Regional Input–Output Tables and the FLQ Formula: A Case Study of Finland

Flegg, Anthony T.; Tohmo, Timo

doi:10.1080/00343404.2011.592138

Cited by 143 publications

(130 citation statements)

References 21 publications

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“…This follows the recommendation of Flegg and Webber (1997), which is supported by the work of Flegg and Tohmo (2013a), as summarised in Section 2 . Using this method, it is possible to estimate the elements in the diagonal input-coefficient matrices, that is: A GG , A WW , A BB .…”

Section: Step 2: Intermediate Inputssupporting

confidence: 61%

“…349-360) and Flegg and Tohmo (2013a). The Cross-Industry LQ (CILQ) extends the SLQ by allowing for the relative size of the sectors engaged in intermediate transactions:…”

Section: Non-survey and Partial-survey Methods For Constructing Io Tamentioning

confidence: 99%

“…Based on analysis of IO tables for Scotland and Peterborough in England, Flegg and Webber (1997) propose that an approximate value for δ = 0.3 "would seem reasonable" (p. 798). Flegg and Tohmo (2013a) Flegg and Tohmo (2013a), this is likely to reflect the fact that the Scottish input coefficients often surpassed corresponding UK coefficients. Similarly, Kowalewski (2013), finds the best results for the German federal state of Baden-Wuerttemberg are 0.11 ≤ δ ≤ 0.17.…”

Section: Non-survey and Partial-survey Methods For Constructing Io Tamentioning

confidence: 99%

“…The FLQ formula is used for a range of δ values and compared with a version of the IO table estimated using SLQs. The upper and lower values of δ chosen here follow Flegg and Tohmo (2013a), who test the appropriateness of δ values in the range 0.15 -0.4 for 20 regions in Finland. To simplify the presentation of results, the industrial sectors are aggregated into a single sector for each region, to identify the extent to which indirect (and, where appropriate, induced effects) impact locally or in other sub-regions.…”

Section: Intermediate Transactionsmentioning

confidence: 99%

See 3 more Smart Citations

Beyond Intermediates: The Role of Consumption and Commuting in the Construction of Local Input–Output Tables

Hermannsson

2016

Spatial Economic Analysis

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Estimating intermediate trade using conventional non-survey methods produces biased results. This problem has led to a methodological recommendation that emphasises the accurate estimation of intermediate trade flows. This paper argues for a qualification of the consensus view: when simulating input-output (IO) tables, analysts need also to consider spill-over effects driven by wage and consumption flows. In particular, for metropolitan economies, capturing wage and consumption flows is essential to obtain accurate Type II multipliers. This is demonstrated by constructing an interregional IO table, which captures the interdependence between a city and its commuter belt, nested within the wider regional economy. JEL Codes: C67; R12; R15; R23.

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Section: Step 2: Intermediate Inputssupporting

confidence: 61%

“…349-360) and Flegg and Tohmo (2013a). The Cross-Industry LQ (CILQ) extends the SLQ by allowing for the relative size of the sectors engaged in intermediate transactions:…”

Section: Non-survey and Partial-survey Methods For Constructing Io Tamentioning

confidence: 99%

Section: Non-survey and Partial-survey Methods For Constructing Io Tamentioning

confidence: 99%

Section: Intermediate Transactionsmentioning

confidence: 99%

See 2 more Smart Citations

Beyond Intermediates: The Role of Consumption and Commuting in the Construction of Local Input–Output Tables

Hermannsson

2016

Spatial Economic Analysis

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“…Regression-type gravity models (e.g., Begg 1985) have been applied and have shown to produce results by and large close to the survey data (Riddington et al 2006). Kronenberg (2010) estimated biregional trades using the Leontief-Strout-type exact solution nonsurvey method that allows crosshauling, which was then discussed in Flegg and Tohmo (2011).…”

mentioning

confidence: 99%

A nonsurvey multiregional input–output estimation allowing cross-hauling: partitioning two regions into three or more parts

Nakano

Nishimura

2012

Ann Reg Sci

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This paper describes a nonsurvey method for estimating multiregional trades without eliminating cross-hauling, when a national biregional input-output table is available. Domestic outflows are assigned by interpolating the biregional trades on the basis of the gravity ratio between the origin and the destinations, with parameters estimated from an earlier survey on interregional transactions. The method is then applied to evaluate multiregional industrial waste disposal and landfill attributed to consumption in the city of Nagoya. Three-regional input-output tables with and without cross-hauling are estimated by partitioning the biregional table between Aichi prefecture and the rest of Japan. JEL Classification

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Industrial Clusters in the Regions of Russia: Growing Pains and Development Constraints Overcoming

Inshakova

Beloglazova³

2020

Lecture Notes in Networks and Systems

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Regional Input–Output Tables and the FLQ Formula: A Case Study of Finland

Cited by 143 publications

References 21 publications

Beyond Intermediates: The Role of Consumption and Commuting in the Construction of Local Input–Output Tables

Beyond Intermediates: The Role of Consumption and Commuting in the Construction of Local Input–Output Tables

A nonsurvey multiregional input–output estimation allowing cross-hauling: partitioning two regions into three or more parts

Industrial Clusters in the Regions of Russia: Growing Pains and Development Constraints Overcoming

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