Staff Discussion Notes showcase the latest policy-related analysis and research being developed by individual IMF staff and are published to elicit comment and to further debate. These papers are generally brief and written in nontechnical language, and so are aimed at a broad audience interested in economic policy issues. This Web-only series replaced Staff Position Notes in January 2011.

Portfolio flows to emerging markets (EMs) tend to be correlated. A possible explanation is the role global benchmarks play in allocating capital internationally, the so-called “benchmark effect.” This paper finds that benchmark-driven investors indeed play a large role in a key segment of the market—the EM local currency government bond market—, accounting for more than one third of total foreign holdings as of end-2014. We find that the prominence of these investors declined somewhat after the May 2013 taper tantrum, but remain high. This distinction is important in understanding the drivers of EM capital flows and their sensitivity to different types of shocks. In particular, a high share of benchmark-driven investors may result in capital flows that are more sensitive to global shocks and less sensitive to country factors.

Major institutional investors in five industrial countries invest cautiously, and very little, in emerging market securities. But only in Germany are regulations on foreign investment a significant constraint.

This paper investigates to what extent low-income developing countries (LIDCs) characterized as frontier markets (FMs) have begun to be subject to capital flows dynamics typically associated with emerging markets (EMs). Using a sample of developing countries covering the period 2000–14, we show that: (i) average annual portfolio flows to FMs as a share of GDP outstripped those to EMs by about 0.6 percentage points of GDP; (ii) during years of heightened stress in global financial markets, portfolio flows to FMs dried up like those to EMs; and that (iii) FMs have become more integrated into international financial markets. Our findings confirm that, in terms of portfolio flows, FMs have become more similar to EMs than to the rest of LIDCs and are therefore more vulnerable to swings in global financial markets conditions. Accordingly, it is important to have in place frameworks to strengthen FMs’ resilience to adverse capital flows shocks.

This paper reviews some of the basic patterns of international capital flows to emerging markets in recent years, including the composition of capital flows, intraregional flow patterns, and the geographical distribution of the flows. A theoretical model that sheds new light on these observed patterns is developed. This model focuses on the cost of financing aspect of capital flows, and shows that the patterns of capital flows are influenced by the combined effects of financial market development and growth potential in the recipient countries. The theoretical predictions of the model are shown to be consistent with the stylized facts.

This dissertation examines the determinants of portfolio inflows to emerging market economies with a special focus on Korea. Chapter 1, "The Determinants of Disaggregated Capital Inflows to Korea", studies the key factors in determining portfolio investment flows to Korea from four separate investment groups: global banks, mutual funds, securities companies, and pension companies. I sort the total portfolio investment flows by each investment group such as global banks, mutual funds, securities companies, and pension companies. The US industrial production index, TED spread, and VIX are included as push factors and the Korean industrial production index, Korean bond rate, Korean stock index, and exchange rate are considered as pull factors. From the structural VAR model with dummy variables, this paper finds that portfolio investment flows to Korea are more affected by push factors during the crisis while they are more dependent on pull factors after the crisis. Portfolio investment flows to the stock market are affected mainly by the domestic stock market and global risk appetite while portfolio investment flows to the bond market react more strongly to US output growth and the domestic interest rate. Finally, this paper finds that the properties of capital inflows from each institution are quite different. For example, securities and mutual funds are more responsive to the stock market index, while insurance and pension companies are more sensitive to domestic output growth. Chapter 2, "The Determinants of Capital Inflows from Each Country", analyzes the determinants of portfolio flows to Korea using portfolio flows from each economy to Korea as the dependent variable. For the empirical model, the investor country factor was added to the existing push-pull approach, and a panel VAR model was used as the estimation method. The results suggest that investor country factors such as shocks on the interest rate and stock market in the investor country are the most important determinants to portfolio flows from advanced economies (AEs) while pull factors of recipient countries mainly drive the portfolio flows from emerging market economies (EMEs). The impact on the stock market is the dominant factor during the Fed's expansionary monetary policy, while the effects of the interest rate are the most important factor after the end of the QE. The results also show that portfolio flows from AEs respond positively to the impact of the investor country's stock market, while those from EMEs respond negatively. This study supports recent findings that the impact of the drivers on the capital flows is dependent on economic conditions and is time-varying. Chapter 3, "The International Spillovers of US Monetary Policy on Capital Flows to Emerging Market Economies", studies the impact of the US Fed's monetary policy on portfolio flows to the emerging economies, differentiating across the investor economies and type of flows. This paper also compares the effects of US monetary policy before and after the end of Quantitative Easing (QE). The results show that equity flows were retrenched to the US and AEs in response to the announcement of QE1 while the total impact of the Quantitative Easing increased the capital inflows to the emerging markets from the advanced economies. This chapter also finds that the response of portfolio flows in response to US monetary policy is conditional on the stance of US monetary policy. The findings build a bridge on the recent controversy over determinants of capital inflows by showing that QE has a significant impact on the capital inflows to EMEs, and its effects are related to the business cycle.

Using a sample of 34 emerging markets and developing economies over the period 2009Q3-2015Q4, the paper employs a panel framework to study the determinants of capital flows, both net and gross, across a wide range of instruments. The baseline regressions are then extended to focus on high and low episodes – quarters with flows one standard deviation above/below mean. Overall, the results suggest that the capital flow slowdown witnessed in recent years is due to a combination of lower growth prospects of recipient countries and worse global risk sentiment. However, the determinants of flows can be considerably different across instruments and across the type of flows considered, net or gross. The sensitivity of certain types of flows, towards push and pull factors, increases during periods of high and low capital flows. Moreover, some variables may not necessarily be significant during normal times, but can be important drivers during such episodes, and vice versa. Indicators like the gap between the U.S. long- and short-term maturity bond yields – not significant during normal times – can be an important driver during high episodes.

Capital flow volatility is a concern for macroeconomic and financial stability. Nonetheless, literature is scarce in this topic. Our paper sheds light on this issue in two dimensions. First, using quarterly data for 65 countries over the period 1970Q1-2016Q1, we construct three measures of volatility, for total capital flows and key instruments. Second, we perform panel regressions to understand the determinants of volatility. The measures show that the volatility of all instruments is prone to bouts, rising sharply during global shocks like the taper tantrum episode. Capital flow volatility thus remains a challenge for policy makers. The regression results suggest that push factors can be more important than pull factors in explaining volatility, illustrating that the characteristics of volatility can be different from those of the flows levels.

In recent years, portfolio flows to emerging markets have become increasingly large and volatile. Using weekly portfolio fund flows data, the paper finds that their short-run dynamics are driven mostly by global “push” factors. To what extent do these cross-border flows and global risk aversion drive asset volatility in emerging markets? We use a Dynamic Conditional Correlation (DCC) Multivariate GARCH framework to estimate the impact of portfolio flows and the VIX index on three asset prices, namely equity returns, bond yields and exchange rates, in 17 emerging economies. The analysis shows that global risk aversion has a significant impact on the volatility of asset prices, while the magnitude of that impact correlates with country characteristics, including financial openness, the exchange rate regime, as well as macroeconomic fundamentals such as inflation and the current account balance. In line with earlier literature, portfolio flows to emerging markets are also found to affect the level of asset prices, as was the case in particular during the global financial crisis.