Abstract
This paper shows that financially remote countries exhibit more positive net external positions, hence hinting at external funding problems for more remote countries. This finding is found to be stronger for emerging and developing countries. However, being located near financially very open countries, being in currency unions with creditor countries, or being highly integrated through financial and trade linkages with a ‘core’ country facilitates net external borrowing. We also find evidence that remoteness affects primarily the gross liability side of the external balance sheet and has a stronger impact on the net equity position than on the net debt position. Consequently, the paper demonstrates the important role of geographic and bilateral factors for a country’s net external wealth.
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Notes
The net external position of the United States has been analysed in-depth over the last years. Gourinchas and Rey (2007) and Habib (2010), among others, find evidence for an ‘exorbitant privilege’ of the United States by running sizeable excess returns on its net external position before the crisis period. This goes along with a net foreign asset position that is less negative than suggested by the current account deficits of the United States.
This corresponds to excluding countries from the reduced sample that are above the 80th percentile in terms of GDP per capita. All of these belong to the group of high-income countries as defined in the the World Bank’s World Development Indicators (2011) database. See Appendix 1 for a list of these countries.
Australia and New Zealand are both very remote countries while also being substantial net debtors with net external positions of −61 and −89 %, respectively, over the period of 2005–2007. This circumstance supports the hypothesis of rich countries being less affected by financial remoteness. As a robustness check we also include Australia and New Zealand in the less advanced sample (based on their large net foreign liability positions), but find the results of the empirical analysis to hold nonetheless.
This point will be further elaborated on in Sect. 3.3.1.
Non-Ricardian behaviour means that the government’s budget constraint is not internalised by private economic agents.
In addition, we included the share of natural resources in total exports as natural resource wealth can be associated with accumulated export revenue. On the other hand, it could also attract FDI inflows. Moreover, we include stock market capitalisation (as a ratio) to GDP, a domestic financial reform index from Abiad et al. (2008), and an aggregate measure of country risk. Among these variables, the financial reform index is the only one found to be significant (with a negative sign). However, the inclusion of these variables reduces the sample size substantially such that the regression results are not reported. We leave it for further research to explore for example the role of cultural factors such as differences in inter-temporal preferences.
These are the United States, the United Kingdom, France, Germany, Japan, the Netherlands, Switzerland, and Ireland.
In fact, very similar measures are used as robustness checks by Rose and Spiegel (2009).
Based on Rose and Spiegel (2004), we use a strict currency union dummy that is equal to 1 if both countries are in a currency union.
Consequently, this composite variable is zero for an economy without any contiguous countries.
In line with the bilateral asset trade literature, we also construct weighting matrices based on common language between countries. However, we do not find significant coefficients for these variables.
We also experiment with different weighting schemes, for example bilateral asset holdings and bilateral trade and find very similar results.
This method reveals that Germany is the ‘core’ for many European countries (supplemented by Austria for Eastern European countries), the United Kingdom for many Asian countries, France for a lot of African countries, and Spain as well as the United States for Latin American countries.
Here, the United States is the core country for the majority of Asian, European, and Latin American countries.
For most Asian and Latin American countries, the United States is the largest export market.
Joint significance of the demographic variables is not found in the estimations presented in columns (2) and (8) of Table 3. This indicates that the demographic variables are of less importance for less advanced countries once we control for international financial remoteness based on pure distance measures.
This is in line with Bussiere et al. (2006) who show that departures from Ricardian equivalence are especially present in liquidity constrained countries.
However, the signs on the IFI and Chinn and Ito variables are negative.
Table 4 Neighbourliness: contiguity Note that the number of observations decreases from 149 to 135, as data coverage of the CPIS database is lower than in the BIS database.
More generally, the coefficient on financial remoteness is very robust to expanding the list of creditor countries. The reason is that the largest creditor countries are all located in Europe, North America, or Asia.
The domestic financial reform index from Abiad et al. (2008) is found to be significant (with a negative sign), while reducing the sample to 88 observations. We leave it for further research to explore for example the role of cultural factors such as differences in inter-temporal preferences.
For example, Klein et al. (2002) suggest that that FDI is information intensive, leading to problems for FDI investors to raise funding for their investments as they have more knowledge about their investment than outsiders. Theoretically, Razin et al. (1998) show that FDI investors are endowed with better information than other foreign investors.
Strikingly, the demographic structure is only significant for the net debt position.
