1 / 34

Liquidity, Institutional Quality, and the Composition of International Equity Flows

Liquidity, Institutional Quality, and the Composition of International Equity Flows. Itay Goldstein (Univ of Pennsylvania) Assaf Razin (Tel Aviv and Cornell Univ) Hui Tong (International Monetary Fund) Conference on International Adjustment, Brussels; 9-10 November 2007. Motivation.

rrosie
Download Presentation

Liquidity, Institutional Quality, and the Composition of International Equity Flows

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Liquidity, Institutional Quality, and the Composition of International Equity Flows Itay Goldstein (Univ of Pennsylvania) Assaf Razin (Tel Aviv and Cornell Univ) Hui Tong (International Monetary Fund) Conference on International Adjustment, Brussels; 9-10 November 2007

  2. Motivation • Little is known about the determinants of equity flows (Foreign Direct Investment vs Foreign Portfolio Investment.) from source countries. • Traditionally, multinational firms engage in FDI, while collective investment funds in FPI. But as in 2006 World Investment Report, investment funds have become important sources of FDI. Their cross-border M&As, reached $135 billion and accounted for 20% of global M&As. • More work is needed to understand the composition of equity flows.

  3. Key Questions and Approaches • This paper focuses on the impact of liquidity on investors' choice between FDI and FPI. • We first extend the theoretical model of Goldstein and Razin (2005) by introducing aggregated liquidity shock and capital market transparency. The extended model predicts that countries with higher probability of aggregate liquidity crises will be the source of more FPI and less FDI.

  4. Findings • To test the prediction, we examine the variation of FPI v.s. FDI for 140 source countries from 1985 to 2004. • Our key explanatory variable is the estimated probability of aggregate liquidity shocks, as proxied by net sale of foreign assets (international reserves, credit and equity) . • The probability of liquidity crises indeed has strong impacts on the composition of foreign investment, as predicted by our model. • Moreover, greater capital market opacity in the source country strengthens the impact of the crisis probability.

  5. Implication of Our Findings • Our findings help explaining the recent trend of collective investment funds as growing sources of FDI, and shed some light on how this trend may be affected by liquidity crunch.

  6. Outline • Theoretical Model • Data • Empirical Model and results • Conclusion

  7. FPI vs FDI • A key difference between FDI and FPI: FDI investors have the management of the firms under their control; but FPI investors delegate decisions to managers. • Hence, direct investors are more informed than portfolio investors regarding projects, which enables them to manage projects more efficiently. • But this info advantage comes with a cost. If investors need to sell the projects before maturity due to liquidity shocks, the price they can get will be lower when buyers know that they have more info on the project. • Tradeoff between management efficiency and liquidity.

  8. Production Function Three periods: 0, 1, 2; Project is initially sold in Period 0 and matures in Period 2. Production function Distribution Function

  9. Value of FDI till Maturity In Period 1, after the realization of the productivity shock, the direct Investor observes the shock and chooses the level of K: Expected Return at t=0

  10. Value of FPI till Maturity • Portfolio Investor has no information on the productivity parameter, and will instruct the manager to maximize the expected return. The chosen level of K then is: Expected return at t=0

  11. Liquidity Shocks and Resale of Investment • Before maturity, investors may need to sell the project due to liquidity shock; • Some direct investors may also pretend that they are facing liquidity shock (after they observe a bad realization of the fundamental); • Period-1 resale price is the asset’s expected value from the buyer's viewpoint.

  12. Resale Value of FDI Productivity level under which the direct owner is selling with no liquidity shock. Resale value from Bayes’ law (Lamda: the exogenous likelihood of liquidity shock) The owner sets the threshold so that she is indifferent between the price paid by buyer and the return if continuing to hold the asset.

  13. Resale Value of FPI • If a portfolio Investor sells the asset, everybody knows that it does so only because of the liquidity shock. Hence the resale value of FPI: Since

  14. Aggregate Liquidity Crises • Here we assume liquidity shocks to individual investors are triggered by aggregate liquidity crises. • During crises, some investors have deeper pockets than others, and thus are less exposed to the liquidity issues. Constrained direct investors need to sell, but they will get a low price, in that buyers do not know whether the sale is due to adverse info or liquidity constraint. • Hence, the attractiveness of FDI decreases, when the probability of a liquidity crisis becomes higher.

