Identifying Optimal Sector Groupings With the Hypothetical Extraction Method*

Temursho, Umed

doi:10.1111/j.1467-9787.2010.00678.x

Cited by 44 publications

(30 citation statements)

References 28 publications

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“…Lemma 1 (which is a particular case of Lemma 2) in Temurshoev (2010a) in terms of Ghosh inverse states that…”

Section: Appendixmentioning

confidence: 99%

“…The convoluted three step extraction procedure for the complete and the incomplete HE measures, however, makes their analytical comparison with other factor linkages impossible, unless a closed form is found for them. Temurshoev (2010a) gives the analytical expression for the reduction in factor usage 9 These intervals, and the ones to follow, are the means of the 15th and 85th percentiles of the corresponding data for 33 countries used in the empirical part of this paper.…”

Section: Overview Of Output-based Linkage Measuresmentioning

confidence: 99%

“…Temurshoev (2010a), for example, considers the difference between the sum of the backward linkages due to the HE of separate industries and the corresponding result due to the HE of a group of the same industries for such factors as water, CO 2 emissions, profits, and net wages. The author then interprets the obtained values of such differences as the degree of redundancy of sectors in terms of their linkage patterns, factor generation and final demand structures.…”

Section: Overview Of Output-based Linkage Measuresmentioning

confidence: 99%

“…Thus, we have the output-to-output multiplier Blair, 1985, 2009,p.328), which is equivalent to the total flow multiplier (Szyrmer, 1984(Szyrmer, , 1992, which is equivalent to the earlier hypothetical extraction (HE) of whole sectors (Paelinck et al, 1965;Strassert, 1968;Schultz, 1977). The last point was first indicated by Szyrmer (1992) and recently proved by Gallego and Lenzen (2005) and Temurshoev (2010a). 2 However, HE offers more flexibility as it allows to extract any subset of transactions instead of deleting only full rows and columns (see Miller and Lahr, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…2 Note that the prime purpose of Temurshoev (2010a) was formulating and deriving an analytical solution (referred to as a group factor worth, yet another label) to the problem of finding a key group of sectors with the HE method. It is a generalization of the HE key sector problem, but the author shows that the two problems are generally not equivalent.…”

Section: Introductionmentioning

confidence: 99%

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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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“…Lemma 1 (which is a particular case of Lemma 2) in Temurshoev (2010a) in terms of Ghosh inverse states that…”

Section: Appendixmentioning

confidence: 99%

Section: Overview Of Output-based Linkage Measuresmentioning

confidence: 99%

Section: Overview Of Output-based Linkage Measuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analytical and Empirical Comparison of Policy-Relevant Key Sector Measures

Temursho¹,

Oosterhaven²

2014

Spatial Economic Analysis

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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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Macroeconomic lockdown and SMEs: the impact of the COVID-19 pandemic in Spain

2021

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The relative importance of small-and mediumsized enterprises (SMEs) and large firms is a recurrent topic in the small business economics literature. This paper presents a real and financial social accounting matrix (FSAM) capable of distinguishing the direct and indirect effects that are transferred from micro-, small, medium, and large firms to the rest of the economy. We use the hypothetical extraction method (HEM) to explore the sequence of reactions associated with shocks that arise from the COVID-19 lockdown. Using a structural model for the Spanish economy, we identify the role of different firm size categories in the aggregate gross domestic product (GDP). Our results allow us to reconcile the mixed narrative that accompanies the evaluation of the role played by these categories in economic activity by revealing that both SMEs and large firms are important for supporting economic activity. In particular, SMEs help explain 43% of the income and two-thirds of the unemployment decline caused by the COVID-19 pandemic. Our findings also show the importance of conditioning SME industrial policy to sectoral analysis. Plain English summary The effects of the macroeconomic lockdown and its transmission to the rest of the economy differ by firm size and across sectors. Using the Spanish context for micro-, small, medium, and large firms, we distinguish the direct and indirect effects caused by the COVID-19 pandemic. The main implications are the following: (1) Research: results emphasize that SMEs and large firms are both important to support economic activity but, in order to account for the relative effects on SMEs, it is crucial to consider the specific sector that receives the disruption. 2) Policy: SMEs are an important focus of business support policies within the EU. According to our estimations, disruptions in SMEs produce larger reductions in demand. These results could support credit policies for SMEs with a strong impact on the aggregate economy due to their greater productive and financial linkages with the domestic economy.

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Identifying Optimal Sector Groupings With the Hypothetical Extraction Method*

Cited by 44 publications

References 28 publications

Analytical and Empirical Comparison of Policy-Relevant Key Sector Measures

Analytical and Empirical Comparison of Policy-Relevant Key Sector Measures

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

Macroeconomic lockdown and SMEs: the impact of the COVID-19 pandemic in Spain

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