MARKET STRUCTURE AND ENTRY: WHERE'S THE BEEF? - CEPR

tabulations provide the information that not all the districts in our sample appear to be
viable markets. If some of our markets were truly ‘impossible’, including them in the
data would bias our results. 14 Using the McD population threshold as a filter would lead
us to exclude 137 district observations, whereas using BK’s threshold would exclude 262
(less than or at most 10% of all observations, but roughly a quarter of new market (0,0)
structure observations). We therefore explored the effects of excluding some markets
from the sample on grounds of small size.
4. A REDUCED FORM APPROACH
4.1. The Model
In this Section, we first present reduced form results, and then discuss different
robustness tests based upon them. We estimate the following reduced form entry function
(as suggested by Reiss, 1996; Berry, 1992):
(5) Π ijt = X' ijt β i + g(
n jt,
m jt , θ i)
+ υ ijt
Subscript i denotes firm ( i ∈ { M , B}
, where M stands for McD and B for BK), j market,
and t the time period; the vector Xijt includes market and (possibly) firm specific
variables; g(.) is a function of existing own (njt) and rival (mjt) outlets in market j (see
also Mazzeo, 1999); and β i and θi are vectors of firm specific parameters to be estimated.
We explore different ways of measuring market structure, two of which are: i) a count
variable for the number of outlets of firm i, i = M, B; and ii) a vector that consists of
indicator variables that take the value unity if the observed market structure is (njt, mjt).
In addition to the usual problems with reduced form, an additional problem is that (5)
does not allow a rich way to control for multi-outlet firms’ opportunity costs of not
entering. In particular, it seems reasonable to assume that the profits from not having any
15