Back into Poverty

Increase in food prices has pushed back into poverty at least 100 million people in 2008 and, according to the United Nations Standing Committee on Nutrition (here, p. 60),

erase at least four years of progress towards the Millennium Development Goal (MDG) 1 target for the reduction of poverty. The household level consequences of this crisis are most acutely felt in LIFDCs [Low-Income Food-Deficit Countries] where a 50% rise in staple food prices causes a 21% increase in total food expenditure, increasing these from 50 to 60% of income. In a high income country this rise in prices causes a 6% rise in retail food expenditure with income expenditure on food rising from 10 to 11%. FAO estimates that food price rises have resulted in at least 50 million more people becoming hungry in 2008, going back to the 1970 figures.

According to the World Bank (here) this means that between 200,000 and 400,000 more children will died every year for malnutrition until 2015.

Thursday, 18 June 2009

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

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

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RSS r-bloggers.com

  • COVID-19 shiny / plotly dashboard
    Governments and COVID-19: Which one stops it faster, better, has fewer people dying? These questions get answered with my dashboard. A contribution to the shiny-contest: https://community.rstudio.com/t/material-design-corona-covid-19-dashboard-2020-shiny-contest-submission/59690 Intro How did Corona spread? Using the animation feature of R-shiny this can be easily tracked.COVID-19 is the major topic in all news channels. The place I live in […]
  • RcppSimdJson 0.0.4: Even Faster Upstream!
    A new (upstream) simdjson release was announced by Daniel Lemire earlier this week, and my Twitter mentions have been running red-hot ever since as he was kind enough to tag me. Do look at that blog post, there is some impressive work in there. We wr...
  • C is for coalesce
    For the letter C, we'll talk about the coalesce function. If you're familiar with SQL, you may have seen this function before. It combines two or more variables into a single column, and is a way to deal with missing data. When you give it a list of va...
  • Custom Power BI visual for Line chart with two Y-Axis
    Power BI support certain type of visuals that are by default available in the document. These are absolutely great and work perfectly fine, have a lot of capabilities to set properties and change the settings. But every so often in…Read more ›
  • RQuantLib 0.4.12: Small QuantLib 1.18 update
    A new release 0.4.12 of RQuantLib arrived on CRAN today, and was uploaded to Debian as well. QuantLib is a very comprehensice free/open-source library for quantitative finance; RQuantLib connects it to the R environment and language. This version doe...

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

  • Noise-mining as standard practice in social science
    The following example is interesting, not because it is particularly noteworthy but rather because it represents business as usual in much of social science: researchers trying their best, but hopelessly foiled by their use of crude psychological theories and cruder statistics, along with patterns of publication and publicity that motivate the selection and interpretation of […]
  • Conference on Mister P online tomorrow and Saturday, 3-4 Apr 2020
    We have a conference on multilevel regression and poststratification (MRP) this Friday and Saturday, organized by Lauren Kennedy, Yajuan Si, and me. The conference was originally scheduled to be at Columbia but now it is online. Here is the information. If you want to join the conference, you must register for it ahead of time; […]
  • More coronavirus research: Using Stan to fit differential equation models in epidemiology
    Seth Flaxman and others at Imperial College London are using Stan to model coronavirus progression; see here (and I’ve heard they plan to fix the horrible graphs!) and this Github page. They also pointed us to this article from December 2019, Contemporary statistical inference for infectious disease models using Stan, by Anastasia Chatzilena et al. […]