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Tag Archives: Statistics & Econometrics

Resisting the ‘statistical significance testing’ temptation

Resisting the ‘statistical significance testing’ temptation Imagine a dictator “game” in which a mixed-sex group of experimental subjects are used as first players who can decide which share of their initial endowment they give to a second player (one person acts as second player for the whole group). Additionally, assume that the experimental subjects are a convenience sample but not a random sample of a well-defined broader population. What kind of...

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The causal revolution in econometrics has gone too far

The causal revolution in econometrics has gone too far Kevin Lewis points us to this recent paper, “Can invasive species lead to sedentary behavior? The time use and obesity impacts of a forest-attacking pest,” published in Elsevier’s Journal of Environmental Economics and Management, which has the following abstract: “Invasive species can significantly disrupt environmental quality and flows of ecosystem services and we are still learning about their...

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What are RCTs good for?

What are RCTs good for? RCTs establish causal claims. They are very good at this. Indeed, given the probabilistic theory of causality it follows formally that positive results in an ideal RCT with treatment C and outcome E deductively implies ‘C causes E in the experimental population’. Though the move from the RCT to a policy prediction that C will cause E when implemented in a new population often goes under the single label, the external validity of the...

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A practice-based account of causal bias

A practice-based account of causal bias No estimated causal results are thus affected solely by the intervention but by many other background attributes and conditions that can give rise to bias between, within or across trial groups. A number of these influence a treatment’s estimated causal effects both within and outside a trial setting. That these and other such demanding preconditions (concauses) would be entirely satisfied for all participants is a...

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The dangers of idealizing randomization

The dangers of idealizing randomization In his history of experimental social science — Randomistas: How radical researchers are changing our world — Andrew Leigh gives an introduction to the RCT (randomized controlled trial) method for conducting experiments in medicine, psychology, development economics, and policy evaluation. Although it mentions there are critiques that can be waged against it, the author does not let that shadow his overwhelmingly...

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Causal inference

Causal effects are comparisons of what did happen with what would have happened if people had received different treatments. Randomized treatment assignment has reduced this problem to the minor technical problem of drawing an inference about a finite population of people on the basis of a probability sample from that population. Expressed differently, if we design an experiment so that the actual world is a random draw from a set of possible worlds, then we can draw...

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The 25 Best Econometrics Blogs and Websites

The 25 Best Econometrics Blogs and Websites Yours truly, of course, feels truly honoured to find himself on the list of the world’s 25 Best Econometrics Blogs and Websites. 2. Bruno Rodrigues 8. Eran Raviv Blog Statistics and Econometrics 13. How the (Econometric) Sausage is Made 14. Lars P Syll Pålsson Syll received a Ph.D. in economic history in 1991 and a Ph.D. in economics in 1997, both at Lund University. He became an associate professor in economic...

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‘Testing’ purchasing power parity theory

‘Testing’ purchasing power parity theory Purchasing power parity doctrine is examined by sophisticated statistical and econometric techniques. The time series of aggregated price levels and the nominal exchange rates are treated as a random sample. Most papers of this type deal with the technical properties of the slightly different data sets. To take some examples (at random): “Two potential problems arise when working with nominal exchange rates and...

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