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

Selva Amazónica, More Valuable Standing Than Felled

An article published on Science this week analyzes the development of the region across the Amazon deforestation frontier. In three words: boom and bust. It means that comparing the Human Development Index of different classes of Brazilian municipalities, from prefrontier municipalities to heavily post frontier deforested municipalities, you can see how the HDI relatively grows in the first phase of the deforestation (on the frontier line) and relatively declines when deforestation is completed.  In other words,

when the median HDI of each class is plotted against deforestation extent, a boom-and-bust pattern becomes apparent, which suggests that relative development levels increase rapidly in the early stages of deforestation and then decline as the frontier advances. Hence, although municipalities with active deforestation had development levels that approached the overall Brazilian median, pre- and postfrontier HDI values were substantially lower and statistically indistinguishable from each other (P > 0.9). These results are robust to the particular thresholds used to define the frontier classes. A boom-and-bust pattern is also found for each of the HDI subindices: standard of living, literacy, and life expectancy.

This strongly suggests that the poor have no choice but to exploit every resource available. It is difficult to think that farmers or loggers do not see that they are compromising their very own future. They simply have no choice. The challenge is giving them a choice.

Friday, 12 June 2009

On the Evolution of Thinking

What if we are becoming the very same Artificial Intelligence that we are trying to design? The doubt has has been raised by Nicholas Carr in an article published one year ago on The Atlantic and now published on Le Monde. The theory is intriguing and the discourse goes, in the words of developmental psychologist Maryanne Wolf, more or less in this direction:

We are not only what we read, We are how we read.

So, learning directly from the voice of Socrates is not the same as learning from the Internet. The way we approach new ideas and knowledge influences how we assimilate them and how we develop our thinking. The risk is that our mind might find so attractive the effectivness of the Google’s algorithm to try to replicate it forgetting all the ambiguity that has made us what we are. What we are so far.

Update: Have a look at this article on Le Monde about the influence of the new information technologies on culture.

Friday, 5 June 2009

tweets


Twitter: frbailo

links


blogroll


RSS r-bloggers.com

  • Model-Based Causal Forests for Heterogeneous Treatment Effects
    A new arXiv paper investigates which building blocks of random forests, especially causal forests and model-based forests, make them work for heterogeneous treatment effect estimation, both in randomized trials and observational studies. ... Continue reading: Model-Based Causal Forests for Heterogeneous Treatment Effects
  • A Major Contribution to Learning R
    Prominent statistician Frank Harrell has come out with a radically new R tutorial, rflow. The name is short for “R workflow,” but I call it “R in a box” –everything one needs for beginning serious usage of R, starting from little or no background. By serious usage I mean real ... Continue reading: A Major […]
  • Evaluating GitHub Activity for Contributors
    Say you have a bug report or feature request to make to a package. How can you use information on GitHub to manage your expectations (will there be a quick fix) and actions (should you go ahead and fork the repository)? In this post, we shall go over ... Continue reading: Evaluating GitHub Activity for […]
  • Developing React Applications in RStudio Workbench
    Introduction RStudio Workbench provides a development environment for R, Python, and many other languages. When developing a performant web application you may progress from Shiny towards tools li... Continue reading: Developing React Applications in RStudio Workbench
  • Food Crisis Analysis and, Forecasting with Neural Network Autoregression
    The war between Russia and Ukraine has affected the global food supply other than many vital things. Primarily cereal crop products have been affected the most because the imports have been provided to the world mainly through Ukraine and Russia. Let’s check the situation we’ve mentioned for G20 ... Continue reading: Food Crisis Analysis and, […]

RSS Simply Statistics

RSS Statistical Modeling, Causal Inference, and Social Science