The above graph borders on chartjunk (and is nothing like Paul Butler’s amazing Facebook map). We can see some variation in color but mostly it is a set of lines between 152 country capitals with no means to determine which … Continue reading → [Read more...]

The intersection of mapping APIs, fast database operations and user engagement offers a lot of very cool crowdsourcing applications ranging from the benign and powerful (Google’s Person Finder) to the minor and questionable (A DUI checkpoints app). Most intriguing in … Continue reading → [Read more...]

When working with labor economics, we often run into issues with selection on variables of interest. Regressing earnings on years of education to estimate the human capital earnings function makes sense at first blush until we imagine that education is … Continue reading → [Read more...]

Two posts ago I mentioned the age-earnings profile but did not provide a regression of log earnings on wage. I also offered, without evidence, that fitting a simple linear regression would be inappropriate. How do I know that? How could … Continue reading → [Read more...]

I like Labor Economics. Partially because it has a nice mix of theory and practical empiricism, but mostly because it seems to be a sub-field with a number of agreed upon stylized facts that grow not out of micro theory … Continue reading → [Read more...]

Here’s a post generated from my own ignorance of statistics (as opposed to just being marred by it)! In Labor Economics we walked through something called the truncated normal distribution. Truncated distributions come up a lot in the sciences because … Continue reading → [Read more...]

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