We consider $N\times N$ Hermitian random matrices with i.i.d. entries. The matrix
is normalized so that the average spacing between consecutive eigenvalues is of order
$1/N$. We study the connection between eigenvalue statistics on microscopic energy scales
$\eta\ll1$ and (de)localization properties of the eigenvectors. Under suitable assumptions
on the distribution of the single matrix elements, we first give an upper bound on the
density of states on short energy scales of order $\eta \sim\log N/N$. We then prove that
the density of states concentrates around the Wigner semicircle law on energy scales
$\eta\gg N^{-2/3}$. We show that most eigenvectors are fully delocalized in the sense that
their $\ell^p$-norms are comparable with $N^{{1}/{p}-{1}/{2}}$ for $p\ge2$, and we obtain
the weaker bound $N^{{2}/{3}({1}/{p}-{1}/{2})}$ for all eigenvectors whose eigenvalues are
separated away from the spectral edges. We also prove that, with a probability very close
to one, no eigenvector can be localized. Finally, we give an optimal bound on the second
moment of the Green function.