Page 426 - Special Topic Session (STS) - Volume 3

STS552 Swapan-Kumar Pradhan et al.

Uses of mirror data: Estimation of household
assets with banks abroad
1
Swapan-Kumar Pradhan , João Falcão Silva 2
1 Senior Statistical Analyst, Monetary and Economic Department, BIS
2 Head of Unit Financial account, BoP and IIP Statistics, Statistics Department, Bank of Portugal

Abstract 3
This paper aims to analyse and estimate cross-border assets of households in
the form of bank deposits and bank loans. Such data are scarce and there is
no comprehensive system to collect and compile this information directly. The
lack of available information combined with a complex delimitation of this
institutional sector represent challenging issues to the compilers. The
international locational statistics of the Bank for International Settlements (BIS)
cover cross-border assets and liabilities of reporting banks broken down by
counterparty sector in individual countries around the world. We apply mirror
data approach to derive assets of households sector in a given country using
source data as the cross-border liabilities of banks to this sector in respective
countries. In addition, we apply our method to estimate data backwards for
periods when International Banking Statistics (IBS) data for this sector are
either limited from 2013Q4 or not available prior to 2013Q4.

Keywords
data gaps; foreign assets/liabilities; households; international banking; mirror
data.

1. Introduction
In a more globalized world, the institutional sector “households” is a
statistical challenge for the compilers due to non-availability of data or access
to accurate data. We address this issue by focusing on cross-border
assets/liabilities of this sector vis-à-vis foreign banks using the BIS locational
banking statistics (LBS). We apply the mirror data approach which refers to
complementary sources that capture similar concepts and is indeed a crucial
statistical tool that allows to fill-in data gaps. The mirror data approach
involves involve comparison of different statistical data sets that can be

3 We thank Bruno Tissot and Philip Wooldridge of the BIS and Filipa Lima, Luís Teles Dias and
Paula Menezes (Bank of Portugal) for their continued encouragement and support on mirror
exercise to enhance the quality and coverage of data. We also thank Patrick McGuire (BIS) and
all the contributions from then central banks, particularly colleagues in the Bank of England
(Marek Rojicek) and Bank of Finland (Johanna Honkanen) for helpful comments, suggestions
and discussions. The views expressed are those of the authors and do not necessarily reflect
those of the Bank for International Settlements or the Bank of Portugal.
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