  We describe the construction of a template set of spectral energy
distributions (SEDs) for the estimation of photometric redshifts of luminous
red galaxies (LRGs) with a Bayesian template fitting method. By examining the
color properties of several publicly available SED sets within a redshift range
of 0<z<0.5 and comparing them to SDSS DR7 data, we show that only some of the
investigated SEDs approximately match the colors of the LRG data throughout the
redshift range, however not at the quantitative level required for precise
photometric redshifts. We generate new SEDs by superposing model SEDs of
composite stellar populations with a burst model, allowing both components to
be reddened by dust, in order to match the data in five different redshift
bins. We select a set of SEDs which represents the LRG data in color space
within five redshift bins, thus defining our new SED template set for
photometric redshift estimates. The results we get with the new template set
and our Bayesian template fitting photometric redshift code (PhotoZ) are nearly
unbiased, with a scatter of \sigma(\Delta z)=0.027 (including outliers), and a
fraction of catastrophic outliers (|z_phot-z_spec|/(1+z_spec)>0.15) of 0.12%.
We show that templates that optimally describe the brightest galaxies
(-24.5<M_R<-22.7) indeed vary from z=0.1 to z=0.5, consistent with aging of the
stellar population. Furthermore, we find that templates that optimally describe
galaxies at z<0.1 strongly differ as a function of the absolute magnitude of
the galaxies, indicating an increase in star formation activity for less
luminous galaxies. Our findings based on the photometry of the SDSS LRGs and
our SED template fitting are supported by comparison to the average SDSS LRG
spectra in different luminosity and redshift bins.
