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

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RSS r-bloggers.com

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  • Visualizing geospatial data in R—Part 2: Making maps with ggplot2
    How to create annotated, multi-layered maps and choropleth maps in R using ggplot2. The post Visualizing geospatial data in R—Part 2: Making maps with ggplot2 first appeared on R-bloggers.
  • DALEX 2.1.0 is live on GitHub!
    Dreamworks animation. Image from: https://www.theatlantic.com/entertainment/archive/2014/11/a-kids-eye-view-of-penguins-of-madagascar/383187/After the awesome reception of my last blog about improvements for DALEX and DALEXtra, I couldn’t stand waiting for the next opportunity to share some details about new features with you. Sadly at some point, I realized that ... The post DALEX 2.1.0 is live on GitHub! first appeared on R-bloggers.

RSS Simply Statistics

  • The Four Jobs of the Data Scientist
    In 2019 I wrote a post about The Tentpoles of Data Science that tried to distill the key skills of the data scientist. In the post I wrote: When I ask myself the question “What is data science?” I tend to think of the following five components. Data science is (1) the application of design […]
  • Palantir Shows Its Cards
    File this under long-term followup, but just about four years ago I wrote about Palantir, the previously secretive but now soon to be public data science company, and how its valuation was a commentary on the value of data science more generally. Well, just recently Palantir filed to go public and therefore submitted a registration […]
  • Asymptotics of Reproducibility
    Every once in a while, I see a tweet or post that asks whether one should use tool X or software Y in order to “make their data analysis reproducible”. I think this is a reasonable question because, in part, there are so many good tools out there! This is undeniably a good thing and […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • The Shrinkage Trilogy: How to be Bayesian when analyzing simple experiments
    There are lots of examples of Bayesian inference for hierarchical models or in other complicated situations with lots of parameters or with clear prior information. But what about the very common situation of simple experiments, where you have an estimate and standard error but no clear prior distribution? That comes up a lot! In such […]
  • Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond
    Charles Margossian, Aki Vehtari, Daniel Simpson, Raj Agrawal write: Gaussian latent variable models are a key class of Bayesian hierarchical models with applications in many fields. Performing Bayesian inference on such models can be challenging as Markov chain Monte Carlo algorithms struggle with the geometry of the resulting posterior distribution and can be prohibitively slow. […]
  • Understanding Janet Yellen
    I don’t know anything about Janet Yellen, the likely nominee for Secretary of the Treasury. For the purpose of this post, my ignorance is OK, even desirable, in that my goal is to try to understand mixed messages that I’m receiving. Two constrasting views on the prospective Treasury Secretary First, here’s Joseph Delaney: So, I […]