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

Brain matters

Saying that education strengths economic growth sounds good old common sense. But proving and measuring this relation is not immediate and therefore interesting. A reasearch, published last year, does it. Eric Hanushek, Dean T. Jamison, Eliot A. Jamison and Ludger Woessmann estimate that

each additional year of average schooling in a country increased the average 40-year growth rate in GDP by about 0.37 percentage points. That may not seem like much, but consider the fact that since World War II, the world economic growth rate has been around 2 to 3 percent of GDP annually. Lifting it by 0.37 percentage points is a boost to annual growth rates of more than 10 percent of what would otherwise have occurred, a significant amount.

Nonetheless, the research suggests that what really matters for economic growth is the quality of education. In other words it is not enough to send children to school: you have to teach them something. Using test-score performances around the world to measure the cognitive skills of students appears

that countries with higher test scores experienced far higher growth rates. If one country’s test-score performance was 0.5 standard deviations higher than another country during the 1960s (…) the first country’s growth rate was, on average, one full percentage point higher annually over the following 40-year period than the second country’s growth rate. Further, once the impact of higher levels of cognitive skills are taken into account, the significance for economic growth of school attainment, i.e., additional years of schooling, dwindles to nothing. A country benefits from asking its students to remain in school for a longer period of time only if the students are learning something as a consequence.

These results are extremely important especially for the countries of the Bottom Billion. What they are saying is that it is better to invest on the quality of the education (where rate of return is much higher) rather than spending to keep students in schools longer.

Tuesday, 17 March 2009

tweets


Twitter: frbailo

links


blogroll


RSS r-bloggers.com

  • R Package for @racently
    I recently wrote about an API for @racently. The next logical step was to build a package which wraps the API so that the data can easily be pulled into R. The package is available here. It is still very much a work in progress: the API only exposes two endpoints, but both of them […]
  • celebRation 2020
    The year 2020 marks the 20th anniversary of the release of R version 1.0.0! To celebrate this, we are inviting the community of R users and developers for a two-day celebRation workshop/mini-conference on February 28-29th 2020 in Copenhagen. We kick off on 28th February with hands-on workshops on two hot topics, namely data visualization using […]
  • Practical Data Science with R 2nd Edition now in-stock at Amazon.com!
    Practical Data Science with R 2nd Edition is now in-stock at Amazon.com! Buy it for your favorite data scientist in time for the holidays!
  • lintools 0.1.3 is on CRAN
    Version 0.1.3 of the lintools package was accepted on CRAN today. This version brings a few internal improvements and switches the testing suite to the tinytest test infrastructure. lintools is provides basic manipulations of linear systems of equalities and inequalities … Continue reading →
  • Sponsorship: SatRdays and useR Groups
    SatRdays SatRdays are great. Low cost R events, held around the world. What's not to love! For the last year, we have been offering automatic sponsorship for all SatRday events. All the organisers have to do is complete a quick questionnaire and the money is sent on it's way. So far we have sponsored seven […]

RSS Simply Statistics

  • Is Artificial Intelligence Revolutionizing Environmental Health?
    NOTE: This post was written by Kevin Elliott, Michigan State University; Nicole Kleinstreuer, National Institutes of Health; Patrick McMullen, ScitoVation; Gary Miller, Columbia University; Bhramar Mukherjee, University of Michigan; Roger D. Peng, Johns Hopkins University; Melissa Perry, The George Washington University; Reza Rasoulpour, Corteva Agriscience, and Elizabeth Boyle, National Academies of Sciences, Engineering, and Medicine. […]
  • You can replicate almost any plot with R
    Although R is great for quickly turning data into plots, it is not widely used for making publication ready figures. But, with enough tinkering you can make almost any plot in R. For examples check out the flowingdata blog or the Fundamentals of Data Visualization book. Here I show five charts from the lay press […]
  • So You Want to Start a Podcast
    Podcasting has gotten quite a bit easier over the past 10 years, due in part to improvements to hardware and software. I wrote about both how I edit and record both of my podcasts about 2 years ago and, while not much has changed since then, I thought it might be helpful if I organized […]

RSS Statistical Modeling, Causal Inference, and Social Science