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Erschienen in:
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2024 | OriginalPaper | Buchkapitel

1. Measuring Global Flow of Funds: Statistical Framework, Data Sources, and Approaches

verfasst von : Nan Zhang, Yiye Zhang

Erschienen in: Global Flow of Funds Analysis

Verlag: Springer Nature Singapore

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Abstract

This chapter aims to provide a measurement for the global flow of funds (GFF), as discussed in four portions. First, the Chapter will define GFF to determine its statistical domains. Second, the document sets out the ideas and existing data sources and integrates them to measure GFF. These concepts and data sources are reflected in the balance of payments, international investment position (IIP), the Coordinated Direct Investment Survey (CDIS), the Coordinated Portfolio Investment Survey, the consolidated banking statistics (CBS), and the rest of the world (ROW) account. Third, the balance sheet approach is used to break down the ROW into IIP components. An external statistics’ matrix (metadata) exercise shows the available external-sector financial data based on the IIP concept. As the outcome of the study, this chapter compiled GFF matrix with the pattern of “from-whom-to-whom.” Fourth, data science is explored to integrate the data sources, improve the timeliness of the existing data transmission, and illustrate how the GFF matrix operates.

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Nächstes Kapitel Global Flow of Funds as a Network: Cross-Border Investment in G20
Fußnoten
1
Financial Stability Board and International Monetary Fund (2009). The Financial Crisis and Information aps Gaps- Report to the G-20 Finance Ministers and Central Bank Governors, p. 10.
 
2
2008 SNA, 505.
 
3
IMF (2016a, 2016b, 2016c), MFSMCG, 288.
 
4
Errico et al. (2013).
 
5
Zhang (2005).
 
6
Rest of the world (ROW), which is a sector in Flow of Funds Account.
 
7
Shrestha et al. (2012).
 
8
Depending on the purpose of the analysis, we can also set the column as a liability and the row as an asset. See Chap. 3 for a detailed explanation.
 
9
This is a theoretical setting of the statistical framework, but there are biases in practice. Because total global assets will not equal to total global liabilities even if we had perfect data sources, with the difference generated by the fact that monetary gold does not have counterpart liability. Another source of inconsistency are the countries’ assets and liabilities vis-à-vis international organizations, as these are not residents of any country.
 
10
When discussing reserve assets, it should be clarified that these are included also on the liabilities side in the IIP data within the relevant functional categories of the relevant countries (except monetary gold).
 
11
The term “mirror data” refers to the same data seen from different perspectives. For instance, banks' loans to households could be called mirror data of household debt to banks.
 
12
IMF, Balance of Payments Manual, 6th edition (BPM6), 111.
 
13
The BIS locational banking statistics (LBS) are reported by banking offices located in selected countries, including many offshore financial centers, and exclude the assets and liabilities of banking offices outside of these countries. The number of LBS-reporting countries increased from 14 in 1977 to 47 in 2017.
 
15
IMF, Balance of payments and international investment position compilation guide, 2017.
 
16
IMF, BIS, and ECB (2015), Handbook on Securities Statistics.
 
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Metadaten
Titel
Measuring Global Flow of Funds: Statistical Framework, Data Sources, and Approaches
verfasst von
Nan Zhang
Yiye Zhang
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
Buch
Global Flow of Funds Analysis

Print ISBN: 978-981-9710-28-7

Electronic ISBN: 978-981-9710-29-4

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-981-97-1029-4_1