Friday, October 31, 2008

Restructuring Schools in Armenian Neighborhoods: Does Social Capital Matter?

Public schools in Yerevan face serious problems of restructuring. Most of the schools have not been renovated since the collapse of the Soviet Union. Does economic well-being affect the level of social capital in the neighborhood? Are the neighborhoods with higher social capital more likely to be willing to participate in school renovations? The answer depends not only on public cooperation, but also on socio-economic well-being. Armine Asryan together with her partner Anush Davtian investigated social capital in four neighborhoods of Yerevan.

According to the researchers, income positively determines the level of social capital -- the higher the income, the higher the social capital; and there is a further relationship between social capital and school renovation -- the higher the social capital, the more likely it is that the community will take part in school renovation. Armine characterized the communities as having low bridging and high bonding capital, which indicate low civic participation apathy and extreme individualism among those four communities.

The researchers developed policy recommendations such as enhancing the transparency of school boards. The data show that most of the respondents who expressed their willingness to support school restructuring affirm that they donate money through school boards. Therefore, clear and continuous reports on the management of the funds will enhance parents' participation in school renovation projects.

The paper is posted on the CRRC-Armenia website. Please let us know what you think.

1 comment:

Anonymous said...

Social capital matters.

Maybe the current socio-economic status doesn't matter as much as hope.

Here a quote from my ebook:

As one reviews Matthew Jackson’s 2005 paper “The Economics of Social Networks,” the thought occurs that there is an urgent need to lock Chris Anderson and Matt Jackson in a room together. Here is a quote from Jackson:
“Another application of obvious importance in understanding how network structure impacts behavior, is to understand how
information propagates through a network, and in particular how people in a social network learn from each other. Taking
a Bayesian perspective is a standard approach in economic modeling, and an obvious starting point. The model of Bala-
Goyal (1998) builds from this perspective (see also Allen (1982) and Ellison and Fudenberg (1993, 1995)).
Bala and Goyal (1998) make a very simple but important point. Consider a series of agents connected in a social network
who all face the same stationary, but random, environment. The network is fixed and time progresses in discrete dates
where agents each choose one of a finite set of actions at each date. The payoffs to the actions are random and their distribution
depends on an unknown state of nature. The agents are all faced with the same set of possible actions and the same
unknown state of nature. They all have identical tastes and face the same uncertainty about the actions. Over time, each agent
observes his or her neighbors choices and outcomes.
The main conclusion is that eventually the agents will converge to choosing the same action, based on the observation that over
time players who observe each others actions and payoffs should eventually come to choose the same action. The intuition
is as follows. We need only reason that any two neighbors earn the same long run utility, as this implies the same must
be true network-wide. If one neighbor is doing better than another, then the neighbor with the poorer payoff will learn from
observing the other agent, and eventually change behavior to obtain a similar payoff. Note that the fact that all agents end
up with the same long run utility does not mean that all agents converge to choosing the right action. However, Bala and
Goyal show that if the network is large enough, and there are enough agents who are optimistic about each possible action
spread throughout the network, then the probability that the society will converge to the best overall action can be made arbitrarily
close to 1. The idea is that there will be sufficiently many experiments by the optimistic agents so that the true payoff
of each action will be learned and then the society will converge to the right action.”
That is how a network economist explains hope. I think.

I hope that you will drop by and add something.