By Ran Abramitzky - Stanford University - 2005
ABSTRACT
The Israeli Kibbutzes, which are voluntary communities based on income equality, are puzzling since they might unravel due to moral hazard and adverse selection. Yet Kibbutzes persisted for
most of the 20th century. How did voluntary communities based on income equality persist within a capitalist environment? What level of equality can they sustain? This paper employs unique data sets at both the Kibbutz-level and the individual-level to analyze Kibbutzes’ choices of their level of income equality, their organizational form and their members’ decisions of whether to leave the Kibbutz. A wealth shock that hit Kibbutzes differentially provides the “natural experiment” that allows me to identify the determinants of the level of equality and the exit rates in each Kibbutz. The main findings are that the most productive members are more likely to leave, that common wealth is a lock-in device that makes exit costly, and that wealthier Kibbutzes are more likely to choose a higher level of income equality. All the patterns in the data are consistent with a simple model of optimal insurance under limited commitment of members to stay in their Kibbutz once their type is realized. This stands in contrast to the view of Kibbutzes as primarily ideological entities. At a broader level, the study of Kibbutzes reveals how potential moral hazard and negative selection determine contractual relationships in organizations such as partnerships and cooperatives.
Paper here
Wednesday, October 11, 2006
Why Personal Ties Cannot Be Bought?
By Casella & Hanaki (2006)
American Economic Review, Papers and Proceedings May 2006, p.p. 261-264
The unambiguous message of our model is that networking transmits information effectively only if its cost is low. When networking is free, it is preferred to signaling by both firms and workers almost without exception. But it is never a very precise mechanism, and if its cost is higher, firms’ hiring decisions interact with workers’ selfselection preventing endogenous improvements in precision. At high cost, signaling transmits information more accurately and supplants networking completely. We are somewhat surprised to conclude in qualified support of the sociologists’ position: networks work best when they are unintentional, and thus free by-products of people’s social life: ethnic, religious, family networks. In this case, they are extremely difficult to substitute with a market mechanism. Nor is it easy to mimic these spontaneous network through the intentional, and thus costly, creation of personal ties, because such action distorts, as opposed to favoring, the transmission of information. If ties are costly, market mechanisms are superior.
Paper here
American Economic Review, Papers and Proceedings May 2006, p.p. 261-264
The unambiguous message of our model is that networking transmits information effectively only if its cost is low. When networking is free, it is preferred to signaling by both firms and workers almost without exception. But it is never a very precise mechanism, and if its cost is higher, firms’ hiring decisions interact with workers’ selfselection preventing endogenous improvements in precision. At high cost, signaling transmits information more accurately and supplants networking completely. We are somewhat surprised to conclude in qualified support of the sociologists’ position: networks work best when they are unintentional, and thus free by-products of people’s social life: ethnic, religious, family networks. In this case, they are extremely difficult to substitute with a market mechanism. Nor is it easy to mimic these spontaneous network through the intentional, and thus costly, creation of personal ties, because such action distorts, as opposed to favoring, the transmission of information. If ties are costly, market mechanisms are superior.
Paper here
Tuesday, October 03, 2006
Winners don't take all: Characterizing the competition for links on the web
By Pennock, Flake, Lawrence, Glover, and Giles (2002)
ABSTRACT
As a whole, the World Wide Web displays a striking ‘‘rich get richer’’ behavior, with a relatively small number of sites receiving a disproportionately large share of hyperlink references and traffic. However, hidden in this skewed global distribution, we discover a qualitatively different and considerably less biased link distribution among subcategories of pages—for example, among all university homepages or all newspaper homepages. Although the connectivity distribution over the entire web is close to a pure power law, we find that the distribution within specific categories is typically unimodal on a log scale, with the location of the mode, and thus the extent of the rich get richer phenomenon, varying across different categories. Similar distributions occur in many other naturally occurring networks, including research paper citations, movie actor collaborations, and United States power grid connections. A simple generative model, incorporating a mixture of preferential and uniform attachment, quantifies the degree to which the rich nodes grow richer, and how new (and poorly connected) nodes can compete. The model accurately accounts for the true connectivity distributions of category-specific web pages, the web as a whole, and other social networks.
Paper here
ABSTRACT
As a whole, the World Wide Web displays a striking ‘‘rich get richer’’ behavior, with a relatively small number of sites receiving a disproportionately large share of hyperlink references and traffic. However, hidden in this skewed global distribution, we discover a qualitatively different and considerably less biased link distribution among subcategories of pages—for example, among all university homepages or all newspaper homepages. Although the connectivity distribution over the entire web is close to a pure power law, we find that the distribution within specific categories is typically unimodal on a log scale, with the location of the mode, and thus the extent of the rich get richer phenomenon, varying across different categories. Similar distributions occur in many other naturally occurring networks, including research paper citations, movie actor collaborations, and United States power grid connections. A simple generative model, incorporating a mixture of preferential and uniform attachment, quantifies the degree to which the rich nodes grow richer, and how new (and poorly connected) nodes can compete. The model accurately accounts for the true connectivity distributions of category-specific web pages, the web as a whole, and other social networks.
Paper here
A classic: The diameter of the world wide web
by Albert, Jeong and Barabasi (1999)
"... we find that the average of d over all pairs of vertices follows hdi = 0.35+2.06 log(N), indicating that the web forms a small-world network"
Full article here
"... we find that the average of d over all pairs of vertices follows hdi = 0.35+2.06 log(N), indicating that the web forms a small-world network"
Full article here
Sunday, October 01, 2006
Power Laws, Weblogs, and Inequality
By Clay Shirky
"Diversity plus freedom of choice creates inequality, and the greater the diversity, the more extreme the inequality..."
Complete article here
"Diversity plus freedom of choice creates inequality, and the greater the diversity, the more extreme the inequality..."
Complete article here
Celebrity in social networks: how can we avoid the power law distribution?
By Ben Werdmuller
"In any information ecosystem, there is an observable tendency for a few sources on a topic - be they journals, websites or people - to have a massive following, a significantly smaller number to have a medium number of followers, and then a final, largest group to have a much smaller number of regular readers. This can be witnessed in the Technorati Top 100: the top 100 blogs range from around 80,900 unique links to 4,900 (quite a decrease), yet Technorati track 26.6 million sites. If the downward link trend continues across all 26.6 million, most weblogs have at most one a handful of links - and therefore a correspondingly small number of readers. I've been wondering for a while how best to verbalise this..."
complete article here
"In any information ecosystem, there is an observable tendency for a few sources on a topic - be they journals, websites or people - to have a massive following, a significantly smaller number to have a medium number of followers, and then a final, largest group to have a much smaller number of regular readers. This can be witnessed in the Technorati Top 100: the top 100 blogs range from around 80,900 unique links to 4,900 (quite a decrease), yet Technorati track 26.6 million sites. If the downward link trend continues across all 26.6 million, most weblogs have at most one a handful of links - and therefore a correspondingly small number of readers. I've been wondering for a while how best to verbalise this...
complete article here
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