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Financial liberalization and patterns of international portfolio holdings

Empirical Economics volume 49, pages 213–234 (2015)Cite this article

Abstract

International financial markets during the past several decades have been characterized by a significant rise in gross international capital flows, increased prominence of nontraditional financial institutions, and globalization of the banking sector. We utilize a 155-country panel framework to present new evidence that financial liberalization is related to reallocation of financial capital around the world. More specifically, we find that deregulation is associated with greater stocks of cross-border financial assets, overall net international indebtedness, and a net portfolio characterized by equity assets and debt liabilities.

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Fig. 1
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Notes

  1. See, for example, Rodrik and Velasco (2000), Lipsey et al. (2001), Wei (2001), Albuquerque (2003), and Prasad et al. (2003).

  2. Financial deregulation has blurred the lines between the objectives, domains, and clients of commercial banks and other financial institutions such as insurance companies, money market funds, and investment banks. Therefore, in our paper we use the term “banking sector” to describe the entirety of the interconnected financial system.

  3. Several other papers have considered the relationship between banking sector characteristics and the resulting cross-border capital flows, albeit on a smaller scale. Campos and Kinoshita (2010) use a sample of over 40 Latin American and transition economies to find that banking sector efficiency (captured by the ratio of overhead costs to total bank assets and the net interest margin) attracts foreign direct investment (FDI). Bruno and Shin (2013) demonstrate that the degree of bank leverage significantly affects cross-country capital flows through the banking sector in 46 developing and developed economies.

  4. Here we measure equity as a combination of portfolio equity and FDI.

  5. Forbes and Warnock (2012) and Fratzscher (2012) include advanced and emerging economies in their analysis, but focus specifically on episodes of substantial increases and decreases in capital flows (examined during the 1980–2009 period in the former, and centered on 2008 crisis in the latter).

  6. “Push” factors, which typically include world interest rates and GDP growth rates, operate by lowering the attractiveness of sending capital to the developed countries. “Pull” factors, such as financial liberalization, macroeconomic reforms, and exchange rate regime, allow foreign investors to choose a particular (typically developing) country of destination for their capital. See Montiel and Reinhart (1999) and Fratzscher (2012) for an overview of the relative empirical importance of these measures.

  7. Haiti received approximately $7.5 billion in aid in the two years since its devastating earthquake in 2010; this capital inflow is almost equal to Haiti’s annual output.

  8. It should be noted that these studies focus specifically on the determinates of FDI flows to developing economies.

  9. We have also attempted to run our estimation for two split samples: advanced economies, and emerging market and developing economies, based on the classification reported in the IMF’s World Economic Outlook reports. However, since the number of countries in the first sample (30) is smaller than the number of instruments, and since we already control for the level of development using per capita GDP, this exercise did not yield any additional insights.

  10. All these tests are robust to violations of the variance-covariance matrix of random effects model. The results of the specifications tests are available from the authors upon request.

  11. Since we are not estimating the four regressions jointly, this minor transformation of the control variables does not compromise our main results.

  12. An alternative way to gauge the relative importance of \(\textit{HFI}\,\) is to compute percent contributions of its variation to the actual, rather than fitted, values of capital stocks volatilities, \(Y_{i,t}\). Mathematically, this entails eliminating the term \(Var\left( \varepsilon _{i,t}\right) \) from the denominator of (2). The results, not reported here for space considerations, are unsurprisingly numerically larger than the ones shown in Table 4.

  13. Staveley-O’Carroll (2013) develops a two-country multiple-asset model in which a global financial intermediary trades in debt and equity assets across national borders. In particular, the model demonstrates that banking liberalization leads to an increase in a country’s gross international asset holdings and to a positive net equity position.

  14. See the special report on international banking, Twilight of the Gods, in the May 11, 2013 issue of the Economist.

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Authors and Affiliations

  1. Department of Economics and Business, Colorado College, 14 E. Cache La Poudre St., Colorado Springs, CO, 80903, USA

    Pedro de Araujo

  2. Department of Economics, Robins School of Business, University of Richmond, 28 Westhampton Way, Richmond, VA, 23173, USA

    Olena Mykhaylova

  3. Economics Department, College of William and Mary, P.O. Box 8795, Williamsburg, VA, 23187, USA

    James Staveley-O’Carroll

Authors
  1. Pedro de Araujo
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  2. Olena Mykhaylova
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  3. James Staveley-O’Carroll
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Corresponding author

Correspondence to Olena Mykhaylova.

Appendix: Data sources and description

Appendix: Data sources and description

Capital stocks

The four measures of capital stocks are taken from the External Wealth of Nations Mark II database, Lane and Milesi-Ferretti (2007). All data are reported in millions of current US dollars.

Gross holdings of assets and liabilities (\(\textit{GH}\)) is the sum of total assets and total liabilities of each country. Total assets is the sum of FDI assets, portfolio equity assets, debt assets, derivatives assets, and foreign exchange reserves (excluding gold holdings). Total liabilities are calculated analogously (excluding foreign exchange reserves).

Net Equity (\(\textit{NE}\)) is calculated as portfolio equity assets \(+\) FDI assets \(-\) portfolio equity liabilities \(-\) FDI liabilities.

Net Debt (\(\textit{ND}\)) is computed as Debt assets (portfolio debt \(+\) other investment) \(-\) Debt liabilities (portfolio debt \(+\) other investment).

Net Foreign Assets (\(\textit{NFA}\)) measures the difference between a country’s total assets and total liabilities.

