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  • Reply to: Realizing Africa's Youth Potential: Africa needs investors to create jobs for its youth, and develop skills   2 days 17 hours ago

    we have to act differently to enable the young population to be productive.......

  • Reply to: Revolutionizing Data Collection: From “Big Data” to “All Data”   1 week 4 hours ago
    Many thanks for your comments. We are certainly interested in your project, particularly the sample bias correction technique. We are also studying the sample bias correction technique and contacting sampling experts in academics. It will be great if we can exchange several ideas on this.
  • Reply to: Revolutionizing Data Collection: From “Big Data” to “All Data”   1 week 4 hours ago
    Thanks for your comments. As you said, the choice of technology can cause biases in responses, which can result in severe biases in poverty and other key socio-economic indicators. In addition to the paper you mentioned, Listening to LAC study also produced many useful and careful studies on this topic. Good news is that we could successfully minimize response biases in our Serbia telephone survey pilot by carefully designing the data collection process based on lessons learned from Listening to LAC and others. I think it is very important to keep improving and sharing our knowledge/experiences on the use of new technology for data collection as well as how to limit possible biases.
  • Reply to: ​The Story of the 2015 World Development Report: Mind, Society, and Behavior   1 week 3 days ago

    Nice synopsis of the WDR 2015 and its production. Particularly liked the part about singing the blank verse epic poetic tribute to neoclassical economics - personally embarrassing, no doubt, but probably unnoticed by others since you would then have been just part of the chorus at the Bank. Look forward to seeing how the WDR influences our colleagues and their mental models going forward. Old habits (and mental models) die hard.

  • Reply to: Revolutionizing Data Collection: From “Big Data” to “All Data”   1 week 3 days ago

    Thanks for your sharing your thoughts Nobuo, I'm particularly keen to find our more about SWIFT. A few teams in the Bank are working on using call detail records - CDRs (mobile phone metadata - a popular big data source) to estimate socio economic variables.

    I agree that as with every data source, it's important to understand biases and try to estimate and correct for them. In the case of CDRs, one sample bias correction technique that appears to work well is to consider the systematic bias to be a function of cell phone penetration and to correct accordingly. This sort of technique of course relies on having good baseline data (e.g. the new DHS which includes questions on mobile phone ownership) and is somewhat limited by the geographic granularity at which official statistics are usually available.

    I'd be keen to have your input on a project we're starting in this area and I'll get in touch shortly. Thanks again!