  We use a suite of simulated images based on Year 1 of the Dark Energy Survey
to explore the impact of galaxy neighbours on shape measurement and shear
cosmology. The hoopoe image simulations include realistic blending, galaxy
positions, and spatial variations in depth and PSF properties. Using the
im3shape maximum-likelihood shape measurement code, we identify four mechanisms
by which neighbours can have a non-negligible influence on shear estimation.
These effects, if ignored, would contribute a net multiplicative bias of $m
\sim 0.03 - 0.09$ in the DES Y1 im3shape catalogue, though the precise impact
will be dependent on both the measurement code and the selection cuts applied.
This can be reduced to percentage level or less by removing objects with close
neighbours, at a cost to the effective number density of galaxies
$n_\mathrm{eff}$ of 30%. We use the cosmological inference pipeline of DES Y1
to explore the cosmological implications of neighbour bias and show that
omitting blending from the calibration simulation for DES Y1 would bias the
inferred clustering amplitude $S_8\equiv \sigma_8 (\Omega _\mathrm{m}
/0.3)^{0.5}$ by $2 \sigma$ towards low values. Finally, we use the hoopoe
simulations to test the effect of neighbour-induced spatial correlations in the
multiplicative bias. We find the impact on the recovered $S_8$ of ignoring such
correlations to be subdominant to statistical error at the current level of
precision.