Index of Economic Freedom

The following indices and their descriptions are obtained from the Index of Economic Freedom, available online at http://www.heritage.org/index.

The index of financial freedom (\(\textit{HFI}\)). “Financial freedom is a measure of banking efficiency as well as a measure of independence from government control and interference in the financial sector. State ownership of banks and other financial institutions such as insurers and capital markets reduces competition and generally lowers the level of available services... The index scores an economy’s financial freedom by looking into the following five broad areas: the extent of government regulation of financial services; the degree of state intervention in banks and other financial firms through direct and indirect ownership; the extent of financial and capital market development; government influence on the allocation of credit; and openness to foreign competition.”

The index of business freedom (\(\textit{BF}\)). “Business freedom is an overall indicator of the efficiency of government regulation of business. The quantitative score is derived from an array of measurements of the difficulty of starting, operating, and closing a business. The business freedom score for each country is a number between 0 and 100, with 100 equaling the freest business environment. The score is based on 10 factors, all weighted equally, using data from the World Bank’s Doing Business study: starting a business—procedures (number); starting a business—time (days); starting a business—cost (% of income per capita); starting a business—minimum capital (% of income per capita); obtaining a license—procedures (number); obtaining a license—time (days); obtaining a license—cost (% of income per capita); closing a business—time (years); closing a business—cost (% of estate); and closing a business—recovery rate (cents on the dollar). Each of these raw factors is converted to a scale of 0 to 100, after which the average of the converted values is computed.”

Investment freedom index (\(\textit{IF}\)). “The index evaluates a variety of restrictions that are typically imposed on investment. Points... are deducted from the ideal score of 100 for each of the restrictions found in a country’s investment regime.” The categories include: the degree of national prescreening of foreign investment; restrictions on land ownership; sectoral investment restrictions; expropriation of investments without fair compensation; foreign exchange controls; and capital controls. Additional points “may be deducted for security problems, a lack of basic investment infrastructure, or other government policies that indirectly burden the investment process and limit investment freedom.”

Index of property rights (\(\textit{PR}\)). “The property rights component is an assessment of the ability of individuals to accumulate private property, secured by clear laws that are fully enforced by the state. It measures the degree to which a country’s laws protect private property rights and the degree to which its government enforces those laws. It also assesses the likelihood that private property will be expropriated and analyzes the independence of the judiciary, the existence of corruption within the judiciary, and the ability of individuals and businesses to enforce contracts. The more certain the legal protection of property, the higher a country’s score; similarly, the greater the chances of government expropriation of property, the lower a country’s score.”

Freedom from corruption (\(\textit{FC}\)). “The score for this component is derived primarily from Transparency International’s Corruption Perceptions Index (CPI)..., which measures the level of corruption in 183 countries. The CPI is based on a 10-point scale in which a score of 10 indicates very little corruption and a score of 0 indicates a very corrupt government. In scoring freedom from corruption, the index converts the raw CPI data to a scale of 0 to 100 by multiplying the CPI score by 10.”

Other controls

Gross domestic product (\(\textit{GDP}\)), measured in millions of current US dollars, is taken from the extended version of the External Wealth of Nations Mark II database, Lane and Milesi-Ferretti (2007).

Population (\(\textit{POP}\)), in thousands. Penn World Table Version 7.1, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, November 2012, series POP.

Trade volume (\(\textit{VOL}\)), measured in current US dollars, is the sum of a country’s imports and exports of goods and services. Source: The World Bank World DataBank (series BX.GSR.GNFS.CD for exports, series BM.GSR.GNFS.CD for imports).

Exchange rate regime (\(\textit{FX}\)) classification (coarse) is taken from Ilzetzki et al. (2008). It ranges from 1 (no separate legal tender; or pre-announced peg or currency board arrangement; or pre-announced horizontal band that is narrower than or equal to \(\pm \)2 %; or de facto peg) to 4 (freely floating), and includes two additional categories beyond free float: 5 (freely falling) and 6 (dual market in which parallel market data is missing).

Sample countries (155)

Albania, Algeria, Angola, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahrain, Bangladesh, Belarus, Belgium, Belize, Benin, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Bulgaria, Burkina Faso, Burundi, Cambodia, Cameroon, Canada, Cape Verde, Central African Rep., Chad, Chile, China, Colombia, Congo, Dem. Rep.of, Congo, Republic of, Costa Rica, Cô te d’Ivoire, Croatia, Cyprus, Czech Republic, Denmark, Djibouti, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Estonia, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hong Kong, Hungary, Iceland, India, Indonesia, Iran, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyz Republic, Lao People’s Dem. Rep., Latvia, Lebanon, Libya, Lithuania, Luxembourg, Macedonia, Madagascar, Malawi, Malaysia, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Sierra Leone, Singapore, Slovak Republic, Slovenia, South Africa, South Korea, Spain, Sri Lanka, Sudan, Swaziland, Sweden, Switzerland, Syrian Arab Republic, Taiwan, Tajikistan, Tanzania, Thailand, Togo, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, United States, Uruguay, Uzbekistan, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe.

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de Araujo, P., Mykhaylova, O. & Staveley-O’Carroll, J. Financial liberalization and patterns of international portfolio holdings. Empir Econ 49, 213–234 (2015). https://doi.org/10.1007/s00181-014-0863-1

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  • DOI: https://doi.org/10.1007/s00181-014-0863-1

Keywords

  • Financial liberalization
  • Portfolio holdings
  • Panel data analysis

JEL Classification

  • E44
  • F21
  • F36