Linkages, Key Sectors and Structural Change: Some New Perspectives

Sonis, Michael; Guilhoto, Joaquim José Martins; Hewings, Geoffrey J. D.; Martins, Eduardo Borges

doi:10.2139/ssrn.2420129

Cited by 31 publications

(55 citation statements)

References 20 publications

(48 reference statements)

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“…In order to solve the problem, a constant returns to scale technology is assumed: the proportions in which different inputs enter the production process of a particular sector are assumed constant over time; i.e., the 16 Cella also decomposes this total linkage coefficient into backward and forward linkages (with backward linkages, however, including some forward elements, and vice versa); Clements (1990) provides an adjustment to Cella's split of the total linkage measure into backward and forward linkage, which also implies a different normalization. Sonis et al (1995) introduce the concept of pure linkages that further disentangles the backward and forward linkages. Cai and Leung (2005) interpret Sonis' pure linkages and suggest an alternative pure forward linkage measure for a symmetrical interpretation of pure backward and forward linkages.…”

Section: Input-output Frameworkmentioning

confidence: 99%

The Unbalanced Growth Hypothesis and the Role of the State: The Case of China’s State-Owned Enterprises

Holz

2010

SSRN Journal

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's unbalanced growth hypothesis suggests that a developing economy invest in industries with high backward and forward linkages. A high degree of linkage means that the initial investment yields large profit opportunities in other industries. These profit opportunities are taken up by entrepreneurs, i.e., lead to investment in the backward and forward linked industries. The higher the degree of linkage of the industry in which the initial investment occurred, the faster the economy grows.China is different from the typical developing economy. Due to a history of planned (balanced) development under state ownership, China at the beginning of the reform period had in place a broad industrial base. The issue of unbalanced growth in China then is one of strategic withdrawal of the state from low-linkage sectors and the continued presence of the state in high-linkage sectors. The evidence suggests that while the degree of linkage plays an important role in generating economic growth in China, current province-specific withdrawal strategies for the state sector may have no effect on economic growth.

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Section: Input-output Frameworkmentioning

confidence: 99%

The Unbalanced Growth Hypothesis and the Role of the State: The Case of China’s State-Owned Enterprises

Holz

2010

SSRN Journal

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“…The effects on each bank are given by Bi 1 , and the total system effect by i Bi 1 , the sum of all elements in the first column of B (i 1 denotes a column vector with 1 in the first element and 0 elsewhere, see footnote 7). In the literature, the so-called Rasmussen-Hirschman "backward" index has been used (see Sonis et al (1995), Hewings (2009), Miller andBlair (2009)), which we denote by h (b) 13 and can be defined for each bank j as follows:…”

Section: Input-output Measures Of Systemic Importancementioning

confidence: 99%

Input–output-based measures of systemic importance

Aldasoro

Angeloni

2014

Quantitative Finance

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One of the remarkable consequences of the recent financial crisis has been the shift in emphasis, in economic analysis as well as policy practice, from the microprudential to the macro-prudential approach to banking regulation and supervision (Hanson et al. (2011)). The micro-prudential approach focuses on controlling the risk of individual banks, taking the rest of the system as given. Since banks are funded largely by deposits, an instrument protected in most countries by a collectively funded safety net, the micro-prudential regulator/supervisor needs to control that bank managers do not take advantage of such protection to assume an unduly high level of risk (moral hazard). However, in the presence of risk externalities, i.e. when risk-taking behavior of individual institutions affects other institutions and the system as a whole, another source of social inefficiency arises, requiring the prudential regulator/supervisor to take a macro-prudential approach. Banks need to be controlled not only in relation to their propensity to undertake high risk due to the protection they enjoy on their liability side, but also in relation to the risk they transmit to other banks with which they are connected by a reciprocal web of exposures. To guide policy it becomes necessary, in this context, to measure the systemic importance of individual banks, i.e. the degree to which they propagate systemic risk by exerting influence on the rest of the system. A large body of literature has developed to define and measure systemic risk and to analyze its implication for the conduct of prudential regulation and supervision (for a comprehensive overview see Bisias et al. (2012)). Broadly speaking, there are two classes of indicators of systemic importance proposed in the recent literature. The first and more widely used class of indicators relies, directly or indirectly, on asset prices distributions and correlations across institutions, assets and time. The second approach, with a rapidly rising literature is that of network analysis Our contribution here consists in proposing an alternative method for measuring the transmission of risk within banking systems, which logically belongs to the second class mentioned in the preceding paragraph, namely that based on balance sheet measures of interconnection. Our approach is new and old at the same time. It is new because, as such, it has never been used in the analysis of banking. It is old because it draws on a well-established and time-honored strand of literature, that of input-output analysis.Taking the balance sheet of the banking system as a point of departure, we derive expressions that closely resemble the traditional Leontief (1941) input-output model. The input-output model makes evident the fact that the production of any sector has two distinct effects on the remaining sectors: on the one hand by increasing production it will demand more inputs from other sectors ("upstream"), on the other it will be able to provide more output to the sectors that depend its production as in...

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“…The notion of "fields of influence" used in the input-output and engineering literature is of help here (see Sonis et al (1995) and the references therein 16 ). What is of interest is how the matrix B (G) changes when one or more elements of the bank interconnection matrix A (O) change.…”

Section: Case Bmentioning

confidence: 99%