Input-Output Approach in an Allocation System

Ghosh, Adarsh

doi:10.2307/2550694

Cited by 568 publications

(298 citation statements)

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“…where (I − A * ) −1 is the well-known Ghosh-inverse (Ghosh, 1958). Aside from the implausibility of, especially, the assumption of fixed trade coefficients, applying 4 and 5 to calculate the wider negative backward impacts of a disaster is problematic for several other reasons.…”

Section: Problems In the Empirical Assessment Of Wider Disaster Impacmentioning

confidence: 99%

On the limited usability of the inoperability IO model

Oosterhaven

2017

Economic Systems Research

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This note shows that the inoperability input-output model (IIM) estimates only a part of mainly the negative indirect economic impacts of disasters, whereas it neglects most of the positive indirect impacts. This means that the IIM is not suited to prioritize industries for policy interventions that aim at reducing the negative impacts of such disasters. Besides, this note shows that the application of the IIM is problematic and tends to overestimate the subset of impacts that the model is able to quantify. Finally, we identify two approaches that much better capture the variety of different disaster impacts. ARTICLE HISTORY

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Section: Problems In the Empirical Assessment Of Wider Disaster Impacmentioning

confidence: 99%

On the limited usability of the inoperability IO model

Oosterhaven

2017

Economic Systems Research

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“…The output inverse was first defined by Ghosh (1958) to represent supply constrained economies and marked the start of a long-running debate which has now been settled (Oosterhaven 1988(Oosterhaven , 2012Rose and Allison 1989;Dietzenbacher 1997;De Mesnard 2007Guerra and Sancho 2011). Oosterhaven (1988, 1989, 1996 has conclusively shown that the quantity interpretation of the Ghosh model is nonsensical and only the price interpretation makes theoretical economic sense.…”

Section: Backward and Forward Linkagesmentioning

confidence: 99%

Exploring Vulnerability and Interdependency of UK Infrastructure Using Key-Linkages Analysis

2015

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It has been argued the UK has experienced significant underinvestment in critical infrastructure over the last two decades. This in turn has resulted in infrastructure that is less capable of assisting the UK economy to grow. This article seeks to undertake an in-depth analysis of the inter-linkages and economic contributions from infrastructure within the UK. It explores the relationship between nine infrastructure sectors and how these sectors contribute to the rest of the UK economy using keylinkage analysis. Each infrastructure sector is shown to be unique in the way it interacts with other economic sectors and in the form of contribution it makes to the economy overall. Infrastructure is found to be a necessary and important part of economic development. The analysis finds that over the last 23 years there has been a decline in the relative economic contribution from infrastructure to UK GVA. Only two infrastructure sectors increased their relative contribution to GVA since 1992. These were the water transport sector and sewerage and sanitary services sector. Railway transport and gas distribution have had the largest relative decline in contribution towards UK GVA with relative contributions decreasing by over 50 % since 1992. The three most important infrastructure sectors contributing to UK GDP are land transport, electricity production and distribution and telecommunications respectively.

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“…They are derived from, respectively, the Leontief (1936Leontief ( , 1941 demand-driven input-output (IO) model and the Ghosh (1958) supply-driven IO model. 4 The solution of the well-known Leontief model, that is x = (I − A) −1 y, delivers a row vector with total output multipliers…”

Section: Overview Of Output-based Linkage Measuresmentioning

confidence: 99%

Analytical and Empirical Comparison of Policy-Relevant Key Sector Measures

Temursho¹,

Oosterhaven²

2014

Spatial Economic Analysis

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Analytical and empirical comparison of policy-relevant key sector measures Temurshoev, U.; Oosterhaven, Jan IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document VersionPublisher's PDF, also known as Version of record Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. AbstractWe consider ten widely used key sector measures (linkages) and identify groups of the most similar indicators on both analytical and empirical grounds. We derive new closed-form formulas for the generalized complete and incomplete hypothetical extraction linkages and add the up till now undefined forward counterpart of the net backward linkage. The analytical relations and some stylized facts enable us to formulate hypotheses about the direction and strength of the relationships between various linkages. To study policyrelevant measures, our empirical tests are based on sectoral income (GDP) linkages, CO 2 -emission linkages and employment linkages for 34 industries and 33 countries. They show that the information on the ten key sector measures may be summarized by four measures.

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Input-Output Approach in an Allocation System

Cited by 568 publications

References 0 publications

On the limited usability of the inoperability IO model

On the limited usability of the inoperability IO model

Exploring Vulnerability and Interdependency of UK Infrastructure Using Key-Linkages Analysis

Analytical and Empirical Comparison of Policy-Relevant Key Sector Measures

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