In this paper we construct a new methodology to measure the international income smoothing and present stronger connectionbetween international asset holding and international income smoothing for OECD countries.Capital Market Integration, Home Bias, Income Smoothing

Balli, Faruk

Jean Louis, Rosmy

Osman, Mohammad

English

Research Papers in Economics

Income Smoothing and Foreign Asset Holdings.
Faruk Balli
Massey University
Rosmy J. Louis
Vancouver Island University
Mohammad Osman
University of Dubai
October 10, 2011
Abstract
In this paper we construct a new methodology to measure the international income
smoothing and present stronger connection between international asset holding and inter-
national income smoothing for OECD countries.
JEL classication: F155, F36, F41
Keywords: Capital Market Integration, Home Bias, Income Smoothing.
11 Introduction
In this paper, we re-examine the ties between international portfolio allocation and income
smoothing. We propose a revised approach of measuring income smoothing via foreign asset
holdings that focuses on factor income inows as opposed to the commonly used net factor
income in the literature mainly proposed by Srensen et al. (2007). A compelling reason for
purely concentrating on factor income inows is mainly that during recession periods wages,
interest, and prots tend to be lower and this may entail a reduction in outows, consequently
an overestimation of net foreign factor income and its impact on income smoothing via inter-
national asset holdings. Using net factor income in our views carries the potential drawback
of producing higher (lower) smoothing than normal during recession (expansion). The factor
income inow by contrast does not suer from this shortcoming. Its movement or magni-
tude does not necessarily synchronize with uctuations in domestic output. Since this paper's
primary concern is to construct the strong tie with the international portfolio allocation and
international income smoothing, it is less likely to add factor outows to get a valid estimation
of income smoothing via domestic investors' international portfolio allocation.
Macroeconomic models are built on the central assumption that economic agents are either
rational or near-rational. Grubel (1968) explains investors' rationale for holding internationally
diversied portfolio by looking at the mean-variance of both portfolios with purely domestic
assets and portfolios with a combination of domestic and foreign assets. He shows that the
mean-variance of the latter is smaller than the former. Lewis (1996 and 1999) substantiates
Grubel's main ndings by providing both theoretical foundation and empirical evidence. How-
ever, Poterba (1991) and Tesar and Werner (1995) have observed that investors in high income
countries do not hold foreign nancial assets as much as they should optimally. A large portion
of their nancial assets are from the domestic market, a behavior that is known as \home bias".
Nevertheless, over the last decade, capital market integration has grown tremendously leading
to higher volumes of international assets trading across borders. This has led to a downward
trend in home bias levels, in particular among high-income OECD members. In aggregate
level data, Srensen et al. (2007) have recently shown that there is a strong connection be-
tween the volume of cross-border assets holding and income smoothing. More intuitively, this
2implies that the more internationally diversied an investor's portfolio is the higher possibility
to smooth income as they are able to switch income from the foreign markets to the domestic
market to keep their levels of consumption relatively stable over time at home.
2 Methodology
The literature on income smoothing via international asset holding suggests that investors
who diversify their portfolio enjoy income smoothing via their holding of international assets.
Therefore, foreign assets' holding is equivalent to an insurance against economic downturns at
home. It is customary in the literature to use the dierence between gross domestic product
(GDP) and gross national product (GNP) as a proxy of the amount of net income ows across
countries to gauge the extent of risk sharing across countries. That is:
GNP  GDP + Rd  Ad   Rf  Af ;
where Af is the stock of domestic assets owned by foreign residents, Rf is the rate of return
on these assets, and Ad and Rd are the stock of and the return on domestically-owned foreign
assets, respectively.1
At the aggregate level, Srensen and Yosha (1998) applied the following regression to
measure income smoothing via cross border asset holdings:
log GDPi
t   log GNPi
t = f;t + f log GDPi
t + i;t ; (1)
where log GDP is the annual change in GDP per capita in constant prices and log GNP is the
annual change in GNP per capita in constant prices. When coecient of f is the coecient
estimate that captures income smoothing from net factor income ows, f;t and i;t are xed
eect and error terms, respectively. A positive value of f implies that net factor income from
