Brian Milner is a “a senior economics writer and global markets columnist” at Canada’s largest and arguably most highly respected newspaper, the Globe and Mail. Milner doesn’t understand what economists mean by the word “efficient,” doesn’t understand the elements of the efficient markets hypothesis (EMH), and, worst, uncritically repeats nonsense from David Orrell, whose awful anti-scientific screed I reviewed here. Why oh why, as Brad DeLong likes to say, can’t we have a better press corps?
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Commonly econometricians conduct inference based on covariance matrix estimates which are consistent in the presence of arbitrary forms of heteroskedasticity; the associated standard errors are referred to as “robust” (also, confusingly, White, or Huber-White, or Eicker-Huber-White) standard errors. These are easily requested in Stata with the “robust” option, as in the ubiquitous

reg y x, robust

Everyone knows that the usual OLS standard errors are generally “wrong,” that robust standard errors are “usually” bigger than OLS standard errors, and it often “doesn’t matter much” whether one uses robust standard errors.  It is whispered that there may be mysterious circumstances in which robust standard errors are smaller than OLS standard errors. Textbook discussions typically present the nasty matrix expressions for the robust covariance matrix estimate, but do not discuss in detail when robust standard errors matter or in what circumstances robust standard errors will be smaller than OLS standard errors. This post attempts a simple explanation of robust standard errors and circumstances in which they will tend to be much bigger or smaller than OLS standard errors.

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A short article I wrote in 2002 regarding the novel arguments in Steve Keen’s Debunking Economics has been hard to track down for a while, so I’m making it available here.

Click here to download a copy (debunk.pdf).

Unfortunately, the link to Keen’s paper on the first page is broken. I attempted to get the paper from Keen’s site, but it’s now behind a paywall! I think the paper was called “A 75th Anniversary Gift for Sraffa,” but I failed to locate a copy.

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Suppose your health insurance becomes more generous, decreasing the proportion of the cost of care for which you are responsible. At the same time, your premium goes up to cover the extra costs faced by your insurer. In standard theory you are better off because you face less financial uncertainty, but you will also tend to consume too much health care because the price you pay is lower than the cost of your treatment. Standard theory suggests that insurance should be designed to optimally trade-off these benefits and costs. But standard theory assumes rationality: suppose instead people systematically make errors when choosing how much health care to consume. Does it make a difference to how we think about health insurance?

In a recently released NBER working paper, “Behavioral hazard in health insurance,” Katherine Baicker, Sendhil Mullainathan, and Joshua Schwartzstein consider behavioral biases that lead people to (specifically, and with loss of generality) underutilize health care. How should we think about designing health insurance in the presence of such biases?

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This post briefly surveys some of the methods and results in the literature on health and income inequality, closing with some remarks on problems with the existing literature and where future research may take us. It is not intended as anything resembling a comprehensive survey; Lynch et al (2004) provides a useful review of the empirical literature up to that time.

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If you glue corn flakes to a globe and infect it with slime, the slime grows between corn flakes in a pattern that looks kind of like roads.

No, I don’t know either.

Adamatzky, A. (2012) The World’s Colonisation and Trade Routes Formation as Imitated by Slime Mould, arXiv:1209.3958.

The plasmodium of Physarum polycephalum is renowned for spanning sources of nutrients with networks of protoplasmic tubes. The networks transport nutrients and metabolites across the plasmodium’s body. To imitate a hypothetical colonisation of the world and formation of major transportation routes we cut continents from agar plates arranged in Petri dishes or on the surface of a three-dimensional globe, represent positions of selected metropolitan areas with oat flakes and inoculate the plasmodium in one of the metropolitan areas. The plasmodium propagates towards the sources of nutrients, spans them with its network of protoplasmic tubes and even crosses bare substrate between the continents. From the laboratory experiments we derive weighted Physarum graphs, analyse their structure, compare them with the basic proximity graphs and generalised graphs derived from the Silk Road and the Asia Highway networks.

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