, 2019; Mastronardi & Romero, 2012), it could be concluded that the use of Flegg's location quotients (FLQ) is the most appropriate of the available location quotient (LQ) techniques. However, this assertion is not without its critics as it relates to the practical impossibility of its proper implementation (Lahr et al, 2020).…”

StateIO - Open Source Economic Input-Output Models for the 50 States of the United States of America

“…Direct collection of interregional trade data via survey is still considered to be too expensive (Lahr, Ferreira, and Többen 2020) and time consuming (Miller and Blair 2009), and, therefore, interregional trade is generally estimated. Lahr et al (Lahr, Ferreira, and Többen 2020) identify four families of estimation techniques: Location Quotients (LQ), Flegg-Location-Quotients (FLQ), Cross-Hauling Adjusted Regionalization Method (CHARM), and econometric approaches. Of these, the LQ has the lowest data requirement, requiring data on employment, labor compensation, or production by industry or commodity and by region of the MRIO model.…”

Enhanced Input-Output Modelling for Improved Assessment of Supply Chain-Wide Environmental Pressures in Space and Time: The Case of China

“…Lack of statistics data that cover the inter-provincial commodity trade in physical terms leads us to model the inter-provincial trade network. Main models that have been used to construct the inter-regional trade networks include computable general equilibrium (CGE) models (Partridge andRickman 1998, West 1995), gravity models (Leontief and Strout 1963, Theil 1967, entropy-maximizing approaches (Roy and Thill 2004, Snickars and Weibull 1977, Wilson 2011, optimization models (Dalin et al 2014, Zhuo et al 2019), and others for example non-survey models (Sargento et al 2012) or behavior-based models (Isard 1998, Lahr et al 2020). However, these models strongly rely on the priori trade information while perform quite differently to a context of very limited trade information.…”