Chilean Funds Research Articles

Pension Funds in Mexico and Chile: A Risk-Reward Comparison

Mexico and Chile have Defined Contributions (DC) pension systems. In both cases affliates are offered several investment funds with, allegedly, different risk-return profiles. Analyzing actual return data for the April 2008-March 2018 period, and using a number of risk (and return) related metrics, we reach quite different conclusions in relation to such funds. In the case of Mexico, the funds delivered returns according to their intended risk profile, and they are consistently ranked correctly in terms of absolute risk, risk-adjusted returns, and cumulative returns. Chilean funds, on the other hand, exhibited erratic risk-return patterns, with the most conservative fund outperforming the riskiest fund in terms of cumulative returns. Overall our analysis is an indictment on the idea of using asset allocation limits to control portfolio risk (Chile), and supports the view that risk is much better controlled using an overall portfolio-level risk metric (Mexico). Since most pension funds still rely heavily on asset-class limits to manage risk, our results should serve as a serious warning against the danger of relying on this practice.

Looking in the Wrong Place: Why Chile Provides No Evidence for Social Security Privatization

The performance of Chile's system of state‐sponsored private pensions has been a major theme for advocates of privatizing U.S. Social Security. Chile's experience also has been criticized by defenders of the current U.S. system. This article explains why, though the critics deserve the upper hand, the whole discussion is misguided. The most basic issue in the policy debate is how adequately pensions could be financed through regulated individual investment in financial markets. Chilean experience offers little evidence on this question because, for the first fifteen years of the system, pensions and accumulations in the Chilean funds had little to do with the kinds of market forces that would be relevant to predicting experience anywhere.