abroad is not perfectly correlated with idiosyncratic output shocks; thereby oering some
income smoothing for the domestic output shocks. As f approaches 1, the country under
consideration experiences greater income smoothing from international asset holdings.
1In fact this is only an approximate relationship between the GDP and GNP. However, we neglect the
remittances which is counted in GNP calculation. For detailed the formula you may check the U.N. Statistics
Database.
3Our approach for excluding the income outows from the net factor income can be explained
by the fact that during recession(expansion) periods wages, interest, and prots tend to be
lower(higher) and this may entail a reduction(expansion) in outows, consequently an overesti-
mation(underestimation) of net foreign factor income and its impact on income smoothing via
international asset holdings. Net factor income in our views carries the potential drawback of
producing higher(lower) smoothing than normal during recession(expansion). However, factor
income inows are not be eected from those estimation biases. Therefore, we reconstruct this
methodology by proposing a measure of income that is reective of purely international asset
holding earnings to capture income smoothing eectively.
Our model can be written as follows;
log GDPini
t   log GDPi
t = f;t + f+ log GDPi
t + i;t ; (2)
where GDPin is dened as GDP + factor income inows. The structure of this equation
documents that we only consider the income inows coming from abroad instead of the net
income ows.
3 Data
We use a broad sample of high-income OECD countries to investigate the relationship between
international portfolio allocation and income smoothing and test whether our innovation of
solely focusing on factor income inow makes a dierence to the existing literature.2 We ob-
tained a pair-wise volume of cross border equity holdings in US dollars from the International
Monetary Fund's Coordinated Portfolio Investment Surveys (CPIS). Total market capitaliza-
tion of equity markets are obtained from the World Development Indicators Database. To
estimate the risk-sharing regressions, we gather national accounts data from OECD National
Accounts{Main Aggregates (Volume I) and detailed tables (Volume II) that cover the period
1970{2006.
2Data set include Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Nether-
lands, Portugal, Spain, Australia, Canada, Japan, Iceland Korea, New Zealand, Norway, Singapore, Sweden,
Switzerland, UK, and US.
4We dene \home portfolio bias" as the excessive investment in domestic portfolio compared
with the optimal amount of allocation of domestic portfolio that international CAPM model.
The home equity bias index is calculated as:
HOMEBIASi
t =
(1   Fi
t)
(1   Di
t)
: (3)
where Fi
t is the foreign equity ratio in total equity portfolio of country i at time t. Total equity
portfolio of country i is equal to stock market capitalization + foreign equity held - amount
of country's equity held by foreigners. Di
t is a ratio of stock market capitalization of country
i to stock market capitalization of the world. Figure 1 contains the home bias levels of the
sample. We clearly observe gradual decrease in the home equity bias which is consistent with
the higher volume of foreign asset trading for the OECD members.
Figure 1 here
4 Empirical Findings
Table 1 shows both our innovation to focus on factor income inows and the net factor income
ows. Both models report higher levels of income smoothing in the very last years which
is perfectly consistent with capital market integration. By looking at Figure 1, for the euro
members, since home equity bias levels are quite lower than non-EMU OECD members, we
shall expect higher level income smoothing via international asset holdings which is further
documented in Table 1.
We carry out a sensitivity analysis to determine whether the dierence in the methodology
stands on rm grounds. We drop Ireland and Netherlands, which have the lowest home equity
bias levels among euro members from the sample.3 The results are reported in Table 2 with
3 panels. Panel A shows the results of the truncated sample dened above. It can be gleaned
that the coecient of smoothing via factor income inows, +, decreases considerably in the
last two sub-periods whereas the net factor income smoothing, f, does not change that much,
though we expected it to decrease also. The coecients in the Panel A indicates that income
3Since it has negative level, Ireland's home equity bias levels has not been reported in Figure 1.
5smoothing is much higher if we consider Ireland and the Netherlands which are the most
\open" countries across the Euro area.
In panel B of Table 2, we drop Greece, the member with the highest home equity bias level
among euro members, from the regression equation instead. Expectedly, the income smoothing
via factor income inows increases from 12 % to 17 % and are statistically signicant for the
last two sub-periods, whereas the former smoothing model does not have that sensitivity,
