Measuring global flow of funds: focus on China, Japan, and the United States

ABSTRACT

This paper aims to establish a new statistical framework for measuring global flow of funds (GFF) based on its inherent mechanisms. It advances a previous theoretical discussion and develops a practical operational statistical matrix. Based on theoretical and practical possibilities the paper gets existing data from the International Investment Position, the Coordinated Direct Investment Survey, the Coordinated Portfolio Investment Survey, and International Banking Statistics are integrated for measuring GFF. The main outcome is a prototype GFF matrix that includes stock data geographically disaggregated by country/region and selected financial instruments. The paper presents a GFF Matrix compiled with the pattern of ‘Country vis-à-vis Country’ matrix, and through using the GFF matrix to analyze the basic status, mutual relationship and existing problems between China, Japan, and the United States in the external financial positions.

KEYWORDS:

• Global flow of funds
• statistical framework
• data sources
• statistical matrix
• financial crisis

Acknowledgements

This research started in 2014 when I worked as a visiting scholar for one year in the statistics department of Stanford University. I would like to especially thank Professor Tze Leung Lai and Stat-Dept-Seminars, who inspired me to launch the research in this area. I would like to thank Mr Dennis Fixler (Bureau of Economic Analysis at U.S. Department of Commerce) for his valuable comments on my paper at the IARIW-OECD special conference (2015). I would also extend my thanks to Mr Celestino Giron (European Central Bank) who is the paper’s discussant on the 35th IARIW conference (2018) and provided helpful and constructive comments. I am grateful to Professor William Barnett, the president of the Society for Economic Measurement, who offered me two opportunities during the study of GFF statistics to host the Invited Session of GFF statistics in the 4th SEM (at MIT, July 27, 2017) and 5th SEM Conference (at Xiamen University, June 10, 2018) to discuss how to establish GFF statistics. It is important to mention that I was twice invited to attend the seminar on GFF organized by IDE-JETRO at Keio University. Many thanks to Prof. Tsujimura, K., Dr Inomata, Prof. Hagino, Prof. Tsujimura, M. and Prof. Kim, for their pertinent advice on my presentation. Many thanks also go to Mr Rob Dippelsman and Mr Robert Heath of IMF’s Statistics Departments for their comments and valuable advice. Finally, the authors would like to thank the anonymous referees and the editor for their helpful comments. Of course, all remaining errors are ours.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 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.

2 The BIS locational banking statistics 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.

Additional information

Funding

This work was supported by the grants-in-aid for scientific research (Japan): [Grant Number Scientific Research (C), 16KT0185].