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Acknowledgments
I am grateful to Philip Lane for very helpful advice and comments. I am also thankful for comments and discussions to the editor Harmen Lehment, two anonymous referees, an anonymous referee of the ECB Working Paper Series, Michael Fidora, Doireann Fitzgerald, Marcel Fratzscher, Maurizio Habib, Christiane Hellmanzik, Paul Scanlon and conference participants at the Conference on “Intra-European Imbalances, Global Imbalances, International Banking, and International Financial Stability,” Berlin 2012, as well as seminar participants at the European Central Bank and at Trinity College Dublin. Financial support of the Irish Research Council for the Humanities and Social Sciences (IRCHSS) from 2008 to 2010 is gratefully acknowledged.
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Appendices
Appendix 1: Country sample and data sources
Country sample
Albania | Djibouti | Lao people’s Dem. Rep | Rwanda |
Algeria | Dominican Republic | Latvia | Samoa |
Angola | Ecuador | Lebanon | Saudi Arabia |
Argentina | Egypt | Lithuania | Senegal |
Armenia | El Salvador | Macedonia | Sierra Leone |
Australia | Equatorial Guinea | Madagascar | Singapore |
Austria | Eritrea | Malawi | Slovak Republic |
Azerbaijan | Estonia | Malaysia | Slovenia |
Bahrain | Ethiopia | Maldives | South Africa |
Bangladesh | Fiji | Mali | Spain |
Belarus | Finland | Malta | Sri Lanka |
Belgium | France | Mauritania | Sudan |
Belize | Gabon | Mauritius | Swaziland |
Benin | Gambia, The | Mexico | Sweden |
Bhutan | Georgia | Moldova | Switzerland |
Bolivia | Germany | Mongolia | Syrian Arab Republic |
Bosnia and Herzegovina | Ghana | Morocco | Tajikistan |
Botswana | Greece | Mozambique | Tanzania |
Brazil | Grenada | Namibia | Thailand |
Bulgaria | Guatemala | Nepal | Togo |
Burkina Faso | Guinea | Netherlands | Tonga |
Burundi | Haiti | New Zealand | Trinidad and Tobago |
Cambodia | Honduras | Nicaragua | Tunisia |
Cameroon | Hungary | Niger | Turkey |
Canada | Iceland | Nigeria | Uganda |
Cape Verde | India | Norway | Ukraine |
Chad | Indonesia | Oman | United Arab Emirates |
Chile | Iran, Islamic Republic of | Pakistan | United Kingdom |
China, P. R.: Mainland | Ireland | Panama | United States |
Colombia | Israel | Papua New Guinea | Uruguay |
Congo, Dem. Rep. of | Italy | Paraguay | Uzbekistan |
Congo, Republic of | Jamaica | Peru | Venezuela, Rep. Bol. |
Costa Rica | Japan | Philippines | Vietnam |
Croatia | Jordan | Poland | Yemen, Republic of |
Cyprus | Kazakhstan | Portugal | Zambia |
Czech Republic | Kenya | Qatar | |
Cote d’Ivoire | Korea | Romania | |
Denmark | Kyrgyz Republic | Russia |
Most advanced countries (in terms of GDP per capita)
Australia | Finland | Japan | Spain |
Austria | France | Korea | Sweden |
Bahrain | Germany | Netherlands | Switzerland |
Belgium | Greece | New Zealand | United Arab Emirates |
Canada | Iceland | Norway | United Kingdom |
Cyprus | Ireland | Qatar | United States |
Denmark | Israel | Singapore | |
Equatorial Guinea | Italy | Slovenia |
Data sources
Variables | Source |
|---|---|
(Net) external position | Lane and Milesi-Ferretti (2007) |
GDP per capita | World Bank—WDI |
Demographic variables | United Nations (2007): World Population Prospects: The 2006 Revision |
Public debt | Panizza (2008) and National Sources |
Distance and contiguous dummy | CEPII (2006) |
Time difference | |
Currency union dummy | Rose and Spiegel (2004) |
Capital account openness | Chinn and Ito (2008) |
Bilateral bank claims | BIS (2009) |
Bilateral portfolio holdings | IMF (2009a) |
Bilateral exports | IMF (2009b) |
Appendix 2: Demographic specification
Our demographic specification follows Fair and Dominguez (1991) and Higgins (1998), and was introduced as a determinant of net external positions by Lane and Milesi-Ferretti (2002). We divide the population into J = 12 age cohorts and the age variables enter the net foreign assets equation as ∑ 12 j=1 α j p jt where p jt is the population share of cohort j in period t and ∑ 12 j=1 α j = 0. We make the restrictions that the coefficients lie along a cubic polynomial
The zero-sum restriction on the coefficients implies that
In turn, we can estimate γ1, γ2, γ3 by introducing the age variables into the specification as
where
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Schmitz, M. Financial remoteness and the net external position. Rev World Econ 150, 191–219 (2014). https://doi.org/10.1007/s10290-013-0168-z
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DOI: https://doi.org/10.1007/s10290-013-0168-z