The duration of fixed exchange rate regimes

such as international reserves, foreign assets, domestic credit, foreign direct investment;
and institutional and political variables, such as regular and irregular executive transfers,
IMF program, corruption, political freedom. Moreover, two studies using logit regressions
include the duration of the exchange rate peg as a determinant of the likelihood of an exit.
Some explanatory variables are significant across most studies: inflation, competitiveness
as measured by the evolution of the real exchange rate, and openness.

The vast majority of existing research ignores the issue of censoring systematically,
except for those papers using duration models. Suppose that we are focusing on exits
between time t1 and time t2 . We will observe some exits between t1 and t2 without being
able to compute the duration when the regime has started before time t1 . Conversely,
some regimes will still be in place after time t₂ , so that we do not observe an exit and
are again not able to compute a duration. The literature on duration models recognizes
this issue as being very important and proposes ways to take censoring into account. To
our knowledge, the studies which include duration as an explanatory variable in a logit
framework disregard the problem. Duttagupta and Otker-Robe (2003) exclude incomplete
spells explicitly. For example, Hong Kong is excluded from the analysis since its currency
board regime is still in place as we write: there is no exit.

3 Econometric methodology

We define the nonnegative random variable T as the duration (or spell) during which a
fixed exchange rate regime is in place¹ . The unconditional probability that the spell will be
shorter than some given value t is given by the cumulative distribution function, written
as F (t) = Pr(T < t). The associated probability density function is written as f (t).
Duration analysis makes use of the reverse cumulative distribution function, referred to as
the survivor function, which is written as S(t) = 1 - F (t).

We will estimate the hazard function which captures the conditional probability that
the spell will terminate at time T = t, given that it has survived until time t. It is given
¹This presentation relies on Kiefer (1988).

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