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

tweets


Twitter: frbailo

links


blogroll


RSS r-bloggers.com

  • Angela Bassa discusses managing data science teams and much more.
    Hugo Bowne-Anderson, the host of DataFramed, the DataCamp podcast, recently interviewed Angela Bassa, the Director of Data Science at iRobot. Here is the podcast link. Introducing Angela Bassa Hugo: Hi there Angela, and welcome to DataFramed. Angela: Thanks, thanks for having me. Hugo: It's a great pleasure to have you on the show, and I'm […]
  • Preview my new book: Introduction to Reproducible Science in R
    I’m pleased to share Part I of my new book “Introduction to Reproducible Science in R“. The purpose of this …Continue reading →
  • How to de-Bias Standard Deviation Estimates
    This note is about attempting to remove the bias brought in by using sample standard deviation estimates to estimate an unknown true standard deviation of a population. We establish there is a bias, concentrate on why it is not important to remove it for reasonable sized samples, and (despite that) give a very complete bias […]
  • Data Science With R Course Series – Week 9
    There are only two more weeks in the course! This week will extend what you learned from the Expected Value by performing an optimization and sensitivity analysis. The optimization and sensitivity analysis will teach you how to identify the maximum bu...
  • RATest. A Randomization Tests package is available on CRAN
    This blog post introduces the RATest package we released a while back on CRAN with my colleague and good friend Mauricio Olivares-Gonzalez. The package contains a collection of randomization tests, data sets and examples. The current version focuses on two testing problems and their implementation in empirical work, mostly related to economics. First, it facilitates […]

RSS Simply Statistics

  • The role of academia in data science education
    I was recently asked to moderate an academic panel on the role of universities in training the data science workforce. I preceded each question with opinionated introductions which I have fused into this blog post. These are weakly held opinions so please consider commenting if you disagree with anything. To discuss data science education we […]
  • Guest Post: Galin Jones on criteria for promotion and tenture in (bio)statistics departments
    Editor’s Note: I attended an ASA Chair’s meeting and spoke about ways we could support junior faculty in data science. After giving my talk Galin Jones, Professor and Director of Statistics at University of Minnesota, and I had an interesting conversation about how they had changed their promotion criteria in response to a faculty candidate […]
  • The economic consequences of MOOCs
    tl;dr check out our new paper on the relationship between MOOC completion and economic outcomes! Last Monday we launched our Chromebook Data Science Program so that anyone with an internet connection, a web browser, and the ability to read and follow instructions could become a data scientist. Why did we launch another MOOC program? Aren’t […]

RSS Statistical Modeling, Causal Inference, and Social Science