Academic journal article NBER Reporter

The Future of Investment in Emerging Markets

Academic journal article NBER Reporter

The Future of Investment in Emerging Markets

Article excerpt

Emerging market investments are certainly not for the faint of heart. In the early 1990s, several papers promoted the high average returns in these markets. Indeed, on the surface, these returns appeared to be much higher than those generated by investing in developed countries. At the same time, several developing countries liberalized their equity markets, allowing foreigners relatively unfettered access to them. As a result of these liberalizations and of domestic U.S. conditions, there was a sharp increase in U.S. capital flows to these equity markets.

Despite the considerable history of research on emerging markets, much of the current work was initiated as a result of the World Bank Conference on Portfolio Investment in Developing Countries, held in Washington in late 1993. Stijn Claessens and Sudarshan Gooptu brought together there a diverse group of academics and practitioners to try to gain a better understanding of emerging equity markets, and a number of myths about emerging markets were put to rest. Some of the ideas presented at the conference motivated much of the research, including my own, on emerging markets over the next five years. That research is discussed here.

Special Challenges

I discuss these data challenges first, because we can ask many interesting questions about emerging markets, but we must take into account the special features of the data before trying to answer these questions. Most empirical research on emerging markets relies on the International Finance Corporation (IFC) indexes. These indexes represent portfolios of securities that comprise at least 60 percent of the market capitalization in each emerging market. For some countries, there are only a few stocks in the IFC index portfolio. For example in December 1997, there were only 15 securities in the IFC global index for Hungary, 17 in the Moroccan portfolio, and 19 in the Venezuelan portfolio. Korea had the largest number (195) of securities. India had 133 securities in its IFC index, but more than 5,000 equity securities are listed in India. The small number of securities in these indexes means that the country portfolio may contain some variance that is usually diversified away with larger portfolios.

The IFC launched its data product in 1981. However, it reports data on eight countries back to December 1975, and on one country back to 1977. These data were "backfilled,"(1) which led to an obvious bias. The stocks selected in 1981 for the indexes would not necessarily be those selected in December 1975. This "look-back bias" should raise the portfolios' observed mean performance.

There may be other biases in emerging market equity data as well. Goetzmann and Jorion(2) showed that historically, markets have emerged, submerged, and re-emerged. For example in the 1920s, Argentina had a larger market capitalization than did the United Kingdom. However, its equity market all but disappeared by the 1930s. When we sample the data from 1981 and calculate statistics based only on this sample, we overlook what has happened in the longer term. While this is true for any market, it is particularly acute in emerging markets.

Further, there is extraordinary volatility in emerging markets. For example, from January 1981 to March 1998 the returns on the U.S. dollar index created by Morgan Stanley Capital International had a standard deviation of 14.4 percent on an annual basis. Among the 28 emerging markets with more than three years of available data, dollar returns in 26 markets had standard deviations that were double the U.S volatility; 9 markets had triple the U.S. volatility; and 7 had more than quadruple the U.S. volatility.

High volatility need not be a problem for analysis, but the data need to be analyzed with care. For example, practitioners were promoting the high average returns of these emerging markets in the early 1990s, while I pointed out (see n. 1) that there is a large difference between arithmetic and geometric average returns. …

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