WikiPrices

Erik Hersman, has recently created a site called Africa Signals. And it is not just a site: it is a wiki site. The site aims to collect and share mobile phone and Internet rates across Africa. (I have found about this site here)

Now. In my experience, one of the many reasons that makes poor a poor farmer is coping with a non-functioning market (I said it two posts ago). So I can just imagine how helpful would be to have a tool to make market work better.

Creating a wiki page to collect and share the price of one particular agricultural product in one particular time in one particular place would be great. But succeeding in integrating such a site with the mobile phone network would be even better.  How to do this? The government of Rwanda is moving in the very same direction without creating a wiki site. (It is difficult to imagine a government managing wikis). But bureaucracy is not something we usually associate with the words efficiency and effectiveness, especially in poor countries. And in any case we do not really need a government to make a site like this work.

Just think about a wiki site collecting and sharing data through sms. Actually Twitter, without the wiki interface, is doing it right now. So, think about a farmer receiving a message with updated price information the night before market day and, on this information, taking his/her decisions. And think about a farmer sending via sms the price information to the wiki site after leaving the market.

We can imagine the farmer to pay for the sms he or she receives and, on the contrary, we can imagine sending sms back to the site to be completely free.  And we can imagine some volunteers to be the administrators of the site (just like Wikipedia).

Tuesday, 28 April 2009

Hard Numbers, Hard Times

In a report published today, Oxfam predicts that by 2015 the average number of people affected by climate-related disasters every year will increase by 54%. The projection is based on a forecasting model that uses data, collected by the Centre for Research on the Epidemiology of Disasters, going back to 1900. Oxfam’s researchers have noticed that climate-related disasters have been increasing in frequency and severity during the last years so they expect that by 2015 375 million people (or 132 million more than in 2007) will be affected. Jeremy Hobbs, Oxfam International’s Executive Director, said that

The humanitarian system works as if it’s a global card game dealing out aid randomly, not based on people’s needs. The response is often fickle – too little, too late and not good enough. The world barely copes with the current level of disasters. A big increase in the numbers of people affected will overwhelm it unless there is fundamental reform of the system that puts those in need at its centre.

And this supposedly happens while NGOs are downsizing their budgets because of the crisis. According to Le Monde, many organizations have seen a significant decrease in private donation during 2009. More deadly predictions on the way?

Tuesday, 21 April 2009

Information Flows on Mobiles

The idea to use mobile phones (here and here) to help economic development in the most remote corners of the world is fascinating and definitely smart. For one thing, mobile phones have already reached the Bottom Billion. In 2007 there were 45 subscribers per 100 inhabitants in the developing countries. That means that we can now expect to have one mobile in every family. Everywhere. As well in communities where services like water, electricity, hospitals, schools or transportation are still far away.

What poor people mostly need are functioning institutions. And market is one of these. If market is not working, farmers will pay higher prices for what they buy and got less money for what they sell.  Moreover they could buy or sell at the wrong time and possibly in the wrong place. In the words of the government of Rwanda,

the success of these farmers has been greatly affected by lack of access to pricing information. Many times, farmers speculate what crops to grow and what prices to charge at harvest. Some farmers depend on middlemen to dictate the prices and in most cases the latter exploit the former. For any farmer to earn a decent living from agriculture, easy access to information on market prices is of paramount importance.

Making information flows on mobile phones could

empower farmers to enable them make more informed market pricing decisions and ultimately more successful farming.

The idea of mobile banking goes in the same direction: making a  service so critical for development accessible to almost everyone. That will not end poverty, but  will probably make the task easier.

Thursday, 16 April 2009

tweets


Twitter: frbailo

links


blogroll


RSS r-bloggers.com

  • Angela Bassa discusses managing data science teams and much more.
    Hugo Bowne-Anderson, the host of DataFramed, the DataCamp podcast, recently interviewed Angela Bassa, the Director of Data Science at iRobot. Here is the podcast link. Introducing Angela Bassa Hugo: Hi there Angela, and welcome to DataFramed. Angela: Thanks, thanks for having me. Hugo: It's a great pleasure to have you on the show, and I'm […]
  • Preview my new book: Introduction to Reproducible Science in R
    I’m pleased to share Part I of my new book “Introduction to Reproducible Science in R“. The purpose of this …Continue reading →
  • How to de-Bias Standard Deviation Estimates
    This note is about attempting to remove the bias brought in by using sample standard deviation estimates to estimate an unknown true standard deviation of a population. We establish there is a bias, concentrate on why it is not important to remove it for reasonable sized samples, and (despite that) give a very complete bias […]
  • Data Science With R Course Series – Week 9
    There are only two more weeks in the course! This week will extend what you learned from the Expected Value by performing an optimization and sensitivity analysis. The optimization and sensitivity analysis will teach you how to identify the maximum bu...
  • RATest. A Randomization Tests package is available on CRAN
    This blog post introduces the RATest package we released a while back on CRAN with my colleague and good friend Mauricio Olivares-Gonzalez. The package contains a collection of randomization tests, data sets and examples. The current version focuses on two testing problems and their implementation in empirical work, mostly related to economics. First, it facilitates […]

RSS Simply Statistics

  • The role of academia in data science education
    I was recently asked to moderate an academic panel on the role of universities in training the data science workforce. I preceded each question with opinionated introductions which I have fused into this blog post. These are weakly held opinions so please consider commenting if you disagree with anything. To discuss data science education we […]
  • Guest Post: Galin Jones on criteria for promotion and tenture in (bio)statistics departments
    Editor’s Note: I attended an ASA Chair’s meeting and spoke about ways we could support junior faculty in data science. After giving my talk Galin Jones, Professor and Director of Statistics at University of Minnesota, and I had an interesting conversation about how they had changed their promotion criteria in response to a faculty candidate […]
  • The economic consequences of MOOCs
    tl;dr check out our new paper on the relationship between MOOC completion and economic outcomes! Last Monday we launched our Chromebook Data Science Program so that anyone with an internet connection, a web browser, and the ability to read and follow instructions could become a data scientist. Why did we launch another MOOC program? Aren’t […]

RSS Statistical Modeling, Causal Inference, and Social Science