leblang2003: Currency attacks

Description

Data on speculative currency attacks and devaluation decisions for 90 countries from 1985 to 1998.

Usage

data(leblang2003)

Arguments

Details

The dataset is taken from Leblang (2003). The unit of observation is the country-month, and the variables are:

outcome: Whether the country faced no speculative attack, defended its currency against an attack, or devalued in response to an attack in the given month
preelec: Indicator for being in the three months prior to an election
postelec: Indicator for being in the three months following an election
rightgov: Indicator for a right-wing party being in power
unifgov: Indicator for unified government: in presidential systems, the same party controlling the presidency and the lower house of the legislature; in parliamentary systems, one party/coalition having a majority of seats
lreserves: Logged ratio of currency reserves to base money in the previous month
realinterest: Domestic real interest rate in the previous month
lexports: Logged ratio of exports to GDP in the previous month
capcont: Indicator for capital controls in the previous year
overval: Overvaluation of the real exchange rate
creditgrow: Domestic credit growth in the previous month
service: External debt service (as percentage of exports) paid in previous month
USinterest: U.S. domestic interest rates in the previous month
contagion: Number of other countries experiencing speculative attacks in the same month
prioratt: Number of prior speculative attacks experienced by the country
nation: Country name
month: Month of observation
year: Year of observation

All of the non-binary variables other than nation, month, and year are standardized to have mean 0 and unit variance.

We are grateful to David Leblang for allowing us to redistribute his data. The original replication file is available in Stata format at https://sites.google.com/site/davidaleblang/data-1 (as of 2015-02-22).

References

David Leblang. 2003. "To Defend or Devalue: The Political Economy of Exchange Rate Policy." International Studies Quarterly 47: 533--559.

Examples

Run this code

## Replicate analysis in Leblang (2003)
data("leblang2003")

## NOTE: Convergence tolerance is set to 1e-4 to reduce testing runtime on
## CRAN; do not reduce tolerance in real applications!
m1 <- egame12(outcome ~
              capcont + lreserves + overval + creditgrow + USinterest + service
              + contagion + prioratt - 1 |
              1 |
              1 |
              unifgov + lexports + preelec + postelec + rightgov + realinterest
              + capcont + lreserves,
              data = leblang2003,
              link = "probit",
              type = "private",
              reltol = 1e-4)

summary(m1)