Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Social Learning with Endogenous Network Formation   I study the problem of social learning in a model where agents move
sequentially. Each agent receives a private signal about the underlying state
of the world, observes the past actions in a neighborhood of individuals, and
chooses her action attempting to match the true state. Earlier research in this
field emphasizes that herding behavior occurs with a positive probability in
certain special cases; recent studies show that asymptotic learning is
achievable under a more general observation structure. In particular, with
unbounded private beliefs, asymptotic learning occurs if and only if agents
observe a close predecessor, i.e., the action of a close predecessor reveals
the true state in the limit. However, a prevailing assumption in these studies
is that the observation structure in the society is exogenous. In contrast to
most of the previous literature, I assume in this paper that observation is
endogenous and costly. More specifically, each agent must pay a specific cost
to make any observation and can strategically choose the set of actions to
observe privately. I introduce the notion of maximal learning (relative to
cost) as a natural extension of asymptotic learning: society achieves maximal
learning when agents can learn the true state with probability 1 in the limit
after paying the cost of observation. I show that observing only a close
predecessor is no longer sufficient for learning the true state with unbounded
private beliefs and positive costs. Instead, maximal learning occurs if and
only if the size of the observations extends to infinity. I provide interesting
comparative statics as to how various settings in the model affect the learning
probability. For instance, the probability to learn the true state may be
higher under positive costs than under zero cost; in addition, the probability
to learn the true state may be higher under weaker private signals.

25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg