  The paper proposes a new bootstrap approach to the Pesaran, Shin and Smith's
bound tests in a conditional equilibrium correction model with the aim to
overcome some typical drawbacks of the latter, such as inconclusive inference
and distortion in size. The bootstrap tests are worked out under several data
generating processes, including degenerate cases. Monte Carlo simulations
confirm the better performance of the bootstrap tests with respect to bound
ones and to the asymptotic F test on the independent variables of the ARDL
model. It is also proved that any inference carried out in misspecified models,
such as unconditional ARDLs, may be misleading. Empirical applications
highlight the importance of employing the appropriate specification and provide
definitive answers to the inconclusive inference of the bound tests when
exploring the long-term equilibrium relationship between economic variables.
