If the Asian Growth Model is not Working Anymore

In 1981 poverty rate in China was 64% of the population, in 2004 the rate was 10%: it means that 500 million people stepped out of poverty (look here and here). China and South-East Asia economies were propelled by export demand and by someone else’s debt. What now? In the words of FT columnist Michael Pettis

The assumption that implicitly underlay the Asian development model – that US households had an infinite ability to borrow and spend – has been shown to be false. This spells the end of this model as an engine of growth.

It seams like bad news for economists pointing at free trade and export-led growth as a practical receipt for development.  It seams like bad news for everybody. People in developing countries need to increase their income, and it is difficult to think how they could find the money in their neighborhoods.

Tuesday, 19 May 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

Crisis from the South

According to Banco de Guatemala, for the first time since 1999, in January 2009 remittances from abroad decreased by 7.75% compared to the same month in 2008. In Guatemala remittance  flows represent 11.89% of GDP. According to the World Bank remittances can represent more than 50% of rurally-based family income and for the International Organization for Migration 30.4% of the population receives money from abroad.

Causes? Probably economic crisis and deportation of  illegal immigrants from the US.

Something is certain: remittances are a strong factor in reducing poverty in Guatemala. If flows continue to decrease is more than probable that poverty will rise in a country where, according to the government, 45,6% of children are already underweight.

Monday, 16 February 2009

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RSS r-bloggers.com

  • r/finance, 1 year later
    The prominent conference R/Finance, held annually in Chicago, had a great program yesterday and today. As I wrote following last year’s conference, the organizers were criticized for including no women in its speaker lineup. The problem was that no women had submitted papers for consideration; no input, thus no output. I’m a member of the […]
  • A new package for panel data analysis in R
    It has been a long time coming, but my R package panelr is now on CRAN. Since I started work on it well over a year ago, it has become essential to my own workflow and I hope it can be useful for others. panel_data object class One key contribution, that I hope can help […]
  • The never-ending editor war (?)
    The creation of this blog post was prompted by this tweet, asking an age-old question: @spacemacs— Bruno Rodrigues (@brodriguesco) May 16, 2019 This is actually a very important question, that I have been asking myself for a long time. An IDE, and plain text editors, are a very important tools to anyone writing code. Most […]
  • Earthquake Analysis (4/4): Cluster Analysis
    Are you interested in guest posting? Publish at DataScience+ directly from your editor (i.e., RStudio). Category Basic Statistics Tags Data Visualisation Maps R Programming This is the fourth part of our post series about the exploratory analysis of a publicly available dataset reporting earthquakes and similar events within a specific 30 days time span. In […]
  • Mapping Tornado Alley with R
    I caught a re-tweet of this tweet by @harry_stevens: THREAD: I wrote a post on @observablehq about a map I made today. It shows a typical day in the life of a graphics journalist: You never know what problems you'll have to solve on deadline! https://t.co/yRhW1wbLxN #d3js #dataviz 1/7 pic.twitter.com/7N6mmK0nz3 — Harry Stevens (@Harry_Stevens) May... […]

RSS Simply Statistics

  • Generative and Analytical Models for Data Analysis
    Describing how a data analysis is created is a topic of keen interest to me and there are a few different ways to think about it. Two different ways of thinking about data analysis are what I call the “generative” approach and the “analytical” approach. Another, more informal, way that I like to think about […]
  • Tukey, Design Thinking, and Better Questions
    Roughly once a year, I read John Tukey’s paper “The Future of Data Analysis”, originally published in 1962 in the Annals of Mathematical Statistics. I’ve been doing this for the past 17 years, each time hoping to really understand what it was he was talking about. Thankfully, each time I read it I seem to […]
  • Interview with Abhi Datta
    Editor’s note: This is the next in our series of interviews with early career statisticians and data scientists. Today we are talking to Abhi Datta about his work in large scale spatial analysis and his interest in soccer! Follow him on Twitter at @datta_science. If you have recommendations of an (early career) person in academics […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • Vigorous data-handling tied to publication in top journals among public heath researchers
    Gur Huberman points us to this news article by Nicholas Bakalar, “Vigorous Exercise Tied to Macular Degeneration in Men,” which begins: A new study suggests that vigorous physical activity may increase the risk for vision loss, a finding that has surprised and puzzled researchers. Using questionnaires, Korean researchers evaluated physical activity among 211,960 men and […]
  • Hey, people are doing the multiverse!
    Elio Campitelli writes: I’ve just saw this image in a paper discussing the weight of evidence for a “hiatus” in the global warming signal and immediately thought of the garden of forking paths. From the paper: Tree representation of choices to represent and test pause-periods. The ‘pause’ is defined as either no-trend or a slow-trend. […]
  • Data quality is a thing.
    I just happened to come across this story, where a journalist took some garbled data and spun a false tale which then got spread without question. It’s a problem. First, it’s a problem that people will repeat unjustified claims, also a problem that when data are attached, you can get complete credulity, even for claims […]