The Regionalization of National Input–Output Tables: A Review of the Performance of Two Key Non-survey Methods

This paper uses survey‐based data for 16 South Korean regions to refine the application of Flegg's location quotient (FLQ) and its variant, the sector‐specific FLQ (SFLQ). These regions vary markedly in terms of size. Especial attention is paid to the problem of choosing appropriate values for the unknown parameter δ in these formulae. Alternative approaches to this problem are evaluated and tested. Our paper adds to earlier research that aims to find a cost‐effective way of adapting national coefficients, so as to produce a satisfactory initial set of regional input coefficients for regions where survey‐based data are unavailable.

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“…For a detailed discussion of these two approaches, seeFlegg and Tohmo (2018). 5 See Bonfiglio and Chelli (2008, table 1).…”

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confidence: 99%

The regionalization of national input‐output tables: A study of South Korean regions

Flegg

Tohmo

2019

Papers in Regional Science

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“…As Flegg and Tohmo (2018a) point out, it should only be used in conjunction with national IO tables where the inter-industry transactions exclude imports (type B tables). In contrast, where the focus is on the overall supply of commodities, Kronenberg's Cross-Hauling Adjusted Regionalization Method (CHARM) can be employed (Többen and Kronenberg, 2015;Flegg and Tohmo, 2018b). CHARM requires type A tables, those where imports have been incorporated into the national transactions table.…”

Section: Theoretical Background: Lq-based Methodsmentioning

confidence: 99%

“…A possible explanation of this phenomenon is that South Korean regions typically import a substantially higher proportion of their inputs from other domestic regions than do Finnish regions. Consequently, to adjust for this disparity in import propensities, a higher value of δ is required in South Korea than in Finland (Flegg and Tohmo, 2018b).…”

Section: Implementing the New Approachmentioning

confidence: 99%

Testing and implementing a new approach to estimating interregional output multipliers using input–output data for South Korean regions

Jahn

Flegg

Tohmo

2020

Spatial Economic Analysis

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Flegg's location quotient (FLQ) is a useful tool in estimating intraregional output multipliers. Here we use it as one component in estimating interregional multipliers. Using statistical information criteria, we demonstrate that, for South Korea, the best approach is to combine the FLQ with a simple trade model. Since the interregional trade flows do not seem to depend much on distances or adjacency, a gravity model is not required. We also find that the industry-specific FLQ (SFLQ) yields the best results when regions are analysed separately, whereas the FLQ outperforms the SFLQ once interregional trade flows are considered.

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“…Besides testing the performance of SDR and the LQ as RPC estimates, we also do so for an approach that follow FLQ techniques. For this, we consider (Flegg & Tohmo, 2013, 2018):

{\dot{ρ}}_{i}^{c} \equiv {SLQ}_{i}^{c} \times λ^{*},

where

{\dot{ρ}}_{i}^{c}

denotes an estimate of the actual RPC

((), ρ_{i}^{c})

for industry i in country c within the EU:

{SLQ}_{i} = ({, \begin{array}{c} ((), q_{i}^{c} / q_{\cdot}^{c}) / ((), q_{i}^{\cdot} / q_{\cdot}^{\cdot}), if ([], ((), q_{i}^{c} / q_{\cdot}^{c}) / ((), q_{i}^{\cdot} / q_{\cdot}^{\cdot})) \leq 1.0 \\ 1, if ([], ((), q_{i}^{c} / q_{\cdot}^{c}) / ((), q_{i}^{\cdot} / q_{\cdot}^{\cdot})) > 1.0 \end{array}),

and

λ^{*} \equiv normalδ \log_{2} ((), 1 + e_{\cdot}^{c} / e_{\cdot}^{\cdot}) .

…”

Section: Rpc Estimatesmentioning

confidence: 99%

“…Flegg, Webber, and Elliott (1995), Flegg and Tohmo (2013, 2016, 2018, 2019), Flegg, Mastronardi, and Romero (2016), Jahn (2017), and Kowalewksi (2015) have examined slightly more complex parametric transforms of LQs to estimate regional supply percentages. Like LQ approaches, when applied row‐wise to a region's technology matrix, these so‐called “FLQs” estimate a region's direct requirements.…”

Section: Introductionmentioning

confidence: 99%

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

Lahr

Ferreira

Többen

2020

Papers in Regional Science

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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.

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The Regionalization of National Input–Output Tables: A Review of the Performance of Two Key Non-survey Methods

Cited by 7 publications

References 22 publications

The regionalization of national input‐output tables: A study of South Korean regions

The regionalization of national input‐output tables: A study of South Korean regions

Testing and implementing a new approach to estimating interregional output multipliers using input–output data for South Korean regions

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

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