Eyes on Guatemala

The Economist has published an article on malnutrition in Guatemala. Hunger is not new in the country, with half of the children population not eating enough Guatemala is the six-worst country in the world, but in some Maya communities children chronic malnutrition can reach 75% (the Economist says 80%). These figures are astonishing, especially because the problem is not food scarcity.

But this as well is hardly new. It was 1981 when Amartya Sen published his Poverty and Famines: An Essay on Entitlement and Deprivation demonstrating that hunger is mostly caused by inequality rather than scarcity. There is no lack of food in Guatemala if you have the money to buy it. In Guatemala City is taking place, as we speak, the 14th Festival Gastronómico Internacional so it seems difficult to talk about a famine or about an emergency (according to the Longman Dictionary an emergency is “an unexpected and dangerous situation that must be dealt with immediately”). The problem is the lack of a functioning state. Because a state cannot function with tax revenues estimated at just 10% of GDP.

Democracy is highly unrepresentative in Guatemala. Who should push for a better redistribution of resources has no voice. National newspapers point constantly the finger at the government (presidency, parliament, judiciary) in a impressive campaign of delegitimation. The Rosenberg tape was just part of it. I’m not defending the government, but saying that criticising it and attempting to systematically destroy its credibility are not quite the same thing. While the headlines cover crime, corruption and hunger the real battle within the country is on the tax reform. A battle that so far every government has badly lost.

Friday, 28 August 2009

Understanding Capitalism

Nobel-winning economist Amartya Sen argues, in an article published on The New York Review of Books, that the way out from the crisis passes through a better understanding of the ideas that contributed to build the actual economic system. Adam Smith, John Maynard Keynes, Arthur Cecil Pigou, should be read, not just quoted. And I quote

Smith viewed markets and capital as doing good work within their own sphere, but first, they required support from other institutions—including public services such as schools—and values other than pure profit seeking, and second, they needed restraint and correction by still other institutions—e.g., well-devised financial regulations and state assistance to the poor—for preventing instability, inequity, and injustice. If we were to look for a new approach to the organization of economic activity that included a pragmatic choice of a variety of public services and well-considered regulations, we would be following rather than departing from the agenda of reform that Smith outlined as he both defended and criticized capitalism.

We must understand how institutions work and make them work better. But not just aiming at economic growth.

There is a critical need for paying special attention to the underdogs of society in planning a response to the current crisis, and in going beyond measures to produce general economic expansion.

A crisis not only presents an immediate challenge that has to be faced. It also provides an opportunity to address long-term problems when people are willing to reconsider established conventions. This is why the present crisis also makes it important to face the neglected long-term issues like conservation of the environment and national health care, as well as the need for public transport (…).

Sunday, 22 March 2009

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RSS r-bloggers.com

  • Monitoring Website SSL/TLS Certificate Expiration Times with R, {openssl}, {pushoverr}, and {DT}
    macOS R users who tend to work on the bleeding edge likely noticed some downtime at this past weekend. Part of the issue was an SSL/TLS certificate expiration situation. Moving forward, we can monitor this with R using the super spiffy {openssl} and {pushoverr} packages whilst also generating a daily report with {rmarkdown} and... Continue […]
  • Evaluate your R model with MLmetrics
    This post will explore using R’s MLmetrics to evaluate machine learning models. MLmetrics provides several functions to calculate common metrics for ML models, including AUC, precision, recall, accuracy, etc. Building an example model Firstly, we need to build a model to use as an example. For this post, we’ll be using a dataset on pulsar […]
  • Data re-Shaping in R and in Python
    Nina Zumel and I have a two new tutorials on fluid data wrangling/shaping. They are written in a parallel structure, with the R version of the tutorial being almost identical to the Python version of the tutorial. This reflects our opinion on the “which is better for data science R or Python?” They both are […]
  • Does Australia need More Fires (but the Right Kind)? A Multi-Agent Simulation
    We have all watched with great horror the catastrophic fires in Australia. Over many years scientists have been studying simulations to understand the underlying dynamics better. They tell us, that “what Australia needs is more fires, but of the right kind”. What do they mean by that? One such simulation of fire is based on […]
  • Some everyday data tasks: a few hints with R (revisited)
    One year ago, I published a post titled ‘Some everyday data tasks: a few hints with R’. In that post, I considered four data tasks, that we all need to accomplish daily, i.e. subsetting sorting casting melting In that post, I used the methods I was more familiar with. And, as a long-time R user, […]

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

  • Are GWAS studies of IQ/educational attainment problematic?
    Nick Matzke writes: I wonder if you or your blog-colleagues would be interested in giving a quick blog take on the recent studies that do GWAS (Genome-Wide-Association Studies) on “traits” like IQ, educational attainment, and income? Matzke begins with some background: The new method for these studies is to claim that a “polygenic score” can […]
  • Causal inference in AI: Expressing potential outcomes in a graphical-modeling framework that can be fit using Stan
    David Rohde writes: We have been working on an idea that attempts to combine ideas from Bayesian approaches to causality developed by you and your collaborators with Pearl’s do calculus. The core idea is simple, but we think powerful and allows some problems previously that only had known solutions with the do calculus to be […]
  • My review of Ian Stewart’s review of my review of his book
    A few months ago I was asked to review Do Dice Play God?, the latest book by mathematician and mathematics writer Ian Stewart. Here are some excerpts from my review: My favorite aspect of the book is the connections it makes in a sweeping voyage from familiar (to me) paradoxes, through modeling in human affairs, […]