In this paper we propose a bootstrap version of the
Wald test for cointegration in a single-equation
conditional error correction model. The multivariate
sieve bootstrap is used to deal with dependence in
the series. We show that the introduced bootstrap
test is asymptotically valid. We also analyze the
small sample properties of our test by simulation
and compare it with the asymptotic test and several
alternative bootstrap tests. The bootstrap test
offers significant improvements in terms of size
properties over the asymptotic test, while having
similar power properties. The sensitivity of the
bootstrap test to the allowance for deterministic
components is also investigated. Simulation results
show that the tests with sufficient deterministic
components included are insensitive to the true
value of the trends in the model and retain correct
size.