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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  • Whose dream is this? When and how to use the Keras Functional API
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  • Moving on as Head of Solutions and AI at Draper and Dash
    Well, what can I say? It has been a blast over the past year and a half. In my time at the company I have managed to work on a number of fascinating projects, here is a list of just some of them: Data Science Platform – this has been the ... The post Moving […]

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    Like a lot of people, I’ve been glued to various media channels trying to learn about the latest with what is going on with COVID-19. I have also been frustrated - like a lot of people - with misinformation and the deluge of preprints and peer reviewed material. Some of this information is critically important […]

RSS Statistical Modeling, Causal Inference, and Social Science

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    Fabio Martinenghi writes: I am a PhD candidate in Economics and I would love to have guidance from you on this issue of scientific communication. I did an empirical study on the effect of a policy. I had an hypothesis, which turned out to be wrong, in the sense the the expected signs of the […]
  • Derived quantities and generative models
    Sandro Ambuehl, who sketched the above non-cat picture, writes: I [Ambuehl] was wondering why we’re not seeing reports measures of Covid19 mortaliy other than the Case Fatality Rate. In particular, what would seem far more instructive to me than CFR is a comparison of the distributions of age at death, depending on whether the diseased […]
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    From an article I published in 2008: Let’s also not forget the benefit of the occasional dumb but fun example. For example, I came across the following passage in a New York Times article: “By the early 2000s, Whitestone was again filling up with young families eager to make homes for themselves on its quiet, […]