  15. The Role of Opacity • The effect of liquidity shocks on FPI/FDI is driven by lack of transparency about the fundamentals of the direct investment. • If the fundamentals of each direct investment were publicly known, then liquidity shocks would not be that costly for direct investors, as the investors would be able to sell the project at fair price without bearing the consequences of the lemons problem.

  16. Data • Stocks of FPI and FDI in market value, for source countries, from Lane and Milesi-Ferretti (2006). It has the data on foreign assets for 140 source countries for the past 30 years. We use the sample from 1985 to 2004, due to higher data availability and reliability. • The convention for distinguishing between portfolio and direct investment is whether the ownership of shares of companies is above or below the 10 percent threshold.

  17. Empirical Model • Panel Model • Control variables: GDP, GDP per capita, stock market capitalization, trade openness, lagged real exchange rate appreciation, and year dummies. • The probability of aggregate liquidity shock at next period is estimated from the Probit model.

  18. Liquidity Crisis • We define liquidity crisis as episodes of negative purchase of external asset, based on the IFS Balance of Payments dataset. • 13% of the sample from 1985 to 2004 experienced liquidity crisis. Developed economies, such as Denmark, Japan, New Zealand and Spain, also experienced crises.

  19. Probit Estimation • We include explanatory variables that are unlikely to affect the FDI and FPI composition directly, but will affect the probability of crisis. • They include: the US real interest rate, source country current account balance/GDP, source country political risk or Standard and Poor’s rating for source countries.

  20. Determinants of FPI and FDI • Higher probability of liquidity crises is associated with higher log(FPI stock/FDI stock). See Table 4.

  21. Determinants of FPI and FDI-Levels • As a robustness check, we find that higher probability of crisis is negatively associated with FDI stock, while positively associated with FPI stock (Table 5). • Hence, what we find is more than the pure capital flight effect. Some may argue that during crisis, it is relatively easier to fly money out of the country in the form of portfolio investment than in the form of direct investment. The capital flight argument would imply that FPI and FDI rise together during crisis, which, however, is inconsistent with Table 5.

  22. Proxies of Capital Market Opacity • Pricewaterhouse-Cooper opacity index (OPA) in year 2001. Including: corruption, efficacy of the legal system, deleterious economic policy, inadequate accounting practices, and detrimental regulatory structures. • Pricewaterhouse sub index on accounting (ACC). • Disclosure score from the 1995 Center for International Financial Analysis and Research Report (CIFAR), measured by the number of items disclosed in annual reports. • The financial disclosure index in the 1999 Global Competitiveness Report (GCR), measuring the perceptions of company CEOs about a country.

  23. Results on Opacity • Higher opacity increases the effect of the predicted liquidity crisis on the FPI/FDI composition. • Again, the findings support the existence of the liquidity consideration. The pure capital flight effect will not assign a role to the interaction of the source country corporate transparency and the probability of crisis. {Note that when transparency is included in the Probit estimation, it does not turn out to be significant there}.

  24. Robustness Check-Probit • In the Probit estimation, we substitute the ICRG political risk indexes with Standard and Poor’s short-term sovereign rating. The results are in Table 7. • The effects of transparency become more significant.

  25. Robustness Check-Actual Occurrence of Crisis • Evidently, this may create endogeneity issues in estimation. But it still serves as useful checks, particularly if there is some concern about the forecasting power of Probit models. • The dynamic panel estimation results are presented in Table 8, with four proxies of opacity (OPA, ACC, CIFAR, and GCR). Again, there we find that the occurrence of liquidity crises at t + 1 increases the ratio of FPI to FDI. Moreover, the impact becomes larger for source countries with opaque capital markets.

  26. Conclusion • Countries that have a high probability of aggregate liquidity crises will be the source of more FPI and less FDI. Moreover, the effect will be more pronounced when corporate transparency declines.

More Related