  We provide a sufficient condition for an invertible (locally strongly) convex
vector-valued function on $\mathbb{R}^N$ to have a (locally strongly) convex
inverse. We show under suitable conditions that if the gradient of each
component of the inverse has negative entries, then this inverse is (locally
strongly) convex if the original is.
