Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userAnalysis of the Bitcoin blockchain: Socio-economic factors behind the adoption
119
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
As the first decentralized digital currency introduced in 2009 together with the blockchain, Bitcoin offers new opportunities both for developed and developing countries. Bitcoin peer-to-peer transactions are independent of the banking system, thus facilitating foreign exchanges with low transaction fees such as remittances, with a high degree of anonymity. These opportunities together with other key factors led the Bitcoin to become extremely popular and made its price skyrocket during 2017. However, while the Bitcoin blockchain attracts a lot of attention, it remains difficult to investigate where this attention comes from, due to the pseudo-anonymity of the system, and consequently to appreciate its social impact. Here we make an attempt to characterize the adoption of the bitcoin blockchain by country. In the first part of the work we show that information about the number of Bitcoin software client downloads, the IP addresses that act as relays for the transactions, and the Internet searches about Bitcoin provide together a coherent picture of the system evolution in different countries. Using these quantities as a proxy for user adoption, we identified several socio-economic indexes such as the GDP per capita, freedom of trade and the Internet penetration as key variables correlated with the degree of user adoption. In the second part of the work, we build a network of Bitcoin transactions between countries using the IP addresses of nodes relaying transactions and we develop an augmented version of the gravity model of trade in order to identify socio-economic factors linked to the flow of bitcoins between countries. In a nutshell our study provides a new insight on the bitcoin adoption by country and on the potential socio-economic drivers of the international bitcoin flow.
rate research
Read More
Bitcoin is a peer-to-peer electronic payment system that popularized rapidly in recent years. Usually, we need to query the complete history of Bitcoin blockchain data to acquire variables with economic meaning. This becomes increasingly difficult now with over 1.6 billion historical transactions on the Bitcoin blockchain. It is thus important to query Bitcoin transaction data in a way that is more efficient and provides economic insights. We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in social science. Specifically, we query and process the Bitcoin transaction input and output data within each daily cohort, which enables us to create datasets and visualizations for some key indicators of Bitcoin transactions, including the daily lifespan distributions of spent transaction output (STXO) and the daily age distributions of the accumulated unspent transaction output (UTXO). We provide a computationally feasible approach to characterize Bitcoin transactions, which paves the way for the future economic studies of Bitcoin.
The world is changing at an ever-increasing pace. And it has changed in a much more fundamental way than one would think, primarily because it has become more connected and interdependent than in our entire history. Every new product, every new invention can be combined with those that existed before, thereby creating an explosion of complexity: structural complexity, dynamic complexity, functional complexity, and algorithmic complexity. How to respond to this challenge? And what are the costs?
In this essay, I attempt to provide supporting evidence as well as some balance for the thesis on `Transforming socio-economics with a new epistemology presented by Hollingworth and Mueller (2008). First, I review a personal highlight of my own scientific path that illustrates the power of interdisciplinarity as well as unity of the mathematical description of natural and social processes. I also argue against the claim that complex systems are in general `not susceptible to mathematical analysis, but must be understood by letting them evolve over time or with simulation analysis. Moreover, I present evidence of the limits of the claim that scientists working within Science II do not make predictions about the future because it is too complex. I stress the potentials for a third `Quantum Science and its associated conceptual and philosophical revolutions, and finally point out some limits of the `new theory of networks.
Socio-economic inequality is measured using various indices. The Gini ($g$) index, giving the overall inequality is the most commonly used, while the recently introduced Kolkata ($k$) index gives a measure of $1-k$ fraction of population who possess top $k$ fraction of wealth in the society. This article reviews the character of such inequalities, as seen from a variety of data sources, the apparent relationship between the two indices, and what toy models tell us. These socio-economic inequalities are also investigated in the context of man-made social conflicts or wars, as well as in natural disasters. Finally, we forward a proposal for an international institution with sufficient fund for visitors, where natural and social scientists from various institutions of the world can come to discuss, debate and formulate further developments.
We propose a general scenario to analyze social and economic changes in modern environments. We illustrate the ideas with a model that incorporating the main trends is simple enough to extract analytical results and, at the same time, sufficiently complex to display a rich dynamic behavior. Our study shows that there exists a macroscopic observable that is maximized in a regime where the system is critical, in the sense that the distribution of events follow power-laws. Computer simulations show that, in addition, the system always self-organizes to achieve the optimal performance in the stationary state.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
