  We revisit systematics in determining the local dark matter density (rho_dm)
from the vertical motion of stars in the Solar Neighbourhood. Using a
simulation of a Milky Way-like galaxy, we determine the data-quality required
to detect the dark matter density at its expected local value. We introduce a
new method for recovering rho_dm that uses moments of the Jeans equations,
combined with a Monte Carlo Markov Chain technique to marginalise over the
unknown parameters. Given sufficiently good data, we show that our method can
recover the correct local dark matter density even in the face of disc
inhomogeneities, non-isothermal tracers and a non-separable distribution
function. We illustrate the power of our technique by applying it to Hipparcos
data [Holmberg & Flynn 2000,2004]. We first make the assumption that the A and
F star tracer populations are isothermal. This recovers
rho_dm=0.003^{+0.009}_{-0.007}Msun/pc^3 (with 90 per cent confidence),
consistent with previous determinations. However, the vertical dispersion
profile of these tracers is poorly known. If we assume instead a non-isothermal
profile similar to the blue disc stars from SDSS DR-7 [Abazajian et al. 2009]
measured by Bond et al. (2009), we obtain a fit with a very similar chi^2
value, but with rho_dm=0.033^{+0.008}_{-0.009}Msun/pc^3 (with 90 per cent
confidence). This highlights that it is vital to measure the vertical
dispersion profile of the tracers to recover an unbiased estimate of the local
dark matter density.
