Real-Financial Linkages in the Canadian Economy: An Input–output Approach

Leung, Danny; Secrieru, Oana

doi:10.1080/09535314.2012.684345

Cited by 14 publications

(7 citation statements)

References 8 publications

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“…Starting with Leontieff and his team at Harvard University, Akhabbar, Antille, Fontela and Pulido (2011) explain how input-output models fared in United States and how the tool of analysis moved to Europe. These models have been used to analyze various topics, among which are quantification of carbon emission effects of production on the environment (Minx, Wiedmann, Wood, Peters, Lenzen, Owen, Scott, Barret, Hubacek, Baiocchi, Paul, Dawkins, Briggs, Guan, Suh and Ackerman, 2009), examination of sectorial energy usage (Lin and Polenske, 1995), identification of key sectors that need to be supported in times of crisis (Luo, 2013), and analysis of interactions between the real and financial sectors (Leung and Secrieru, 2012). Though frequently denoted in terms of value units, input-output tables in quantity units can also be constructed.…”

Section: Literature Reviewmentioning

confidence: 99%

Regional Input-Output Analysis of A Mega-Event: Possible Impact of EXPO on Izmir Economy

Aydoğuş¹,

Değer²,

Çalışkan³

et al. 2015

Anadolu Üniversitesi Sosyal Bilimler Dergisi

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Section: Literature Reviewmentioning

confidence: 99%

Regional Input-Output Analysis of A Mega-Event: Possible Impact of EXPO on Izmir Economy

Aydoğuş¹,

Değer²,

Çalışkan³

et al. 2015

Anadolu Üniversitesi Sosyal Bilimler Dergisi

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“…Like Leung and Secrieru [8] and Aray, Pedauga and Velázquez [9] we estimated the Property Income matrix (

) breakdown by institutional sector and type of instruments defined in Eq. (1) by using the information embedded on the assets and liabilities matrix of each institutional sector compiled in the financial instruments matrix (

) represented in Eq.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Property income from-whom-to-whom matrices: A dataset based on financial assets–liabilities stocks of financial instrument for Spain

2018

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A common problem in compiling and updating Social Accounting Matrices (SAM) or Input-Output tables is that of incomplete information. In the case of the submatrix ‘Property Income of the Account Allocation of Primary Income’, the information published by the National Bureau of Statistics of Spain (INE) is limited because it is not possible to build the set of from-whom-to-whom sub-matrix on income interest, dividends, securities and rents with only the subtotals presented in the Integrated Economic Accounts (IEA). This because the income distribution received and paid for by each institutional sector required for a financial SAM is not available, i.e. the INE does not break down the data by institutional destination and source. In this sense, our contribution rely on estimating a complete series of from-whom-to-whom matrices of Property Income for the Spanish economy between 1999 and 2016, in which we have devoted special attention to staying in line with the Data Gaps Initiative (DGI-2) recommendation released by the Financial Stability Board (FSB) and the International Monetary Fund (IMF), claiming that more focus is needed on data sets that support the monitoring of risks in the financial sector in response to regulatory and macro-financial emerging policy needs).

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“…Furthermore, firms experiencing variability in cash flow tend to hold fewer substitutes of cash, and firms with a tendency to spend frequently on R&D tend to become financially distressed. Leung and Secrieru (2012) study the strength of real financial linkages by applying input-output analysis. They calculate and compare multipliers with and without endogenous financial flows to test the impact of financial flows when there is a final demand shock in the economy, finding that it increases the impact of a final demand shock on output by 4%-11%.…”

Section: Literature Reviewmentioning

confidence: 99%

Financing Constraints and Investment Efficiency in Canadian Real Estate and Construction Firms: A Stochastic Frontier Analysis

2021

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This article models the behavior of 179 listed and unlisted real estate and construction firms (RECFs) in Canada to study how financial constraints impact the investment efficiency of these real estate firms during the 2004–2020 period. Investment efficiency is interpreted here as the ability and ease of a firm to convert investment opportunities into actual investments. The results show that Canadian RECFs are strongly dependent on two sources of financing: equity financing and debt financing. Equity financing helped ease financing constraints due to a cash flow increase but was unlikely to decrease the uncertainty of follow-up financing of investments of these companies. This study constructed an investment efficiency index (IEI) for all 179 RECF firms. The results showed an investment rate loss of approximately 62% of the RECF firms due to financing constraints during the above period. The IEI of RECFs in Canada has demonstrated a descending pattern, and the investment efficiency level slipped from 0.47 to 0.40 from 2004 to 2020. Furthermore, a regional analysis demonstrates that compared with the RECFs located in Ontario, the investment efficiency indices of RECFs in Quebec and British Columbia were more volatile. Small RECFs demonstrated a very steady trend in investment efficiency during the sample period, which was completely different from the patterns displayed by large and medium RECFs.

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Real-Financial Linkages in the Canadian Economy: An Input–output Approach

Cited by 14 publications

References 8 publications

Regional Input-Output Analysis of A Mega-Event: Possible Impact of EXPO on Izmir Economy

Regional Input-Output Analysis of A Mega-Event: Possible Impact of EXPO on Izmir Economy

Property income from-whom-to-whom matrices: A dataset based on financial assets–liabilities stocks of financial instrument for Spain

Financing Constraints and Investment Efficiency in Canadian Real Estate and Construction Firms: A Stochastic Frontier Analysis

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