Appendix I: Data Sources and Definitions
Appendix II: Turbulent Episode Dates
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Western Hemisphere Department, International Monetary Fund, and Moore School of Business, University of South Carolina. The authors wish to thank Benedict Clements, Jeronim Zettelmeyer, Roberto Garcias-Saltos, seminar participants at the International Monetary Fund’s Western Hemisphere Department seminar series and Janice Boucher Breuer for helpful comments and suggestions
The Latin American countries considered in this paper are Argentina, Brazil, Chile, Colombia, Mexico, Peru, and Venezuela. These represent approximately 90 percent of the Latin American and Caribbean region’s GDP.
Masson (1998) employs the term “spillovers” for effects that arise from macroeconomic interdependence among developing countries, but following Gelos and Sahay (2001), this paper uses the term in a broader sense where a “spillover” is any type of impact on other countries financial markets.
There are many other studies on both short-run and long-run linkages between the U.S. and Latin American equity markets. These include Claessens and others (2001); Chen and others (2002); and Garrett and others (2004)).
The measure being used here is the “new” VIX. Details on the computation of VIX are provided in http://www.cboe.com/micro/vix/vixwhite.pdf.
The standard deviations are based on 20-day rolling averages of VIX data. We chose 20 days as typically there are 20 trading days in a month
See data Appendix II for dates.
We carried out our analysis with just the 11 episodes and found our results did not differ much from those obtained using the 13 episodes. Thus, we report results based on the 13 episodes only.
As standard in the literature, daily returns are based on U.S dollars, which emphasizes the perspective of foreign investors.
Since exchange rates are based on the euro, our data is restricted and starts from 1999 onwards.
The number of lags for the endogenous variables was generally found higher in tranquil period. Lags higher than one for the exogenous variables were generally not significant.
Although interest rates are an imperfect measure of aggregate shocks, they are a good proxy for global shifts in real economic variables and/or policies that affect asset market performance. Forbes and Rigobon (2002) follow a similar approach.
The failure to find more pronounced statistically significant differences is driven by the large standard errors found for the models estimated on turbulent times.