  Photometric redshift uncertainties are a major source of systematic error for
ongoing and future photometric surveys. We study different sources of redshift
error caused by choosing a suboptimal redshift histogram bin width and propose
methods to resolve them. The selection of a too large bin width is shown to
oversmooth small scale structure of the radial distribution of galaxies. This
systematic error can significantly shift cosmological parameter constraints by
up to $6 \, \sigma$ for the dark energy equation of state parameter $w$.
Careful selection of bin width can reduce this systematic by a factor of up to
6 as compared with commonly used current binning approaches. We further discuss
a generalised resampling method that can correct systematic and statistical
errors in cosmological parameter constraints caused by uncertainties in the
redshift distribution. This can be achieved without any prior assumptions about
the shape of the distribution or the form of the redshift error. Our
methodology allows photometric surveys to obtain unbiased cosmological
parameter constraints using a minimum number of spectroscopic calibration data.
For a DES-like galaxy clustering forecast we obtain unbiased results with
respect to errors caused by suboptimal histogram bin width selection, using
only 5k representative spectroscopic calibration objects per tomographic
redshift bin.
