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Measuring global flow of funds: who-to-whom matrix and financial network

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  • Data Science: Present and Future
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Abstract

This study improves upon global flow of funds (GFF) statistics to measure global financial stability at the national and cross-border sectoral levels. After investigating the data sources and rebuilding the statistical framework to establish the GFF statistical matrix of G20 countries, we evaluate their financial risks and influences. We then connect the GFF matrix with the sectoral account data and the flow of funds to establish the sectoral from-whom-to-whom financial stock matrix (FFSM). The FFSM focuses on counterparty national and cross-border exposures of the sectors in China, Japan, and the United States to construct country-specific financial networks and connect each country-level network based on cross-border exposures. The analytical results systematically show the financial relationships among G20 countries in the GFF, the characteristics of overseas investment among China, Japan, and the United States, and external shocks and internal influences.

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Notes

  1. They are (1) build-up of risk in the financial sector, (2) cross-border financial linkages, (3) vulnerability of domestic economies to shocks, and (4) improving communication of official statistics.

  2. For the first version of the GFFM, see Zhang and Zhao’s paper (2019, 535–536).

  3. For the calculation method of Table Y refer to Zhang (2020), 108–110.

  4. The ROW sector in the FA is designed from a foreign standpoint, so the assets and liabilities of the ROW sector show an opposite relationship when observed from the domestic standpoint, and the assets of the ROW sector are the liabilities of the domestic.

  5. To avoid double counting, the claims, that is, loans and deposits, of JP to CN in Table A6.2-S banks' cross-border positions on residents of JP in the LBS account are subtracted from the claims of FC by ROW in FFSM (see Table 3).

  6. CPIS: Table 10, Reported Portfolio Investment Assets by Sector of Holder, and Sector and Economy of Nonresident Issuer for Specified Economies, December 2018.

  7. Leontief (1941).

  8. See Zhang and Zhao’s paper (2019, 545).

Abbreviations

BIS:

Bank for International Settlements

BOP:

Balance of payments

BPM6:

BOP and IIP manual, sixth edition

BSA:

Balance sheet approach

CBS:

Consolidated banking statistics

CDIS:

Coordinated direct investment survey

CNBS:

Center for National Balance Sheets of China

CPIS:

Coordinated Portfolio Investment Survey

DAL:

Domestic assets and liabilities

DI:

Direct investment

EAL:

External assets and liabilities

EALM:

External assets and liabilities matrix

EC:

Eigenvector centrality

FA:

Financial accounts

FBS:

Financial balance sheets

FC:

Financial corporations

FD:

Financial derivatives

FDI:

Foreign direct investment

FFA:

Flow of funds accounts

FFSM:

From-whom-to-whom financial stock matrix

FSB:

Financial Stability Board

GG:

General government

GFF:

Global flow of funds

GFFM:

Global flow of funds matrix

HH:

Household and HPISH

IBS:

International Banking Statistics

ICA:

Influence coefficients of assets

IFS:

International Financial Statistics

IIP:

International Investment Position

IMF:

International Monetary Fund

MFS:

Monetary and financial statistics

NFC:

Non-financial corporations

LBS:

Locational banking statistics

OI:

Other investment

Others:

Other economies

PI:

Portfolio investment

ROW:

Rest of the world

SCL:

Sensitivity coefficients of liabilities

SNA:

System of national accounts

W-to-W:

Who-to-whom

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Acknowledgements

I thank Celestino Giron (European Central Bank), my paper’s discussant at the 35th International Association for Research in Income and Wealth Conference ((IARIW, August 2018), for his valuable and enlightening advice. The latest development of GFF research is my discussion paper presented at the 36th IARIW Virtual General Conference (August 2021). I would also like to thank Artak Harutyunyan (Statistics Department, IMF), this paper’s discussant, who gave constructive forward suggestions for the paper. I thank Editor Makoto Aoshima and two anonymous reviewers for their constructive and valuable comments. Of course, all remaining errors are the author’s.

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  1. Faculty of Economic Sciences, Hiroshima Shudo University, Hiroshima, 731-3195, Japan

    Nan Zhang

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Correspondence to Nan Zhang.

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Zhang, N. Measuring global flow of funds: who-to-whom matrix and financial network. Jpn J Stat Data Sci 5, 899–942 (2022). https://doi.org/10.1007/s42081-022-00175-x

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