Volunteering and the Strategic Value of Ignorance



In the analysis of the war of attrition, if individual i knows his cost of provision,
we will denote by
iL (⅛) player i with low (high) cost of provision. Moreover, we will
have to allow individuals to randomize their concession time. Consequently, a mixed
strategy of an uninformed individual
i {1,2} will be a cumulative distribution
function
Fi. Moreover, qi (t) will be the probability that i concedes exactly at t,
and it will be employed to describe pure strategies. If
i acquires information, we
denote by
FiL (FiH ) the distribution function that corresponds to the mixed strategy
i chooses when his cost is low (high). Again, we will use qiL (t) and qiH (t) to describe
type-contingent pure strategies in case
i acquires information.

Mixed strategies that individuals choose in the different continuation games will
exhibit a common structure. For this purpose, we define a function
Φ as

( 1 (1 q0) e (,  0 t < t

Φ (t; c,f,q0) = <  1 (1 q0) (ɪ,  t t<T

(2)


[ 1,                  t T

Φ (t; c, t^, q0) describes a cumulative distribution function of concession times t with
positive mass in the interval
(0,t), no mass in (t, T), and possibly a mass point at
zero (of size
q0) and/or a mass point at T.

No individual knows his cost of provision. If neither of the individuals knows
his true provision cost, both choose their waiting time based on their expected cost
c, and the volunteering game is strategically equivalent to the war of attrition with
complete information.9

Consider individual i and suppose that j waits until T with probability one. If
i concedes in ti < T, his expected payoff is V c ti. For ti = T, he gets a payoff
of
V c/2 T. Thus, if T < c/2, ti = T is strictly preferred to any ti < T,
and there is an equilibrium where both wait until
T with probability one, which
is the unique equilibrium. If, however,
T > c/2, i’s best response to t7∙ = T is to

9This holds because individuals are assumed to be risk-neutral and the payoffs are linear in the
provision cost. Thus maximizing expected payoffs is equivalent to the maximization based on the
expected cost.



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