even it reacts in the opposite direction after we drop Greece. In Panel C of Table 3, we
performed a similar test for non-EU OECD members, by dropping Switzerland, having the
lowest home equity bias level among OECD-EU members, income smoothing through our
methodlogy decreases from 3 % to 2 % whereas regressions based up on the net income ows
does not show that level of sensitivity after dropping Switzerland.
This simulation demonstrates that a clear relationship between foreign equity holdings
and income smoothing via net factor inows exists but the same cannot be said for net factor
income inows. In light of these facts, and considering the genuine relationship between the
foreign asset holdings and income smoothing, we surmise that our approach of using factor
income inows is superior to the existing net factor income approach in the literature to
measure income smoothing via capital markets across countries.
This paper has made a practical contribution to the literature in explaining the factors
underlying income smoothing. However, we have only considered the equity market and found
that it is the most signicant factor. Also, considering recent literature to believe that interna-
tional debt securities' trading does not have such power. This is consistent with recent studies
by Pagano (2004), Codogno et al.(2003), and Balli (2008). These authors nd that there is a
high correlation between bond markets which restrains income smoothing.4
4Adjaout et al.(2002) concluded that since government bond yield dierentials across euro region are in
very small amount and corporate bond returns are highly correlated, euro bond bias, which is very high across
OECD countries, does not create ample opportunity for income smoothing.
65 Conclusion
In this paper we present new empirical evidence on the linkages between international asset
trading and income smoothing. We have used factor income inows instead of net factor
income that is common in the literature and found strong correlation between risk sharing and
international asset holdings. Our results are more robust compared to the previous literature
estimations.
7References
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Balli, F. (2008) Spillover eects on government Bond yield spreads in Euro zone. Does perfect
integration exist among EMU members? Journal of Economics and Finance Forthcom-
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Codogno, L., Favero, C., and Missale, A. (2003) EMU and government bond spreads, Eco-
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American Economic Review, 58, 1299{1314.
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8Table 1: Income Smoothing (percent) via International Factor Income.
Panel A: OECD-EU
1971{1980 1981{1990 1991{2000 2001{2006
f+ {1.64 {0.52 2.32 2.96
(0.95) (0.94) (1.47) (2.66)
f 1.41 {2.95 {1.98 2.26
(0.62) (1.42) (1.29) (2.93)
Panel B: EMU
1971{1980 1981{1990 1991{2000 2001{2006
f+ 0.43 {3.1 6.25 12.13
(0.91) (1.52) (2.06) (6.06)
f -0.98 {2.01 4.61 9.47
(0.75) (1.93) (2.34) (2.52)
Notes.OECD{EU: Australia, Canada, Japan, Korea Republic, New Zealand, Norway,
Switzerland, and US. EMU: Austria, Belgium, Finland, France, Germany, Greece, Ireland,
Italy, Netherlands, Portugal, and Spain. We exclude Luxembourg, since it is an outlier with
its position. Percentages of shocks absorbed at each level of smoothing. Standard errors in
brackets. The table shows, for incoming factor income, the coecient f+, the GLS estimate
of the slope in the regression of log(GDPi+ international factor income received) log GDPi
on log GDPi. The coecient f, is the GLS estimate of the slope in the regression of
log GDPi   log GNPi on log GDPi.
9Table 2: Income Smoothing (percent) from International Factor Income.
Panel A: EMU without Ireland and Netherlands
1971{1980 1981{1990 1991{2000 2001{2006
f+ 1.14 {4.04 0.57 4.87
(0.81) (1.81) (2.23) (5.82)
f {1.23 {3.32 {0.3 8.48
(0.69) (1.75) (2.57) (2.63)
Panel B: EMU without Greece
1971{1980 1981{1990 1991{2000 2001{2006
f+ 1.34 {2.03 7.31 17.06
(0.86) (1.77) (2.06) (6.86)
f {1.64 {3.13 4.49 5.33
(0.77) (1.93) (2.41) (3.17)
Panel C: OECD-EU without Switzerland
1971{1980 1981{1990 1991{2000 2001{2006
f+ {2.75 {3.61 1.16 1.63
(0.88) (1.42) (1.79) (1.94)
f 0.83 {3.37 {3.13 2.11
(0.61) (0.92) (1.43) (3.46)
Notes.OECD{EU: Australia, Canada, Japan, Korea Republic, New Zealand, Norway,
Switzerland, and US. EMU: Austria, Belgium, Finland, France, Germany, Greece, Ireland,
Italy, Netherlands, Portugal, and Spain. Percentages of shocks absorbed at each level of
smoothing. Standard errors in brackets. The table shows, for incoming factor income, the
coecient f+, the GLS estimate of the slope in the regression of log(GDPi+ international
factor income received) log GDPi on log GDPi. The coecient f, is the GLS estimate of
the slope in the regression of log GDPi   log GNPi on log GDPi.
10

Income smoothing and foreign asset holdings.

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